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The corrosion mechanism taking place in an aqueous phase with or without mechanical contact is electrochemical in nature. The electrochemical signal is one of the primary sources of information that relates to behavior in potential, current, and electrical charge of a corroding electrode. It arises from processes that cause corrosion and other electrochemical reactions. In a sliding contact in an ionic electrolyte medium, electrochemistry is more likely to interfere with the tribological behavior of tribocorrosion systems. In recent years, attempts by researchers have been made to control the material loss by electrochemical methods for various engineering systems.

Applied online for monitoring in-situ uniform, localized, galvanic, or more forms of corrosion, such techniques are very convenient means to measure corrosion rate of materials. Such methods can also be used in different ways to evaluate their ability to protect materials (as inhibitors, protective layers, coatings). In this chapter, theoretical and experimental applications, fundamental aspects, limits of the electrochemical techniques for corrosion, and tribocorrosion monitoring are presented. Standards developed, so far, by various standardization organizations are reported. Fundamentals of traditional and advanced corrosion methods are described, focusing on their advantages, i.e. sensitivity to low corrosion rates, short experimental duration, and well-established theoretical understanding.

1. Application of electrochemical techniques for determining corrosion rates

In the section below, practical examples are described of how a number of electrochemical techniques could be used to forecast corrosion or tribocorrosion behavior in practical case studies. The focus is on laboratory tests for rapid corrosion or tribocorrosion tests. The examples do not provide bit-by-bit procedures for screening most or all potentialities. Also, the discussion is not about how to set up and conduct electrochemical corrosion or tribocorrosion experiments. Such information can be readily found in instruction guidelines manual or standard references [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]. The accent is put on the interest and validity of combination techniques to provide a better understanding of the corrosion process and more reliable predictions.

1.1. Linear polarization resistance (LPR)

The concept of “polarization resistance” has presumably been initiated by Bonhoeffer and Jena in 1951 [18]—a subsequent to Wagner and Traud’s works [19, 20]. In their study of the electrochemical behavior of iron samples of different carbon contents, they found that the slope of the polarization curve, i.e., the rate of potential change E with external current i, at the corrosion potential (or open-circuit potential of a mixed electrode), was low for some iron samples and large for others. Defining this slope as “polarization resistance,” R_P, as a result of Lange’s suggestion, it was found that there was an unambiguous correlation between the polarization resistance and the corrosion rate, whereas no correlation was found between the carbon content and the rate of corrosion.

Subsequently, Stern and Geary [21] were the first authors to theoretically establish a linear relationship between the polarization resistance and the corrosion rate based on the kinetics of electrochemical reactions (i.e., corrosion current at open-circuit conditions) and the concept of mixed potential theory, first formulated by Wagner and Traud in 1938 (i.e., parameters of the cathodic and anodic E/i relations) [19]. The advantages and limitations of their method have been discussed in a series of published articles [19, 21, 22], and the linearity of the slope of current-potential plot around the corrosion potential has been verified by experimental evidence, thereby avoiding the problem of large current densities. Their theory has been experimentally supported by other authors [19, 21, 22] for different materials and under a variety of environmental conditions. From the 1960s, plenty of publications [23, 24] reported on the use of the polarization technique, which quickly became one of the main electrochemical techniques routinely adapted to rapid corrosion rate measurements, a condition necessary to its success in industrial monitoring corrosion operations.

For a system in which electrode processes involve a slow reaction step at the electrode surface, the rate of reaction is limited by activation overvoltage; the relationship between the reaction rate, or net current density i, and the driving force for the reaction, or potential E, is given by the Butler-Volmer equation. This equation relates i, for a single electrode process, such as Eq. (1) to E by the formula (2),Fe↔Fe2++2e−Fe↔Fe2++2e− E1i=i0[exp(αnFηRT)−exp((1−α)nFηRT)]=i0[exp(αnF(E−Erev)RT)−exp((1−α)nF(E−Erev)RT)]i=i0expαnFηRT−exp1−αnFηRT=i0expαnFE−ErevRT−exp1−αnFE−ErevRT E2

where η is the overpotential, i₀ the exchange current density (rate of either the forward or reverse half-cell reaction) at the equilibrium potential E_rev, αthe transfer coefficient (usually close to 0.5, but must be between 0 and 1), and n the number of electrons transferred.

The graphical representation of the Butler-Volmer equation, as shown in Figure 1, is called the polarization curve.

Stern and Geary’s theory [21] is based on a simplified corrosion process assuming that only one anodic reaction and one cathodic reaction are involved during the corrosion process. It is therefore inevitable that erroneous results occur when the corrosion process involves more than one anodic or cathodic reaction. To address this problem, Mansfeld and Oldham [25] presented a modification of the Stern-Geary equation by including more than one oxidation and one reduction reaction in a complicated corrosion process. The current-overpotential relationship at electrodes is set by a number of complex physical and chemical phenomena based on experimental conditions. The reactions occurring at the electrode/electrolyte interface are heterogeneous chemical processes that may involve elementary electron-transfer steps (one or more steps) over the electrochemical double layer, ion-transfer, potential independent or chemical steps, etc.

It is well known that the electrochemistry of corroding metals involves two or more half-cell reactions. Suppose there is a simple corrosion system, such as an iron metal (a corroding working electrode) immersed in a sulfuric acid solution, in addition to Eq. (1), the following half-cell reaction (Eq. (3)) also occurs:H2++2e−↔H2H2++2e−↔H2 E3

The dissolution of Fe takes place in the acid electrolyte. At equilibrium, the total anodic rate is equal to the total cathodic rate. In this case, the net rate of either Fe dissolution or hydrogen evolution can be measured at the electrode potential of the steady-state freely corroding condition. This potential refers to the corrosion potential E_corr, which lies between the equilibrium potentials of the two individual half-cell reactions. At E_corr, the net rate corresponds to the uniform corrosion rate, i_corr, at free corrosion condition. In such system, the relationship between the overpotential (η, applied potential minus corrosion potential) and the current (flowing between the working electrode and the auxiliary counter electrode) is governed by the fundamental Butler-Volmer equation given as follows:i=i0[exp(αnFηRT)−exp((1−α)nFηRT)]=i0[exp(αnF(E−Ecorr)RT)−exp((1−α)nF(E−Ecorr)RT)]i=i0expαnFηRT−exp1−αnFηRT=i0expαnFE−EcorrRT−exp1−αnFE−EcorrRT E4

In Figure 1, the linear relationship between the polarization resistance and the corrosion rate can be easily illustrated graphically. In the small region near the corrosion potential, E_corr, only a very small perturbation potential, usually less than ±30 mV (typically ±10 mV), is applied above or below the corrosion potential, yielding a linear relationship between the overpotential (η = E − E_corr) or the polarization from the corrosion potential and the current. Due to this smooth excitation, the LPR technique is not expected to interfere with corrosion reactions. The slope of that linearized curve (i − E) is defined as the polarization resistance, R_P, of a corroding electrode (in ohms cm⁻² if the current density is plotted or in ohms if the current is plotted), which is mathematically interpreted asRP=(∂η∂i)|E−Ecorr=0RP=∂η∂iE−Ecorr=0 E5

where i is the current density corresponding to a particular value of E.

The corrosion current, I_corr, can be calculated when the overpotential approaches zero and is related to R_P as follows:Icorr=1Rp.babc2.303(ba+bc)Icorr=1Rp.babc2.303ba+bc E6

where b_a and b_c are the so-called anodic and cathodic Tafel slopes or Tafel parameters, respectively (cf. infra). The corrosion current density, i_corr, can thus be calculated from Eq. (6) if R_P and Tafel constants (b_a and b_c) are known.

ASTM G59 describes an experimental procedure required to carry out polarization resistance measurement [10]. In agreement with this standard, the potential should be scanned from −30 mV to +30 mV of the corrosion potential at a rate of 0.167 mV s⁻¹.

Many of the foregoing determined corrosion key parameters are based on empirical observations. As with any empirical method, due to the high number of factors involved in a corrosion or tribocorrosion system (e.g., environmental changes, temperature, pH, reagent as chloride ions, pressure, specimen geometry, test setup configuration, etc.), it is not uncommon to observe that the values of b_a, b_c, and R_P are influenced by these operational parameters and are therefore subject to change. Of significance, the slope generated from the i–E curve around the corrosion potential may not be linear and may or may not be symmetrical in the anodic and cathodic regions. The symmetry of the curve (i–E) at the point of equilibrium or at open-circuit potential is obtained only when b_a and b_c are equal. These values are required for computing the corrosion current and are usually determined by the Tafel extrapolation method (cf. infra).

It is worthy to note that the measurements of R_p can be derived potentiodynamically or by the method of stepwise potentiostatic polarization or by anodic step pulse method. In the potentiodynamic method, the potential is swept at a constant rate (typically 60 mV/h) from the active (cathodic) direction to the noble (anodic) region passing through the corrosion potential while tracking the current density continuously. More information regarding this method can be found elsewhere [3]. Similarly, in the step pulse method, an applied potential is incremented in steps of ±5 or ± 10 or ± 20 mV, starting from a negative potential moving to a positive potential through the corrosion potential. The value of R_p is determined from the slope of the plot of the potential-current. Prior to the tests, a steady-state corrosion potential is required. The open-circuit potential of the corrosion system is first measured, typically for 1 hour (during which time the corrosion potential of most electrodes is stabilized) or until it reaches a stationary state.

Progress is made through competitive advantages between different measurement techniques, including a rapidity in current measurement (generally rather quickly in a few minutes), where only a lower excitation is required (less than ±30 mV, generally ±10 mV), so that the corrosion rate would not be affected by corrosion reactions, an easy measurement of low corrosion rates (less than 0.1 mil/year (2.5 μm/year), and measurements taken repeatedly, the LPR technique can be considered as a nondestructive technique and used for online corrosion monitoring of uniform corrosion rates useful for the field.

The main drawback of this technique is that the Tafel parameters must be known in advance in order to convert the polarization resistance into the corrosion rate. To tackle this problem, several numerical methods [8, 9, 26, 27, 28] have been proposed to obtain both Tafel parameters and corrosion rate from the same polarization measurement in the vicinity of the corrosion rate. Nevertheless, the success is limited since the Tafel parameters thus determined will not be very accurate, which may compromise the nondestructive nature of the LPR technique. Another disadvantage of the LPR method lays in the fact that it will not work properly in low conductive media. Basically, the LPR technique can only be used to determine uniform corrosion rates; it can hardly provide information about localized corrosion.

1.1.1. Illustrative examples of the application of LPR in corrosion and tribocorrosion systems

A modified electrochemical noise technique, namely, electrochemical emission spectroscopy (EES) [29], offers one of the most convincing examples of the application of the LPR technique in tribocorrosion [30]. Indeed, the analysis of noise data in a potential-current plane shows the transposition of the statistical resistance due to electrochemical noise to the resistance due to linear polarization. Noise resistance is often considered equivalent to the polarization resistance, R_P [31, 32, 33]. The noise resistance, R_N, calculated using a method proposed by Eden et al. [33], for mild steel passive alloy in 0.05 M H₂SO₄ (corrosion under activation control), is of the order of 48 Ω without any sliding contact. The LPR measured on this mild steel after EES monitoring is shown in Figure 2a. The comparative value of R_P obtained by the LPR technique is 50 Ω. The R_Nvalue obtained using the EES technique is therefore very close to the R_Pobtained by the LPR technique. Under tribocorrosion conditions (5 N normal force, 10 Hz sliding frequency, 200 μm peak-to-peak displacement amplitude), the plane plot of the potential-current data under steady-state wear-corrosion regime shows a best-fit line through the data points with a positive slope of 54 Ω (see Figure 2b), which roughly corresponds to R_N (48 Ω) or R_P (50 Ω in Figure 2a). Notwithstanding, no attempt has been made to relate these resistance measurements with the breakdown (i.e., depassivation) or the buildup of any kind of passive film (i.e., repassivation) on the mild steel surface subjected to either a mechanical stimuli (e.g., active-passive wear track zone area or metastable pit area) or in the absence of wear (free corrosion), characteristic phenomena of localized corrosion.

1.2. Tafel extrapolation method

In 1905, Julius Tafel [34] presented the experimental relationship between the current, I, and the overpotential, η, during an electrocatalytic test of the reduction reaction of hydrogen (i.e., protons to form molecular hydrogen) on a number of electrode metals such as Hg, Sn, Bi, Au, Cu, Ni, and so on:η=a+blogIη=a+blogI E7

where the overpotential η is defined as the difference between the potential of the working electrode, E, and the equilibrium potential.

The existence of a linear relationship between E and log I has been demonstrated when the electrode is polarized at sufficiently large potentials, and far away from the corrosion potential both in anodic and cathodic directions [34], as can be seen in the polarization curve depicted in Figure 3. The portions in which such relationships prevail are called Tafel portions or Tafel regions.

This can be mathematically expressed asI=Icorr[exp(2.303ηba)−exp(−2.303ηbc)]=Icorr[exp(2.303(E−Ecorr)ba)−exp(−2.303(E−Ecorr)bc)]I=Icorrexp2.303ηba−exp−2.303ηbc=Icorrexp2.303E−Ecorrba−exp−2.303E−Ecorrbc E8

where E_corr is the corrosion potential, E the applied potential, η the overpotential (difference between E and E_corr), I the current, I_corr the corrosion current, and b_a and b_c are the Tafel constants or Tafel parameters derived from E − log I plots as the anodic and cathodic slopes in the Tafel regions, respectively.

Extrapolating from the Tafel portions of either anodic or cathodic or both, an intersection point is obtained at E_corr, from which I_corr is readily available from the log I axis. Therefore, it is possible to obtain simultaneously the corrosion current, I_corr, and the Tafel parameters (i.e., b_a and b_c) from this method.

In order to obtain the Tafel portions in the anodic and cathodic regions, the electrode has to be polarized far away from its corrosion potential, e.g., ±250 mV away from E_corr. Eq. (8) can be rearranged, as appropriate, to choose one single polarization direction, either anodic or cathodic way.

At sufficiently larger values of η (100 mV ≤ η ≤ 500 mV), in the anodic direction (i.e., η = η_a), Eq. (8) can be rearranged as,ηa=balogIIcorrηa=balogIIcorr E9

Likewise, at sufficiently larger values of η, in the cathodic direction (i.e., η = η_c), Eq. (8) can be modified as,ηc=−bclogIIcorrηc=−bclogIIcorr E10

The polarization curve can be measured either dynamically or statically (either in the potential-controlled mode or in the current-controlled mode). The dynamic polarization techniques can be carried out relatively fast, but the drawback is that the Tafel parameters are scanning rate dependent. The static polarization techniques may produce better Tafel parameters, but they are very time-consuming.

Tafel extrapolation measurements can be performed either by the potentiodynamic method or by the stepwise potentiostatic polarization method [35]. As in R_P measurements, in both methods, corrosion potential is first measured, typically for 1 h (during which time corrosion potentials of most electrodes are stabilized) or until it stabilizes. After that, the potential step—at increments of ±25 or ± 50 or ± 100 mV, every 5 min, recording the current at the end of each 5-min period—is applied (potential-step method), or the potential is scanned at a constant rate (typically 0.6 V/h) (potentiodynamic method). In both methods, the experiment is started at the corrosion potential, and the cathodic polarization is first conducted by applying an overpotential of approximately 500 mV or until gas evolution (e.g., hydrogen) occurs at the electrode, at a constant rate of 0.6 V/h. Following, the corrosion potential is measured again (typically for 1 h), and then anodic polarization is conducted by applying an overpotential so that the potential at the end of the anodic polarization reaches +1.6 V versus SCE. Tafel plots are generated by plotting both anodic and cathodic data in a semilog paper as E-log I. From the plot, three values are determined: the anodic Tafel slope, the cathodic Tafel slope, and I_corr (from back-extrapolation of both anodic and cathode curves to E_corr). The main advantage of this method is that it provides a simple, straightforward method to determine Tafel parameters, namely, b_a and b_c.

The disadvantage of the Tafel technique is that large current densities are often required to generate the complete Tafel plots. The use of large current densities can alter the surface conditions of the specimen (e.g., permanent change or surface damage), thereby distorting the results and increasing complications due to mass transport and uncompensated electrolyte resistance. The measurement of current density over a wide potential range may also distort the results if the adsorption of some species is potential dependent. Since this method applies a large overpotential to the metal surface (e.g., anodic polarization), therefore, the technique is rather destructive and can hardly be used for online corrosion monitoring purposes and in particular in the field. An ASTM G5 standard provides a procedure for constructing an anodic polarization plot [36]. However, it does not supply a method to construct a cathodic polarization plot nor a procedure to determine the corrosion current by the Tafel extrapolation method.

1.3. Corrosion rate determination by electrochemical noise analysis (ENA)

Many of the electrochemical techniques, among those described earlier, measure the electrochemical response of the corrosion system following the application of an external disturbance. In the last 50 decades, an original concept has emerged where it was possible to use the inherent noise of the electrochemical system as a stimulus to measure both potential and current changes [31, 32, 37, 38, 39, 40, 41, 42, 43]. Broadly, measured inconsistently in corrosion experiments, the electrochemical noise was first considered an unwanted or undesirable artifact that comes from measuring instruments or pickups from the environment. This is why this misleading name was cast. This sort of noise can be easily observed during corrosion potential measurements because the measured corrosion potential always fluctuates slightly, usually randomly. Random fluctuations result from stochastic processes [44], and, considering each chemical process is stochastic in nature, it generates noise.

Since the pioneer work of Iverson [45], who has reported a relation between the frequency or amplitude of the electrochemical noise and the inhibiting power of the environment for a number of metals and alloys (e.g., aluminum alloys, magnesium, mild steel, etc.), there has been a growing interest toward the measurement of electrochemical noise and its peculiar relationship with localized corrosion [11, 12, 31, 32, 41, 46, 47, 48, 49, 50, 51]. In this respect, electrochemical noise measurements obtained from the analysis of corrosion potential or current fluctuations provide a new approach to the study of corrosion processes in reactive environments such as aqueous media or hot aggressive gases or even under the effect of mechanical stimuli, e.g., tribocorrosion. Indeed, mechanical friction of solids in contact with a corrosive environment is likely to generate (i) noise due to stochastic contact between randomly distributed surface asperities and (ii) noise due to the synergy of wear-corrosion processes resulting from the activity of the surfaces and controlled by the response of potential-current transients and the configuration of the wear track area, coordinated by the coupling effects of wear and corrosion in the tribo-electrochemical cell. Among the possibilities offered by the measurement of electrochemical noise sources during an electrochemical or a tribo-electrochemical system, the following can be retained: adsorption–desorption processes, e.g., formation and detachment of gas bubbles; fluctuations in the mass transport rate and in temperature; interfacial nucleation and growth processes; degradation processes due dielectric film disruption; kinetics of atom exchange at the surface sites, e.g., Johnson’s noise in the interfacial impedance; and so on.

While multiple case studies on electrochemical noise have been regularly reported in recent years, even greater progress is possible, with the scope for increased breakthrough in science and technology (e.g., novel materials, precision tools on macro-to-nanoscopic scales, availability and intelligent use of these materials and tools, and so on). In particular, the main focus of these investigations is to promptly obtain in situ mechanistic information on the repassivation and breakdown of passive films and to monitor any process associated with confined corrosion and/or tribo- or bio-tribocorrosion [46, 47, 51]. It has been, indeed, suggested that the noise is caused by film breakdown and repassivation processes, and given the dynamic competition between these two processes, pitting will initiate. However, the foundation for using electrochemical noise analysis for determining the corrosion rate of an electrode is still a subject of debate within the scientific community. Indeed, the fundamental approach is not as robust as that of other techniques. On the other hand, the advantage of the noise analysis is that it is not necessary to apply any external polarization and the system is in natural corrosion conditions. This renders the technique as nondestructive and nonintrusive, capable of monitoring basic changes in an electrochemically active system. This makes it particularly suitable for online corrosion monitoring in the laboratory, especially for localized corrosion monitoring, detection of general corrosion, crevice investigation, stress corrosion cracking [12, 52, 53], fretting corrosion, or be used in the assessment of anti-corrosive organic coatings, and other surface inhomogeneity case studies [43, 46, 47]. Several approaches extend the use of electrochemical noise measurements in both pilot plant and field facilities, its use is not merely limited to the foregoing phenomena, but its development is justified especially when measurements are performed in systems with very low conductivity, where, for e.g., the impedance technique fails because of the loss of signal in the high resistance of the solution (cf. infra).

1.3.1. Instrumentation for electrochemical noise measurements in corrosion and tribocorrosion systems

Electrochemical noise is a generic term used to describe the naturally occurring fluctuations in potential and current, which is due to spontaneous changes in electrode kinetics and mechanisms [33]. When applied to corrosion studies, electrochemical noise may be redefined as the spontaneous fluctuations observed in potential and current at the free corrosion potential. The electrochemical noise can thus be classified into potential noise and current noise. There are three major possible modes for measuring potential and current noise in a corrosion system, but the most common mode uses two nominally identical working electrodes, WE₁ and WE₂ (WE₁ as the corroding metal and WE₂ as a counter electrode), and a noise-free reference noble electrode, RE [33] (see Figure 4a). The current flowing between the two working electrodes is measured by a zero-resistance ammeter (ZRA), and their potential is monitored versus the reference electrode through a voltmeter (V) under free corrosion conditions. The two other leftover modes are two identical working electrodes WE₁ and WE₂ with a bias potential [54] (not shown here) and one WE coupled to a micro-counter electrode (MC, e.g., Pt wire tip) [29, 46, 47, 55] (see Figure 4b). This last mode of electrochemical noise analysis seems to be a promising way to obtain unambiguous estimates of the rate of chemical wear in a tribocorrosion experiment as evidenced by some recent investigations [46, 47, 51] but also to predict the corrosion rate of localized corrosion in a free corroding system [29, 31, 32, 37, 38, 39, 40, 41, 42, 43, 44, 45, 47, 48, 49, 50, 56].

1.3.2. Electrochemical noise data management process

The overall approach to analyzing noise data is the assessment of mechanistic information from either time-domain analysis, frequency-domain analysis, or both, using statistical methods [44, 57, 58]. If the information in the time-domain records is evident, time-domain analysis is sufficient to distinguish different processes (e.g., different forms of corrosion).

In what follows, one assumes that all various types of noise are excluded from this description, with the exception of the thermal noise. Except for the last noise, all other noise sources can be minimized or eliminated using careful strategy within reasonable limits of materiality. Effective and convenient ways include the removal of unwanted environmental and instrumental noise from the electrochemical noise, e.g., by shielding electrical connections/wires for coupling the electrodes to the experimental apparatus, by using a Faraday cage to exclude electrostatic/electromagnetic influences, even by implementing analogue/digital filters to eliminate systematic noise at frequencies different than the frequency of interest, and so on. Guidelines for the calibration of noise measuring device can be found elsewhere [13, 59].

1.3.3. Noise resistance

The basic quantitative approach is the time-domain analysis of the noise signal. The noise resistance, R_N, is defined as the ratio of the standard deviations of potential/current noise signal time dependent, σ(t):RN=σE(t)σI(t)RN=σEtσIt E11

Eq. (11) implies that in the case where a low-driving force noise produces a high current density noise between the two electrodes (WE₁ and WE₂), the yielding noise resistance will be low. Noise resistance, R_N, has been shown to correlate well with the polarization resistance, R_P, as determined by EIS for certain corrosion systems. This latter being directly related to the corrosion current [14, 29, 60] is using the Stern-Geary equation and Tafel slopes. Notwithstanding, much work has been devoted trying to best match R_N or the normalized R_N (per unit of exposed surface area) to the corrosion resistance or the corrosion rate [5, 14, 31, 32, 37, 38, 39, 40, 41, 42, 43, 44, 45, 48, 49, 50, 60]. Although signal analysis in the time domain is well established, an approach based on spectral analysis is gaining more and more importance in research laboratories. It consists of transforming the potential and current noise fluctuations recorded in the frequency domain using the Fast Fourier Transform (FFT) method [61].

The frequency range for which the FFT is commonly performed extends from 1 mHz up to 1 Hz. The spectral noise plots are similar to those of impedance plots. The spectral noise resistance, R_SN, is given by the ratio of the potential and current FFTs at each frequency, and the limiting value, R_SN⁰, can be used as a measure of the corrosion resistance:RSN(f)=(EFFT(f)IFFT(f))RSNf=EFFTfIFFTf E12

The log–log plot of R_SN versus f is similar to the impedance plot, and the spectral noise resistance limit R_SN⁰ is given byR0SN=limf→0RSN(f)RSN0=limf→0RSNf E13

Another approach would be to examine the spectral noise response in terms of power spectral densities (PSD). These latter are calculated from the FFT or using the maximum entropy method (MEM) [62]. R_SN is determined from the PSDs by the relation (14):RSN(f)=(EPSD(f)IPSD(f))1/2RSNf=EPSDfIPSDf1/2 E14

It has been shown that the use of a single data set of potential and current noise [32] would yield identical values of R_SN as calculated by either Eqs. (13) or (14). In some cases, R_SN⁰ is bound to R_N or R_P as,RN=RSN(0)=RPRN=RSN0=RP E15

effective if the impedance of the two electrodes is identical and much higher than the resistance of the test solution between them [5, 32, 63]. Experiments have validated this relationship for several systems [5, 31, 63]. Nonetheless, there is no agreement on the fundamental basis for the relationship between noise resistance and corrosion rate.

1.3.4. Illustrative examples of the application of electrochemical noise in tribocorrosion systems

Investigations into electrochemical kinetics make common point research between tribocorrosion and corrosion. The study of localized phenomena of depassivation and repassivation is essential to understand the mechanisms of corrosion-wear as well as to reduce the material loss. The possibility of using the electrochemical noise detection technique as a promising tool to study the electrochemical properties of well-controlled damaged surfaces has been widely considered due to its nondestructive nature and its potential in online corrosion monitoring applications. Time-spatially resolved measurements should provide more reliable data on the electrochemical part of tribocorrosion. The noise analysis in relation to depassivation-repassivation events randomly distributed in time and space can be traced back to Oltra et al. [64]. The power spectral density (PSD) of the noise under the impact of the jet particles was related to the Fourier transform of individual repassivation transients obeying a Poisson distribution. Later, the application of electrochemical noise analysis to tribocorrosion was reviewed. Investigations involving PSD noise analyses on various tribo-electrochemical cells for passivating materials were conducted by Ponthiaux et al. [65], by Déforge et al. [51], and in more details by Berradja et al. [46, 66]. In this latter work, the noise spectra were measured on AISI 304 L stainless steel versus corundum in a Ringer’s solution in a pin-on-disk tribometer under stationary sliding-corrosion regime conditions, either at open-circuit potential or at a controlled potential. The PSD of the current noise has been interpreted as resulting from the overlap of the large number of discrete repassivation transients at the contact junctions, including the double-layer charge and the strong dependence of depassivation and repassivation kinetic rates of the oxide surface film on the sliding frequency. This was consistent with the shift in the PSD plots of the current noise fluctuations by about a decade when the sliding frequency was varied from 0.1 to 1 Hz (see Figure 5). Similar findings were obtained via Déforge et al. [51] by dividing open-circuit potential fluctuations to the impedance of the electrode. A 1/f low-frequency noise is explained by a long-term drift of the surface conditions. Only a minor influence of the applied normal load was observed on the PSD plots, recommending reaching the limit rate of the depassivation of the oxide surface film.

Application of the noise analysis to tribocorrosion offers the feasibility to record in parallel the PSD of normal and tangential force fluctuations and their tie-in with the current noise data (see Figure 6). Force fluctuations show an almost flat spectrum (white noise) as expected following short random mechanical interactions between colliding asperities, whereas the current noise is consistent with finite time-constant transient responses to the depassivation events.

1.4. Corrosion forecast by electrochemical impedance spectroscopy (EIS)

The EIS has matured greatly over the past 25 years as a tool in corrosion protection research and has proven to be one of the most useful electrochemical characterization techniques presently available. In practice, EIS has become a standardized research tool for corrosion prediction [15] and found wide applications in both fundamental and applied laboratory researches [67]. Recent applications in tribocorrosion reflect the steady progress of the EIS method in terms of research and development [62]. Compared with the LPR technique, the EIS technique is considered more advanced, since it has the ability to study high-impedance systems, in which the conventional LPR technique has failed, such as coatings and linings [16, 68], high pure water, and organic coating/metal systems [69] or corrosion in a low conductive solution [70]. This technique is especially useful for evaluating corrosion inhibitors [24, 71], analyzing the corrosion mechanisms [72, 73], and so on.

A significant number of tutorials have been addressed on the EIS experimental setup, the measurement methodology, and data analysis methods [27, 74, 75, 76, 77, 78]. The technique has been of a great deal of concern to the extent that an ASTM standard, i.e., ASTM G106-89, has been produced to provide the practitioner with a test method to verify that the electronic equipment, the electrochemical cell, and the spectrum generation algorithm impedance work properly [15].

1.4.1. Principle of the EIS technique

The EIS technique normally uses a typical three-electrode cell system controlled by a potentiostat, similar to that used in the LPR technique. Unlike the previous time-resolved techniques, where the current system response is either the consequence of a large voltage perturbation from the steady-state condition (case of Tafel extrapolation) or from a smaller perturbation (case of LPR method), in the EIS approach, however, by applying a small varying perturbation over a range of frequency, it is possible to probe the full response of the electrochemical system, and not just the resistive components. In that respect, a small AC signal, i.e., alternating potential or voltage V(ω) typically a sine wave of amplitude ±10 mV of the corrosion potential, is applied over a wide range of frequency (typically from 10⁵ down to 10⁻² or 10⁻³ Hz) at a number of discrete frequencies (typically 5–10 frequencies per decade), and the alternating current response, i(ω), is measured at each frequency, ω (i.e., the ac polarization or angular frequency, ω = 2πf). For a linear system, the current response signal will be a sine wave of the same frequency as the excitation signal (voltage) but shifted in phase. This is transmitted to a frequency response analyzer or a lock-in amplifier to calculate the impedance and phase shift. Full frequency sweeps provide phase-shift information that can be used in combination with equivalent circuit models to gain valuable information from the complex interface of the corrosion system. The frequency-dependent impedance is determined by the relation: Z(ω)=V(ω)/i(ω)Zω=Vω/iω .

1.4.2. Electrode/electrolyte electrochemical interface circuit

Basically, the electrode/electrolyte interface is characterized by a separation of charges resulting in the creation of parallel planes of electrical charges whose behavior is similar to a circuit consisting of a capacitor and a resistor in parallel and certainly not to a perfect capacitor. Indeed, the current flowing in a perfect capacitor would cease when the latter would be fully charged, hence the need to add a resistor in parallel to let a weak current flow. An electrochemical interface can be viewed as an electrical circuit, or called the equivalent circuit, composed of a number of elements such as resistances (R), capacitances (C), and inductances (L) [26]. Explanations of the EIS results are usually based on the equivalent circuit used. Many software programs and packages are now available for fitting the impedance spectra to analogous circuits [15], a strategy often used to analyze data. Further information on the EIS measurements and instrumentation can be found elsewhere [15, 17, 79, 80].

Not all the available proposed equivalent circuits to model electrochemical interfaces can actually satisfy what is applied to a freely corroding system. In most cases, the impedance corresponding to a simple corrosion process, under activation control, can be represented by the well-known Randles’ [81] equivalent circuit (RC circuit) which allows to describe the behavior of many electrochemical electrode/electrolyte interfaces. A typical example is shown in Figure 7, where R_S, R_CT, and C_DL represent labels for the solution resistor, the Faradaic charge transfer resistor, and the double-layer capacitance, respectively. The capacity is associated with the separation of charges at the electrode/electrolyte interface as in the case of a working electrode having a surface film (e.g., AISI 304 stainless steel immersed in a 0.5 M H₂SO₄ electrolyte), in which case the capacity of the equivalent circuit can be associated with the capacity of the passive oxide surface film and the resistor in parallel with the capacitor is considered as the charge transfer resistance, R_CT (or the polarization resistance, R_P, under EIS-free corrosion conditions), while the ohmic resistance in solution, R_S, between the working electrode and the reference electrode is in series with the parallel resistor and the capacitor. If the amplitude of the perturbation signal is small enough (e.g., a voltage less than 20 mV), R_CT can be regarded as equivalent to the linear polarization resistance (R_P).

The behavior of such an electrochemical interface can be described by Eq. (16):Z(ω)=Rs+Rp1+(jωRPCDL)βZω=Rs+Rp1+jωRPCDLβ E16

R_CT or R_P can be determined in several ways. A convenient way is to use the Nyquist diagram. For the simple Randles-type equivalent circuit as shown in Figure 7, the corresponding Nyquist diagram is displayed in Figure 8, in which a perfect semicircle is observed. The high-frequency response is used to determine the component of R_S involved in the measurement. R_S can be read directly from the abscissa when the angular frequency ω (ω = 2πf) tends to be infinite (f_max or f → ∞). The total resistance (R_P + R_S) can also be read from the abscissa when ω approaches zero (f_min or f → 0). So, R_P can be determined by subtracting the R_S value from the low-frequency measurement. The conversion of the polarization resistance into a corrosion rate requires an independent empirical measurement of the Tafel slopes using a potentiodynamic polarization method and/or harmonic distortion analysis or otherwise taken from the literature. The double-layer capacitance, C_DL, can also be determined for a system exhibiting a behavior similar to that of a perfect RC circuit from the values of R_P and the maximum frequency, f_max, that corresponds to the frequency of the point at which the imaginary component has a maximum value, viz.:

CDL=12πfmaxRpCDL=12πfmaxRp E17

It is worth of note that in practice, f cannot really go as high as infinite; it is inevitable that some extrapolation has to be made. Extrapolation at the high-frequency limit usually presents few issues because the impedance becomes nonreactive at frequencies as low as 10 kHz in most cases [82]. On the other hand, reactance is still commonly observed at frequencies as low as 10⁻³ Hz [82]. Therefore, special precautions must be taken to obtain reliable data and to avoid possible artifacts [17, 83]. Furthermore, the measurement cycle time depends on the frequency range used, in particular the low frequencies. For instance, a single-frequency cycle at 10⁻³ Hz needs about 15 min of testing time. A high-to-low-frequency analysis moving down to 10⁻³ Hz frequency likely requires more than 2 hours of scan time. In order to perform a normal standard corrosion monitoring with the EIS technique, assistance is needed to optimize the use of the high-frequency data and reduce measurement time. There is a constant need to improve data processing and analysis in order to minimize uncertainties and to allow the EIS technique becoming user-friendly for corrosion monitoring in both laboratory and field facilities, though it must be emphasized that the need for an easy-to-deploy field instrument has always been an obstacle to online corrosion monitoring with the EIS technique.

An alternative to the impedance model in the Nyquist diagram involves the conversion of the impedance into a complex number. The impedance can thus be designated by an amplitude, |Z|, and a phase shift, ϕ, or by the sum of the real (Z′) and imaginary (Z″) components, such that,Z(ω)=Z'(ω)+jZ”(ω)Zω=Z′ω+jZ”ω E18

Both the log|Z| data and the phase angle ϕ are plotted against the angular frequency, log ω, of the excitation signal, a format which substitutes for the Nyquist diagram, i.e., the so-called Bode diagram. Figure 9 shows how the same data (Nyquist plot) appears in a Bode plot format with respect to the equivalent circuit of Figure 7.

Highest (ω_H) and lowest frequencies (ω_L) can be readily determined. As shown in Figure 9, Z is independent of the frequency at ω_H and ω_L, limit values represented by horizontal lines. From these lines, values of R_S and (R_S + R_CT) can be measured. This analysis forms the basis of the corrosion monitoring as proposed by Tsuru et al. [74] to allow the determination of |Z| at each frequency in the horizontal portions of the Bode diagram.

Sometimes, it is not convenient to perform impedance measurements at very low frequencies (as in DC techniques such as linear polarization). However, it is still possible to extrapolate the polarization resistance, R_P, from the Bode diagram. In Figure 9, the low- and high-frequency breakpoints (i.e., ω_L and ω_H, respectively) can be determined from the 45° phase angle Bode diagram (see the pseudo-Gaussian curve). The intersection point A can be determined from the log ω_H and R_S. By extrapolating from A toward the central linear portion of the |Z| curve, a linear line can be determined. On this line, point B is obtained at log ω_L.With the projection of point B to the log|Z| axis, the total resistance (R_S + R_CT) can be measured. In this way, R_P can be determined. At intermediate frequencies, the capacitor affects the response of the overall RC circuit.

The situation struggles when diffusion processes govern the corrosion behavior. A convenient way to deal with this complication is to add a Warburg impedance. The latter describes the impedance of the concentration and diffusion processes in the equivalent circuit as shown in Figure 10.

The Warburg impedance, Z_W, is given by the equationZW=σwω√−jσwω√ZW=σwω−jσwω E19

where σ_w is the Warburg coefficient.

Eq. (19) implies that, whatever the frequency, the real and imaginary parts of the Warburg impedance are equal and inversely proportional to σ_w^½. In the Nyquist plot, this impedance will result in a straight line at a constant phase angle at 45°, as shown in Figure 10. However, the effect of the Warburg impedance can complicate the correct estimate of the R_P value in certain cases. Therefore, the impedance data must be numerically adjusted to fit with the correct model to facilitate the extraction of the total resistance (R_S + R_P) from the abscissa or by using an appropriate modeling software. However, the situation can readily become more complicated if other effects, such as time-constant dispersion, adsorption processes, and so on, are taken into account; the time-constant dispersion, which can be caused by inhomogeneities in the corroded surface, results in a depression of the semicircle [75, 76]. Adsorption, on the other hand, can reveal a second semicircle at low frequencies [77]. All these effects can occur simultaneously [27], making the interpretation of impedance data rather more difficult [78, 84] (Figure 11).

There is a need for an appropriate model equivalent circuit beyond the existing model standards to remedy that shortcoming. An “appropriate” model is understood not only as a good fit of the impedance data but also as a rational explanation of the underlying corrosion mechanism. Moreover, the requirement of sophisticated AC frequency generator and analyzer and the time needed to acquire the complete impedance diagram (particularly in the range of low frequency) impose a serious limitation in real-time corrosion monitoring applications. Other disadvantages include a priori knowledge of the Tafel parameters in order to convert the polarization resistance into a corrosion rate and the fact that it is too difficult to detect and monitor localized corrosion, even if such applications have been explored [85, 86].

1.4.3. Illustrative examples of the application of EIS in corrosion and tribocorrosion systems

Attempts were made to use the EIS technique in corrosion and corrosion-wear monitoring of Fe-31% Ni electrode immersed in 0.5 M H₂SO₄ [87]. The corresponding Nyquist impedance diagrams were recorded at an anodic potential of −675 mV/SSE (+100 mV/open-circuit potential) before and during sliding-corrosion as shown in Figure 12. At this potential, the prevailing reaction is dissolution. At high frequency, under free corrosion and unloaded conditions, the capacitive arc reveals the influence of the dielectric properties of the electrochemical double layer and the charge transfer due to electrochemical reactions. Under sliding conditions, the size of the capacitive arc increases, suggesting an increase in the transfer resistance and a decrease in the reactivity of the surface, consistent with the effect of mechanical straining of the worn surface. At low frequency, however, the inductive arc indicates the relaxation of the surface concentration of adsorbed intermediate species involved in the dissolution mechanism. Under corrosion-wear conditions, the kinetics of the dissolution process is apparently modified, as revealed by the second inductive loop in the diagram. Given that not all of these investigations have been concluded, a detailed explanation is not straightforward, and further research is recommended. Although these impedance measurements provide a convenient way to study the mechanism of electrochemical reactions involved in tribocorrosion processes, still the interpretation of impedance records during sliding-corrosion experiments is rather difficult because of the heterogeneous surface-state condition. Actually, a nonuniform distribution of the electrochemical impedance on the steel surface must be taken into account. The action of friction can be analyzed thoroughly if this distribution is known. Equivalent electrical circuit models or finite element models could be used to obtain impedance distributions and to calculate the overall impedance.

2. Comparison of the techniques for the assessment of corrosion rate

The transposition of the foregoing electrochemical techniques to corrosion situations is illustrated in [63] for the assessment of corrosion rate. The results presented in Table 1 summarize the data generated by the different techniques for Fe electrodes in 0.5 M H₂SO₄ under well-controlled conditions and their corresponding corrosion current densities, resistances, and required parameters which determined those data.

Table 1.

Data outcomes determined by different electrochemical techniques on Fe in 0.5 M H₂SO₄.

Reproduced from [63] with permission from Wiley Online Library.

All these techniques monitor the electrode response following the stimulation by a potential variation in time or frequency domain with the exception of the electrochemical noise analysis technique. The extent of the potential stimulation and the current response decreases in the order from Tafel extrapolation method, linear polarization, EIS, to electrochemical noise. Each of these techniques provides the necessary information for a given corroding system, and there are trade-offs involved in the comparative decision of which is the best to use.

Author: Abdenacer Berradja

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STEP1: Open the absorption graph of the material, which is obtained from the UV Vis spectroscopy.

Theory Behind Calculations: UV Vis Spectroscopy absorption peak means the Electrons are absorbing the Energy at some specific wavelength. Electrons are absorbing Energy means the Electrons are going to excited state from its ground state. Electrons are going to excited state from its ground state means the material is having band gap, thus which can be determine by absorption wavelength.

Energy Equation of Quantum Mechanics:

Energy (E) = Planks Constant (h) * Speed of Light (C) / Wavelength (λ)

Where, Energy (E) = Band gap, Planks constant (h) = 6.626×10^-34 Joules sec, Velocity of Light (C) = 2.99×10^8 meter/sec and Wavelength (λ) = Absorption peak value. Also 1eV = 1.6×10^-19 Joules (Conversion factor)

By this formula band gap can be calculated easily, from UV Vis spectroscopy absorption peak.

The basis of the spectrophotometer
In general, the amount of light absorbed by a substance in a liquid state is directly related to the concentration of that substance in the liquid. If the sample is solid, it must first be dissolved in a clear solvent to be measurable. The sample solvent (known as the control) is usually considered without adsorption or in practice its partial adsorption is less than the total adsorption (sample with solvent). The sample with the solvent is usually poured into a clear glass container or a quartz container and placed in front of the light passing through the spectrophotometer. This dish is called Cell or Quvette. Of course, using add-ons on the spectrometer device, solid or gas samples can also be analyzed, which will be discussed in detail in the articles of this article.

The spectrophotometer uses a tungsten lamp to produce visible light and a deuterium lamp to produce ultraviolet or UV light. The normally measured wavelength range in this device is from 1100 nm to 190 nm. More equipped devices are usually used to measure areas outside this range. Given that a particular molecule may absorb light in a well-defined region of the wavelength range, the light produced must be separated and adjustable to the component wavelengths in a given region. Grating Mirror or prism mirror is used to uniformize the light in the spectrophotometer.

Parts of the ultraviolet and visible spectrometer
the source of light
Prism or grating mirror
Monochromator
Detector, detector or photodiode
Processor
The following figure shows an overview of how this device works.

Visible ultraviolet spectrophotometer
Spectrophotometer device diagram

In the visible and ultraviolet spectrometer, after the light passes through the solution, the remaining light sample is inside a detector of Photomultiplier or Photodiode type and after computer processing as a number of one hundred as the percentage of light transmission or its logarithm with The title of the light absorption number appears on the display. Calculations of light absorption or transmission follow Lambert Beer’s law. Mathematically, the amount of light I0 passes through an environment with length X and concentration C, the intensity of the residual light I after passing through the environment is:
I = I0e-KCX
In this relation, K will be a relative constant (absorption coefficient). Therefore, the absorption of the environment or A is obtained as follows:
A = log (I0 / I) = KCX

Spectrophotometer is available in two types of single beam single beam and double beam double beam. The single beam system compares the light absorbed after placing the sample in the device with the main light before placing the sample in the device. One of the advantages of this system is its simplicity, smallness and cheapness, and one of its disadvantages is a small error due to the instability of the measurement environment.

But the two-beam system has two beams, one of which goes to the detector at the same time and the other passes through the sample and the difference between the two is calculated. One of the advantages of this system is more accuracy compared to the single-beam system, and its disadvantages are its complexity and more expensive price. The image below is a schematic of a 2-ray spectrophotometer.

Depending on the spectral region in which the spectral region is performed and which radiation properties (absorption, emission, transmission, scattering, reflection, etc.) are examined, the type of electronic transmissions and consequently the type of spectroscopy and device will be different.
In nasal spectroscopy, absorption is a process in which a chemical species in a transparent medium selectively attenuates (reduces its intensity) certain frequencies of electromagnetic radiation. In the ultraviolet / visible region, the energy of electromagnetic radiation is such that it causes electron transitions in valence electrons. For atoms and ions in the elemental state, the energy of each level is due to the movement of electrons around the nucleus. These states of energy are called electronic states. In addition to having electron energy levels, molecules also have vibrational energy levels and rotational energy levels. These alignments result from the vibration between the atoms in the molecule and from the rotation of the molecules around their own center of mass in space, respectively. In the energy level level diagram, several rotational levels are placed between the two vibrational levels and several vibrational levels are placed between the electronic level levels. Accordingly, each electronic level has vibrating levels and each vibrating level in turn has its own rotational levels. Each of these energy states is about ten times smaller than each other

1. EIS Spectrum Analyser

EIS Spectrum Analyser is a standalone program for analysis and simulation of impedance spectra. The analyser routine is based on algorithms of the PDEIS spectrometer. In the original (potentiodynamic) version the impedance data analysis is applied on a 3D spectrum and gives dependences of the ac response components on electrode potential.

This standalone program has been adapted to solve a wide range of tasks in the common (stationary) impedance spectroscopy. In addition to data fitting to equivalent circuits with resistors, capacitors, inductors, constant phase, Warburg (3 types), user-defined and Gerischer elements, the EIS Spectrum Analyser provides various tests for data consistency and quality of fit. It has also a built-in impedance spectra simulation routine, tools for impedance data processing (subtraction of circuit elements and subcircuits, normalisation for electrode surface area) and plotting in various formats. The program is free for noncommercial use.

See: http://www.abc.chemistry.bsu.by/vi/analyser/

2. ZsimpWin

ZSimpWin is a EIS Data Analysis program that does not require user-input on initial values. ZSimpWin is an Electrochemical Impedance Spectroscopy (EIS) Data Analysis Software integrated with the 
VersaStudio software to provide straightforward and versatile equivalent circuit model fitting.  Innovative concepts have been implemented to achieve the following performance:

• Minimal user input: The user specifies a job by selecting a model for an impedance data set, and simply requests execution to ZSimpWin.  
• Automatic analysis: Parameters associated with the selected model are determined automatically. ZSimpWin assigns an initial guess of these parameters (default = Auto Setup option), starts computation using the initial guess, finds results, improves these results a number of times until desired results are obtained, and then saves the final results. 
• Batch Analysis: Setup a batch by including multiple jobs and process in sequence.  
• Output results in various forms: Results consist of plots, estimated parameters, and historical records of computation process.  Each or several combinations can be printed or copied to Windows clipboard. 
  
• Requires only mouse button clicks:  The whole process requires no entry of numbers or character strings.                                                                
• Compatible with Windows 10, 8 , 7 and XP.

See: https://www.ameteksi.com/products/software/zsimpwin

3. Zview

ZView software from Scribner Associates offers best-in-class equivalent circuit modeling. Fit common circuits instantly, generate publication-quality graphs quickly. ZView integrates easily with SAI measurement softwares, and supports testing hardware from Solartron, PAR, and others. Increase your data processing efficiency quickly and easily with ZView.

See: https://sai-zview1.software.informer.com/3.4/

Introduction of EIS

Electrochemical impedance spectroscopy (EIS) is one of the most powerful methods in the study of corrosion. The EIS method can be used to measure the rate or rate of corrosion, monitor corrosion, determine coating integrity, and study the mechanism of reactions. In this article, which is a compilation, translation and purification of references [1] and [2], the applications, limitations and benefits of this method are introduced. EIS is usually performed by applying an AC current signal to a state-steady electrochemical system and then measuring the current response. Because the amount of disturbance applied, the AC signal, is a small excitation signal, EIS is essentially a non-destructive technique. To apply this method requires a geometrically corroded cell that includes a reference electrode, as well as equipment capable of measuring and recording the electrical response of an electrochemical cell over a wide range of applied AC frequencies. When a small sine voltage is applied to an electrochemical system according to Equation 9, a sine current response in the form of Equation 2 will be observed. Due to the lack of rapid response of relaxation processes or the release of dipoles, the rotation of bipolar components in response to the applied alternating electric field results in a phase change.

Typical measurements in EIS are usually made in a three-electrode system, as shown in Figure 9. The entire set includes an electrochemical cell, a frequency generator, a frequency response analyzer (FRA), and a computer that is used to control experiments and store information. A potentiostat is used to control the electrode potential. The FRA is the heart of the system that calculates the imaginary and real parts of impedance. The frequency studied is usually in the cell range. 0.01–100,000 Hz (cycles / s) Electrochemical, the test material is embedded as an electrode working. Electrode counters, which must be neutral and not involved in the electrochemical reaction, are usually made of Pt, gold, or graphite. Reference electrodes are usually conventional saturated calomel electrodes (SCE) or AgCl / Ag electrodes. However, in many applications, such as thin electrolyte layers or in high temperature environments, conventional reference electrodes do not work properly. In these cases, systems without conventional reference electrodes should be used. As an example, we can refer to the two-electrode system, which usually consists of two identical electrodes consisting of test materials (Figure 2-a) and is widely used in atmospheric corrosion monitoring [5. [Figure 2-b) Indicates that it is used to monitor high-corrosion corrosion. , Multi-electrode array (Figure 2-c) can be used for EIS monitoring.

An uncompensated electrolyte resistance (Rs), a specific capacitance value related to the coating applied to the metal surface (Cc), a hole resistance in the coating of resistance pathways (pore solution resistance) (Rcp) in the coating where ions are transported, a The specific capacitance corresponding to the double layer in the solution / metal (Cdl) and a resistance (Rp) which is the resistance of the charge transfer process (ie corrosion), and in other words, the resistance to polarization at the solution / metal interface. In Beaunier rectified circuits, usually other additional components, such as the constant phase element (CPE), the phase component of the inductance or induction coefficient (L) and the resistor (W (Warburg,) replace the resistor or capacitor. Special capacitance, accuracy and quality of experimental data fitting with these circuits are improved, but the physical interpretation of the results will be ambiguous, this is because the CPE module can not be easily obtained with capacitor capacitance, and the capacity power calculation is calculated. Capacitor from CPE parameters requires accurate knowledge of the physical reasons for CPE behavior [7.] An example of a Nyquist diagram and its equivalent wind diagram in doubt ل 4 is given. The position of the equivalent circuit components in these diagrams is given on each diagram. In addition to common, simple equivalent circuit models, more complex physical models are sometimes used to interpret EIS data obtained from more complex systems. An example is the line transmission model (TML), which was first used by Levie de in his research on porous electrodes [11] [TML model and its modified models for analyzing EIS data on atmospheric corrosion under electrolyte layers Thin [5] as well as stress corrosion [12] have been used.

Atmospheric corrosion is an electrochemical process that usually occurs beneath a thin electrolyte surface layer, in the presence or absence of salt contaminants and dissolved gases in these layers. It has been shown that the atmospheric corrosion rate of metals depends on the thickness of the electrolyte thin film. The thickness of the electrolyte layer affects the rate of oxygen transfer through the electrolyte layer and the dissolution of corrosion products. The rate of oxygen transfer determines the rate of cathodic reaction (in neutral and alkaline solutions) and the dissolution of corrosion products determines the anodic process. Monitoring or corrosion of thin electrolytic films using conventional electrochemical methods is challenging The electrolyte is thin, very high, leading to a sharp drop in ohmic potential and a non-uniform current distribution that makes it difficult to measure the corrosion rate [5. The solution resistance is estimated from the impedance measured in the high frequency range of the EIS spectrum, and the sum of the resistivity (Rp) and the solution resistance (RS) from the impedance in the low frequency range. Figure 4b: The calculated resistive palliation is then converted to the corrosion rate of the metal. To study atmospheric corrosion of the metal surface under thin electrolytic layers (100010-1000 ~) by EIS, it is possible to expose the corrosion cell to the atmosphere. weather Use outside or use laboratory-drier simulation cycles [19–13,10,9,5. Used in epoxy resin (Figure 2-A) to make cells. The study can be done in two ways: either the impedance spectrum is recorded over a wide range of applied frequencies or the impedance value is checked continuously at two constant frequencies. The study of EIS spectrum in a wide frequency range has shown that a one-dimensional equivalent circuit model called TML can be used to model the corrosion rate in these systems [5. Palrization is calculated from the impedance difference measured at the above two frequencies. The corrosion rate is then calculated using the polarization resistance [5]. Nishikata et al. [5] also used shoulder-shaped electrodes to study atmospheric corrosion to EIS. Impedance information was monitored at 10 mHz and 10 kHz. The results showed that the inverse of the mean impedance at low frequency completely corresponds to the corrosion rate obtained by gravimetry. Wetting of Time also occurs when the amount of solution conductivity or high frequency impedance image (Rs image) exceeds a threshold value. One of the disadvantages of this method in the study of atmospheric corrosion is that if the metal surface is covered with a thick layer of corrosion products, the low frequency impedance can not be equated to the polarization resistance. Finally, Ma et al. [20] used a complex multi-electrode system to study atmospheric corrosion and found the results to be more accurate than two-electrode systems. 3.2 Corrosion of reinforced concrete Rebar (in concrete is the main reason for reducing the life of reinforced concrete structures that are exposed to strong corrosive environments) such as marine environment. Therefore, reinforcement corrosion monitoring is very important to assess the health status of reinforced concrete. Various methods are used to evaluate corrosion in reinforced concrete, and electrochemical methods are among the most common. Among these, EIS is an attractive technique because, as mentioned earlier, it is almost a non-destructive method. In addition, EIS is suitable for environments with very high strength, such as concrete, because it is essentially a transient method and does not require the system to be in a stable state [21. [In steel systems (reinforcement) / Concrete, information Various parameters such as the presence of surface films, concrete properties, joint joint corrosion and mass transfer phenomena can be obtained from the EIS method [21. [22] [In addition, the high-frequency impedance of information in Moore Provides dielectric properties of concrete, and low-frequency impedance information on the properties of passive films (surface oxide layers) on steel. Studies that began three decades ago have proven the validity of EIS as a technique for studying rebar corrosion in concrete, both experimentally and theoretically. John et al. (9189) monitored corrosion of rebar in high porosity concrete using EIS. They obtained both the corrosion rate of the steel rebars and the information on the steel surface layers. Later, more fundamental work was done by McDonald et al. To establish the application of EIS in the detection of rebar corrosion in concrete [3]. In this work, the rebar was simulated as a one-dimensional electrical transmission line. Their results show that imaginary and real components of impedance and phase angle can be used to detect corrosion of rebar embedded in concrete, but this is only possible at very low frequencies (for example, 1 mHz). It was also found that monitoring the peak voltage at the concrete surface just above the rebar helps to fully detect corrosion.

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In this course the general introduction to Raman spectroscopy and microscopy will be provided and practical tips as well as examples will be given. The capability of Raman spectroscopy for the analysis of real-life samples (paint components, clays, coating materials, etc.) taken from historical and archaeological objects will be discussed.

1. Principles of Raman spectroscopy

Raman spectroscopy is widely used in the investigation of cultural heritage materials due to its high spatial resolution (typically in the range of 1 to 10 µm), large amount of obtainable information, non-destructivity and ability to perform in-situ analysis.^1,2 With Raman spectroscopy it’s possible to analyse various materials: minerals, inorganic and organic pigments, binding media, varnishes, ceramics, plastics, textile fibres etc.²

The following video explains the principles and instrumentation of Raman spectroscopy.https://www.uttv.ee/embed?id=29055

Similarly to infrared spectroscopy, Raman spectroscopy is classified as vibrational spectroscopy.³ Raman spectroscopy is based on Raman scattering (or Raman effect) that reveals the vibrational, rotational and other low frequency modes of molecules⁴. In this technique, the sample is exposed to an intense beam of monochromatic light (typically a laser beam) in the frequency range of visible, near-infrared or near-ultraviolet region.⁵ The electromagnetic radiation, interacting with a substance, can be transmitted, absorbed, or scattered⁶. When the monochromatic radiation is scattered by molecules, the majority of the radiation undergoes the common Rayleigh scattering (radiation’s  frequency/wavelength is unchanged). However, a small fraction of the scattered radiation is observed to have a slightly different frequency from that of the incident radiation. This is known as the Raman effect⁷. The Raman lines show up pairwise. The dominant Stokes lines have a lower frequency (longer wavelength) than the initial radiation, whereas the weaker (often nondetectable) anti-Stokes lines have a higher frequency (shorter wavelength).^4,5 The frequency shifts are virtually independent of the excitation wavelength and are characteristic of the particular substance/molecule. Usually one only records the relatively strong Stokes lines, which therefore are attributed a positive frequency shift. Such spectral coordinate is called the Raman shift and measured in wavenumbers (in cm^-1).⁴ See scheme in Figure 1.

Figure 1. Scheme of Raman scattering.

In Raman spectroscopy, as it is a scattering technique, samples are simply placed in the laser beam and the scattered radiation is collected and analysed⁸. Raman spectrometer measures the wavelength-dependent intensity of the inelastically scattered light.

The obtained Raman spectra are essentially vibrational spectra. Hence, if presented in the Raman shift scale, they are directly comparable to corresponding infrared absorption spectra (see Figure 2). However, Raman spectrum arises in a different manner and the rules, which vibrations are Raman-active (and thus produce signals in the spectrum), are different. It turns out that a vibration is Raman-active (i.e. revealed as a spectral line in the Raman spectrum), if the polarizability of the molecule changes during the vibration.⁷ It often happens that vibrations that are active (or give high-intensity signals) in Raman scattering are inactive (or give low-intensity signals) in the infrared, and vice versa.⁷Therefore, Raman spectra often provide complementary information to IR spectra.

Figure 2. Raman (laser 514.5 nm) and IR spectra of benzene.

1.1. Instrumentation

There are two types of Raman spectrometers: dispersive spectrometers (based on the use of diffraction grating) and interferometer containing Fourier-transform Raman spectrometers (FT-Raman)⁹.

In general the main components of Raman spectrometers are presented on the following scheme:

In Raman spectroscopy, the choice of excitation wavelength and intensity is very important. Different wavelengths are suitable for the analysis of different types of material. The wavelength will affect the Raman intensity, spatial resolution, background fluorescence, and potential damage to the sample. Almost exclusively lasers are used as excitation sources, because they are highly monochromatic, give high-intensity radiation and can be efficiently focused due to their high coherence. Only continuous wave (CW) lasers are used, as pulsed lasers easily damage the sample. Some popular CW lasers are presented in Table 1. Traditionally, laser wavelengths up to 830 nm have been used in dispersive instruments while the 1064 nm laser line has been employed in FT-Raman setups. With the availability of sensitive InGaAs array detectors, it has become meaningful to use also the 1064 nm lasers with dispersive Raman instruments.

Table 1. Laser sources for Raman spectroscopy.

Raman scattering efficiency decreases with increasing excitation wavelength as λ⁻⁴. However, short-wavelength lasers more easily induce fluorescence, absorb in the sample or cause other undesirable effects due to their high photon energy. Hence, most common laser wavelengths in Raman spectroscopy are in the visible and NIR region (such as 633 or 785 nm) which offer low fluorescence whilst retaining relatively high Raman intensity. For samples which exhibit fluorescence even under red excitation (for example dyes), the 1064 nm laser may be needed. While near-infrared lasers have a smaller photon energy, compared to visible lasers, they are usually more powerful, in order to compensate for the reduced Raman scattering efficiency. Therefore, they may still damage the sample. It is especially important for strongly absorbing (black) samples, in which case the UV/visible lasers (operating at lower intensities) may yield a stronger Raman signal.

Dispersive Raman spectrometers

A dispersive spectrometer utilizes a diffraction grating to angularly disperse the light. As a result, at the detector plane, different wavelengths become spatially separated. Nevertheless, prior to entering the spectrometer, the incoming light should go through a special edge or notch filter to suppress the primary (Raman-scattered) light and thereby reduce the scattering inside the spectrometer. A matrix detector is used to record the dispersed spectrum. Typically, a silicon-based cooled CCD is used, which is very sensitive in the visible and NIR region (up to 1100 nm).

FT-Raman spectrometers

Commercial FT-Raman spectrometers were introduced in the late 1980s¹⁰. Their operating principle is similar to that of FTIR spectrometers and is based on an interferometer. As the Raman-scattered light enters the instrument, the interferometer selectively modulates the individual spectral components by systematically changing an optical path length difference. The resulting beam of light is recorded by a point detector. FT-Raman is superior to a dispersive instrument in the near-IR region beyond 1000 nm. Commonly, the 1064 nm laser excitation along with germanium or indium gallium arsenide (InGaAs) detector is used. They also offer excellent wavelength accuracy and can potentially combine IR absorption and Raman measurement capacity in single instrument. However, FT-Raman frequently needs to use high laser intensities due to the reduced Raman scattering efficiency at longer wavelengths, which may damage the sample.

Different types of Raman Spectroscopy

A variety of Raman instruments and special techniques are used for the analysis of cultural heritage materials. The choice of instrument determines the sensitivity, spectral range and resolution, spatial resolution, availability of different excitation sources, and convenience of operation. 

• Micro-Raman spectrometer (or Raman microscope) is the most common bench-top Raman instrument. A high-resolution spectrometer (either dispersive or FT) and one or several laser sources are coupled through an optical microscope. The excitation beam is focused and the secondary emission is collected simultaneously by the microscope objective in backscattering geometry. A high-numerical aperture (NA) objective yields both a high spatial resolution and a high collection efficiency.
• Surface-enhanced Raman spectroscopy (SERS) involves inelastic light scattering by molecules placed close to nanometal surfaces, which amplify the scattering by plasmonic resonance. One approach is to study molecules adsorbed onto corrugated metal surfaces such as silver or gold nanoparticles¹¹. Another approach is to stimulate the molecules by a sharp metal tip. Such tip-enhanced Raman spectroscopy is typically implemented by combining a confocal microscope and a scanning probe microscope. 
• In Resonance Raman spectroscopy (RRS) the incident photon energy is close in energy to an electronic transition of a compound or material under examination. 
• In a portable Raman spectrometer, a miniature dispersive spectrometer and a small laser source are integrated into a portable, hand-held device. Hence, the instrument can be used to perform in situ analysis in museums, archives, also outdoors on archaeological sites for the analysis of mural or cave paintings. Such portable devices frequently employ a fiber-optic probes. 

1.2. Problems with Raman spectroscopy

Compared to IR absorption, the primary disadvantage of Raman spectroscopy is the fluorescent background (see Figure 3). As Raman scattering is inherently weak, one has to use an intense laser beam for excitation, and for many materials, this results in a strong fluorescence – either due to the material itself of impurities. Sometimes even trace impurities – if they are strongly fluorescent – can lead to disturbing fluorescence background. Fortunately, Raman lines are spectrally close to the laser beam whereas fluorescence has typically a large Stokes shift. 

Figure 3. Example of the fluorescence in the Raman spectrum of red lead containing paint.

Relative to the Raman signal, the fluorescent background can be highly intense and even the tail of the fluorescence band may obscure the Raman spectrum. Although the problem can be partially resolved by careful sample preparation, time resolved spectroscopy or coherent anti-Stokes Raman spectroscopy (CARS), there will always be experiments that remain difficult to perform.⁷

In addition to fluorescence, intense focused laser irradiation can cause heating and degradation of the sample. The problems are typical for organic, soft, photosensitive or dark/coloured materials whereas transparent inorganic materials have usually quite high damage threshold.

2. Analysis with Raman spectroscopy

In the following video Senior Research Fellow Dr. Valter Kiisk demonstrates and explains how to perform measurements with a typical micro-Raman spectrometer.https://www.uttv.ee/embed?id=29396

Identification of the composition of the studied material is often based on the comparison of its Raman spectrum with a spectral library of reference materials.¹² Different papers and books have been published from where Raman spectra or information about excitation wavelengths and list of wavenumbers in the Raman spectra are available ^5,13,14. Also a very valuable on-line database is made available by the Infrared & Raman Users Group (IRUG)– http://irug.org/ – from where different Raman (and also IR) spectra of cultural heritage materials can be obtained free of charge.

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Infrared (IR) spectroscopy is based on molecular vibrations caused by the oscillation of molecular dipoles. Bonds have characteristic vibrations depending on the atoms in the bond, the number of bonds and the orientation of those bonds with respect to the rest of the molecule. Thus, different molecules have specific spectra that can be collected for use in distinguishing products or identifying an unknown substance (to an extent.)

Collecting spectra through this method goes about one of three general ways. Nujol mulls and pressed pellets are typically used for collecting spectra of solids, while thin-film cells are used for solution-phase IR spectroscopy. Spectra of gases can also be obtained but will not be discussed in this guide.

Infrared Optical Materials and Handling

While it is all well and wonderful that substances can be characterized in this fashion one still has to be able to hold the substances inside of the instrument and properly prepare the samples. In an infrared spectrometer (Figure 4.2.14.2.1)

the sample to be analyzed is held in front of an infrared laser beam, in order to do this, the sample must be contained in something, consequently this means that the very container the sample is in will absorb some of the infrared beam.

This is made somewhat complicated by the fact that all materials have some sort of vibration associated with them. Thus, if the sample holder has an optical window made of something that absorbs near where your sample does, the sample might not be distinguishable from the optical window of the sample holder. The range that is not blocked by a strong absorbance is known as a window (not to be confused with the optical materials of the cell.)

Windows are an important factor to consider when choosing the method to perform an analysis, as seen in Table 4.2.14.2.1 there are a number of different materials each with their own characteristic absorption spectra and chemical properties. Keep these factors in mind when performing analyses and precious sample will be saved. For most organic compounds NaCl works well though it is susceptible to attack from moisture. For metal coordination complexes KBr, or CsI typically work well due to their large windows. If money is not a problem then diamond or sapphire can be used for plates.

Proper handling of these plates will ensure they have a long, useful life. Here follows a few simple pointers on how to handle plates:

• Avoid contact with solvents that the plates are soluble in.
• Keep the plates in a dessicator, the less water the better, even if the plates are insoluble to water.
• Handle with gloves, clean gloves.
• Avoid wiping the plates to prevent scratching.

That said, these simple guidelines will likely reduce most damage that can occur to a plate by simply holding it other faults such as dropping the plate from a sufficient height can result in more serious damage.

Preparation of Nujol Mulls

A common method of preparing solid samples for IR analysis is mulling. The principle here is by grinding the particles to below the wavelength of incident radiation that will be passing through there should be limited scattering. To suspend those tiny particles, an oil, often referred to as Nujol is used. IR-transparent salt plates are used to hold the sample in front of the beam in order to acquire data. To prepare a sample for IR analysis using a salt plate, first decide what segment of the frequency band should be studied, refer to Table 4.2.14.2.1 for the materials best suited for the sample. Figure 4.2.24.2.2 shows the materials needed for preparing a mull.

Preparing the mull is performed by taking a small portion of sample and adding approximately 10% of the sample volume worth of the oil and grinding this in an agate mortar and pestle as demonstrated in Figure 4.2.34.2.3 . The resulting mull should be transparent with no visible particles.

Another method involves dissolving the solid in a solvent and allowing it to dry in the agate pestle. If using this method ensure that all of the solvent has evaporated since the solvent bands will appear in the spectrum. Some gentle heating may assist this process. This method creates very fine particles that are of a relatively consistent size. After addition of the oil further mixing (or grinding) may be necessary.

Plates should be stored in a desiccator to prevent erosion by atmospheric moisture and should appear roughly transparent. Some materials such as silicon will not, however. Gently rinse the plates with hexanes to wash any residual material off of the plates. Removing the plates from the desiccator and cleaning them should follow the preparation of the mull in order to maintain the integrity of the salt plates. Of course, if the plate is not soluble in water then it is still a good idea just to prevent the threat of mechanical trauma or a stray jet of acetone from a wash bottle.

Once the mull has been prepared, add a drop to one IR plate (Figure 4.2.44.2.4 ), place the second plate on top of the drop and give it a quarter turn in order to evenly coat the plate surface as seen in Figure 4.2.54.2.5 . Place it into the spectrometer and acquire the desired data.

Always handle with gloves and preferably away from any sinks, faucets, or other sources of running or spraying water.

Spectra acquired by this method will have strong C-H absorption bands throughout several ranges 3,000 – 2,800 cm^-1 and 1,500 – 1,300 cm^-1 and may obscure signal.

Cleaning the plate is performed as previously mentioned with hexanes or chloroform can easily be performed by rinsing and leaving them to dry in the hood. Place the salt plates back into the desiccator as soon as reasonably possible to prevent damage. It is highly advisable to polish the plates after use, no scratches, fogging, or pits should be visible on the face of the plate. Chips, so long as they don’t cross the center of the plate are survivable but not desired. The samples of damaged salt plates in Figure 4.2.64.2.6 show common problems associated with use or potentially mishandling. Clouding, and to an extent, scratches can be polished out with an iron rouge. Areas where the crystal lattice is disturbed below the surface are impossible to fix and chips cannot be reattached.

FIgure 4.2.64.2.6 A series of plates indicating various forms of physical damage with a comparison to a good plate (Copyright: Colorado University-Boulder).

Preparation of Pellets

In an alternate method, this technique is along the same lines of the nujol mull except instead of the suspending medium being mineral oil, the suspending medium is a salt. The solid is ground into a fine powder with an agate mortar and pestle with an amount of the suspending salt. Preparing pellets with diamond for the suspending agent is somewhat illadvised considering the great hardness of the substance. Generally speaking, an amount of KBr or CsI is used for this method since they are both soft salts. Two approaches can be used to prepare pellets, one is somewhat more expensive but both usually yield decent results.

The first method is the use of a press. The salt is placed into a cylindrical holder and pressed together with a ram such as the one seen in (Figure 4.2.74.2.7 ). Afterwards, the pellet, in the holder, is placed into the instrument and spectra acquired.

An alternate, and cheaper method requires the use of a large hex nut with a 0.5 inch inner diameter, two bolts, and two wrenches such as the kit seen in Figure 4.2.84.2.8 . Step-by-step instructions for loading and using the press follows:

1. Screw one of the bolts into the nut about half way.
2. Place the salt pellet mixture into the other opening of the nut and level by tapping the assembly on a countertop.
3. Screw in the second bolt and place the assembly on its side with the bolts parallel to the countertop. Place one of the wrenches on the bolt on the right side with the handle aiming towards yourself.
4. Take the second wrench and place it on the other bolt so that it attaches with an angle from the table of about 45 degrees.
5. The second bolt is tightened with a body weight and left to rest for several minutes. Afterwards, the bolts are removed, and the sample placed into the instrument.

Some pellet presses also have a vacuum barb such as the one seen in (Figure 4.2.84.2.8 . If your pellet press has one of these, consider using it as it will help remove air from the salt pellet as it is pressed. This ensures a more uniform pellet and removes absorbances in the collected spectrum due to air trapped in the pellet.

Preparation of Solution Cells

Solution cells (Figure 4.2.94.2.9 ) are a handy way of acquiring infrared spectra of compounds in solution and is particularly handy for monitoring reactions.

A thin-film cell consists of two salt plates with a very thin space in between them (Figure 4.2.104.2.10 ). Two channels allow liquid to be injected and then subsequently removed. The windows on these cells can be made from a variety of IR optical materials. One particularly useful one for water-based solutions is CaF₂ as it is not soluble in water.

Cleaning these cells can be performed by removing the solution, flushing with fresh solvent and gently removing the solvent by syringe. Do not blow air or nitrogen through the ports as this can cause mechanical deformation in the salt window if the pressure is high enough.

Deuterated Solvent Effects

One of the other aspects to solution-phase IR is that the solvent utilized in the cell has a characteristic absorption spectra. In some cases this can be alleviated by replacing the solvent with its deuterated sibling. The benefit here is that C-H bonds are now C-D bonds and have lower vibrational frequencies. Compiled in Figure 4.2.114.2.11 is a set of common solvents.

This effect has numerous benefits and is often applied to determining what vibrations correspond to what bond in a given molecular sample. This is often accomplished by using isotopically labeled “heavy” reagents such as ones that contain ²H, ¹⁵N, ¹⁸O, or ¹³C.

Basic Troubleshooting

There are numerous problems that can arise from improperly prepared samples, this section will go through some of the common problems and how to correct them. For this demonstration, spectra of ferrocene will be used. The molecular structure and a photograph of the brightly colored organometallic compound are shown in Figure 4.2.124.2.12 and Figure 4.2.134.2.13 .

Figure 4.2.144.2.14 illustrates what a good sample of ferrocene looks like prepared in a KBr pellet. The peaks are well defined and sharp. No peak is flattened at 0% transmittance and Christiansen scattering is not evident in the baseline.

Figure 4.2.154.2.15 illustrates a sample with some peaks with intensities that are saturated and lose resolution making peak-picking difficult. In order to correct for this problem, scrape some of the sample off of the salt plate with a rubber spatula and reseat the opposite plate. By applying a thinner layer of sample one can improve the resolution of strongly absorbing vibrations.

Figure 4.2.164.2.16 illustrates a sample in which too much mineral oil was added to the mull so that the C-H bonds are far more intense than the actual sample. This can be remedied by removing the sample from the plate, grinding more sample and adding a smaller amount of the mull to the plate. Another possible way of doing this is if the sample is insoluble in hexanes, add a little to the mull and wick away the hexane-oil mixture to leave a dry solid sample. Apply a small portion of oil and replate.

Figure 4.2.174.2.17 illustrates the result of particles being too large and scattering light. To remedy this, remove the mull and grind further or else use the solvent deposition technique described earlier.

Characteristic IR Vibrational Modes for Hydrocarbon Compounds

Table4.2.34.2.3 The stretching bands for alkenes.

Fourier Transform Infrared Spectroscopy of Metal Ligand Complexes

The infrared (IR) range of the electromagnetic spectrum is usually divided into three regions:

• The far-infrared is always used for rotational spectroscopy, with wavenumber range 400 – 10 cm⁻¹ and lower energy.
• The mid-infrared is suitable for a detection of the fundamental vibrations and associated rotational-vibrational structure with the frequency range approximately 4000 – 400 cm⁻¹.
• The near-Infrared with higher energy and wave number range 14000 – 4000 cm⁻¹, can excite overtone or higher harmonic vibrations.

For classical light material interaction theory, if a molecule can interact with an electromagnetic field and absorb a photon of certain frequency, the transient dipole of molecular functional group must oscillate at that frequency. Correspondingly, this transition dipole moment must be a non-zero value, however, some special vibration can be IR inactive for the stretching motion of a homonuclear diatomic molecule and vibrations do not affect the molecule’s dipole moment (e.g., N₂).

Mechanistic Description of the Vibrations of Polyatomic Molecules

A molecule can vibrate in many ways, and each way is called a “vibrational mode”. If a molecule has N atoms, linear molecules have 3N-5 degrees of vibrational modes whereas nonlinear molecules have 3N-6 degrees of vibrational modes. Take H₂O for example; a single molecule of H₂O has O-H bending mode (Figure 4.2.184.2.18 a), antisymmetric stretching mode (Figure 4.2.184.2.18 b), and symmetric stretching mode (Figure 4.2.184.2.18 c).

If a diatomic molecule has a harmonic vibration with the energy, 4.2.14.2.1 , where n+¹/₂ with n = 0, 1, 2 …). The motion of the atoms can be determined by the force equation, 4.2.24.2.2 , where k is the force constant). The vibration frequency can be described by 4.2.34.2.3 . In which m is actually the reduced mass (m_red or μ), which is determined from the mass m₁ and m₂ of the two atoms, 4.2.44.2.4 .En = −hv(4.2.1)(4.2.1)En = −hvF = −kx(4.2.2)(4.2.2)F = −kxω = (k/m)1/2(4.2.3)(4.2.3)ω = (k/m)1/2mred = μ = m1m2m1 + m2(4.2.4)(4.2.4)mred = μ = m1m2m1 + m2

Principle of Absorption Bands

In IR spectrum, absorption information is generally presented in the form of both wavenumber and absorption intensity or percent transmittance. The spectrum is generally showing wavenumber (cm^-1) as the x-axis and absorption intensity or percent transmittance as the y-axis.

Transmittance, “T”, is the ratio of radiant power transmitted by the sample (I) to the radiant power incident on the sample (I₀). Absorbance (A) is the logarithm to the base 10 of the reciprocal of the transmittance (T). The absorption intensity of molecule vibration can be determined by the Lambert-Beer Law, \label{5} . In this equation, the transmittance spectra ranges from 0 to 100%, and it can provide clear contrast between intensities of strong and weak bands. Absorbance ranges from infinity to zero. The absorption of molecules can be determined by several components. In the absorption equation, ε is called molar extinction coefficient, which is related to the molecule behavior itself, mainly the transition dipole moment, c is the concentration of the sample, and l is the sample length. Line width can be determined by the interaction with surroundings.A = log(1/T) = −log(I/I0) = εcl(4.2.5)(4.2.5)A = log(1/T) = −log(I/I0) = εcl

The Infrared Spectrometer

As shown in Figure 4.2.194.2.19 , there are mainly four parts for fourier transform infrared spectrometer (FTIR):

• Light source. Infrared energy is emitted from a glowing black-body source as continuous radiations.
• Interferometer. It contains the interferometer, the beam splitter, the fixed mirror and the moving mirror. The beam splittertakes the incoming infrared beam and divides it into two optical beams. One beam reflects off the fixed mirror. The other beam reflects off of the moving mirror which moves a very short distance. After the divided beams are reflected from the two mirrors, they meet each other again at the beam splitter. Therefore, an interference pattern is generated by the changes in the relative position of the moving mirror to the fixed mirror. The resulting beam then passes through the sample and is eventually focused on the detector.
• Sample compartment. It is the place where the beam is transmitted through the sample. In the sample compartment, specific frequencies of energy are absorbed.
• Detector. The beam finally passes to the detector for final measurement. The two most popular detectors for a FTIR spectrometer are deuterated triglycine sulfate (pyroelectric detector) and mercury cadmium telluride (photon or quantum detector). The measured signal is sent to the computer where the Fourier transformation takes place.

A Typical Application: the detection of metal ligand complexes

Some General Absorption peaks for common types of functional groups

It is well known that all molecules chemicals have distinct absorption regions in the IR spectrum. Table 4.2.74.2.7 shows the absorption frequencies of common types of functional groups. For systematic evaluation, the IR spectrum is commonly divided into some sub-regions.

• In the region of 4000 – 2000 cm^–1, the appearance of absorption bands usually comes from stretching vibrations between hydrogen and other atoms. The O-H and N-H stretching frequencies range from 3700 – 3000 cm^–1. If hydrogen bond forms between O-H and other group, it generally caused peak line shape broadening and shifting to lower frequencies. The C-H stretching bands occur in the region of 3300 – 2800 cm^–1. The acetylenic C-H exhibits strong absorption at around 3300 cm^–1. Alkene and aromatic C-H stretch vibrations absorb at 3200-3000 cm^–1. Generally, asymmetric vibrational stretch frequency of alkene C-H is around 3150 cm^-1, and symmetric vibrational stretch frequency is between 3100 cm^-1 and 3000 cm^-1. The saturated aliphatic C-H stretching bands range from 3000 – 2850 cm^–1, with absorption intensities that are proportional to the number of C-H bonds. Aldehydes often show two sharp C-H stretching absorption bands at 2900 – 2700 cm^–1. However, in water solution, C-H vibrational stretch is much lower than in non-polar solution. It means that the strong polarity solution can greatly reduce the transition dipole moment of C-H vibration.
• Furthermore, the stretching vibrations frequencies between hydrogen and other heteroatoms are between 2600 – 2000cm^-1, for example, S-H at 2600 – 2550 cm^–1, P-H at 2440 – 2275 cm^–1, Si-H at 2250 – 2100 cm^–1.
• The absorption bands at the 2300 – 1850 cm^–1 region usually present only from triple bonds, such as C≡C at 2260 – 2100 cm^–1, C≡N at 2260 – 2000 cm^–1, diazonium salts –N≡N at approximately 2260 cm^–1, allenes C=C=C at 2000 – 1900 cm^–1. The peaks of these groups are all have strong absorption intensities. The 1950 – 1450 cm^–1 region stands for double-bonded functional groups vibrational stretching.
• Most carbonyl C=O stretching bands range from 1870 – 1550 cm^–1, and the peak intensities are from mean to strong. Conjugation, ring size, hydrogen bonding, and steric and electronic effects can lead to significant shifts in absorption frequencies. Furthermore, if carbonyl links with electron-withdrawing group, such as acid chlorides and acid anhydrides, it would give rise to IR bands at 1850 – 1750 cm^–1. Ketones usually display stretching bands at 1715 cm^-1.
• None conjugated aliphatic C=C and C=N have absorption bands at 1690 – 1620 cm^–1. Besides, around 1430 and 1370cm^-1, there are two identical peaks presenting C-H bending.
• The region from 1300 – 910 cm^–1 always includes the contributions from skeleton C-O and C-C vibrational stretches, giving additional molecular structural information correlated with higher frequency areas. For example, ethyl acetate not only shows its carbonyl stretch at 1750 – 1735 cm^–1, but also exhibits its identical absorption peaks at 1300 – 1000 cm^–1 from the skeleton vibration of C-O and C-C stretches.

General Introduction of Metal Ligand Complex

The metal electrons fill into the molecular orbital of ligands (CN, CO, etc.) to form complex compound. As shown in Figure 4.2.204.2.20 , a simple molecular orbital diagram for CO can be used to explain the binding mechanism.

The CO and metal can bind with three ways:

• Donation of a pair of electrons from the C-O σ* orbital into an empty metal orbital (Figure 4.2.214.2.21 a).
• Donation from a metal d orbital into the C-O π* orbital to form a M-to-CO π-back bond (Figure 4.2.214.2.21 b).
• Under some conditions a pair of carbon π electron can donate into an empty metal d-orbital.

Some Factors to Include the Band Shifts and Strength

Herein, we mainly consider two properties: ligand stretch frequency and their absorption intensity. Take the ligand CO for example again. The frequency shift of the carbonyl peaks in the IR mainly depends on the bonding mode of the CO (terminal or bridging) and electron density on the metal. The intensity and peak numbers of the carbonyl bands depends on some factors: CO ligands numbers, geometry of the metal ligand complex and fermi resonance.

Effect on Electron Density on Metal

As shown in Table 4.2.84.2.8 , a greater charge on the metal center result in the CO stretches vibration frequency decreasing. For example, [Ag(CO)]+show higher frequency of CO than free CO, which indicates a strengthening o

f the CO bond. σ donation removes electron density from the nonbonding HOMO of CO. From Figure, it is clear that the HOMO has a small amount of anti-bonding property, so removal of an electron actually increases (slightly) the CO bond strength. Therefore, the effect of charge and electronegativity depends on the amount of metal to CO π-back bonding and the CO IR stretching frequency.

If the electron density on a metal center is increasing, more π-back bonding to the CO ligand(s) will also increase, as shown in Table 4.2.94.2.9 . It means more electron density would enter into the empty carbonyl π* orbital and weaken the C-O bond. Therefore, it makes the M-CO bond strength increasing and more double-bond-like (M=C=O).

Ligation Donation Effect

Some cases, as shown in Table 4.2.94.2.9 , different ligands would bind with same metal at the same metal-ligand complex. For example, if different electron density groups bind with Mo(CO)₃ as the same form, as shown in Figure 4.2.224.2.22 , the CO vibrational frequencies would depend on the ligand donation effect. Compared with the PPh₃ group, CO stretching frequency which the complex binds the PF₃ group (2090, 2055 cm^-1) is higher. It indicates that the absolute amount of electron density on that metal may have certain effect on the ability of the ligands on a metal to donate electron density to the metal center. Hence, it may be explained by the Ligand donation effect. Ligands that are trans to a carbonyl can have a large effect on the ability of the CO ligand to effectively π-backbond to the metal. For example, two trans π-backbonding ligands will partially compete for the same d-orbital electron density, weakening each other’s net M-L π-backbonding. If the transligand is a π-donating ligand, the free metal to CO π-backbonding can increase the M-CO bond strength (more M=C=O character). It is well known that pyridine and amines are not those strong π-donors. However, they are even worse π-backbonding ligands. So the CO is actually easy for π-back donation without any competition. Therefore, it naturally reduces the CO IR stretching frequencies in metal carbonyl complexes for the ligand donation effect.

Geometry Effects

Some cases, metal-ligand complex can form not only terminal but also bridging geometry. As shown in Figure 4.2.234.2.23 , in the compound Fe₂(CO)₇(dipy), CO can act as a bridging ligand. Evidence for a bridging mode of coordination can be easily obtained through IR spectroscopy. All the metal atoms bridged by a carbonyl can donate electron density into the π* orbital of the CO and weaken the CO bond, lowering vibration frequency of CO. In this example, the CO frequency in terminal is around 2080 cm^-1, and in bridge, it shifts to around 1850 cm^-1.

Pump-probe Detection of Molecular Functional Group Vibrational Lifetime

The dynamics of molecular functional group plays an important role during a chemical process, chemical bond forming and breaking, energy transfer and other dynamics happens within picoseconds domain. It is very difficult to study such fast processes directly, for decades scientists can only learn from theoretical calculations, lacking experimental methods.

However, with the development of ultrashort pulsed laser enable experimental study of molecular functional group dynamics. With ultrafast laser technologies, people develop a series of measuring methods, among which, pump-probe technique is widely used to study the molecular functional group dynamics. Here we concentrate on how to use pump-probe experiment to measure functional group vibrational lifetime. The principle, experimental setup and data analysis will be introduced.

Principles of the Pump-probe Technique

For every function group within a molecule, such as the C≡N triple bond in phenyl selenocyanate (C₆H₅SeCN) or the C-D single bond in deuterated chloroform (DCCl₃), they have an individual infrared vibrational mode and associated energy levels. For a typical 3-level system (Figure 4.2.244.2.24 , both the 0 to 1 and the 1 to 2 transition are near the probe pulse frequency (they don’t necessarily need to have exactly the same frequency).

In a pump-probe experiment, we use the geometry as is shown in Figure 4.2.254.2.25 . Two synchronized laser beams, one of which is called pump beam (E_pu) while the other probe beam (E_pr). There is a delay in time between each pulse. The laser pulses hit the sample, the intensity of ultrafast laser (fs or ps) is strong enough to generated 3^rd order polarization and produce 3^rd order optical response signal which is use to give dynamics information of molecular function groups. For the total response signals we have \label{6} , where µ₁₀ µ₂₁ are transition dipole moment and E₀, E₁, and E₂ are the energies of the three levels, and t₃ is the time delay between pump and probe beam. The delay t₃ is varied and the response signal intensity is measured. The functional group vibration life time is determined from the data.

S = 4μ410e−i(E1−E0)t3/h−Γt3(4.2.6)(4.2.6)S = 4μ104e−i(E1−E0)t3/h−Γt3

Typical Experimental Set-up

The optical layout of a typical pump-probe setup is schematically displayed in Figure 4.2.264.2.26 . In the setup, the output of the oscillator (500 mW at 77 MHz repetition rate, 40 nm bandwidth centered at 800 nm) is split into two beams (1:4 power ratio). Of this, 20% of the power is to seed a femtosecond (fs) amplifier whose output is 40 fs pulses centered at 800 nm with power of ~3.4 W at 1 KHz repetition rate. The rest (80%) of the seed goes through a bandpass filter centered at 797.5nm with a width of 0.40 nm to seed a picosecond (ps) amplifier. The power of the stretched seed before entering the ps amplifier cavity is only ~3 mW. The output of the ps amplifier is 1ps pulses centered at 800 nm with a bandwidth ~0.6 nm. The power of the ps amplifier output is ~3 W. The fs amplifier is then to pump an optical parametric amplifier (OPA) which produces ~100 fs IR pulses with bandwidth of ~200 cm^-1 that is tunable from 900 to 4000 cm^-1. The power of the fs IR pulses is 7~40 mW, depending on the frequencies. The ps amplifier is to pump a ps OPA which produces ~900 fs IR pulses with bandwidth of ~21 cm^-1, tunable from 900 – 4000 cm^-1. The power of the fs IR pulses is 10 ~ 40 mW, depending on frequencies.

In a typical pump-probe setup, the ps IR beam is collimated and used as the pump beam. Approximately 1% of the fs IR OPA output is used as the probe beam whose intensity is further modified by a polarizer placed before the sample. Another polarizer is placed after the sample and before the spectrograph to select different polarizations of the signal. The signal is then sent into a spectrograph to resolve frequency, and detected with a mercury cadmium telluride (MCT) dual array detector. Use of a pump pulse (femtosecond, wide band) and a probe pulse (picoseconds, narrow band), scanning the delay time and reading the data from the spectrometer, will give the lifetime of the functional group. The wide band pump and spectrometer described here is for collecting multiple group of pump-probe combination.

Data Analysis

For a typical pump-probe curve shown in Figure 4.2.274.2.27 life time t is defined as the corresponding time value to the half intensity as time zero.

Table 4.2.104.2.10 shows the pump-probe data of the C≡N triple bond in a series of aromatic cyano compounds: n-propyl cyanide (C₃H₇CN), ethyl thiocyanate (C₂H₅SCN), and ethyl selenocyanate (C₂H₅SeCN) for which the ν_C≡N for each compound (measured in CCl₄ solution) is 2252 cm^-1), 2156 cm^-1, and ~2155 cm^-1, respectively.

A plot of intensity versus time for the data from TABLE is shown Figure 4.2.284.2.28 . From these curves the C≡N stretch lifetimes can be determined for C₃H₇CN, C₂H₅SCN, and C₂H₅SeCN as ~5.5 ps, ~84 ps, and ~282 ps, respectively.

From what is shown above, the pump-probe method is used in detecting C≡N vibrational lifetimes in different chemicals. One measurement only takes several second to get all the data and the lifetime, showing that pump-probe method is a powerful way to measure functional group vibrational lifetime.

Attenuated Total Reflectace- Fourier Transform Infrared Spectroscopy

Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is a physical method of compositional analysis that builds upon traditional transmission FTIR spectroscopy to minimize sample preparation and optimize reproducibility. Condensed phase samples of relatively low refractive index are placed in close contact with a crystal of high refractive index and the infrared (IR) absorption spectrum of the sample can be collected. Based on total internal reflection, the absorption spectra of ATR resemble those of transmission FTIR. To learn more about transmission IR spectroscopy (FTIR) please refer to the section further up this page titled Fourier Transform Infrared Spectroscopy of Metal Ligand Complexes.

First publicly proposed in 1959 by Jacques Fahrenfort from the Royal Dutch Shell laboratories in Amsterdam, ATR IR spectroscopy was described as a technique to effectively measure weakly absorbing condensed phase materials. In Fahrenfort’s first article describing the technique, published in 1961, he used a hemicylindrical ATR crystal (see Experimental Conditions) to produce single-reflection ATR (Figure 4.2.294.2.29 ). ATR IR spectroscopy was slow to become accepted as a method of characterization due to concerns about its quantitative effectiveness and reproducibility. The main concern being the sample and ATR crystal contact necessary to achieve decent spectral contrast. In the late 1980’s FTIR spectrometers began improving due to an increased dynamic range, signal to noise ratio, and faster computers. As a result ATR-FTIR also started gaining traction as an efficient spectroscopic technique. These days ATR accessories are often manufactured to work in conjunction with most FTIR spectrometers, as can be seen in Figure 4.2.304.2.30 .

Total Internal Reflection

For additional information on light waves and their properties please refer to the module on Vertical Scanning Interferometry (VSI) in chapter 10.1.

When considering light propagating across an interface between two materials with different indices of refraction, the angle of refraction can be given by Snell’s law, 4.2.74.2.7 , where none of the incident light will be transmitted.φc = φmax(4.2.7)(4.2.7)φc = φmax

The reflectance of the interface is total and whenever light is incident from a higher refractive index medium onto a lower refractive index medium, the reflection is deemed internal (as opposed to external in the opposite scenario). Total internal reflectance experiences no losses, or no transmitted light (Figure 4.2.314.2.31

Supercritical internal reflection refers to angles of incidence above the critical angle of incidence allowing total internal reflectance. It is in this angular regime where only incident and reflected waves will be present. The transmitted wave is confined to the interface where its amplitude is at a maximum and will damp exponentially into the lower refractive index medium as a function of distance. This wave is referred to as the evanescent wave and it extends only a very short distance beyond the interface.

To apply total internal reflection to the experimental setup in ATR, consider n₂ to be the internal reflectance element or ATR crystal (the blue trapezoid in Figure 4.2.324.2.32 )

where n₂ is the material with the higher index of refraction. This should be a material that is fully transparent to the incident infrared radiation to give a real value for the refractive index. The ATR crystal must also have a high index of refraction to allow total internal reflection with many samples that have an index of refraction n₁, where n₁<n₂.

We can consider the sample to be absorbing in the infrared. Electromagnetic energy will pass through the crystal/sample interface and propagate into the sample via the evanescent wave. This energy loss must be compensated with the incident IR light. Thus, total reflectance is no longer occurring and the reflection inside the crystal is attenuated. If a sample does not absorb, the reflectance at the interface shows no attenuation. Therefore if the IR light at a particular frequency does not reach the detector, the sample must have absorbed it.

The penetration depth of the evanescent wave within the sample is on the order of 1µm. The expression of the penetration depth is given in 4.2.84.2.8 and is dependent upon the wavelength and angle of incident light as well as the refractive indices of the ATR crystal and sample. The effective path length is the product of the depth of penetration of the evanescent wave and the number of points that the IR light reflects at the interface between the crystal and sample. This path length is equivalent to the path length of a sample in a traditional transmission FTIR setup.dp=λ2πn1(sinω−(n1n2)2)1/2(4.2.8)(4.2.8)dp=λ2πn1(sinω−(n1n2)2)1/2

Experimental Conditions

Refractive Indices of ATR Crystal and Sample

Typically an ATR attachment can be used with a traditional FTIR where the beam of incident IR light enters a horizontally positioned crystal with a high refractive index in the range of 1.5 to 4, as can be seen in Table 4.2.114.2.11 will consist of organic compounds, inorganic compounds, and polymers which have refractive indices below 2 and can readily be found on a database.

Single and Multiple Reflection Crystals

Multiple reflection ATR was initially more popular than single reflection ATR because of the weak absorbances associated with single reflection ATR. More reflections increased the evanescent wave interaction with the sample, which was believed to increase the signal to noise ratio of the spectrum. When IR spectrometers developed better spectral contrast, single reflection ATR became more popular. The number of reflections and spectral contrast increases with the length of the crystal and decreases with the angle of incidence as well as thickness. Within multiple reflection crystals some of the light is transmitted and some is reflected as the light exits the crystal, resulting in some of the light going back through the crystal for a round trip. Therefore, light exiting the ATR crystal contains components that experienced different number of reflections at the crystal-sample interface.

Angle of Incidence

It was more common in earlier instruments to allow selection of the incident angle, sometimes offering selection between 30°, 45°, and 60°. In all cases for total internal reflection to hold, the angle of incidence must exceed the critical angle and ideally complement the angle of the crystal edge so that the light enters at a normal angle of incidence. These days 45° is the standard angle on most ATR-FTIR setups.

ATR Crystal Shape

For the most part ATR crystals will have a trapezoidal shape as shown in Figure 4.2.314.2.31. This shape facilitates sample preparation and handling on the crystal surface by enabling the optical setup to be placed below the crystal. However, different crystal shapes (Figure 4.2.334.2.33 ) may be used for particular purposes, whether it is to achieve multiple reflections or reduce the spot size. For example, a hemispherical crystal may be used in a microsampling experiment in which the beam diameter can be reduced at no expense to the light intensity. This allows appropriate measurement of a small sample without compromising the quality of the resulting spectral features.

Crystal-sample contact

Because the path length of the evanescent wave is confined to the interface between the ATR crystal and sample, the sample should make firm contact with the ATR crystal (Figure 4.2.344.2.34 ). The sample sits atop the crystal and intimate contact can be ensured by applying pressure above the sample. However, one must be mindful of the ATR crystal hardness. Too much pressure may distort the crystal and affect the reproducibility of the resulting spectrum.

The wavelength effect expressed in \label{7} shows an increase in penetration depth at increased wavelength. In terms of wavenumbers the relationship becomes inverse. At 4000 cm^-1 penetration of the sample is 10x less than penetration at 400 cm^-1 meaning the intensity of the peaks may appear higher at lower wavenumbers in the absorbance spectrum compared to the spectral features in a transmission FTIR spectrum (if an automated correction to the ATR setup is not already in place).

Selecting an ATR Crystal

ATR functions effectively on the condition that the refractive index of the crystal is of a higher refractive index than the sample. Several crystals are available for use and it is important to select an appropriate option for any given experiment (Table 4.2.114.2.11 ).

When selecting a material, it is important to consider reactivity, temperature, toxicity, solubility, and hardness.

The first ATR crystals in use were KRS-5, a mixture of thallium bromide and iodide, and silver halides. These materials are not listed in the table because they are not in use any longer. While cost-effective, they are not practical due to their light sensitivity, softness, and relatively low refractive indices. In addition KRS-5 is terribly toxic and dissolves on contact with many solvents, including water.

At present diamond is a favorable option for its hardness, inertness and wide spectral range, but may not be a financially viable option for some experiments. ZnSe and germanium are the most common crystal materials. ZnSe is reasonably priced, has significant mechanical strength and a long endurance. However, the surface will become etched with exposure to chemicals on either extreme of the pH scale. With a strong acid ZnSe will react to form toxic hydrogen selenide gas. ZnSe is also prone to oxidation and care must be taken to avoid the formation of an IR absorbing layer of SeO₂. Germanium has a higher refractive index, which reduces the depth of penetration to 1 µm and may be preferable to ZnSe in applications involving intense sample absorptions or for use with samples that produce strong background absorptions. Sapphire is physically robust with a wide spectral range, but has a relatively low refractive index in terms of ATR crystals, meaning it may not be able to test as many samples as another crystal might.

Sample Versatility

Solids

The versatility of ATR is reflected in the various forms and phases that a sample can assume. Solid samples need not be compressed into a pellet, dispersed into a mull or dissolve in a solution. A ground solid sample is simply pressed to the surface of the ATR crystal. For hard samples that may present a challenge to grind into a fine solid, the total area in contact with the crystal may be compromised unless small ATR crystals with exceptional durability are used (e.g., 2 mm diamond). Loss of contact with the crystal would result in decreased signal intensity because the evanescent wave may not penetrate the sample effectively. The inherently short path length of ATR due to the short penetration depth (0.5-5 µm) enables surface-modified solid samples to be readily characterized with ATR.

Powdered samples are often tedious to prepare for analysis with transmission spectroscopy because they typically require being made into a KBr pellet to and ensuring the powdered sample is ground up sufficiently to reduce scattering. However, powdered samples require no sample preparation when taking the ATR spectra. This is advantageous in terms of time and effort, but also means the sample can easily be recovered after analysis.

Liquids

The advantage of using ATR to analyze liquid samples becomes apparent when short effective path lengths are required. The spectral reproducibility of liquid samples is certain as long as the entire length of the crystal is in contact with the liquid sample, ensuring the evanescent wave is interacting with the sample at the points of reflection, and the thickness of the liquid sample exceeds the penetration depth. A small path length may be necessary for aqueous solutions in order to reduce the absorbance of water.

Sample Preparation

ATR-FTIR has been used in fields spanning forensic analysis to pharmaceutical applications and even art preservation. Due to its ease of use and accessibility ATR can be used to determine the purity of a compound. With only a minimal amount of sample this researcher is able to collect a quick analysis of her sample and determine whether it has been adequately purified or requires further processing. As can be seen in Figure 4.2.354.2.35 , the sample size is minute and requires no preparation. The sample is placed in close contact with the ATR crystal by turning a knob that will apply pressure to the sample (Figure 4.2.364.2.36 ).

ATR has an added advantage in that it inherently encloses the optical path of the IR beam. In a transmission FTIR, atmospheric compounds are constantly exposed to the IR beam and can present significant interference with the sample measurement. Of course the transmission FTIR can be purged in a dry environment, but sample measurement may become cumbersome. In an ATR measurement, however, light from the spectrometer is constantly in contact with the sample and exposure to the environment is reduced to a minimum.

Application to Inorganic Chemistry

One exciting application of ATR is in the study of classical works of art. In the study of fragments of a piece of artwork, where samples are scarce and one-of-a-kind, ATR is a suitable method of characterization because it requires only a small sample size. Determining the compounds present in art enables proper preservation and historical insight into the pieces.

In a study examining several paint samples from a various origins, a micro-ATR was employed for analysis. This study used a silicon crystal with a refractive index of 2.4 and a reduced beam size. Going beyond a simple surface analysis, this study explored the localization of various organic and inorganic compounds in the samples by performing a stratigraphic analysis. The researchers did so by embedding the samples in both KBr and a polyester resins. Two embedding techniques were compared to observe cross-sections of the samples. The mapping of the samples took approximately 1-3 hours which may seem quite laborious to some, but considering the precious nature of the sample, the wait time was acceptable to the researchers.

The optical microscope picture ( Figure 4.2.374.2.37 ) shows a sample of a blue painted area from the robe of a 14^th century Italian polychrome statue of a Madonna. The spectra shown in Figure 4.2.384.2.38 were acquired from the different layers pictured in the box marked in Figure 4.2.374.2.37 . All spectra were collected from the cross-sectioned sample and the false-color map on each spectrum indicates the location of each of these compounds within the embedded sample. The spectra correspond to the inorganic compounds listed in Table 4.2.124.2.12 , which also highlights characteristic vibrational bands.

The deep blue layer 3 corresponds to azurite and the light blue paint layer 2 to a mixture of silicate based blue pigments and white lead. Although beyond the ATR crystal’s spatial resolution limit of 20 µm, the absorption of bole was detected by the characteristic triple absorption bands of 3697, 3651, and 3619 cm^-1 as seen in spectrum d of Figure 4.2.374.2.37 . The white layer 0 was identified as gypsum.

To identify the binding material, the KBr embedded sample proved to be more effective than the polyester resin. This was due in part to the overwhelming IR absorbance of gypsum in the same spectral range (1700-1600 cm^-1) as a characteristic stretch of the binding as well as some contaminant absorption due to the polyester embedding resin.

To spatially locate specific pigments and binding media, ATR mapping was performed on the area highlighted with a box in Figure 4.2.374.2.37 . The false color images alongside each spectrum in Figure 4.2.384.2.38 indicate the relative presence of the compound corresponding to each spectrum in the boxed area. ATR mapping was achieved by taking 108 spectra across the 220×160 µm area and selecting for each identified compound by its characteristic vibrational band.

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In thermogravimetric analysis (TGA), a sample is continually weighted while heating, as an inert gas atmosphere is passed over it. Many solids undergo reactions that evolve gaseous byproducts. In TGA, these gaseous byproducts are removed and changes in the remaining mass of the sample are recorded. Three variations are commonly employed:

• Dynamic TGA – Temperature continues to increase over time as mass is recorded. This allows simulataneous identification of how much gas is removed and the temperature at which it occurs.
• Static TGA – Temperature is held constant as the mass is measured. This can be used to gain more information on a decomposition that happens at a certain temperature or to investigate a material’s ability to withstand a given temperature.
• Quasistatic TGA – Sample is heated in multiple temperature intervals, and held at those intervals for a time, often until the mass stabilizes. This is ideal for investigating substances that are known to decompose in various ways at different temperatures, and better characterizing the way in which they decompose.

How to interpret the data

Figure 1 shows a TGA curve in green. Figure from Physical Methods in Chemistry and Nanoscience by Pavan M.V. Raja and Andrew R. Barron (chemlibretext link).

Data from thermogravimetric analysis is often shown by a graph representing mass as a function of temperature for dynamic TGA. For static TGA, mass is instead plotted as a function of time at a given temperature. Quasistatic TGA produces multiple mass vs. time plots for various temperatures. The derivative of the mass change with temperature is often plotted on the same graph to improve ease of identifying the points at which different mass changes occur; especially helpful in cases where multiple decomposition reactions happen in close proximity to one another.

Examples of some characteristic TGA curves for dynamic TGA

Figure 1. Classification of the different observable TGA Curves. Image source

In general, mass fluctuations correspond to chemical reactions, with some exceptions. A common example is drying, which can easily be seen as a quick initial drop at the beginning of heating that isn’t known to correspond to any chemical reactions. Evaporation/sublimation may also appear on the plot depending on the material to be analyzed. Multistage decomposition is also common, and shows as a step-like pattern. In some cases, these steps may blend together during dynamic TGA, necessitating either far slower heating rates, or step-wise methods like quasistatic TGA. Note that TGA itself may not be sufficient to identify the decomposition products; chemical testing of the sample after TGA analysis is often required to ascertain the identities of suspected decomposition products. TGA itself does not identify substances; other methods such as chemical testing or differential calorimetry must performed alongside TGA to verify the identity of products. 

Good literature examples 

TGA is vital when designing materials that are intended to withstand high temperatures, as if there is even slight decomposition of the material at a temperature that the material would be expected to encounter, devices made of the material may fail over repeated use. The carefully controlled environment of the TGA analyzer also allows for measuring decomposition reaction kinetics. Differential scanning calorimetry can be incorporated into the TGA analyzer to allow for monitoring potential phase changes. Phase changes generally require addition of heat, yet do not increase the temperature of the sample undergoing a phase change. Furthermore, different phases of a material have different heat capacity, and the temperature change per joule of heat applied will vary with phase. By adding a reference pan to the TGA analyzer, changes in the heat capacity in addition to mass changes can be monitored. In this way, both phase changes and thermal decomposition reactions can be simultaneously measured by TGA.

TGA used for decomposition reaction:

Figure S6. Thermogravimetric analysis (TGA) under pure nitrogen flow at 100 mL/min to show a) clean decomposition of 3DP-HKUST-1gel and b) decomposition of 3DP-HKUST-1gelTEA showing that it has several side products during decomposition. (Lim et al. 2019)

Figure 2b. Thermogravimetric analysis (TGA) under simulated ambient conditions (SI section 5), showing desolvation followed by oxidation of 3DP-HKUST-1gel to CuO.

The authors are looking to use colloidal gels containing only ethanol and Cu3(BTC)2 (BTC = 1,3,5-benzenetricarboxylate) (HKUST-1) nanoparticles as ink for the direct ink writing (DIW) of pure densely packed and self-standing Metal-organic frameworks (MOF) monoliths. Traditionally they are synthesized in powder form. The authors are observing the decomposition behavior of the 3DP-HKUST-1gel (made using DIW) and 3DP-HKUST-1gel-TEA (made by triethylamine-induced HKUST-1 gels). It can be observed in the sudden change in weight over the 100-200 °C for Figure S6b that several side products have formed as oppsed to Figure S6a which shows a much cleaner decomposition. The Figure seen in the paper was Figure 2b, the authors attibute the first weight change (16.2 mg) to residual molecules such as H2O, acetate from the copper (II) acetate monohydrate precursor, and excess ethanolic solvent that is trapped inside the 3DP-HKUST-1gel structure. The second weight change (6.2 mg) was observed at 300 °C and is caused by the decomposition of the organic linkers and network. 

In-depth reading and works cited

1. Physical Methods in Chemistry and Nanoscience by Pavan M.V. Raja and Andrew R. Barron (chemlibretext link).
2. A Beginners Guide Thermogravimetric Analysis (TGA): A Beginners Guide to TGA that has FAQ and basic information.
3. Thermogravimetry Analysis (TGA) – online training course: Youtube training course that as good explanation about how the TGA works. Also has good examples of plots and how to understand them.
4. Thermogravimetric Analysis (TGA) & Differential Scanning Calorimetry (DSC): Slideshow with information about the TGA. Includes figures on classification of curves, how balance works, analyis of curves, effects of heat rate, shifts caused by heat rate, etc.
5. THERMAL ANALYSIS OF POLYMERS – Fundamentals and Applications: (WARNING!: This link will download a whole 388 pg. book!) Has a whole chapter dedicated to TGA.

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TGA is a powerful and robust technique to explore the thermal stability of a material. By accurately monitoring the weight of a sample while heating at a constant rate, we can measure changes in a sample’s weight and attribute this to a specific material response to a thermal stress (Figure 1). This is perfect for exploring, in detail, decomposition temperatures and ensuring a material performs adequately in a given temperature range.

During a test, a carrier gas flows over the sample and the weighing mechanism.  This carrier gas serves two purposes: protecting the internals from corrosion/oxidation above 500 °C, and to interact with the sample through gas-solid or gas-liquid reactions. By providing an inert atmosphere, we can test the thermal stability of a material. Reducing environments can explore gas-solid phase reduction reactions or protect specific samples from being oxidized. By the nature of the sensitivity of the TGA balance, we also can observe the absorption of gas onto a porous material at various temperatures. This is an ideal technique for exploring metal organic frameworks, or catalytic porous materials. Owing to the sensitivity of the balance on our SETARAM Labsys Evo instrument, we have ideal sensitivity for running thermokinetic experiments. This experiment has applications towards thermal stability of a given material at elevated temperatures.

The SETARAM Labsys offers the ability to perform TGA analysis up to 1600 °C and additionally under a variety of gas mixtures due to our gas-mixing option.

Differential Scanning Calorimetry (DSC)

DSC is a flexible technique to explore thermal transitions within a given sample. By heating a sample and measuring the heat flow as compared to a reference standard, we can access thermoanalytical information on a given material. DSC curves are generated by plotting heat flow (mW) vs sample temperature (°C), and an example plot is found in Figure 2, and demonstrates the melting and fusion of Indium Corp. Indalloy 80Au/20Sn solder. In this case, we observe a phase change (solid-liquid followed by liquid-solid); however, we can also observe other thermal transitions within a material, such as evaporation, thermal transitions between polymorphs, and determination of key thermal constants. One of these key thermal constants is heat capacity (Cp), which an be difficult to acquire due to the demanding experiment required to gain access to this information. Heat capacity requires precise and very specific sensitivity of the DSC sensor, as it is a very small and difficult thermal effect to capture effectively. Owing to our 3D Calvet type sensor on our µDSC 7, we have the capability to measure such small thermal effects (0.02 µW) requiring the upmost sensitivity and precision from 0 – 120 °C. For higher temperatures, our SETARAM Labsys Evo instrument has a specifically designed 3D-psuedo-Calvet sensor, which allows TAL to perform C_p testing with better than 2% accuracy from ambient temperatures to 1600 °C. This very sensitive and difficult to determine thermal effects also include the glass transition point (T_g), water state in materials and other thermodynamic and thermokinetic effects.

Differential Thermal Analysis (DTA)

DTA is a similar technique to DSC, however instead of measuring the heat flow between the furnace temperature and the sample, you measure the temperature difference between a sample and a standard reference using thermocouples. This is particularly useful for phase-change materials and the study of organic and polymeric materials using analytical precision. Owing to the more sensitive detector within typical DTA sensors, DTA testing is particularly useful for running thermokinetic experiments due to the lower thermal inertial barrier. TAL offers DTA testing from ambient to 1200 °C, allowing us to explore thermal effects at elevated temperature, capabilities which we have newly acquired.

While each of these techniques may be used to probe into a single physical characteristic of a material, the real power we provide is simultaneous thermal analysis techniques for niche applications on a single sample. With TAL’s Labsys Evo 1600 and DSC 131, we offer capabilities to include high temperature ranges with mixtures of gases. For example, TAL offers TGA, DSC and DTA experiments from ambient temperatures up to 1600 °C. Figure 3 shows a TGA-DSC decomposition experiment captured on our Setaram Labsys Evo apparatus, where CuSO₄•5H₂O decomposition can be measured by TGA (water, SO₂ and O₂) and DSC. In addition to these coupled thermal experiments, we offer the capacity to provide gas mixtures for high precision control over the exact atmospheric exposure during thermal analysis runs. TAL also offers the capacity to run samples under vacuum (10^-3 Bar) using our Labsys Evo system, which is useful for isolating gas-sample interactions. TAL also offers pressurized DSC experimentation, allowing for the study of various samples under 200 psi. This can provide insight into thermal transitions under pressure, such as those in the oil and fuel industry or in the case of high-pressure lubricants.

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Raman spectroscopy is a powerful vibrational technique used widely in chemistry, materials science, geology, biology, and industrial laboratories. To make the most of this analytical tool, proper software is essential for spectrum acquisition, visualization, processing, and interpretation. While many commercial solutions exist, there are also free and open tools that are capable, flexible, and ideal for researchers, students, and laboratories on a budget.

1. Spectragryph – Free Optical Spectroscopy Software

Spectragryph Official Site (free for academic and private use)

Spectragryph is a versatile and widely-used optical spectroscopy package supporting Raman, FTIR, UV-VIS, fluorescence, LIBS, and XRF formats. It allows users to import multiple vendor file formats, plot and edit spectra, perform baseline correction, smoothing, peak labeling, and automated batch processing. The software is free for academic and private use, and offers features such as spectral database search, multi-spectrum display, and hardware control for live data acquisition. Spectroscopy

Key Advantages:

• Multi-format support and drag-and-drop data handling
• Batch export, undo/redo, and interactive visualization
• Ability to integrate free spectral libraries like RRUFF mineral spectra Spectroscopy

⚠️ Note: Distribution and licensing for commercial use require a paid license; free academic licenses may need re-verification over time. Spectroscopy

2. RRUFF – Free Raman Database & Identification Tools

RRUFF Raman & Mineral Database (with download tools)

The RRUFF Project provides a comprehensive open database of Raman spectra, X-ray diffraction patterns, and chemical data for thousands of minerals. Although the original “CrystalSleuth” software (used to search and compare spectra) is bundled in legacy downloads, the RRUFF data itself can be imported into many newer tools and databases for free identification and research purposes. RRUFF

Why It’s Useful:

• Large library of reference Raman spectra for minerals
• Free access for educational and research use
• Can be used with software such as Spectragryph or third-party viewers RRUFF

3. Raman Tool Set – Free Basic Raman Processor

While not listed in your original links, Raman Tool Set is a notable free program dedicated to Raman data analysis. It supports baseline correction, normalization, smoothing, and chemometric functions like PCA and cluster analysis — all valuable for simple spectral processing without cost. Wikipedia

Commercial Software You May Compare

Though not free, these commercial solutions represent the professional standard in Raman data handling. Including them in your article gives context about what users gain by paying — and helps highlight the value of free alternatives.

Bruker OPUS

Bruker’s OPUS software is a professional spectroscopy suite supporting IR, NIR, and Raman data acquisition and evaluation. It offers advanced visualization, database tools, and compliance-ready features for regulated environments. Bruker

Thermo Scientific GRAMS/AI

GRAMS/AI is a robust spectroscopy platform often bundled with Thermo instruments. It provides extensive processing and analysis functions for Raman as well as other spectroscopies, widely used in research and industry (Thermo Scientific documentation). Invalid URL

Renishaw Raman Software

Renishaw offers dedicated software for its Raman instruments, focused on spectral acquisition, processing, and material identification. This platform integrates features for instrument control and data analysis tailored to Renishaw hardware. Invalid URL

HORIBA LabSpec 6

LabSpec 6 is a comprehensive spectroscopy suite used with HORIBA Raman systems. It includes visualization, hyperspectral mapping, baseline correction, multivariate analysis, and reporting tools. This software illustrates the advanced feature sets available in commercial packages. Spectroscopy Online

Raman-Analytik Software

Some spectrometer vendors (e.g., Raman-Analytik) provide their own analysis tools with fast fingerprinting, background removal, and database search capabilities — often bundled with hardware or available for download. Raman Analytik

Tips for Using Free Raman Software

• Combine tools with databases: Pair free analysis software (like Spectragryph) with open spectral libraries such as RRUFF for improved identification.
• Watch format compatibility: Free tools vary in supported file types — converting proprietary formats (e.g., Bruker or Renishaw raw files) may require intermediate export or converters.
• Consider workflow needs: If advanced imaging, 3D mapping, or multivariate quantification is required, commercial packages may offer higher performance — but for basic peak analysis, free tools suffice.

Introduction to Raman spectroscopy

When an electromagnetic radiation passes through a transparent medium, existing species scatter part of the beam in all directions. In 1928, C. V. Raman discovered that the wavelength corresponding to a small fraction of the radiation scattered by certain molecules was different from the wavelength of the original radiation (ie, inelastic scattering occurs). Wavelengths vary depending on the molecular structure of the compounds. Raman spectroscopy is based on the analysis of these differences to determine the molecular structure of different compounds [1].

Scattering is a physical process in which a type of radiation such as light, sound, or even a beam of moving particles (such as ions, electrons, etc.) collides with particles or different surfaces in a direct path in which He is moving and deviates and is forced to move in one or more other directions (Figure 1). Scattering usually occurs in all directions [2].
Due to the collision of light with matter, we will have two types of scattering according to the wavelength of the scattered radiation:

1. Rayleigh scattering is caused by particles that are much smaller than the wavelength of the radiation. Due to this type of scattering, the radiation wavelength does not change and is also classified as elastic scattering. The most obvious example of this type of scattering is the blue color of the sky, which occurs due to the scattering of shorter wavelengths in the visible spectrum.
2. Raman scattering, in which the initial wavelength changes due to the transfer of energy between the photons and the matter molecules, and the wavelength increases due to the loss of energy, or the wavelength decreases due to the capture of energy. Finds. The magnitude of these energy changes (whether decreasing or increasing) is proportional to the frequency of the molecular vibrations of the light scattering species. Raman scattering will be divided into two general categories. The first group, which has a longer wavelength (less energy) than the original radiation, is called Stokes, and the second group, which has a shorter wavelength (more energy) than the original radiation, is known as anti-Stokes. 2].
3. Spectrum Raman
   Figure 2 shows a part of a Raman spectrum for CCl4 species in which the sample is irradiated with a laser source with a wavelength of 488 nm. In a horizontal axis Raman spectrum, generally in terms of the scattered radiation wave number (ῡ) or, as shown below, in terms of the changes made in the scattered beam wave number (ῡ2) relative to the source radiation wave number (ῡ1), ie in terms of the wave number changes ( 2) (which in practice indicates the scatter created in a specific wave number). While the vertical axis shows the intensity of the peaks in relative terms. Note that the relationship between the wave number of a radiation and its wavelength (λ), frequency (υ) and energy (E) is as follows and has a unit of cm-1:
   ῡ = 1 / λ and ῡ = υ / c
   E = hυ = hcῡ

As can be seen in the figure below, the Stokes lines are more intense, which is justified by their higher probability of occurrence, as photons are more likely to lose energy due to contact with the material environment than to receive them. Is energy. Another thing to keep in mind is that the amount of Raman Shifts (written numerically above the peaks) is independent of the laser wavelength used to excite the sample. It should also be noted that Riley scattering is located exactly at the wavelength equal to the source wavelength, its displacement rate is zero and its intensity is much higher than the Stokes and anti-Stokes lines [2].

Before continuing the discussion, it is necessary to point out that due to the continuity of the material, in order to better understand the following sections, it is better to first read the article on infrared spectroscopy. Below, due to the great similarity and complementarity of infrared and Raman spectroscopy techniques, a comparison is made on the differences.

3. Investigation of differences between Raman technique and infrared spectroscopy
   Studies have shown that shifts in the wavelength (wave number) of the source due to Raman scattering are in the infrared spectral range. In simpler terms, the difference between the energy of the source radiation and the scattered radiation is equal to the energy of the waves in the middle infrared range (see the article Infrared Spectroscopy). As mentioned in the article on infrared spectroscopy, this amount of energy is sufficient only for transitions between molecular vibrational levels of molecules (Molecular Vibrational Levels), and in this respect two methods are similar to each other. The Raman scattering spectrum and the infrared spectrum for a particular species are often very similar. There are many similarities between the two methods, but it should be noted that despite these similarities, the two techniques are different in principle and theory in that they are usually used as a complement to each other. In the paper introducing the infrared spectroscopy method, it is mentioned that one of the necessary conditions for a particular bond to be active in infrared spectroscopy is to cause a net change in dipole moment due to the absorption of radiation (Refer to the main article).

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It is the shift in wavelength of the inelastically scattered radiation that provides the chemical and structural information. Raman shifted photons can be of either higher or lower energy, depending upon the vibrational state of the molecule under study. A simplified energy diagram that illustrates these concepts is shown below.

Stokes radiation occurs at lower energy (longer wavelength) than the Rayleigh radiation, and anti-Stokes radiation has greater energy. The energy increase or decrease is related to the vibrational energy levels in the ground electronic state of the molecule, and as such, the observed Raman shift of the Stokes and anti-Stokes features are a direct measure of the vibrational energies of the molecule. A schematic Raman spectrum may appear as shown below.

The energy of the scattered radiation is less than the incident radiation for the Stokes line and the energy of the scattered radiation is more than the incident radiation for the anti-Stokes line. The energy increase or decrease from the excitation is related to the vibrational energy spacing in the ground electronic state of the molecule and therefore the wavenumber of the Stokes and anti-Stokes lines are a direct measure of the vibrational energies of the molecule.

In the example spectrum, notice that the Stokes and anti-Stokes lines are equally displaced from the Rayleigh line. This occurs because in either case one vibrational quantum of energy is gained or lost. Also, note that the anti-Stokes line is much less intense than the Stokes line. This occurs because only molecules that are vibrationally excited prior to irradiation can give rise to the anti-Stokes line. Hence, in Raman spectroscopy, only the more intense Stokes line is normally measured – Raman scattering is a relatively weak process. The number of photons Raman scattered is quite small. However, there are several processes which can be used to enhance the sensitivity of a Raman measurement.

Simplified energy diagram

If the wavelength of the exciting laser coincides with an electronic absorption of a molecule, the intensity of Raman-active vibrations associated with the absorbing chromophore are enhanced by a factor of 102 to 104. This resonance enhancement or resonance Raman effect can be extremely useful, not just in significantly lowering the detection limits, but also in introducing electronic selectivety. Thus the resonance Raman technique is used for providing both structural and electronic insight into species of interest.

Metalloporphyrins, carotenoids and several other classes of biologically important molecules have strongly allowed electronic transitions in the visible, making them ideal candidates for resonance Raman spectroscopy. Resonance selectivity has a further practical use, in that spectrum of the chromophoric moiety is resonance enhanced and that of the surrounding environment is not. For biological chromophores, this means that absorbing active centres can be specifically probed by visible excitation wavelengths, and not the surrounding protein matrix (which would require UV lasers to bring into resonance).

Resonance Raman spectroscopy is also an important probe of the chemistry of metal centred complexes, fullerenes, polydiacetylenes and other “exotic” molecules which strongly absorb in the visible. Although many more molecules absorb in the ultraviolet, the high cost of lasers and optics for this spectral region have limited ultraviolet (UV) resonance Raman spectroscopy to a small number of specialist groups.

Schematic Raman spectrum

Vibrations which are resonantly enhanced fall into two or three general mechanistic classes. The most common case is Franck-Condon enhancement, in which a component of the normal coordinate of the vibration occurs in a direction in which the molecule expands during an electronic excitation. The more the molecule expands along this axis when it absorbs light, the larger the enhancement factor. The easily visualized ring breathing (in-plane expansion) modes of porphyrins fall into this class. Vibrations which couple two electronic excited states are also resonantly enhanced, through a mechanism called vibronic enhancement. In both cases, enhancement factors roughly follow the intensities of the absorption spectrum. The fuller theory of resonance enhancement is beyond the scope of this section.

Resonance enhancement does not begin at a sharply defined wavelength. In fact, enhancement of 5x to 10x is observed if the exciting laser is within even a few 100 wavenumbers below the electronic transition of a molecule. This “pre-resonance” enhancement can be experimentally useful.

The Raman scattering from a compound (or ion) adsorbed on or even within a few Angstroms of a structured metal surface can be 103 to 106x greater than in solution. This surface-enhanced Raman scattering is strongest on silver, but is observable on gold and copper as well. At practical excitation wavelengths, enhancement on other metals is unimportant.

SERS arises from two mechanisms:

1. The first is an enhanced electromagnetic field produced at the surface of the metal. When the wavelength of the incident light is close to the plasma wavelength of the metal, conduction electrons in the metal surface are excited into an extended surface electronic excited state called a surface plasmon resonance. Molecules adsorbed or in close proximity to the surface experience an exceptionally large electromagnetic field. Vibrational modes normal to the surface are most strongly enhanced.
2. The second mode of enhancement is by the formation of a charge-transfer complex between the surface and analyte molecule. The electronic transitions of many charge transfer complexes are in the visible, so that resonance enhancement occurs. Molecules with lone pair electrons or pi clouds show the strongest SERS. The effect was first discovered with pyridine.

Other aromatic nitrogen or oxygen containing compounds, such as aromatic amines or phenols, are strongly SERS active. The effect can also be seen with other electron-rich functionalities such as carboxylic acids. The intensity of the surface plasmon resonance is dependent on many factors including the wavelength of the incident light and the morphology of the metal surface. The wavelength should match the plasma wavelength of the metal. This is about 382 nm for a 5μm silver particle, but can be as high as 600nm for larger ellipsoidal silver particles. The plasma wavelength is to the red of 650nm for copper and gold, the other two metals which show SERS at wavelengths in the 350-1000 nm region. The best morphology for surface plasmon resonance excitation is a small (<100nm) particle or an atomically rough surface. SERS is commonly employed to study monolayers of materials adsorbed on metals, including electrodes.

Other popular surfaces include colloids, metal films on dielectric substrates and, recently, arrays of metal particles bound to metal or dielectric colloids through short linkages. Although SERS allows easy observation of Raman spectra from solution concentrations in the micromolar (10x-6) range,non-reproducability of quantitative measurements has in the past marred its utility for analytical purposes. However, standardization in production of SERS active media is steadily improving its potential in this area also.

UVRRS is a powerful tool in the molecular analysis of complex biological systems. Most biological systems absorb UV radiation and hence have the ability to offer resonance with UV Raman excitation. This results in the highly selective resonance Raman effect enabling enhancement of important biological targets such as protein or DNA. For example, excitation around 200nm enhances the Raman peaks from vibrations of amide groups; excitation around 220nm enhances peaks from certain aromatic residues. The Raman scatter from water is weak, allowing for analysis of very weak aqueous systems.

Fiber optic UVRRS configuration

Due to the selective nature of UVRRS, a tunable laser is typically required as the excitation source. Since truly tunable continuous-wave lasers are not yet available, a Nd:YAG-pumped dye laser with frequency-doubled output is one suitable UVRRS system. Depending on the dyes used, this laser setup can give almost any required UV wavelength. Intensified CCDs (ICCDs) with UV photocathodes, back-illuminated CCDs or CCDs with UV enhancing (BASF lumogen)coatings can be used as detectors for UVRRS. These detectors are used on account of their high detection efficiency and multichannel capabilities. The primary obstacle to the merging of the worlds of UVRRS and fiber-optic spectroscopy is solarization, the process by which UV radiation causes opacity of fiber-optics (even quite pure silica fibers). This opacity impairs transmission, rendering standard fiber-optics useless for UVRRS.

Species of Interest

Pulsed lasers are typically utilized in the study of short-lived species. A laser pulse can be supplied to a molecular system with enough energy to redistribute the electrons in a molecule causing the formation of an excited state as illustrated on the right. The Raman spectrum of this excited state molecule can be studied either using the same laser pulse or a different pulse from a second laser (single color and two-color pulsed Raman). Excited states of interest can have lifetimes, from picoseconds to milliseconds, but the majority can be studied using gating in the order of 5ns. As the majority of excited states are generated using UV and visible lasers, photocathodes with high UV and visible Quantum Efficiencies (QEs) are typically suitable.

Schematic of pump-probe (two color) Raman

The simplest pulsed laser experiments are so-called single-color experiments where high irradiance laser pulses are used both to initiate the photoreaction, and then to Raman probe the transient species created within the pulse width. By opening the intensifier tube as shown on the right, only the Raman spectrum of the excited state will be recorded. This pulse/ICCD gate combination will be repeated and accumulated hundreds to thousands of times in order to achieve a good overall signal-to-noise ratio with high dynamic range.

In Time Resolved Resonance Raman (TR3) spectroscopy, pairs of laser pulses of different wavelength are used to photolyse (optically “pump”) and then to Raman probe the transient species of interest. The spectral window of the spectrograph/detector is chosen so that it corresponds to the frequency range of the Raman scattering from the probe laser.

Pulsed two color Raman layout with delays under the control of a delay generator

In Time Resolved Resonance Raman (TR3) spectroscopy, pairs of laser pulses of different wavelength are used to photolyse (optically “pump”) and then to Raman probe the transient species of interest. The spectral window of the spectrograph/detector is chosen so that it corresponds to the frequency range of the Raman scattering from the probe laser.

The time evolution of the transient signal is monitored by recording a series of spectra at different delays after the photolysis event, i.e. at a series of time delays between the excitation and probe pulses. The ICCD camera or either of the lasers can supply the trigger. A delay generator is used to control the delays.

In Raman microscopy, a research grade optical microscope is coupled to the excitation laser and the spectrometer, thus producing a platform capable of obtaining both conventional images and in addition generating Raman Spectra from sample areas approaching the diffraction limit (~1 micron). Imaging and spectroscopy can be combined to generate “Raman cubes”, 3- dimensional data sets, yielding spectral information at every pixel of the 2D image.

A motorized xyz microscope stage can be used to automatically record spectral files, which will constitute the basis of Raman images, Raman maps or a set of Raman spectra recorded from preselected points. Specific software routines will allow the quick and easy reconstruction of these maps. The possibility of generating two-dimensional and three-dimensional images of a sample, using various special features, is an evident advantage over either traditional spectroscopy or microscopy.

Time delay sequences

The first ever Raman “instrument” was constructed in 1928. This instrument used monochromatized sunlight as a light source and a human eye as a detector. Raman instrumentation was developed (based around arc lamps and photographic plates) and soon became very popular up until the 1950s. Since these early days, Raman instrumentation has evolved markedly. Modern instrumentation typically consists of a laser, Rayleigh filter, a few lenses, a spectrograph and a detector (typically a CCD or ICCD).

Typical Continuous Wave (CW) Raman layout

One of the major advantages of dispersive Raman is that it offers the possibility to select the optimal laser excitation wavelength to permit the recording of the best Raman information. For example, wavelengths can be selected to offer the best resonance with the sample under investigation.

One might also need to tune wavelength to avoid fluorescence and thermal emission backgrounds. Nowadays, it is possible to use laser lines from UV, (down to 200nm) up to the infrared, (1.06μm Nd:YAG laser line), from microWatts up to several Watts.

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Light interacts with matter in different ways, transmitting through some materials, while reflecting or scattering off others. Both the material and the colour (wavelength) of the light affect this interaction. We call the study of this light ‘spectroscopy’. Which parts of the visible spectrum enter our eyes determines which colours we perceive.

A substance might appear blue, for example, if it absorbs the red parts of the spectrum of light falling upon it, only reflecting (or scattering) the blue parts into our eyes.

Raman spectroscopy looks at the scattered light

If you were to shine blue light—from just one part of the spectrum—onto the material, you might expect to just see blue light reflected from it, or no light at all if it is completely absorbed (i.e. a black material).

However, by using a Raman spectrometer, you can see that often a very tiny fraction of the scattered light has a different colour. It has changed frequency because, during the scattering process, its energy changed by interacting with molecular vibrations. This is the Raman scattering process, named after its discoverer, the famous Indian physicist C.V. Raman. He was awarded the 1930 physics Nobel Prize for this great discovery.

By studying the vibration of the atoms we can discover the chemical composition and other useful information about the material.

The Raman effect is very weak; only about 1 part in 10 million of the scattered light has a shifted colour. This is too weak to see with the naked eye, so we analyse the light with a highly sensitive spectrometer.

Raman spectrometers

These systems consist of:

• one or more single coloured light sources (lasers)
• lenses (both to focus the light onto the sample and to collect the scattered light)
• filters (to purify the reflected and scattered light so that only the Raman light is collected)
• a means of splitting the light into its constituent colours (normally a diffraction grating or prism)
• a very sensitive detector (to detect the weak light)
• a device such as a computer to control the whole system, display the spectrum and enable this information to be analysed

Raman scattering offers significant advantages for the investigation of materials over other analytical techniques, such as x-raying them or seeing how they absorb light (e.g. infrared absorption or ultraviolet absorption).

aman spectroscopy reveals the chemical and structural composition of samples. Generally, all materials produce Raman spectra, with the exception of pure metals.

Raman scattering

Raman scattering occurs when light interacts with molecular vibrations. This is similar to the more widely known infrared absorption spectroscopy, but different rules apply. A change in molecular polarisability is required during the vibration for the Raman effect to occur.

You will see some vibrations in the Raman spectrum that are not visible in the infrared spectrum, and vice-versa, because of the different selection rules. For example, Raman spectroscopy is superb for studying the carbon atoms that make up the structure of diamond, unlike infrared absorption spectroscopy.

Scattered light

The first step in producing a Raman spectrum is to illuminate your sample with a monochromatic light source, such as a laser.

Most of the light that scatters off is unchanged in energy (‘Rayleigh scattered’). A minute fraction—perhaps 1 part in 10 million—has lost or gained energy (‘Raman scattered’). This Raman shift occurs because photons (particles of light) exchange part of their energy with molecular vibrations in the material.

Where energy is lost the Raman scattering is designated as ‘Stokes’; where energy is gained the Raman scattering is designated as ‘anti-Stokes’. We rarely use anti-Stokes Raman light as it is less intense than the Stokes, however it does represent equivalent vibrational information of the molecule.

Vibrating atoms

The change in energy depends on the frequency of vibration of the molecule. If it is very fast (high frequency)—light atoms held together with strong bonds—the energy change is significant. If it is very slow (low frequency)—heavy atoms held together with weak bonds—the energy change is small.

Raman spectrometers

Renishaw inVia systems consist of:

• single or multiple lasers, from UV (244 nm) to IR (1064 nm) – switch with a single click
• high quality objective lenses, from high confocal 100× to long working distance and immersion options
• custom designed motorised spectrometer lenses­ – automatically align for each configuration
• laser-line-specific Rayleigh filters with a dual filter arrangement to optimise sensitivity
• highest quality master diffraction gratings provide exceptional dispersion and longevity
• thermoelectrically cooled (- 70 ºC) CCD detector – stable and sensitive
• high specification multi-core PC for data collection and analysis

Raman spectra

We graphically depict the results of our measurements as Raman spectra. We plot the intensity of the scattered light (y-axis) for each energy (frequency) of light (x-axis). The frequency is traditionally measured in a unit called the wavenumber (number of waves per cm, cm^-1).

We plot the x-axis frequencies relative to that of the laser as it is the shift in energy of the light that is of particular interest.

How do I get the information I want from my spectrum?

You can tell a great deal about a material from its Raman spectrum, with different features relating to different aspects of the material.

The key features are:

The Raman shifts and relative intensities of all of the Raman bands of the material
With this, we can identify the material.

Individual band changes
A band may shift, narrow or broaden, or vary in intensity. These changes can reveal information about stresses in the sample, variations in crystallinity, and the amount of material respectively.

Variations in spectra with position on the sample
This will reveal changes in the uniformity (homogeneity) of the material. You can analyse at several arbitrary points, or systematically measure an array of points (enabling the production of images of composition, stress, crystallinity, etc.)

What do the Raman bands represent?

It is easy to understand the Raman spectrum of crystals with a regular array of identical atoms, all in the same configuration (such as the carbon atoms in diamond). In these cases, you often see just one dominant Raman band (because there is just one molecular environment of the crystal).

The Raman spectrum of polystyrene, however, is much more complex because the molecule is less symmetric and has hydrogen atoms in addition to carbon atoms. There are also different bond types connecting the atoms.

Vibration frequencies

The frequencies of vibration depend on the masses of the atoms involved and the strength of the bonds between them. Heavy atoms and weak bonds have low Raman shifts. Light atoms and strong bonds have high Raman shifts.

We see the high frequency carbon-hydrogen (C-H) vibrations in the polystyrene spectrum at about 3000 cm^-1. The low frequency carbon-carbon (C-C) vibrations are at around 800 cm^-1. The C-H vibrations have a higher frequency than the C-C vibrations because hydrogen is lighter than carbon.

We see the vibrations of two carbon atoms linked by strong double bonds (C=C) at around 1600 cm^-1. This is at a higher frequency than two carbon atoms lined by a weaker single bond (C-C, 800 cm^-1).

You can use these simple rules to explain many of the features of Raman spectra.

Vibrations in detail

You can see more subtle effects if you inspect spectra closely. The strength of bonds also affects their vibration rates. For example, the C-H vibrations of polystyrene appear in two bands, at approximately 2900 cm^-1 and 3050 cm^-1. The carbons in the former are part of carbon chains (‘aliphatic’), whereas the carbons in the latter form part of carbon rings (‘aromatic’).

You can view the vibrations of a complex molecule as partly consisting of many simple diatomic vibrations. However the full richness of the Raman spectrum can only be understood by considering the vibrations of larger groups of atoms (such as the expanding/contracting ‘breathing mode’ of the aromatic carbon ring that appears at 1000 cm^-1 in polystyrene).

Low frequency vibrations

You can also study Raman bands with low Raman shifts, below 100 cm^-1. These originate from very heavy atoms or very large-scale vibrations, such as the whole crystal lattice vibrating. Renishaw’s Raman instruments enable you to study these modes and explore a wide range of materials and crystals, and distinguish between different crystalline forms (polymorphs).

The big picture

A Raman spectrum therefore consists of a range of features, each associated with a vibrational mode. The spectrum is unique to the material and enables you to identify it. It is important to note that, although a full understanding of the vibrational modes is of interest, you rarely need this as you can use a reference database for identification.

When a sample is illuminated by a laser, both Raman scattering and photoluminescence (PL) can occur. The latter can be many times stronger than the former and can prevent successful Raman analysis.

PL comprises both fluorescence and phosphorescence processes and originates from an absorption/emission process between different electronic energy levels in the material. The amount and type of PL depends on which material you are studying and which laser wavelength you are using. Unwanted fluorescence interference can normally be avoided by choosing an appropriate laser wavelength.

• Energy diagram showing absorption of light and the processes involved in the emission of light as fluorescence and phosphorescence.

What PL can tell us

In many cases photoluminescence carries useful information that can facilitate sample analysis and augment the Raman data. inVia confocal Raman microscopes are suited to the analysis of both Raman scattering and PL.

Fluorescence imaging (a type of PL) is often employed in the biological sciences, where fluorescent tags are used to reveal the presence and distribution of molecular species. However, this approach is more invasive than Raman analysis, which is typically tag-free. Renishaw’s inVia confocal Raman microscope can be used to generate images of fluorescent tags, but more commonly provides valuable tag-free chemical information.

You can also use PL to study crystal defects, such as atomic vacancies and substitutions. This is of particular importance for materials such as diamond and silicon carbide (SiC). Not only can you identify the defect, but you can also tell if the crystal has internal stresses.

• Stress image generated from the ruby R2 PL band position

How to avoid PL backgrounds

Occasionally PL bands are strong and broad, masking Raman information. You can counter this by using a different laser wavelength. This can move the Raman bands away from the peak emission of the PL band and may even avoid generation of the PL entirely.

Ideally, a Raman instrument should be able to switch rapidly and easily between different laser wavelengths, so that you can select or avoid PL features, depending on your requirements.

Raman images (sometimes referred to as maps) depict a variation in spectral information from different points on, or in your sample. They can take the form of one-dimensional profiles, two-dimensional images, or three-dimensional rendered volumes. With them, you can rapidly see how a Raman parameter alters with position.

The parameter could be as simple as the intensity of a particular Raman band, or you could derive it from a more complicated analysis of the whole Raman spectrum.

The two main methods of collecting the spectral data to generate these images are Raman mapping and Raman imaging.

• White light and Raman images of washing powder

Raman mapping

Raman mapping collects a spectral hypercube (a Raman spectrum from each position on the sample in a single file), rather than a simple intensity image. The hypercube is analysed to produce Raman images.

There are several Raman mapping methods, such as:

• Point-by-point mapping
  The laser is focused to a spot. A motorised stage moves the sample under the laser. Spectra are sequentially acquired from an array of sample points spanning the defined region of interest. Fast versions of this are Renishaw’s StreamHR™ and StreamHR Rapide.
• Line focus mapping
  This is similar to point-by-point mapping, but the laser illuminates a line on the sample, rather than a spot. This enables you to simultaneously collect spectra from multiple positions on the sample, saving time. With this method you can use higher laser powers without damaging the sample (reducing exposure times). Renishaw’s StreamLine™ is a sophisticated modern implementation of this concept.

It is important to consider the potentially undesirable effects of undersampling when mapping. This is most clearly illustrated when point-by-point mapping: parts of the sample will be ‘missed’ if the laser spot is smaller than the spacing between acquisition points. Renishaw has solved this problem through the use of the StreamLine™ Slalom mode.

Generating Raman images from map data

Once all the Raman spectra are collected from the mapping experiment, they can be analysed to produce profiles, images or rendered volumes. Analysis options in Renishaw’s WiRE software include:

• Intensity at one frequency in the spectrum
  This produces an equivalent image to that from Raman imaging. These are quick to generate but may be misleading because it is not possible to differentiate between intensities arising from a Raman band of interest and those associated with a broad background fluorescence.
• Curve fit parameters
  All the spectra in the set have a theoretical curve fitted to one of the Raman bands. Images are then made based on the theoretical curve parameters for each spectrum. Images are often made using the centre frequency of the curve (band), or the full width at half maximum (FWHM), as this is sensitive to stresses and crystallinity within the sample respectively.
• Multivariate parameters
  Images can be generated using chemometric tools, such as generic principal component analysis (PCA), or Renishaw’s Empty Modelling™, which is optimised for Raman data. The Empty Modelling method reveals systematic variations between the Raman spectra, and highlights the distribution of these variations across the sample as an image. This is achieved without the need for prior knowledge of what is present within the sample, which greatly simplifies the analysis process. Multivariate analysis is very powerful because it uses information from the entire spectrum, not just one part of it (intensity at one frequency) or one curve-fitted band. This typically results in higher quality Raman images.

Raman imaging

Raman imaging is analogous to taking a photograph; spectral intensity values are collected simultaneously from the entire area of interest. The laser illuminates a square or circular region on the sample. The light is filtered so that the intensity of just one narrow part of the spectrum is recorded on the detector.

The single image collected contains limited information, just the intensity of the light at that frequency. However, these images can be acquired rapidly. This is especially true if you have a high power laser; because the light is spread over an area, you can use all the power without damaging your samples, with correspondingly short exposure times.

Two-dimensional images are typically produced using this method. Renishaw’s True Raman Imaging is an example of Raman imaging.

Note that it is possible to collect intensity values covering multiple points of the spectrum by using multiple and/or tuneable filters.

Spatial resolution

Point-by-point Raman mapping

Spatial resolution is determined by a combination of the laser spot size and the spacing between acquisition points on the sample.

• Laser spot size
  This is a function of the objective magnification and the laser wavelength (higher magnification and shorter wavelengths produce smaller spot sizes)
• Spacing between acquisition points on the sample (sampling)
  This is a function of the sample stage (ideally stages should have a large travel range while still enabling a step size down to 100 nm, smaller than the smallest spot size)

Raman imaging

Spatial resolution is determined by the magnification of the optics in the system and the size of the elements in the detector. Ultimately this is limited, by the inherent wavelike nature of light, to a little under a micrometre.