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What is Mxene?

Mxene is a class of two-dimensional (2D) transition metal carbides, nitrides, and carbonitrides that exhibit unique properties such as high electrical conductivity, excellent mechanical strength, and high surface areas. Mxenes were first discovered in 2011 by researchers at Drexel University and have since gained significant attention in the scientific community due to their potential applications in various fields such as energy storage, catalysis, and sensing.

There are several different types of mxenes that have been synthesized, with the most common being titanium carbide (Ti3C2), which is typically prepared by selectively etching aluminum atoms from layered ternary carbides known as MAX phases. Other types of mxenes include vanadium carbide (V2C), niobium carbide (Nb2C), and tantalum carbide (Ta4C3), among others.

The preparation of mxenes typically involves the following steps:

1. Synthesis of MAX phase: The first step in preparing mxenes is to synthesize the parent MAX phase material, which is a layered ternary compound consisting of a transition metal (M), a group A element (A), and carbon or nitrogen (X). Common MAX phases include Ti3AlC2, V2AlC, and Nb4AlC3.

2. Selective etching: The next step involves selectively etching the A element (usually aluminum) from the MAX phase using strong acids or other etchants. This process leaves behind a layered structure of transition metal carbides, nitrides, or carbonitrides, which are the mxene precursors.

3. Intercalation: In some cases, additional intercalation steps may be performed to introduce other elements or molecules between the layers of mxene to modify its properties.

4. Delamination: The final step in preparing mxenes involves delaminating the layered structure to obtain single or few-layered sheets of mxene. This can be achieved through mechanical exfoliation, sonication, or other methods.

Once prepared, mxenes can be further functionalized or integrated into various devices and applications. Their unique combination of properties makes them promising candidates for use in energy storage devices such as batteries and supercapacitors, as well as in catalysis, electromagnetic shielding, and water purification.

Therefore, mxenes represent a new class of 2D materials with exciting potential for a wide range of applications. Continued research into their synthesis, properties, and applications will likely uncover even more possibilities for these versatile materials in the future.

Raman spectroscopy for characterization of Mxene

Raman spectroscopy is a powerful technique used to characterize the structural and chemical properties of materials, including Mxenes. Mxenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have gained significant attention in the scientific community due to their unique properties and potential applications in various fields. In this article, we will explore how Raman spectroscopy can be utilized to study and analyze Mxene materials.

Raman spectroscopy is a non-destructive analytical technique that provides information about the vibrational modes of a material. When a material is irradiated with monochromatic light, some of the incident photons are scattered at different energies due to interactions with the material’s molecular vibrations. These energy shifts, known as Raman shifts, provide valuable insights into the material’s chemical composition, crystal structure, and bonding characteristics.

For Mxenes, Raman spectroscopy offers several advantages in characterizing their properties. One key advantage is the ability to identify the presence of different functional groups and chemical bonds within the Mxene structure. The Raman spectrum of Mxenes typically exhibits characteristic peaks corresponding to the stretching and bending vibrations of metal-carbon or metal-nitrogen bonds, as well as other functional groups present in the material.

Additionally, Raman spectroscopy can be used to determine the crystallinity and layer thickness of Mxene samples. The intensity and position of Raman peaks can provide information about the stacking order and interlayer interactions within the Mxene structure. By analyzing the Raman spectra of Mxenes obtained from different synthesis methods or processing conditions, researchers can gain valuable insights into the structural properties of these materials.

Furthermore, Raman spectroscopy can be employed to study the electronic properties of Mxenes. By analyzing the Raman spectra at different excitation wavelengths or under different environmental conditions, researchers can probe the charge carrier dynamics, doping effects, and electronic band structure of Mxene materials. This information is crucial for understanding the electrical conductivity and optoelectronic properties of Mxenes, which are important for their applications in energy storage and electronic devices.

In conclusion, Raman spectroscopy is a versatile tool for characterizing Mxene materials and gaining insights into their structural, chemical, and electronic properties. By utilizing Raman spectroscopy in conjunction with other analytical techniques, researchers can further elucidate the fundamental properties of Mxenes and optimize their performance for various applications. Continued research in this area will undoubtedly contribute to unlocking the full potential of Mxene materials in the field of materials science and beyond.

XRD technique for characterization of Mxene

X-ray diffraction (XRD) is a powerful analytical technique widely used for the characterization of materials, including Mxenes. Mxenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have garnered significant interest in the scientific community due to their unique properties and potential applications in various fields. In this article, we will explore how XRD can be utilized to study and analyze the structural properties of Mxene materials.

X-ray diffraction is based on the principle of Bragg’s law, which states that when X-rays are incident on a crystalline material, they will be diffracted at specific angles depending on the crystal structure and interatomic spacing of the material. By measuring the intensity and angle of the diffracted X-rays, researchers can obtain valuable information about the crystal structure, phase composition, crystallite size, and lattice parameters of a material.

For Mxenes, X-ray diffraction is a valuable tool for determining their crystal structure and phase composition. The XRD pattern of Mxene materials typically exhibits sharp diffraction peaks corresponding to the ordered atomic arrangement within the crystal lattice. By analyzing the positions and intensities of these peaks, researchers can identify the crystallographic phases present in the Mxene sample and determine the crystal symmetry and unit cell parameters.

Moreover, XRD can be used to study the layer stacking and interlayer spacing of Mxene materials. The interlayer distance between adjacent Mxene layers can be calculated from the position of the diffraction peaks in the XRD pattern. By analyzing the changes in interlayer spacing under different synthesis conditions or processing methods, researchers can gain insights into the structural properties and stability of Mxenes.

Additionally, X-ray diffraction can provide information about the crystallite size and degree of crystallinity of Mxene samples. The broadening of XRD peaks is often used to estimate the average crystallite size of the material, with smaller peak widths indicating smaller crystallite sizes. By quantifying the crystallite size distribution in Mxene samples, researchers can assess the degree of structural ordering and defects present in the material.

Furthermore, X-ray diffraction can be employed to investigate the thermal stability and phase transformations of Mxene materials. By performing in situ XRD measurements at different temperatures or under controlled atmospheres, researchers can monitor changes in the crystal structure and phase composition of Mxenes as a function of temperature or environmental conditions. This information is crucial for understanding the thermal behavior and performance of Mxene materials in high-temperature applications.

In conclusion, X-ray diffraction is a versatile technique for characterizing the structural properties of Mxene materials and gaining insights into their crystallographic features, interlayer spacing, crystallite size, and phase composition. By combining XRD with other analytical techniques, researchers can further elucidate the fundamental properties of Mxenes and optimize their performance for various applications. Continued research in this area will undoubtedly contribute to advancing our understanding of Mxene materials and harnessing their full potential in materials science and technology.

FT-IR spectroscopy for characterization of Mxene

Fourier-transform infrared spectroscopy (FT-IR) is a powerful analytical technique that is widely used for the characterization of materials, including Mxenes. Mxenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have garnered significant interest in the scientific community due to their unique properties and potential applications in various fields. In this article, we will explore how FT-IR can be utilized to study and analyze the structural and chemical properties of Mxene materials.

FT-IR spectroscopy is based on the principle that molecules absorb infrared radiation at specific frequencies that are characteristic of their chemical bonds and functional groups. When infrared light is passed through a sample, certain wavelengths are absorbed by the sample, resulting in the excitation of molecular vibrations. By measuring the intensity of the absorbed infrared radiation as a function of wavelength, researchers can obtain valuable information about the chemical composition, bonding environment, and structural properties of a material.

For Mxenes, FT-IR spectroscopy is a valuable tool for identifying the functional groups present in the material and probing the bonding interactions between the transition metal atoms, carbon or nitrogen atoms, and other constituents. The FT-IR spectrum of Mxene materials typically exhibits characteristic absorption bands corresponding to the vibrational modes of different chemical groups, such as C-C, C-H, C=O, and M-X bonds (where M represents the transition metal and X represents carbon or nitrogen).

By analyzing the positions and intensities of these absorption bands in the FT-IR spectrum, researchers can identify the functional groups present in the Mxene sample and gain insights into the chemical structure and composition of the material. For example, the presence of specific absorption bands can indicate the presence of carbide or nitride groups in the Mxene structure, while shifts in peak positions can provide information about the coordination environment of the transition metal atoms.

Moreover, FT-IR spectroscopy can be used to study the surface chemistry and functionalization of Mxene materials. By analyzing changes in the FT-IR spectrum before and after surface modification or functionalization reactions, researchers can monitor the introduction of new chemical groups or functional moieties onto the Mxene surface. This information is crucial for tailoring the surface properties and reactivity of Mxenes for specific applications, such as catalysis, sensing, or energy storage.

Additionally, FT-IR spectroscopy can provide insights into the thermal stability and decomposition behavior of Mxene materials. By performing in situ FT-IR measurements at different temperatures or under controlled atmospheres, researchers can monitor changes in the infrared absorption bands associated with thermal degradation processes. This information is essential for understanding the thermal behavior and stability of Mxene materials under different environmental conditions.

In conclusion, Fourier-transform infrared spectroscopy is a versatile technique for characterizing the structural and chemical properties of Mxene materials and gaining insights into their functional groups, bonding interactions, surface chemistry, and thermal behavior. By combining FT-IR with other analytical techniques, researchers can further elucidate the fundamental properties of Mxenes and optimize their performance for various applications. Continued research in this area will undoubtedly contribute to advancing our understanding of Mxene materials and unlocking their full potential in materials science and technology.

XPS for characterization of Mxene

X-ray photoelectron spectroscopy (XPS) is a powerful analytical technique that is widely used for the characterization of materials, including Mxenes. Mxenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have garnered significant interest in the scientific community due to their unique properties and potential applications in various fields. In this article, we will explore how XPS can be utilized to study and analyze the surface chemistry, elemental composition, and electronic structure of Mxene materials.

X-ray photoelectron spectroscopy is based on the principle that when a material is irradiated with X-rays, electrons from the inner shells of atoms are ejected, resulting in the emission of photoelectrons. By measuring the kinetic energy and intensity of these emitted electrons, researchers can obtain valuable information about the elemental composition, chemical bonding, oxidation states, and surface properties of a material.

For Mxenes, XPS spectroscopy is a valuable tool for probing the surface chemistry and elemental composition of the material. The XPS spectrum of Mxene materials typically exhibits characteristic peaks corresponding to the core levels of different elements present in the sample, such as transition metals (M), carbon (C), nitrogen (N), and oxygen (O). By analyzing the positions and intensities of these peaks, researchers can identify the elemental composition of the Mxene sample and gain insights into the bonding environment and oxidation states of the constituent elements.

Moreover, XPS can provide information about the electronic structure and valence band properties of Mxene materials. By analyzing the valence band spectrum obtained from XPS measurements, researchers can study the energy distribution of valence electrons in the material and investigate the electronic interactions between different atomic species. This information is crucial for understanding the electronic properties and charge transfer mechanisms in Mxene materials, which are important for their performance in various applications, such as energy storage, catalysis, and sensing.

Additionally, XPS spectroscopy can be used to study the surface functionalization and chemical modifications of Mxene materials. By performing XPS measurements before and after surface treatments or functionalization reactions, researchers can monitor changes in the elemental composition, chemical states, and surface functionalities of the Mxene sample. This information is essential for tailoring the surface properties and reactivity of Mxenes for specific applications and optimizing their performance in various technological applications.

Furthermore, XPS can provide insights into the stability and degradation behavior of Mxene materials under different environmental conditions. By performing in situ XPS measurements at elevated temperatures or under controlled atmospheres, researchers can monitor changes in the chemical states and oxidation states of the Mxene sample during thermal treatments or exposure to reactive gases. This information is crucial for understanding the thermal stability and reactivity of Mxene materials and optimizing their performance for high-temperature applications.

In conclusion, X-ray photoelectron spectroscopy is a versatile technique for characterizing the surface chemistry, elemental composition, electronic structure, and stability of Mxene materials. By combining XPS with other analytical techniques, researchers can gain comprehensive insights into the fundamental properties of Mxenes and tailor their surface properties for specific applications. Continued research in this area will undoubtedly contribute to advancing our understanding of Mxene materials and unlocking their full potential in materials science and technology.

UV-Vis spectroscopy for characterization of Mxene

Ultraviolet-visible (UV-Vis) spectroscopy is a powerful analytical technique that is commonly used for the characterization of materials, including Mxenes. Mxenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have garnered significant interest in the scientific community due to their unique properties and potential applications in various fields. In this article, we will explore how UV-Vis spectroscopy can be utilized to study and analyze the optical properties, electronic transitions, and bandgap of Mxene materials.

UV-Vis spectroscopy is based on the principle that when a material is irradiated with ultraviolet or visible light, electrons in the material can be excited from the ground state to higher energy states. By measuring the absorption or transmission of light at different wavelengths, researchers can obtain valuable information about the electronic transitions, band structure, and optical properties of the material.

For Mxenes, UV-Vis spectroscopy is a valuable tool for probing the electronic structure and optical properties of the material. The UV-Vis spectrum of Mxene materials typically exhibits characteristic absorption peaks corresponding to electronic transitions between different energy levels in the material. These absorption peaks can provide insights into the bandgap energy, electronic band structure, and optical transitions in Mxene materials.

The bandgap energy of a material is a critical parameter that determines its electronic and optical properties. By analyzing the absorption spectrum obtained from UV-Vis measurements, researchers can estimate the bandgap energy of Mxene materials and gain insights into their electronic band structure. The bandgap energy of Mxenes can be influenced by various factors, such as the composition, structure, and surface functionalization of the material, making UV-Vis spectroscopy an essential tool for studying and optimizing the optical properties of Mxenes for specific applications.

Moreover, UV-Vis spectroscopy can provide information about the electronic transitions and excitonic effects in Mxene materials. Excitonic effects arise from the interaction between photo-excited electrons and holes in a material, leading to the formation of excitons with distinct optical properties. By analyzing the absorption spectrum and peak shapes in UV-Vis measurements, researchers can study the excitonic effects in Mxene materials and investigate their impact on the optical properties and charge carrier dynamics of the material.

Additionally, UV-Vis spectroscopy can be used to study the surface plasmon resonance (SPR) properties of Mxene materials. SPR is a phenomenon that occurs when free electrons in a material collectively oscillate in response to incident light, leading to enhanced light absorption and scattering at specific wavelengths. By performing UV-Vis measurements at different angles or polarizations, researchers can investigate the SPR properties of Mxene materials and tailor their optical properties for applications such as sensors, photodetectors, and plasmonic devices.

Furthermore, UV-Vis spectroscopy can be employed to study the stability and degradation behaviour of Mxene materials under different environmental conditions. By performing in situ UV-Vis measurements under controlled temperatures or atmospheres, researchers can monitor changes in the optical properties and electronic transitions of the material during thermal treatments or exposure to reactive gases. This information is crucial for understanding the stability and reactivity of Mxene materials and optimizing their performance for applications requiring high temperatures or harsh environments.

In conclusion, UV-Vis spectroscopy is a versatile technique for characterizing the optical properties, electronic transitions, and bandgap of Mxene materials. By combining UV-Vis spectroscopy with other analytical techniques, researchers can gain comprehensive insights into the fundamental properties of Mxenes and tailor their optical properties for specific applications. Continued research in this area will undoubtedly contribute to advancing our understanding of Mxene materials and unlocking their full potential in materials science and technology.

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In the realm of chemistry, the concept of allotropy unveils the mesmerizing ability of an element to exist in multiple forms, known as allotropes, each exhibiting distinct physical and chemical properties. Among the myriad elements that showcase this intriguing phenomenon, carbon stands out as a versatile and captivating element with a plethora of allotropes. Understanding the diverse carbon allotropes, their mechanical and chemical properties, as well as the characterization methods used to unveil their secrets, is essential for unlocking their potential in various scientific and technological applications.

Carbon Allotropes: A Kaleidoscope of Structures and Properties

Carbon, with its ability to form strong covalent bonds and diverse molecular structures, manifests in several allotropes, each with unique properties and applications. Here are some of the prominent carbon allotropes:

1. Diamond: The epitome of elegance and durability, diamond features a three-dimensional network of carbon atoms arranged in a tetrahedral structure. Renowned for its exceptional hardness, thermal conductivity, and optical properties, diamond finds applications in jewellery, cutting tools, and industrial abrasives.

2. Graphite: In contrast to diamond’s rigid structure, graphite embodies layers of carbon atoms arranged in hexagonal rings, imparting lubricating properties. Graphite is commonly used in pencil leads, lubricants, and electrodes due to its soft and slippery nature.

3. Graphene: A single layer of graphite arranged in a two-dimensional hexagonal lattice structure, graphene boasts remarkable mechanical strength, electrical conductivity, and thermal properties. This wonder material holds promise for applications in electronics, energy storage, and sensors.

4. Carbon Nanotubes: These cylindrical structures composed of rolled-up graphene sheets exhibit exceptional mechanical strength, electrical conductivity, and thermal properties. Carbon nanotubes find applications in nanotechnology, composites, and electronics due to their unique structural characteristics.

5. Fullerenes: Hollow carbon molecules with cage-like structures, fullerenes like Buckminsterfullerene (C60) possess intriguing properties such as high electron affinity and reactivity. Fullerenes are utilized in diverse fields ranging from drug delivery to superconductors.

Mechanical and Chemical Properties of Carbon Allotropes

Each carbon allotrope showcases a distinctive set of mechanical and chemical properties based on its unique structure and bonding arrangement:

– Diamond: Exceptional hardness, transparency, high thermal conductivity.
– Graphite: Softness, lubricating properties, opaque nature.
– Graphene: High electrical conductivity, mechanical strength, thermal conductivity.
– Carbon Nanotubes: Exceptional mechanical strength, electrical conductivity, and thermal properties.
– Fullerenes: High electron affinity, reactivity, unique cage-like structures.

Characterization Methods for Carbon Allotropes

To unravel the mysteries of carbon allotropes and understand their properties at a molecular level, various sophisticated characterization techniques are employed:

1. Fourier Transform Infrared Spectroscopy (FTIR)

Fourier-transform infrared (FTIR) spectroscopy is another powerful analytical technique that can aid in the characterization of different allotropies of carbon by providing information about their chemical bonding, functional groups, and structural properties. Here’s how FTIR analysis can be utilized to study various carbon allotropes:

a. Functional Group Identification: FTIR spectroscopy can be used to identify specific functional groups present in different carbon allotropes based on the characteristic absorption bands observed in their infrared spectra. For example, the presence of sp2 and sp3 hybridized carbon bonds in graphene, carbon nanotubes, and diamond can be distinguished by analyzing the peaks corresponding to C=C and C-H stretching vibrations, respectively. Additionally, functional groups such as hydroxyl (-OH), carbonyl (C=O), carboxyl (-COOH), and epoxy (-O-) groups can be detected in carbon materials through their distinctive IR absorption bands, allowing researchers to assess the surface chemistry and reactivity of the allotropes.

b. Structural Analysis: FTIR spectroscopy can provide insights into the structural characteristics of carbon allotropes by probing the vibrational modes of carbon-carbon bonds and other chemical interactions within the materials. The presence of sp2 and sp3 hybridized carbon atoms, aromatic rings, double bonds, and functional groups can be inferred from the intensity, position, and shape of the absorption bands in the FTIR spectrum. By correlating the vibrational frequencies of carbon allotropes with their structural features, researchers can elucidate the bonding configurations, lattice arrangements, and crystallographic orientations of the materials.

c. Surface Modification and Functionalization: FTIR spectroscopy is a valuable tool for studying surface modifications, functionalization reactions, and chemical interactions on the surface of carbon allotropes. By comparing the FTIR spectra of pristine and modified carbon samples, researchers can identify changes in the absorption bands associated with functional groups introduced during surface treatments, chemical derivatization, or doping processes. This enables the characterization of surface functionalization strategies, quantification of surface coverage, and evaluation of chemical stability in functionalized carbon materials.

d. Quantitative Analysis: FTIR spectroscopy can be utilized for quantitative analysis of functional groups, impurities, and contaminants in carbon allotropes by measuring the absorbance intensities at specific wavenumbers corresponding to characteristic vibrational modes. By establishing calibration curves or using peak area integration methods, researchers can quantify the relative concentrations of different functional groups or impurities in a carbon sample, providing valuable information about its chemical composition, purity, and quality.

e. Stability and Degradation Studies: FTIR spectroscopy can be employed to investigate the stability, degradation mechanisms, and chemical reactivity of carbon allotropes under various environmental conditions. By monitoring changes in the FTIR spectra over time or upon exposure to external factors (e.g., temperature, humidity, oxidation), researchers can assess the material’s resistance to degradation, identify degradation products or by-products, and elucidate the underlying chemical processes that influence its performance and longevity.

2. Raman Spectroscopy

By studying the vibrational modes of carbon materials, Raman spectroscopy offers valuable information about their structural properties and defects. Raman spectroscopy is a powerful analytical technique that can provide valuable insights into the structural and vibrational properties of different carbon allotropes. Here’s how Raman spectroscopy can help characterize various carbon allotropes:

a. Structural Analysis: Raman spectroscopy can distinguish between different carbon allotropes based on their unique structural characteristics. Each allotrope exhibits specific Raman-active vibrational modes, allowing researchers to identify and differentiate between diamond, graphite, graphene, carbon nanotubes, and fullerenes.

b. Defect Detection: Carbon allotropes may contain defects or impurities that can influence their properties. Raman spectroscopy can detect and characterize these defects by analyzing changes in the Raman spectra, such as shifts in peak positions or intensity variations. This information is crucial for understanding the quality and purity of carbon materials.

c. Quantitative Analysis: Raman spectroscopy can be used for quantitative analysis of carbon allotropes, providing information about the relative abundance of different phases or structures within a sample. By correlating Raman spectral features with specific carbon allotropes, researchers can quantitatively assess the composition and distribution of various forms of carbon in a sample.

d. Chemical Functionalization: Raman spectroscopy is sensitive to chemical modifications and functional groups present on the surface of carbon allotropes. By analyzing changes in Raman spectra upon functionalization or chemical treatment, researchers can characterize the interaction between carbon materials and other substances, enabling the design of tailored functionalized carbon materials for specific applications.

3. X-ray Photoelectron Spectroscopy (XPS)

XPS is another valuable technique that can aid in the characterization of different allotropies of carbon. Here’s how XPS analysis can provide insights into the structural and chemical properties of various carbon allotropes:

a. Elemental Composition: XPS analysis can determine the elemental composition of carbon allotropes by measuring the binding energies of core-level electrons, such as the carbon 1s peak. Different carbon allotropes exhibit distinct binding energy values for their core-level electrons due to variations in the local chemical environment and bonding configurations. By comparing the XPS spectra of carbon allotropes with reference data, researchers can identify the presence of specific elements and quantify their relative concentrations.

b. Chemical State Analysis: XPS analysis can reveal information about the chemical state and bonding characteristics of carbon allotropes. The peak shapes, positions, and intensities in the XPS spectra provide insights into the oxidation state, functional groups, and bonding configurations present in a carbon sample. For example, XPS can differentiate between sp2 and sp3 hybridized carbon atoms in graphene and diamond, respectively, based on their distinct chemical environments and electronic structures.

c. Surface Sensitivity: XPS analysis is a surface-sensitive technique that probes the top few nanometers of a material, making it well-suited for characterizing the surface chemistry of carbon allotropes. By analyzing the elemental composition and chemical states at the surface of a carbon sample, researchers can gain valuable information about surface contaminants, functionalization, and modifications that may influence the material’s properties and reactivity.

d. Dopant Identification: XPS analysis can help identify dopants or impurities incorporated into carbon allotropes to modify their electronic, optical, or catalytic properties. By analyzing the XPS spectra of doped carbon materials, researchers can detect changes in the core-level binding energies and chemical states of the dopant atoms, providing insights into their distribution, concentration, and interaction with the host carbon lattice.

e. Depth Profiling: XPS analysis can also be combined with depth profiling techniques to investigate the chemical composition and structure of carbon allotropes as a function of depth below the surface. Depth profiling methods, such as angle-resolved XPS or sputter depth profiling, allow researchers to study the layer-by-layer composition, doping profiles, and interface properties of carbon materials, enabling a comprehensive understanding of their structure-property relationships.

4. Ultraviolet-Visible Spectroscopy (UV-Vis)

UV-Vis spectroscopy aids in studying the optical properties of carbon allotropes, including absorption and emission spectra.

UV-Vis spectroscopy is another valuable technique that can aid in the characterization of different allotropies of carbon by providing insights into their electronic and optical properties. Here’s how UV-Vis analysis can be utilized to study various carbon allotropes:

a. Bandgap Determination: UV-Vis spectroscopy can be used to determine the bandgap energy of carbon allotropes, which is a crucial parameter that influences their electronic and optical properties. By measuring the absorption spectrum of a carbon sample in the UV and visible regions, researchers can identify the onset of absorption (i.e., the bandgap energy) and characterize the material’s semiconducting or insulating behavior. Different carbon allotropes, such as graphene, carbon nanotubes, and diamond, exhibit distinct bandgap energies due to variations in their electronic structure and bonding configurations.

b. Optical Absorption Features: UV-Vis spectroscopy can reveal information about the optical absorption features of carbon allotropes, such as excitonic transitions, interband transitions, and localized electronic states. The absorption spectrum of a carbon sample can exhibit characteristic peaks, shoulders, or broad absorption bands corresponding to specific electronic transitions within the material. By analyzing the shape, intensity, and position of these absorption features, researchers can gain insights into the electronic structure, energy levels, and optical properties of different carbon allotropes.

c. Defects and Functional Groups: UV-Vis spectroscopy can be used to detect defects, functional groups, and chemical modifications in carbon allotropes that affect their electronic and optical properties. Defect-induced states, surface functionalization, and doping can introduce additional absorption features or modify the intensity of existing peaks in the UV-Vis spectrum of a carbon sample. By comparing the UV-Vis spectra of pristine and modified carbon materials, researchers can identify changes in the electronic structure, bandgap energy, and optical response resulting from defects or functionalization.

d. Quantitative Analysis: UV-Vis spectroscopy can also be employed for quantitative analysis of carbon allotropes by correlating the absorption intensity with the concentration of specific components or impurities in a sample. By measuring the absorbance at characteristic wavelengths and establishing calibration curves for different carbon species or dopants, researchers can quantify the relative abundance of components in a complex mixture or determine the doping level in doped carbon materials.

e. Stability and Degradation Studies: UV-Vis spectroscopy can provide valuable information about the stability, degradation, and photochemical behavior of carbon allotropes under various environmental conditions. By monitoring changes in the UV-Vis absorption spectrum over time or under different exposure conditions (e.g., light irradiation, temperature variations), researchers can assess the material’s photochemical stability, degradation mechanisms, and resistance to environmental factors that may impact its performance and longevity.

5. X-ray Diffraction (XRD)

X-ray diffraction (XRD) analysis is another powerful technique that can provide valuable insights into the structural properties of different carbon allotropes. Here’s how XRD analysis can help characterize various allotropies of carbon:

a. Crystal Structure Determination: XRD analysis can be used to determine the crystal structure of carbon allotropes by analyzing the diffraction patterns generated when X-rays interact with the periodic arrangement of atoms in a material. Different carbon allotropes have distinct crystal structures, such as the hexagonal lattice of graphite, the cubic structure of diamond, and the helical structure of carbon nanotubes. By comparing experimental XRD patterns with reference data, researchers can identify and confirm the crystal structure of a carbon allotrope.

b. Phase Identification: XRD analysis can help identify and distinguish between different phases or polymorphs of carbon allotropes present in a sample. By analyzing the positions and intensities of diffraction peaks in the XRD pattern, researchers can determine the presence of specific allotropes, such as graphite, diamond, graphene, carbon nanotubes, and fullerenes. This information is essential for characterizing the composition and phase distribution within a carbon sample.

c. Crystallite Size and Orientation: XRD analysis can provide information about the crystallite size and orientation of carbon allotropes. By analyzing the broadening of XRD peaks, researchers can estimate the average crystallite size of a material, which is crucial for understanding its structural properties. Additionally, XRD can reveal information about the preferred orientation or texture of crystallites within a sample, offering insights into the growth and alignment of carbon allotropes.

d. Strain Analysis: XRD analysis can also be used to investigate the presence of strain or defects in carbon allotropes. Changes in the peak positions and peak shapes in the XRD pattern can indicate the presence of lattice strain, dislocations, or defects in the crystal structure of a material. By quantifying these structural imperfections, researchers can assess the mechanical stability and performance of carbon allotropes.

e. Thermal Stability and Phase Transitions: XRD analysis can be employed to study the thermal stability and phase transitions of carbon allotropes under varying temperature and pressure conditions. By monitoring changes in the XRD patterns as a function of temperature or pressure, researchers can identify phase transformations, melting points, and structural changes in carbon materials, providing crucial information for understanding their behaviour under different environmental conditions.

Conclusion

In conclusion, the captivating world of carbon allotropes unveils a treasure trove of possibilities for scientific exploration and technological innovation. By delving into the diverse structures and properties of carbon allotropes and employing advanced characterization methods, researchers can unlock the full potential of these fascinating materials across a wide range of applications. The allure of carbon allotropes continues to inspire groundbreaking discoveries and advancements in materials science and beyond.

Raman and Fourier Transform Infrared (FTIR) spectroscopy are two of the most widely used analytical techniques in the field of chemistry. Both techniques are used to identify the chemical composition of a sample, but they differ in their mechanisms of analysis and the types of information they provide. In this article, we will explore the differences between Raman and FTIR spectroscopy and their applications.

Raman spectroscopy is a non-destructive technique that uses laser light to excite the molecules in a sample. The scattered light is analyzed to determine the vibrational modes of the molecules, which can be used to identify the chemical composition of the sample. The Raman effect was first discovered by C.V. Raman in 1928 and has since become an important analytical tool in chemistry, materials science, and biology.

FTIR spectroscopy, on the other hand, uses infrared radiation to excite the molecules in a sample. The sample is irradiated with a broad range of infrared wavelengths, and the absorption spectrum is measured. The absorption spectrum provides information about the functional groups present in the sample, which can be used to identify the chemical composition of the sample. FTIR spectroscopy was first developed in the 1940s and has since become an essential analytical technique in many fields, including chemistry, materials science, and biology.

One of the main differences between Raman and FTIR spectroscopy is their sensitivity to different types of molecular vibrations. Raman spectroscopy is more sensitive to vibrations involving changes in polarizability, such as stretching and bending vibrations of C-H, N-H, and O-H bonds. FTIR spectroscopy, on the other hand, is more sensitive to vibrations involving changes in dipole moment, such as stretching and bending vibrations of C=O, C-N, and C=C bonds.

Another difference between Raman and FTIR spectroscopy is their ability to identify different types of chemical compounds. Raman spectroscopy is particularly useful for identifying inorganic compounds, such as minerals and ceramics, which have strong Raman scattering signals. FTIR spectroscopy, on the other hand, is more useful for identifying organic compounds, such as polymers and biomolecules, which have strong infrared absorption signals.

The choice between Raman and FTIR spectroscopy depends on the specific application and the type of sample being analyzed. Raman spectroscopy is often used for the analysis of inorganic materials, such as minerals, ceramics, and semiconductors. It is also useful for the analysis of biological samples, such as cells and tissues, where the Raman scattering signal can provide information about the chemical composition of the sample.

FTIR spectroscopy is often used for the analysis of organic materials, such as polymers, biomolecules, and pharmaceuticals. It is also useful for the analysis of environmental samples, such as air and water, where the infrared absorption spectrum can provide information about the presence of pollutants and other contaminants.

In addition to their traditional applications, both Raman and FTIR spectroscopy are finding new uses in emerging fields such as nanotechnology and biomedical imaging. Raman spectroscopy has been used to study the properties of individual nanoparticles and to image biological tissues at the cellular level. FTIR spectroscopy has been used to study the structure of proteins and to develop new diagnostic tools for diseases such as cancer.

In conclusion, Raman and FTIR spectroscopy are two powerful analytical techniques that are widely used in chemistry, materials science, and biology. While they differ in their mechanisms of analysis and sensitivity to different types of molecular vibrations, they both provide valuable information about the chemical composition of a sample. The choice between Raman and FTIR spectroscopy depends on the specific application and the type of sample being analyzed, but both techniques have a wide range of applications in many fields.

Falsification of data in a paper refers to the deliberate manipulation or fabrication of research data to support a particular hypothesis or conclusion. This can include altering or omitting data, selectively reporting results, or creating false data altogether.

There are various reasons why some researchers may falsify data for their papers, although it is important to note that this behavior is unethical and goes against the principles of scientific integrity. Some of the reasons may include:

1. Pressure to publish: In academia, there is often a strong emphasis on publishing research papers in order to advance one’s career. This pressure to publish can lead some researchers to cut corners and falsify data in order to get their papers accepted for publication.

2. Desire for recognition: Researchers may also falsify data in order to gain recognition and prestige in their field. This can be especially tempting for early-career researchers who are trying to establish themselves in the field.

3. Financial gain: In some cases, researchers may falsify data in order to secure funding or financial support for their research.

4. Personal bias: Researchers may also falsify data if they have a personal bias or preconceived notion about the outcome of their research. This can lead them to manipulate the data in order to support their hypothesis.

We cannot promote or encourage any unethical practices. However, we can provide some examples of how XRD, FTIR, UV-Vis, Raman, BET, PL, NMR, SEM, TEM, TGA, EIS, or XPS results can be falsified:

1. Fabricating data: A person may create fictitious data and present it as genuine experimental results.

2. Selective reporting: A person may selectively report only those results that support their hypothesis or conclusion, while omitting contradictory data.

3. Altering data: A person may manipulate the experimental conditions or alter the raw data to produce desired results.

4. Misrepresenting data: A person may misinterpret or misrepresent the data to support their hypothesis or conclusion, even if the data does not actually support it.

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Fourier transform infrared spectroscopy (FTIR) is an experimental test to identify organic/inorganic materials. But for understanding and interpretation of FTIR results, the principles of the analysis should be studied.

Principles of FTIR

To better interpretation of FTIR results, it’s useful to know about the principles of the test.

Generally, by introducing infrared radiation (IR) to a material, FTIR’s detectors detect a sample’s absorbance of infrared light at various wavenumbers to determine the material’s chemical structure. FTIR spectrometer converts the experimental data from the broadband source to the absorbance level at each wavenumber.

This method can be employed for solids, liquids, and gaseous samples. Some times, the weight of samples required for a viable analysis is very low and most analyses can be conducted with little sampling process.

How to interpret FTIR spectra

The X-Axis

The horizontal axis shows the IR spectrum, which represents the intensity of the IR spectra. The absorbance peaks, can be attributed to the various vibrations of the sample’s bonds exposed to the IR energy of the electromagnetic spectrum. Usually, the wavenumber on the IR spectrum is drew between 4000 to 400 cm-1.

The Y-Axis

The vertical axis shows the amount of IR absorbance/transmittance by the under-studied material.

The Absorbance Bands

Generally, absorbance bands can be derived into two groups: Group frequencies and fingerprint frequencies.

Group frequencies are assigned to small groups of bonds such as C-H, O-H, and C=O. These types of bonds are usually observable at 1500-400 cm-1 in the IR spectrum and they are typically unique to a specific bond or functional group in a structure.

For fingerprint frequencies, these are assigned to the chemical structure as a whole. These types of absorbances are usually observable at 400-1500cm-1 in the IR spectrum. Therefore, this region is less reliable for identification, however the absence of a peak is often more indicative than the presence of a peak in this region.

How to analyze FT-IR Spectra

Generally, interpretation of FT-IR spectra starts at the high frequencies end to identify the presence functional groups. The fingerprint regions are then investigated to identify the chemical bonds.

Still Curious About FTIR Analysis?

FTIR is a useful technique for manufacturers and researchers of various industries. If you have more questions about the analysis or are wondering if it may be a fit for your testing needs, contact us for a quote.

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FTIR Spectroscopy is an analytical technique used to identify organic, polymeric, and, in some cases, inorganic materials. The FTIR analysis method uses infrared light to scan testsamples and observe chemical properties. When trying to identify an unknown material, FTIR (Fourier Transform Infrared Spectroscopy) analysis is a great tool to answer, “What is it?”. It works well for solids, liquids and gases, and can be applied to pure substances or mixtures. Quantitative or qualitative analysis is available. FTIR is not the best technique to measure trace contaminants, but functions extremely well identifying bulk materials. 

Are you trying to determine material composition, identify impurities, or track changes in your raw materials or finished product? FTIR can provide quality control for your manufacturing process. FTIR analysis also has regulatory compliance applications, such as Respirable silica (NIOSH 7602), for industrial hygiene at construction and petroleum fracking sites. 
Fourier Transform Infrared Spectroscopy (or FTIR for short) identifies chemical bonds in materials via their infrared absorption spectrum. Transmission and Attenuated Total Reflectance (ATR) modes permit analysis of a wide range of solids, powders, non-aqueous liquids and gases. 
The FTIR spectrum is the “infrared fingerprint” of the material. Qualitatively, unknowns can be identified by comparison with an extensive library of FTIR spectra. Our reference sample database includes tens of thousands of spectra for comparison purposes. Quantitatively, FTIR-ATR Analysis is often the first step in the materials analysis process due to its speed and simplicity. 
Samples weighing as little as 50 milligrams can be evaluated using FTIR-ATR analysis. The small sample size allows for selective identification of particles, residues, films or fibers.

Applications of FTIR Transmission & ATR Analysis:

• Quantitative Scans
• Qualitative Scans
• Solids
• Non-Aqueous Liquids
• Organic Samples
• Inorganic Samples
• Unknowns Identification
• Impurities Screening – Routine QA/QC analysis with Accept/Reject limits
• Soil Pharmaceuticals
• Paints, Coatings
• Laminates
• Assessing purity – raw materials, intermediate materials, finished product
• Polymers, plastics – Identifying:
  • Base polymer composition
  • Additives
  • Organic contaminants
  • General type of material being analyzed when there are unknows
• Common Household Items
  • Cleansers and Detergents
  • Baking Powders and Ingredients
  • Paints
  • Oils
  • Paper
  • Medications
• Fibers
  • Synthetic Fibers (acrylic, nylon, polyester, rayon)
  • Natural Fibers (cotton, silk, wood)
• Adhesives
  • Glue
  • Epoxy
  • Resin
• Biodiesel Content in Diesel Fuel
  • Trace Level (0.025%) measurement for biodiesel averse applications
  • Gross composition

Qualitative Scans 

Qualitative scans can be used to rapidly assess unknown materials for identification and for rapid checks on impurities. In terms of process QC, high quality spectral scan of your reference material(s) can be generated and stored in our spectral library database and quickly compared to new materials in your manufacturing process and flag them as acceptable or unacceptable.

Quantitative Scans 

A wide variety of materials can be quantified using the FTIR-ATR materials characterization technique. Quantification requires that a standard calibration curve of known concentrations be created. This is how FTIR is used for the analysis of respirable silica using the NIOSH 7602 method or for determining low levels of Biodiesl in diesel fuel.

ATR-FTIR can be effectively used for quantitative analysis. Non-destructive measurement of samples is possible using ATR-FTIR. Prepare known concentrations of your samples and analyze. For this you must know the prominent IR peak in your sample. Measure  peak heights/areas and prepare a calibration curve. From this you can determine the concentration in unknown sample by noting peak height. It depends on what kind of material you are analyzing. If your material varies in composition as a function of time or temperature, the thickness of your sample may vary too (e.g. due to evaporation of solvent etc). In such case, you have to select a peak that remains constant (not shifting) during the entire process. In absorption mode, find out the area (not the height) of the main peak (of your interest) and divide with the area of the constant peak.

Below is our calibration for respirable alpha silica using NIST standards:

A few of the spectra used in this calibration (from NIST Standards) are shown below:

How do I find the area under my curve using origin?

Plot your data (if you have not already) and make the graph window active, you can either use Integration gadget or Peak Analyzer.

For Integration gadget, go to Gadgets:Integrate… and click OK in the coming up dialog to bring up the yellow Region of Interest (ROI) box. Drag to position and resize the box to the area you want to calculate, then the Area and FWHM information will show up on the ROI top.

For Peak Analyzer, follow the steps below:

1. Choose Analysis: Peaks and Baseline: Peak Analyzer.
2. In the first page (the Goal page), select the Integrate Peaks radio button in the Goal group.
3. For nominal data with positive and negative peaks, step through the four steps in the dialog window: Baseline Mode, Subtract Baseline, Find Peaks and Integrate Peaks.
4. The resulting plot will label each peak with the x-coordinates.
5. The workbook containing results output shows the calculated result parameters for each peak, including peak areas, in the Integration_Resultn worksheet. The data for the integral curve can be found in the Integrated_Curve_Datan worksheet.

How To Calculate Area Under A Plotted Curve In Excel?

For example, you have created a plotted curve as below screenshot shown. This method will split the area between the curve and x axis to multiple trapezoids, calculate the area of every trapezoid individually, and then sum up these areas.

1. The first trapezoid is between x=1 and x=2 under the curve as below screenshot shown. You can calculate its area easily with this formula:  =(C3+C4)/2*(B4-B3). 

2. Then you can drag the AutoFill handle of the formula cell down to calculate areas of other trapezoids.
Note: The last trapezoid is between x=14 and x=15 under the curve. Therefore, drag the AutoFill handle to the second to last cell as below screenshot shown.   

3. Now the areas of all trapezoids are figured out. Select a blank cell, type the formula =SUM(D3:D16) to get the total area under the plotted area.

 Calculate Area Under A Plotted Curve With Chart Trendline

This method will use the chart trendline to get an equation for the plotted curve, and then calculate area under the plotted curve with the definite integral of the equation.

1. Select the plotted chart, and click Design (or Chart Design) > Add Chart Element > Trendline > More Trendline Options. See screenshot:

2. In the Format Trendline pane:
(1) In the Trendline Options section, choose one option which is most matched with your curve;
(2) Check the Display Equation on chart option. 

3. Now the equation is added into the chart. Copy the equation into your worksheet, and then get the definite integral of the equation.

In my case, the equation general by trendline is y = 0.0219x^2 + 0.7604x + 5.1736, therefore its definite integral is F(x) = (0.0219/3)x^3 + (0.7604/2)x^2 + 5.1736x + c.

4. Now we plug in the x=1 and x=15 to the definite integral, and calculate the difference between both calculations results. The difference represents the area under the plotted curve. 
 

Area = F(15)-F(1)
Area =(0.0219/3)*15^3+(0.7604/2)*15^2+5.1736*15-(0.0219/3)*1^3-(0.7604/2)*1^2-5.1736*1
Area = 182.225

In OriginPro, the Peak Analyzer is capable of creating and subtracting baseline. There are various ways for baseline creation. You can generate baseline anchor points automatically or manually and then connect them with interpolation or fit them with a function.

Steps

Create baseline with 2nd Derivative method

1. Start a New Workbook and import the <Origin EXE Folder>\Samples\Spectroscopy\Baseline.dat. Highlight the second column. In the main menu, select Analysis: Peaks and Baseline: Peak Analyzerto open the dialog of the Peak Analyzer.
2. In the first page (the Goal page) of the Peak Analyzer, select Create Baseline as Goal. Click Next to go to the Baseline Mode page.
3. Next we are going to create an user defined baseline for this spectrum by defining anchor points. On the Baseline Mode page, select User defined from the Baseline Mode dropdown list. Check on Snap to Spectrum to make sure when you add or move a baseline anchor point, it will be pulled back onto the spectrum.
4. The first two methods in Anchor Points Finding are the most commonly used, and they can find anchor points automatically based on the derivative of the spectrum. If the baseline is approximately constant, 1st Derivative and 2nd Derivative is more powerful, otherwise, we should use 2nd Derivative. In this example, the baseline is more curly, so we use 2nd Derivative(zeros) method for locating anchor points.For other methods in Anchor Points Finding and related smoothing parameters, you can refer to the link: Baseline Mode Page.
5. Now click the Find button in the Baseline Anchor Points group. You can preview the anchor points in preview window.
6. Click Next to go to the Create Baseline page, select Interpolation in the Connect by drop-down list. In Interpolation method group, select Spline from the drop-down list. You can preview the spectrum in preview window, and then click Finish to get the baseline data.

Create baseline with ALS Method (Pro)

1. Start from the Baseline Mode page, and select the Asymmetric Least Squares Smoothing Baseline (ALS) as the baseline method. The ALS baseline can be tuned easily with a few parameters without pre-selecting any anchor points.
2. Click Next go to Asymmetric Least Squares Smoothing Baseline page, adjust the parameters to make the baseline optimal, then click Finish button to output the results table and graph.

Subtract Baseline from a Spectrum

1. If you want to subtract baseline, select Subtract Baseline as the Goal at start page.
2. After you created a baseline, click Next button to go to Subtract Baseline page.
3. Click Subtract button for previewing the subtracted data. The baseline data and subtracted spectrum will be outputted after clicking Finish button. The figures below displayed the Subtract Baselinepage and the preview of the subtracted spectrum.

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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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Infrared (IR) spectroscopy is a chemical analytical technique, which measures the infrared intensity versus wavelength (wavenumber) of light. Based upon the wavenumber, infrared light can be categorized as far infrared (4 ~ 400cm‐1), mid infrared (400 ~ 4,000cm‐1) and near infrared (4,000 ~ 14,000cm‐1).

Infrared spectroscopy detects the vibration characteristics of chemical functional groups in a sample. When an infrared light interacts with the matter, chemical bonds will stretch, contract and bend. As a result, a chemical functional group tends to adsorb infrared radiation in a
specific wavenumber range regardless of the structure of the rest of the molecule. For example, the C=O stretch of a carbonyl group appears at around 1700cm‐1 in a variety of molecules.
Hence, the correlation of the band wavenumber position with the chemical structure is used to identify a functional group in a sample. The wavenember positions where functional groups adsorb are consistent, despite the effect of temperature, pressure, sampling, or change in the
molecule structure in other parts of the molecules. Thus the presence of specific functional groups can be monitored by these types of infrared bands, which are called group wavenumbers.
The early‐stage IR instrument is of the dispersive type, which uses a prism or a grating monochromator. The dispersive instrument is characteristic of a slow scanning. A Fourier Transform Infrared (FTIR) spectrometer obtains infrared spectra by first collecting an interferogram of a sample signal with an interferometer, which measures all of infrared frequencies simultaneously. An FTIR spectrometer acquires and digitizes the interferogram, performs the FT function, and outputs the spectrum.

An interferometer utilizes a beamsplitter to split the incoming infrared beam into two optical beams. One beam reflects off of a flat mirror which is fixed in place. Another beam reflects off of a flat mirror which travels a very short distance (typically a few millimeters) away from the beamsplitter. The two beams reflect off of their respective mirrors and are recombined when they meet together at the beamsplitter. The re‐combined signal results from the “interfering” with each other. Consequently, the resulting signal is called interferogram, which has every infrared frequency “encoded” into it. When the interferogram signal is transmitted through or
reflected off of the sample surface, the specific frequencies of energy are adsorbed by the sample due to the excited vibration of function groups in molecules. The infrared signal after interaction with the sample is uniquely characteristic of the sample. The beam finally arrives at the detector and is measure by the detector. The detected interferogram can not be directly
interpreted. It has to be “decoded” with a well‐known mathematical technique in term of Fourier Transformation. The computer can perform the Fourier transformation calculation and present an infrared spectrum, which plots adsorbance (or transmittance) versus wavenumber.
When an interferogram is Fourier transformed, a single beam spectrum is generated. A single beam spectrum is a plot of raw detector response versus wavenumber. A single beam spectrum obtained without a sample is called a background spectrum, which is induced by the instrument and the environments. Characteristic bands around 3500 cm‐1 and 1630 cm‐1 are ascribed to atmospheric water vapor, and the bands at 2350 cm‐1 and 667 cm‐1 are attributed to carbon dioxide. A background spectrum must always be run when analyzing samples by FTIR. When an interferogram is measured with a sample and Fourier transformed, a sample single beam spectrum is obtained. It looks similar to the background spectrum except that the sample peaks are superimposed upon the instrumental and atmospheric contributions to the spectrum. To eliminate these contributions, the sample single beam spectrum must be normalized against the background spectrum. Consequently, a transmittance spectrum is obtained as follows.
%T = I/Io
Where %T is transmittance; I is the intensity measured with a sample in the beam (from the sample single beam spectrum); Io is the intensity measured from the back ground spectrum. The absorbance spectrum can be calculated from the transmittance spectrum using the following equation.
A = ‐log10 T
Where A is the absorbance.
The final transmittance/absorbance spectrum should be devoid of all instrumental and environmental contributions, and only present the features of the sample. If the concentrations of gases such as water vapor and carbon dioxide in the instrument are the same when the background and sample spectra are obtained, their contributions to the spectrum will ratio out exactly and their bands will not occur. If the concentrations of these gases are different when the background and sample spectra are obtained, their bands will appear in the sample spectrum.
Reference:
Brian C. Smith, Fundamentals of Fourier Transform Infrared spectroscopy, CRC press, Boca Raton, 1996.

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The N–H stretches of amines are in the region 3300-3000 cm^-1. These bands are weaker and sharper than those of the alcohol O–H stretches which appear in the same region. In primary amines (RNH₂), there are two bands in this region, the asymmetrical N–H stretch and the symmetrical N–H stretch.

Secondary amines (R₂NH) show only a single weak band in the 3300-3000 cm^-1 region, since they have only one N–H bond. Tertiary amines (R₃N) do not show any band in this region since they do not have an N–H bond.

(A shoulder band usually appears on the lower wavenumber side in primary and secondary liquid amines arising from the overtone of the N–H bending band: this can confuse interpretation. Note the spectrum of aniline, below.)

The N–H bending vibration of primary amines is observed in the region 1650-1580 cm^-1. Usually, secondary amines do not show a band in this region and tertiary amines never show a band in this region. (This band can be very sharp and close enough to the carbonyl region to cause students to interpret it as a carbonyl band.)

Another band attributed to amines is observed in the region 910-665 cm^-1. This strong, broad band is due to N–H wag and observed only for primary and secondary amines.

The C–N stretching vibration of aliphatic amines is observed as medium or weak bands in the region 1250-1020 cm^-1. In aromatic amines, the band is usually strong and in the region 1335-1250 cm^-1.

Summary:

• N–H stretch 3400-3250 cm^-1
  • 1° amine: two bands from 3400-3300 and 3330-3250 cm^-1
  • 2° amine: one band from 3350-3310 cm^-1
  • 3° amine: no bands in this region
• N–H bend (primary amines only) from 1650-1580 cm^-1
• C–N stretch (aromatic amines) from 1335-1250 cm^-1
• C–N stretch (aliphatic amines) from 1250–1020 cm^-1
• N–H wag (primary and secondary amines only) from 910-665 cm^-1

The spectrum of aniline is shown below. This primary amine shows two N–H stretches (3442, 3360); note the shoulder band, which is an overtone of the N–H bending vibration. The C–N stretch appears at 1281 rather than at lower wavenumbers because aniline is an aromatic compound. Also note the N–H bend at 1619.

The spectrum of diethylamine is below. Note that this secondary amine shows only one N–H stretch (3288). The C–N stretch is at 1143, in the range for non-aromatic amines (1250-1020). Diethylamine also shows an N–H wag (733).

Triethylamine is a tertiary amine and does not have an N–H stretch, nor an N–H wag. The C–N stretch is at 1214 cm^-1 (non-aromatic).