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1- DTSA-II

DTSA-II is a multi-platform software package for quantitative x-ray microanalysis. DTSA-II was inspired by the popular Desktop Spectrum Analyzer (DTSA) package developed by Chuck Fiori, Carol Swyt-Thomas, and Bob Myklebust at NIST and NIH in the ’80’s and early ’90’s.

DTSA-II has being designed with the goal of making standards-based microanalysis more accessible for the novice microanalyst. We want to encourage standards-based analysis by making it as easy as possible to get reliable results. Many operations which had previously required user intervention under DTSA now are performed entirely by the software. Furthermore, the software attempts to guide the user step-by-step through common processes while performing quality control sanity checks. While this might not provide the flexibility that some sophisticated users may desire, we feel that this philosophy is more consistent with the way laboratories are moving towards technicians responsible for multiple techniques and away from experts in single techiques. We encourage users who desire the additional power and flexibility available in the EPQ library to learn to script using Jython or to create their own alternative user interface. EPQ is much more capable than the fraction exposed via DTSA-II.

DTSA-II is based on an entirely new code base written by Nicholas W. M. Ritchie. The codebase has been carefully divided into a shared algorithm library which forms the basis for a handful of software products and a user interface shell. DTSA-II is the user interface shell and the EPQ library is the algorithm library.

DTSA-II remains under active development. Many features – some fairly basic – remain unimplemented. Other features have not been tested as much as the developer might like. The program made available to the public via this web site represents the current best available version in the judgement of the developer. DTSA-II remains experimental software and no representations are made regarding the suitability of the product for any particular application.

Major features:

• Basic IO and Display
  • Read energy dispersive x-ray spectra in a variety of different commercial and non-commercial formats including the industry standard EMSA format
  • Display and overlay spectra with various scaling options on linear/log/sqrt axes
  • Copy/save/print the spectrum display as a bitmap/PNG file
  • Output the spectra as a GNUPlot file for publication quality output
  • Overlay labeled x-ray emission lines and x-ray absorption edges
  • Define and integrate regions-of-interest
  • View spectrum contextual information
  • Archive spectra to a searchable database
  • Sub-sampling of spectral data to simulate shorter acquisition times
  • Basic spectrum math functions
  • Background modeling or background stripping
  • Energy axis linearization
  • Spectrum smoothing
  • Peak removal (trimming)
  • Peak search / identification
• Spectrum Simulation
  • Analytical (φ(ρz)) simulations of energy dispersive x-ray spectra
    • Normal or oblique incidence angle
    • Variable beam energies, beam fluxes, materials
  • Monte carlo simulations of energy dispersive x-ray spectra
    • Spectra from bulk samples
    • Mounted or unmounted thin films
    • Cubical or spherical particles with or without a substrate
  • Simulated spectra may be manipulated as experimental spectra
  • Variety of detector options including Si(Li), SDD and microcalorimeter
• Standards-based Quantification
  • Standards-based quantification of EDS spectra
  • Filter-fit linear-least squares fitting of reference spectra
  • Quantification based on references or like-standards
  • φ(ρz) correction of the k-ratios
  • ζ-factor correction of thin-film samples
  • Results reported as HTML with estimates of uncertainty
• Reporting
  • Actions are recorded in a daily HTML activity report
  • Report may be opened in an alternative HTML viewer
• Platforms and Source Code
  • DTSA-II is based on the EPQ library – a full-featured library of electron probe quantification algorithms
  • DTSA-II only exposes a fraction of the power within the EPQ library. The remainder may be accessed via custom Java applications or via Jython scripting.
  • The EPQ library includes the full NISTMonte for Monte Carlo simulation of electron/x-ray transport
  • DTSA-II / EPQ library are available as source code
  • DTSA-II / EPQ library are written in Java SE 6 compatible source
  • DTSA-II / EPQ library can execute on any platform supporting Java SE 6 or later
  • DTSA-II / EPQ library is regularly tested on Windows XP, Ubuntu Linux & Apple OS X

Disclaimer

This software was developed at the National Institute of Standards and Technology by employees of the Federal Government in the course of their official duties. Pursuant to title 17 Section 105 of the United States Code this software is not subject to copyright protection and is in the public domain. DTSA and the EPQ library are experimental systems. NIST assumes no responsibility whatsoever for its use by other parties, and makes no guarantees, expressed or implied, about its quality, reliability, or any other characteristic. We would appreciate acknowledgement if the software is used. This software can be redistributed and/or modified freely. The author requests that any derivative works bear some notice that they are derived from it, and any modified versions bear some notice that they have been modified.

Any mention of commercial products is for information only; it does not imply recommendation or endorsement by NIST nor does it imply that the products mentioned are necessarily the best available for the purpose.

See: https://cstl.nist.gov/div837/837.02/epq/dtsa2/

2. HyperSpy

HyperSpy is an open source Python library which provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal (e.g. a 2D array of spectra a.k.a spectrum image). HyperSpy aims at making it easy and natural to apply analytical procedures that operate on an individual signal to multi-dimensional arrays, as well as providing easy access to analytical tools that exploit the multi-dimensionality of the dataset. Its modular structure makes it easy to add features to analyze different kinds of signals.

Highlights

• Two families of named and scaled axes: signal and navigation.
• Visualization tools for multi-dimensional spectra and images.
• Easy access multi-dimensional curve fitting and blind source separation.
• Built on top of NumPy, SciPy, matplotlib and scikit-learn.
• Modular design for easy extensibility.

The development has been motivated by the data analysis needs of the electron microscopy community but it is proving useful in many other fields.

See: https://hyperspy.org/

3. AZtec

• AZtecFeature is an innovative particle analysis system specifically optimised for usability and high-speed throughput. It combines the raw speed and sensitivity of the Ultim Max Silicon Drift Detector with the superior analytical performance and ease of use of the AZtec® EDS analysis suite to create the most advanced automated particle analysis platform on the market. Gunshot Residue Analysis in the SEM with AZtecGSR is fast and accurate: it gives reproducible Gunshot Residue Analysis results to ASTM E1588 – 10e1.
• AZtecGSR combines ease of use through its guided workflow, with the ultimate accuracy using the latest Ultim Max detectors and Tru-Q® algorithms. LayerProbe is an exciting software tool for thin film analysis in the SEM. An option for the AZtec EDS microanalysis system, LayerProbe is faster, more cost-effective and higher resolution than dedicated thin film measurement tools.The most powerful EBSD software available, AZtecHKL combines speed and accuracy of results for routine analysis, with the flexibility and power required for applications that push the frontiers of EBSD.
• AZtec3D combines simultaneous EDS and EBSD data acquisition & analysis with the automated milling capabilities of a FIB-SEM.AZtecLiveOne software platform is the ideal solution for carrying out a complex task like EDS as quickly and as easily as possible. No need for substantial training or advanced knowledge of the EDS technique. Users can be trained in a matter of minutes and will have complete confidence in their results. AZtecTEM is an innovative EDS software specifically optimised for advanced TEM applications. AZtecSynergy provides a powerful solution for the simultaneous collection of EDS and EBSD data. All of the tools to collect excellent integrated data are included in one place with no complicated switching from one navigator to another.
• AZtecSteel is an automated steel inclusion analysis package developed specifically for the analysis and classification of steel inclusions using Energy Dispersive X-ray microanalysis (EDS) in a scanning electron microscope (SEM). It detects, measures and analyses the inclusions, processes the resulting data set to published standard methods, and includes functionality to plot complex ternary diagrams. AZtecLive is a revolutionary new approach to EDS analysis that enables a radical change in the way users perform sample investigation in the SEM. It combines a live electron image with live X-ray chemical imaging to give an intuitive new way of interacting with your samples. Collecting good quality data is only the beginning of any complete EBSD analysis. AZtecCrystal provides all the necessary tools to process and interrogate your EBSD data and to solve your materials problems. Seamlessly integrated with AZtecHKL or operated as a standalone program, AZtecCrystal sets the standard in EBSD data processing for experts and novices alike.
• AZtecAM is a powerful, automated, solution for the analysis of metal powders used in additive manufacturing. Based on AZtecFeature, AZtecAM optimises the particle analysis workflow to enable the rapid and accurate characterisation of metal powders. AZtecMineral is a powerful, automated, Mineral Liberation Analysis solution. It enables ore characterisation, provides vital data on metal recovery and enables process yield characterisation using multipurpose SEMs. It is also a valuable tool for the characterisation of rocks in research environments, enabling the automation of otherwise laborious optical analyses.

See: https://engineering.virginia.edu/oxford-instruments-offering-free-aztec-suite-software-electron-microscopy-analysis

4. ESPRIT Family

ESPRIT 2 unites four analytical methods under a single user interface. These include EDS for SEM and (S)TEM, WDS, Micro-XRF for SEM and EBSD. This makes it easy for the user to switch between methods with a single mouse click. Additionally, it facilitates combining different method results from the same sample area and to so gain much more information. To name only the most important, coupling of following methods is supported:

• EDS and EBSD
• EDS and WDS
• EDS and Micro-XRF for SEM

The software is designed to suit the needs of all levels of users – from beginner to expert. Novices will benefit from the assistants that help performing routine tasks without having to learn details of the measurement method. More experienced users will value the option to drill down deeper, when they need it, meaning both detailed setup of measurements as well as in-depth analysis of results and automation of tasks.

See: https://www.bruker.com/en/products-and-solutions/elemental-analyzers/eds-wds-ebsd-SEM-Micro-XRF/software-esprit-family.html

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Interaction of an electron beam with a sample target produces a variety of emissions, including x-rays. An energy-dispersive (EDS) detector is used to separate the characteristic x-rays of different elements into an energy spectrum, and EDS system software is used to analyze the energy spectrum in order to determine the abundance of specific elements. EDS can be used to find the chemical composition of materials down to a spot size of a few microns, and to create element composition maps over a much broader raster area. Together, these capabilities provide fundamental compositional information for a wide variety of materials.

How it Works – EDS

EDS systems are typically integrated into either an SEM or EPMA instrument. EDS systems include a sensitive x-ray detector, a liquid nitrogen dewar for cooling, and software to collect and analyze energy spectra. The detector is mounted in the sample chamber of the main instrument at the end of a long arm, which is itself cooled by liquid nitrogen. The most common detectors are made of Si(Li) crystals that operate at low voltages to improve sensitivity, but recent advances in detector technology make availabale so-called “silicon drift detectors” that operate at higher count rates without liquid nitrogen cooling.

An EDS detector contains a crystal that absorbs the energy of incoming x-rays by ionization, yielding free electrons in the crystal that become conductive and produce an electrical charge bias. The x-ray absorption thus converts the energy of individual x-rays into electrical voltages of proportional size; the electrical pulses correspond to the characteristic x-rays of the element.

Strengths

• When used in “spot” mode, a user can acquire a full elemental spectrum in only a few seconds. Supporting software makes it possible to readily identify peaks, which makes EDS a great survey tool to quickly identify unknown phases prior to quantitative analysis.
• EDS can be used in semi-quantitative mode to determine chemical composition by peak-height ratio relative to a standard.

Limitations

• There are energy peak overlaps among different elements, particularly those corresponding to x-rays generated by emission from different energy-level shells (K, L and M) in different elements. For example, there are close overlaps of Mn-K_α and Cr-K_β, or Ti-K_α and various L lines in Ba. Particularly at higher energies, individual peaks may correspond to several different elements; in this case, the user can apply deconvolution methods to try peak separation, or simply consider which elements make “most sense” given the known context of the sample.
• Because the wavelength-dispersive (WDS) method is more precise and capable of detecting lower elemental abundances, EDS is less commonly used for actual chemical analysis although improvements in detector resolution make EDS a reliable and precise alternative.
• EDS cannot detect the lightest elements, typically below the atomic number of Na for detectors equipped with a Be window. Polymer-based thin windows allow for detection of light elements, depending on the instrument and operating conditions.

Results

A typical EDS spectrum is portrayed as a plot of x-ray counts vs. energy (in keV). Energy peaks correspond to the various elements in the sample. Generally they are narrow and readily resolved, but many elements yield multiple peaks. For example, iron commonly shows strong K_α and K_βpeaks. Elements in low abundance will generate x-ray peaks that may not be resolvable from the background radiation.

EDS spectrum of multi-element glass (NIST K309) containing O, Al, Si, Ca, Ba and Fe (Goldstein et al., 2003). 

EDS spectrum of biotite, containing detectable Mg, Al, Si, K, Ti and Fe (from Goodge, 2003). 

References

• Severin, Kenneth P., 2004, Energy Dispersive Spectrometry of Common Rock Forming Minerals. Kluwer Academic Publishers, 225 p.–Highly recommended reference book of representative EDS spectra of the rock-forming minerals, as well as practical tips for spectral acquisition and interpretation.
• Goldstein, J. (2003) Scanning electron microscopy and x-ray microanalysis. Kluwer Adacemic/Plenum Pulbishers, 689 p.
• Reimer, L. (1998) Scanning electron microscopy : physics of image formation and microanalysis. Springer, 527 p.
• Egerton, R. F. (2005) Physical principles of electron microscopy : an introduction to TEM, SEM, and AEM. Springer, 202.
• Clarke, A. R. (2002) Microscopy techniques for materials science. CRC Press (electronic resource)

Related Links

• Petroglyph–An atlas of images using electron microscope, backscattered electron images, element maps, energy dispersive x-ray spectra, and petrographic microscope– Eric Chrisensen, Brigham Young University
• SEM/EDX webpage from Indiana University – Purdue University Fort Wayne

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X-ray is a kind of electromagnetic wave, the same as light. The wavelength of visible light is 400 to 800nm, while the wavelength of x-ray is much shorter (higher energy), at 0.001nm to 10nm, and is known to have strong penetrating power.

Fig. 1 shows the interactions between a material and X-ray, and various analysis methods that make use of these interactions. These interactions provide important clues for learning the state of a material. As a familiar example, an X-ray image for medical application is a well-known use of transmission X-ray. Here we will introduce an elemental analysis method called fluorescent X-ray spectrometry.

Fig.1 Analytical methods and its application interaction of X-ray and matter

Fluorescent X-ray Spectrometry

When irradiating X-rays onto a material, fluorescent X-ray (characteristic X-ray), which has energy (wavelength) unique to the element that composes the material will be generated. When we measure the fluorescent X-ray energy, the contained element is identified (qualitative analysis), and we can calculate the concentration (quantitative analysis) from the intensity of the fluorescent X-ray of each element. Thus, the qualitative or quantitative analyses of a material by irradiating X-rays onto an unknown material and analyzing the fluorescent X-ray that is generated, is called fluorescent X-ray spectrometry.

There are two types of fluorescent X-ray spectrometry; the wavelength dispersive type (WDXRF) using analyzing crystals, and the energy dispersive type (EDXRF) using semiconductor detectors (EDS).

Comparison between Energy Dispersive Type and Wavelength Dispersive Type Spectrometers

The characteristics of a wavelength dispersive type spectrometer (WDXRF) are high sensitivity, high accuracy, high resolution, and high reproducibility. We can expect sensitivity and accuracy at levels one order of magnitude higher than those of the energy dispersive type spectrometer (EDXRF). These characteristics are provided by a high-power X-ray tube (3 to 4 kW) and its cooling device, a goniometer which makes complicated movements and an exchange mechanism for the analyzing crystal and detector and so on. Naturally, the instruments are larger, with a complicated structure and high price. The specimen surface is required to be flat and the available analysis area is from several mm to 30mm or so. This type of device is suitable for process management where specimens with the same form are analyzed one after another.

The characteristics of the energy dispersive type spectrometer (EDXRF) are simple structure and low price, its adaptability to a variety of specimens, and its user-friendliness. The X-ray bulb is compact (several tens W) and air-cooled, and since the EDS (semiconductor detector) itself performs the analysis, a complicated spectroscopy section is not necessary.

The roughness or shape of specimen does not matter, so analysis of large specimens or micro areas is possible. Each characteristic is shown in Fig. 2. The images are the large instrument for WDXRF, and the compact simple instrument for EDXRF.

Wavelength Dispersive Type (WDXRF) Advantages: High Sensitivity, High Resolution High Accuracy, High Reproducibility Disadvantages: Complicated and large-sized, high price Specimen is limited to flat platesEnergy Dispersive Type (EDXRF) Advantages: Simple Operation, compact, low price Flexibility in specimen shape Disadvantages: Low resolution (overlapped peaks) Cooling mechanism requiring liquid nitrogen or the like

Fig.2 Comparison between Wavelength Dispersive Type (WDXRF) and Energy Dispersive Type (EDXRF)

Sampling of Solid/Powder/Liquid Samples

One of the characteristics of EDXRF is the ease of use. Sampling of solid, powder, and liquid samples is explained below.

Sampling of Solid Sample

Analysis of a solid sample is possible by simply placing the sample at the X-ray illumination position.

In case of small sample, use of a dedicated cell will make it easier to set the sample. Fig. 3 shows a simplified illustration of the solid sample sampling method.

Fig.3 Sampling of Solid Sample

Sampling of Powder Sample (rock, soil, incinerated ash, etc)

Powder samples are typically analyzed by producing a pellet using a compression device. As a simplified method, analysis is possible on the powder placed into a specially-designed cell. Fig. 4 shows a simplified illustration of the powder sample sampling method.

Fig.4 Sampling of Powder Sample

Sampling of Liquid Sample

For liquid samples, a dedicated cell is used. Fill a dedicated cell with the liquid and analyze. In addition, there is another method where you can drop liquid onto a filter, dry it, and then analyze it. Fig. 5 shows a simplified illustration of liquid sample sampling methods.

Fig.5 Sampling of Liquid Sample

FP Quantitative Method / Film Thickness Analysis of Thin Film Sample

FP (fundamental parameter) quantitative method

The EDXRF instrument employs a theoretical calculation method called the FP quantitative method, allowing quantitative analysis of an unknown sample without the need for a standard sample.
The FP quantitative method assumes that the sample is uniform, sufficiently large and thick, and that all elements (100% in total) are quantified. Naturally, a sample must satisfy these assumptions, so attention is needed.The flow chart of FP quantitative method is shown in Fig. 6.

Fig.6 The flow chart of FP quantitative method

Flow Chart Explanation

1. First, measure the unknown sample and obtain the measurement intensity.
2. Assume the initial concentration of the sample and obtain a calculated intensity using the FP method.
3. Compare the measurement intensity and the calculated intensity.
4. Change the assumed concentration so that the measurement intensity and the calculated intensity match.
5. Obtain a new calculated intensity with the new assumed concentration using the FP method.
6. Repeat steps 3 to 5.
7. The assumed concentration that gives a calculated concentration that matches the measurement concentration is the analysis result.

Film Thickness Analysis of Thin Film Sample

In the case of a thin film sample, there is a correlation between the x-ray intensity of the elements composing the film and the film thickness. Therefore, by irradiating X-rays onto the surface of a thin film and measuring the X-ray intensity of the elements composing the film, the film thickness can be analyzed without destroying it.

A Single layer film can be analyzed using a calibration curve, but with the calibration curve method, a standard sample must be prepared for each kind of film. When the thin film FP quantitative method is used, it is not only possible to analyze single layer films, but also to analyze the thickness and composition of each layer in a multi-layer thin film, up to 5 layers , without a standard sample, which is very convenient. Fig. 7 shows a diagram of the thin film FP method, Fig. 8 shows a measurement example of Au/Ni/Cu film.

Thin Film FP (fundamental parameter) method

• Simultaneous non-destructive analysis of thickness and composition of thin film
• Up to 5 layers, and up to 20 elements for each layer
• Film thickness of about 10nm to 10μm (differs depending on element)
• Standard sample is not necessary (theoretical calculation)
• Information of layering order, elements, and density of the film is needed.

Fig.7 Schematic diagram of a thin film FP method

Fig.8 Measurement of the film Au / Ni / Cu thin film FP method

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The Scanning Electron Microscope (SEM) produces images by probing the specimen with a focused electron beam that is scanned across a rectangular area of the specimen (raster scanning).

There are two families of electron guns:

• Conventional thermionic emitters such as Tungsten (W) or Lanthanum hexaboride (LaB6) tipped filaments.
• Tungsten field emission gun (FEG) , warm or Cold FEG. A pointed emitter is held at several kilovolts (2000-7000 V) so that there is sufficient potential at the emitter surface to cause field electron emission.

Field emission gun (FEG) is used to produce an electron beam that is smaller in diameter, more coherent and up to three orders of magnitude greater current density or brightness.

scrollable

Energy of electrons is depending of Voltage: 1 Kev to 50KeV

Current (A): Number of electrons /unit of time

1 amp = 1 coulomb/sec 1 coulomb ~ 6 x10¹⁸ electrons

Example if the current measured at sample is around 10^-9A to 10^-12 A then the number of electrons is around 6X10⁶ to 6X10⁹ electrons/sec.

Environmental Scanning Electron Microscope (ESEM)

ESEM is a variety of SEM called environmental scanning electron microscope. It can produce images of sufficient quality and resolution with the samples being wet or contained in low vacuum or gas. This greatly facilitates imaging biological samples that are unstable in the high vacuum of conventional electron microscopes. The major disadvantage of transmission electron microscope is the need for extremely thin sections of the specimens, typically about 100 nanometers. Biological specimens are typically required to be chemically fixed, dehydrated and embedded in a polymer resin to stabilize them sufficiently to allow ultrathin sectioning. Sections of biological specimens, organic polymers and similar materials may require special treatment with heavy atom labels in order to achieve the required image contrast.

ESEM is especially useful for non-metallic, uncoated and biological materials. The presence of gas, mainly Argon, around a sample permits to work with pressure greater than 500 Pa compared to conventional SEM requirements samples under vacuum about 10-3 to 10-4 Pa. This vacuum level creates the possibility to operate on non-conductive samples without any preparation or hydrated specimens without charging.

Transmission Electron Microscope (TEM)

In a Transmission Electron Microscope (TEM), the electron beam is accelerated by an anode typically at +100 keV (40 to 400 keV) with respect to the cathode, focused by electrostatic and electromagnetic lenses, and transmitted through the specimen that is in part transparent to electrons and in part scatters them out of the beam. When it emerges from the specimen, the electron beam carries information about the structure of the specimen that is magnified by the objective lens system of the microscope.

The spatial variation in this information (the “image”) may be viewed by projecting the magnified electron image onto a fluorescent viewing screen coated with a phosphor or scintillator material such as zinc sulfide. Alternatively, the image can be photographically recorded by exposing a photographic film or plate directly to the electron beam, or a high-resolution phosphor may be coupled by means of a lens optical system or a fiber optic light-guide to the sensor of a digital camera. The image detected by the digital camera may be displayed on a monitor or computer.

A transmission electron microscope can achieve better than 50 pm resolution and magnifications of up to about 10,000,000x whereas most light microscopes are limited by diffraction to about 200 nm resolution and useful magnifications below 2000x. Generally, the image resolution of an SEM is at least an order of magnitude poorer than that of a TEM. However, because the SEM image relies on surface processes rather than transmission, it is able to image bulk samples up to many centimeters in size and (depending on instrument design and settings) has a great depth of field, and so can produce images that are good representations of the three dimensional shape of the sample.

The Scanning Transmission Electron Microscope (STEM) rasters a focused incident probe across a specimen that (as with the TEM) has been thinned to facilitate detection of electrons scattered through the specimen. The high resolution of the TEM is thus possible in STEM. The focusing action (and aberrations) occurs before the electrons hit the specimen in the STEM, but afterward in the TEM.

Focused ion beam (FIB)

Focused ion beam, also known as FIB, is a technique used particularly in the semiconductor industry, materials science and increasingly in the biological field for site-specific analysis, deposition, and ablation of materials. A FIB setup is a scientific instrument that resembles a scanning electron microscope (SEM). However, while the SEM uses a focused beam of electrons to image the sample in the chamber, a FIB setup uses a focused beam of ions instead. Unlike an electron microscope, FIB is inherently destructive to the specimen.

When the high-energy gallium ions strike the sample, they will sputter atoms from the surface. Gallium atoms will also be implanted into the top few nanometers of the surface, and the surface will be made amorphous. A FIB-SEM consists in a system with both electron and ion beam columns, allowing the same feature to be investigated using either of the beams. A FIB-SEM system uses a beam of Ga+ ion to mill into the surface to locate a feature or defect of interest. The integrated SEM then uses a focused beam of electrons to image the sample in the chamber.

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Atomic force microscopy (AFM) is a technique with multiple applications in biology. This method is a member of the broad family of scanning probe microscopy and was initially developed in 1986 by Binnig et al to overcome the disadvantages of the scanning tunneling microscopy (STM) [1]. In the case of STM, only conductive materials can be studied as the resolution is obtained by using a tunneling current between a sharp probe and the sample surface[1]. In contrast, AFM uses small forces on the surface by a probe, thus do not damage samples and can provide information of surface topography of biological materials. AFM soon attracted the attention of the biophysical scientists in biomembrane as well as synthetic membrane research due to its capability of observing biological molecular system with resolution on nanometer scale and its possibility of three dimensional imaging [2].

Fundamental Elements of AFM

An atomic force microscope consists of a flexible cantilever containing a sharp probe, laser, photodiode detector, piezoelectric scanner and feedback electronics [3]. The microscope obtains the surface topography by scanning the tip in gentle touch with the sample. The tip motion is monitored by the piezoelectric scanner. As the tip scans the sample, the forces between the tip and the sample surface cause the cantilever to bend. A photodiode detector detects the deflection of a laser beam reflected off the back of the cantilever onto a two- segment photodiode. In most operating modes, a feedback circuit connected to the cantilever deflection sensor keeps the interaction between the tip and the sample at a fixed value and controls the tip-sample distance. The feedback signal is recorded by a computer to reconstruct a 3D image of the surface topography.

The force between the probe and the sample surface depends on the spring constant (stiffness of the cantilever) and the tip-sample distance). The amount of force is calculated based on Hooke’s law:F=−kx(6.1.1)(6.1.1)F=−kx

• FF: Force
• kk: spring constant
• xx: cantilever deflection.

Imaging modes

There are three primary imaging modes in AFM: contact, non-contact and intermittent (tapping) mode [4]. During contact mode, the probe is in contact with the sample and repulsive Van der Waals forces prevail, whilst attractive Van der Waals forces are dominant when the tip moves further away from the sample surface [5].

Contact Mode

In contact mode, the tip is constantly in touch with the sample surface. The applied force is kept constant while the tip scans the surface, creating the surface image [4]. This imaging mode is good for samples with rough and rigid surfaces as it provides fast scanning with high resolution. One disadvantage of this imaging mode is that soft samples like tissues can be deformed or damaged due to the applied force. This drawback can be solved by measuring the sample in aqueous environments to reduce the interaction force between the tip and the sample.

Tapping Mode

In tapping mode, the tip is not in constant contact with the sample surface. Instead, the cantilever is oscillated at its resonant frequency, which makes the tip lightly tap on the surface during scanning. A constant tip-sample interaction is maintained by monitoring the oscillation amplitude and an image is obtained [4]. Several parameters that affect the image contrast are the height, phase signals and amplitude [6]. Phase signals are influenced by material properties of the sample, for example viscoelasticity [6]. The force during scanning is greatly reduced, therefore this mode is useful for biological samples, where the samples are easily damageable or loosely bound to their surface. However, this imaging mode requires a slower scanning speed and is more challenging to measure in liquids.

Non-contact mode

There is no contact between the sample surface and the probe in non-contact mode. The probe oscillates above the sample surface, forming a weak attractive force between the tip apex atom and the sample surface atom. Feedback signals are obtained by measuring a frequency shift in the mechanical oscillation of the cantilever [6].

The force exerted on the surface sample is very low in this case. Moreover, as there is no contact between the probe and the surface, the probe lifetime can be extended. Another advantage of this operating mode is the possibility to observe an atomic defect if the very weak attractive force can be detected. The drawback of this mode is the reduction of resolution, and the oscillation of the cantilever is affected in case there are contaminants on the sample surface. Usually this operation mode requires a careful control of the environment (in UHV) to carry out [7].

Cantilever and Tips

The scanning probe is an important component of the AFM. The dimensions of the cantilever are in micrometer range, while its tip has a radius of a few nanometers [4]. Different cantilever lengths, shapes and materials lead to various spring constants and resonant frequencies. The most common materials of the probes are silicon nitride (Si₃N₄) or silicon (Si) [5]. Figure 6.1.46.1.4 shows a scanning electron microscope (SEM) image of a silicon nitride (4a, 4b) and silicon (4c, 4d) cantilever chip, where a tiny tip having a pyramid shape is integrated at the end. The silicon nitride probe is often used in static contact mode, where the stiffness of the cantilever should be as low as possible [4]. The silicon probe is usually used in dynamic operation mode, which requires higher values for the spring constant to reduce noise and instabilities [4].

Typically, spring constants of AFM cantilevers vary between 0.01 Nm^-1 and 100 Nm^-1, enabling a force sensitivity of 10-11N [4]. The force sensitivity is influenced by thermal, electrical and optical noise. [5] For biological samples, cantilevers in contact mode often have resonance frequencies between 5 and 50 kHz in vacuum [8]. Figure 6.1.56.1.5 reports an AFM tip made of carbon nanotubes (CNTs), which was a breakthrough in terms of resolution. CNTs tips have a high aspect ratio, small diameter, and a well-defined surface chemistry, therefore appearing to be the ideal probe for biological applications [4].

AFM on membranes

Native membranes studied by AFM

Biomembrane sample preparation

In order to study membranes using AFM, the membranes need to be fixed on a flat solid support [8]. Several solid supports such as mica, highly ordered pyrolitic graphite (HOPG), template stripped gold and molybdenum disulfide have proved to give high resolution images [6, 8]. While mica is an insulator and exposes a hydrophilic surface, HOPG is a good conductor and hydrophobic [8]. The similarity between these two substrates is an atomically flat surface [8]. Based on chemical adsorption mechanism, membranes are attached onto the solid support by adjusting pH and ionic strength. As the gap between membrane and the support is very small (0.5-2nm), this may cause impaired mobility for membrane proteins that are directly attached to the support [6]. Furthermore, the adsorption force may affect the conformation of the membrane proteins. To sum up, current sample preparation methods still need further consideration in order to study dynamics and structure of native membrane proteins.

AFM images of native membrane

AFM can obtain the images of native membranes at submolecular resolution, which is a great advantage comparing to other methods [6]. It is effective in providing information of the native organization of membrane proteins and their complexes. Figure 6.1.66.1.6 shows an example of the study of native membrane using AFM. Disk membranes were prepared from mouse retina and then attached on mica support [6]. The AFM image revealed tight rows of dimers packed in the structure arrangement of rhodopsin [6]. This provides a platform for interaction with arrestin and transducin.

Model lipid membranes studied by AFM

Preparation of supported lipid bilayers.

Supported lipid bilayers (SLBs) have been used as a biomimetic model for biomembranes in numerous studies [3, 9]. This system consists of two lipid leaflets spread on a solid support [3]. Although this model lacks some features of the real membranes, it still provides an insight of the structural organization and characteristics of cell membranes. The first method to prepare SLBs is the fusion of lipid vesicles on solid supports [9]. The vesicles are prepared via sonication or extrusion, then adsorbed on the surface of the solid support. The adsorbed vesicles either form larger vesicles by fusing together, or directly rupture and form SLBs.

Another method is to use a hydrophilic substrate on which two consecutive lipid monolayers are deposited by Langmuir-Blodgett transfer [3]. A Teflon-coated trough contains the aqueous solution, with two movable Teflon barriers used to control the area for lipid spread and form a monolayer at the air-water interface. There is also a balance to measure the surface pressure, controlling lipid packing. The solid support is then pulled vertically through the lipid monolayer, depositing the first lipid layer on the substrate. The transference of the second lipid layer can be completed by dipping the lipid support either horizontally or vertically. This technique can be applied to fabricate SLBs having two different lipid composition.

AFM studies of SLBs formation.

SLBs formation process by fusing lipid vesicles on solid supports can be studied in situ by AFM technique, as illustrated in Figure 6.1.76.1.7. The vesicles spread from the edge towards the center, then stacked on top of each other. The edges of the top and bottom bilayers are joined together to form bigger patches.

Different protocols to prepare multi-component and phase-separated SLBs can affect the asymmetry of the resulting SLBs. In Figure 6.1.86.1.8, the extruded small unilamellar vesicles (SUVs) composed of DLPC/DSPC are heated at 65⁰C, then fused on mica at 20⁰C. The resulting SLB are fully symmetric fluid/gel membranes. On the other hand, using sonicated SUVs heated at 20⁰C prior to fusion results in a completely asymmetric SLBs.

Summary

AFM is a powerful technique for scientists to have an insight in membrane biophysics. Advantages of this method including:

• The ability to image cell surfaces, molecular assemblies in their native aqueous environment at a very high resolution.
• No requirement of a conductive sample.
• Provide 3-D surface profiles.
• The ability to operate in liquid environment and ambient air.

Disadvantages of AFM are limited scanning area and the scanning speed.

Recently there have been some progress in improving AFM scanning speed and resolution, for example high speed AFM (HS-AFM) or high resolution AFM (HR-AFM) [10, 11]. HF-AFM consists of modified components in order to maximize scanning seed, for example soft small cantilevers having high resonance frequencies, high resonance frequency scanners and fast data acquisition devices [10]. AFM is also combined with several techniques such as fluorescence microscopy to acquire more efficient data [9]. The potential improvement of AFM will enhance the possibility to apply this technique in a wider range of biological fields.

References

1. Binnig, G., C. F. Quate, and C. Gerber, Atomic force microscope. Phys. Rev. Lett, 1986(56): p. 930–933.
2. D.J.Muller, Y.F.D., Atomic force microscopy as a multifunctional molecular toolbox in nanobiotechnology. Nat.Nanotechnol, 2008. 3: p. 261-269.
3. Morandat, S., et al., Atomic force microscopy of model lipid membranes. Anal Bioanal Chem, 2013. 405(5): p. 1445-61.
4. Alessandrini, A. and P. Facci, AFM: a versatile tool in biophysics. Measurement Science and Technology, 2005. 16(6): p. R65- R92.
5. Bullen, R.A.W.a.H.A., Lecture notes: Introduction to Scanning Probe Microscopy
6. Frederix, P.L., P.D. Bosshart, and A. Engel, Atomic force microscopy of biological membranes. Biophys J, 2009. 96(2): p. ​329- ​38.
7. S. Morita, R.W., E. Meyer, Noncontact Atomic Force Microscopy. Springer, 2002. 1.
8. Muller, D.J. and A. Engel, Atomic force microscopy and spectroscopy of native membrane proteins. Nat Protoc, 2007. 2(9): p. ​2191-7.
9. Goksu, E.I., et al., AFM for structure and dynamics of biomembranes. Biochim Biophys Acta, 2009. 1788(1): p. 254-66.
10. Ando, T., T. Uchihashi, and N. Kodera, High-speed AFM and applications to biomolecular systems. Annu Rev Biophys, 2013. ​42: p. 393-414.
11. Bippes, C.A. and D.J. Muller, High-resolution atomic force microscopy and spectroscopy of native membrane proteins. Reports on Progress in Physics, 2011. 74(8): p. 086601.

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Vibrating Sample Magnetometry (VSM) is a measurement technique which allows to
determine the magnetic moment of a sample with very high precision. The aim of this
lab course M106 is to enlarge upon the use of this widespread technique introduced in
the lab course B512, where different ferromagnetic samples were characterized
concerning magnetic hysteresis and demagnetization. Here, we will gain a deeper
understanding of the behavior of magnetic materials and its measurement.

In order to
lay the foundations, first the measurement principle and the properties of ferromagnetic
materials will be summarized (magnetic domains, magnetic hysteresis,
demagnetization) and then we will elaborate on the magnetic anisotropy of
ferromagnetic materials.

A vibrating sample magnetometer (VSM) systems are used to measure the magnetic properties of materials. The vibrating component causes a change in the magnetic field of the sample, which generates an electrical field in a coil based on Faraday’s Law of Induction.

If the sample is placed within a uniform magnetic field H, a magnetization M will be induced in the sample. In a VSM, the sample is placed within suitably placed sensing coils, also held at the desired angle.

And the vibrating sample component is made to undergo sinusoidal motion, i.e., mechanically vibrated.

The hysteresis loop shows the “history dependent” nature of magnetization of a ferromagnetic material. Once the material has been driven to saturation, the magnetizing field can then be dropped to zero and the material will retain most of its magnetization (it remembers its history).

Procedure
Before using the VSM, you must carry out a series of configuration steps.
• Insert the Ni standard into the VSM. The standard is ball-shaped, therefore
magnetically isotropic, and has a magnetic moment of 6.92 emu at 5000 Oe.
• Find the exact position of the standard in respect to the center of the pickup coils. The
vibrating rod can be adjusted by three screws on top of the VSM for x, y and z
direction. The pickup coils are connected in a way that, the sample being in the center
of the coils, there will be a signal minimum along x-, a maximum along y- and a
maximum again along z-direction.
• Run Calibrations → Moment gain to calibrate the instrument, i.e. to convert the
measured voltage signal into the correct value of the magnetic moment.
After calibration of the VSM, the following measurements aim to address two topics. The
first part covers basic magnetic characterization and the information that can be
deduced from magnetization curves. The second part cope with demagnetization.

1. Magnetocrystaline anisotropy energy:
   Fix the Fe single crystal to the sample holder. Set H0 to 3500 G and record the
   magnetic moment of the crystal during a 360° rotation of the sample.
   Find the angles corresponding to the different crystallographhic / magnetic axes and
   record the magnetization curves of the easy axis and the hard axis.
2. Stress induced magnetic anisotropy
   Mount a sheet sample clamped in a sample holder provided by the supervisor into the
   VSM. Record the magnetization curves of the sample with and without applied stress
   along and perpendicular to the stress direction.
   Determine the volume of each sample that you have measured

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Operation

A sample is made to oscillate using a vibrational unit extended on a rod. The sample is placed between two electromagnetic pieces which are used as the applied field for this this experiment. With the sample oscillating induces a voltage between the search coils which creates a signal to determine the magnetic properties of the sample. Reference coils are used to create a reference signal such that noise generated from the signal can be filtered using a lock-in amplifier [1]. Because the signal and the reference signal are directly related through its voltage and amplitude means that precise measurements can be recorded using a voltmeter. Calibration methods are important to determine the relation between the voltages induced by the magnetic field and the sample and their magnetic properties.

Calibrating the applied field is done by increasing the voltage in steps measuring the field until reaching a maximum. The system is calibrated using a nickel standard normally as a number of volts per unit of magnetic moment. Many materials such as types of barium ferrite or alnico materials can be placed inside to determine properties. These properties include remanence, coercivity, intrinsic coercivity and operating points once the system has been calibrated.

Advantages and Disadvantages in terms of experimental facets

The key advantage is the precision and accuracy of VSMs. Taking measurements at a range of angles once detection arrangements for the coils have been devised can be done. The advantage of sample vibration perpendicularly to the applied field can be found once the detection coils have been arranged appropriately. This means that there is the ability to test the sample at different angles. The positioning of the coils are done in a way to reduce the effects of sample position variation and external field variation- essentially deep into the applied field shown in figure 1. Disadvantages are that they are not well suited for determining the magnetisation loop or the hysteresis curve due to the demagnetising effects of the sample. Another problem is that, particularly for the VSM used in the third year laboratory is that temperature dependence cannot be controlled.

Figure 1. A schematic layout of the VSM

2. B-H Hysteresis Loop Tracer

Operation

The B-H hysteresis loop tracer is essentially two coils, one with a sample and the other which is empty for comparison. The insertion of a sample into the pickup coils causes a voltage proportional to the rate of change of the vector field to occur across the difference amplifier. After passing through an integrator, a voltage proportional to the intrinsic induction is passed to the Y-amp of the oscilloscope. This voltage combined with an X-voltage representing the magnetising field generated from the solenoid without the sample results in the generation of a hysteresis loop on the oscilloscope. Calibration is through a balance and phase adjustment to establish a trace on the oscilloscope. They are done to make sure that the magnetising field is linear and that every vector corresponds to the applied field. Measurements for the magnetic properties can then be made.

Advantages and disadvantages in terms of experimental facets

The coils have the ability to heat the sample such that temperature variance can be observed in the way that the material behaves when influenced by a magnetic field. On the other hand, this could cause overheating of the system which could result in a failure. Using a BH-looper can give the user a more improved visualisation compared to a VSM of the way a material behaves. The values plotted on the scope are only proportional to the absolute values, therefore display yields qualitative not quantitative information about a material magnetic properties. The precision is generally low compared to a VSM. Because a hysteresis loop is viewed using an oscilloscope means that observations of whether the material is a soft or hard magnetic material. And this is why it is used in quality control testing industries like the control of ferromagnetic oxides in a magnetic tape factory.

Figure 2. A schematic layout of a BH loop tracer [2].

3(I) Difference between concepts of Vector Field B, Magnetisation M and the magnetising field H

The vector field B represents the magnetic induction. Magnetisation M is the magnetic moment per unit volume of a solid. Magnetising H field is the magnetic field strength. These three quantities are related by the equation.

With μ₀ being the permittivity of free space. To show the difference between these quantities, hysteresis loops for a magnetic material shown in figure 4 are used. One of the key differences shown is that the magnetisation saturates whereas the B field increases at a constant rate for certain values for H. The magnetisation is generated by the spin and the orbital angular momentum of electrons in the solid. H is generated outside the material by electrical currents[3]. Therefore, from the equation above, the B field is the combination of H and M which shows the difference between the quantities with the inclusion of the permittivity of free space.Find out how UKEssays.com can help you!

A way to show the difference between the 3 parameters is through the representation of a bar magnet in a magnetic field shown in figure 3. Unfortunately, due to the age of the diagram, the labels are a bit old. Hence the ‘True’ field denotes the vector field B and the Applied field represents the magnetisation M. However, the arrows represent the direction and strength of each parameter. It is clear from figure 3 that the Magnetisation is much stronger than the demagnetising field.

Figure 3 An example of a magnet being demagnetised in an applied field

From figure 4, the two sketches representing of B and M against H can give an understanding of other magnetic properties of the material. The curve on the left can show the saturation of the magnetic material as well as the remanence M_r– the remaining magnetisation after the applied field has been turned off. The right hand diagram can show the remanent induction B_r and the saturation point of the applied field. In terms of the difference between the parameters, M, B and H, they yield different properties of the material in question.

Figure 4 Hysteresis loops showing (a) M and (b) B field against H

3(II) The difference between the susceptibility and relative permeability

The relative permeability μ_r and susceptibility χ are very closely related as shown by the equation below:

The relative permeability represents a characterisation of magnetic materials. Paramagnetic or diamagnetic materials have permeabilities close to the permeability of free space. However for ferromagnetic materials, the permeability is large in comparison. It represents a multiplication factor. For example, the use of an iron core with a relative permeability is 200 times greater than just an air coil used. So this is a measure of the actual magnetic field within a ferromagnetic material. Susceptibility is a measure to an extent to which a material may be magnetised in a magnetic field. It represents a ratio of how much a material is magnetised compared to the applied field on that material [4]. So the susceptibility specifies how much the relative permeability differs from one as shown in the equation above.

References

[1] Foner S 1959 Versatile and Sensitive Vibrating-Sample Magnetometer* Rev. Sci. Instrum. 30 548–57

[2] Howling D H 1956 Simple 60-cps Hysteresis Loop Tracer for Magnetic Materials of High or Low Permeability Rev. Sci. Instrum. 27 952

[3] Jiles D 1990 Introduction to Magnetism and Magnetic Materials (Chapman and Hall)

[4] Magnetic Susceptibilty http://www.britannica.com/EBchecked/topic/357313/magnetic-susceptibility

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Increasing media storage density continues to be a very active area of research. Magnetic media may be divided into particulate and continuous media.

Particulate media are comprised of small magnetic particles bonded on a plastic tape or disk, the thickness of the magnetic overcoat is typically on the order of 10,000 Å. Since these are single domain particles, the information is stored by inverting the magnetization of some of the particles. Continuous media are metallic thin films, typically a few hundred angstroms in thickness. Particulate media are advantageous in that they are relatively simple to prepare and are chemically stable, however their recording density is relatively low.

Continuous media on the other hand have higher storage densities and the shapes of their hysteresis loops (and hence recording characteristics) may be varied in a controlled way.

Hard and Soft Magnetic Materials

Magnetic materials are classified into two broad categories, soft or hard. Soft magnetic materials are characterized by large permeabilities and very small coercivities, typically less than 1 Oe. Hard magnetic materials are most often used in permanent magnet applications, and are characterized by large saturation magnetizations, large coercivities, typically greater than 10 kOe, and also by large energy products (i.e., BHmax). Intermediate magnetic materials are generally characterized by coercivities on the order of 1 kOe, and these materials are usually used in magnetic media.

Intermediate magnetic materials include; Gamma-Fe₂O₃, Co₈₀Cr₂₀, Co₇₇Ni₁₀O₁₃, and thin films. The characteristics of any magnetic material, whether it is hard, soft, or intermediate, are best described in terms of their hysteresis loop. The most common measurement method employed for hysteresis loop determinations at ambient temperature is the Vibrating Sample Magnetometer (VSM).

This paper will discuss the utility of the VSM in the characterization of magnetic media materials. We will limit our discussion to longitudinal recording media, i.e., where the magnetization is parallel to the plane defined by the substrate/film. Perpendicular media, where the magnetization is perpendicular to the plane defined by the substrate/film, and magneto-optical materials are currently enjoying considerable research effort because of their potential for increasing areal storage densities.

Vibrating Sample Magnetometer (VSM) Systems

Vibrating Sample Magnetometer (VSM) systems are used to measure the magnetic properties of materials as a function of magnetic field, temperature, and time. They are ideally suited for research and development, production testing, quality and process control. Powders, solids, liquids, single crystals, and thin films are all readily accommodated in a VSM.

Contemporary commercial VSM’s feature virtually automated operation via data acquisition/control and analysis software that runs on a personal computer, thus making the VSM accessible to the non-specialist. This has dramatically increased the utility of this measurement technique in a broad range of measurement applications.

Theory of Operation of Vibrating Sample Magnetometer Systems

If a material is placed within a uniform magnetic field H, a magnetic moment m will be induced in the sample. In a VSM, a sample is placed within suitably placed sensing coils, and is made to undergo sinusoidal motion, i.e., mechanically vibrated. The resulting magnetic flux changes induce a voltage in the sensing coils that is proportional to the magnetic moment of the sample.

The magnetic field may be generated by an electromagnet, or a superconducting magnet. Variable temperatures may be achieved using either cryostats or furnace assemblies. In the context of the current discussion, we will consider electromagnet based systems only, as magnetic media are usually characterized at ambient temperature, and for only moderate field strengths. Tape and thin film samples to 1 inch in diameter may be characterized in the Lake Shore VSM.

The Hysteresis Loop

In the case of a typical recording medium the hysteresis loop gives the relation between the magnetization M and the applied field H. A hysteresis loop of a magnetic recording medium is illustrated schematically in Figure 1.

The parameters extracted from the hysteresis loop that are most often used to characterize the magnetic properties of magnetic media include; the saturation magnetization Ms, the remanence Mr, the coercivity Hc, the squareness ratio SQR, S* which is related to the slope at Hc , and the switching field distribution SFD. The loop illustrated in Figure 1 shows the behavior for the easy axis of magnetization (i.e., in the anisotropy direction). The loop has a rectangular shape and exhibits irreversible changes of the magnetization.

The hard axis loop, where the hard axis is at right angles to the easy axis, is more or less linear and generally hysteresis free, i.e., the magnetization is reversible. Magnetic materials that show a preferential direction for the alignment of magnetization are said to be magnetically anisotropic. When a material has a single easy and hard axis, the material is said to be uniaxially anisotropic.

The intrinsic saturation is approached at high H, and at zero-field the remanence is reached. The squareness ratio is given by the ratio of (M_r/M_s) and is essentially a measure of how square the hysteresis loop is.

In general, large SQR values are desired for recording medium. The formal definition of the coercivity Hc is the field required to reduce the magnetization to zero after saturation. The physical meaning of Hc is dependent on the magnetization process, and may be the nucleation field, domain wall coercive field, or anisotropy field.

H_c is a very complicated parameter for magnetic films and is related to the reversal mechanism and the magnetic microstructure, i.e., shape and dimensions of the crystallites, nature of the boundaries, and also the surface and initial layer properties, etc.

Parameters of Importance to Magnetic Media

S* and SFD are of particular importance in characterizing the magnetic properties of magnetic media. S* is related to the slope of the hysteresis loop at Hc, i.e., dM/dH|H_c = M_r/(H_c(1 – S*)). This is known as the Williams-Comstock construction. For longitudinal recording media there are two important parameters associated with the recording process that are intimately related to S*.

Namely, the maximum output signal depends on Mr, Hc, and S*, and the optimal bias current also depends on S*. The SFD = ΔH/Hc where ΔH is the full width at half maximum of the differentiated curve dM/dH (as illustrated in Figure 1) can be thought of as a distribution function of the number of units reversing at a certain field. For a particulate medium without collective behavior, the SFD has a close relation to particle size distribution because differently sized and shaped particles will reverse at different field strengths.

For longitudinal media the SFD is related to recording parameters such as noise, optimal bias current, and time dependent behavior. Media with high Hc and small SFD are desirable for high density recording.

Remanence Curves

In addition to the full hysteresis loop properties of magnetic media, there has been increased interest in the measurement of remanence curves. Measurement of remanence determines only the irreversible component of magnetization and thus enables the phenomena of switching to be deconvoluted from the hysteresis measurement, which generally includes a reversible component.

There are two principle remanence curves; the isothermal remanence (IRM) and the DC demagnetization curve (DCD). The IRM is measured after the application and removal of a field with the sample initially demagnetized. The DCD is measured from the saturated state by application of increasing demagnetizing fields. Both are illustrated schematically in Figure 2. These remanence curves are of importance because they yield the true SFD for the material. The VSM may also be used to measure the IRM and DCD remanence curves.

The remainder of this paper will present magnetic data for thin film magnetic media, thus demonstrating the utility of the Lake Shore VSM for measuring media magnetic properties.

Magnetic Measurements Using the Lake Shore VSM

The Lake Shore VSM features variable-gap electromagnets providing field strengths to over 2 tesla. Experimental flexibility, both in terms of achievable field strengths, and in terms of allowable sample sizes are provided since the gap spacing may be adjusted to maximize either.

Auto-rotation and Vector options facilitate investigations of anisotropy in magnetic media. With the auto-rotation option the sample may be rotated such that the applied field is oriented parallel to either the easy or hard axis of magnetization, or at any angle in between. The Vector option, which includes 2-axis or 3-axis coil sets placed at right angles to one another, permits simultaneous measurement of both easy and hard axis magnetization for fields oriented parallel to either axis. This option also permits the derivation of torque since torque is equal to the cross product of the field and magnetization vectors (i.e., t = M x H).

Data collection is fully automated with Windows based data acquisition/control and analysis software. Broad application versatility is maintained since measurement parameters may be easily defined and controlled. The software automatically extracts any of a number of parameters, e.g., Ms, Mr, Hc, SQR, S*, SFD, etc., directly from the measured hysteresis loop. And, extensive data analysis capabilities are also provided, e.g., derivative (SFD) curves, substrate and paramagnetic background corrections, etc.

Measurement Results

Hysteresis Loops for a Thick Film Disk Material

Figure 3 shows the initial, minor, and major hysteresis loop for a thin film disk material. In the context of the present discussion, the minor loops of magnetic media are sometimes of interest as they relate to modeling of the write process. Taken together with the major loop, the minimum head field strength required to ensure saturation and hence maximum remanence are determined.

Magnetization Curve, Major Hysteresis Loop and Remanence Curve for a Flexible Magnetic Media Material

Figure 4 shows the initial magnetization curve, major hysteresis loop, and also the DCD demagnetization or remanence curve for a flexible magnetic media material.

Major Hysteresis Loop for a Flexible Media Material

Figure 5 shows the major hysteresis loop for a flexible media material, and the derivative curves are also illustrated. These derivative curves are directly related to S* and the SFD. Since small SFD’s are desirable, the sharpness and width of these derivative curves are of interest. A narrow and stable switching transition produces a small SFD, and hence the derivative curves yield useful information concerning the magnetic structure of the media, which in turn is related to the microstructure and chemical inhomogeneities in the layer. These parameters are principally related to the deposition process itself.

Isothermal Remanence (IRM) and DC Demagnetization (DCD) Remanence Curves for a Flexible Media Material

Figure 6 shows the isothermal remanence (IRM) and DC demagnetization (DCD) remanence curves for a flexible media material. Interaction effects may be investigated by analyzing these curves. If the particulate media is characterized by non-interacting particles then a Henkel plot, i.e. IRM(H) vs. DCD(H), will be linear, and the forward and reverse SFD’s will be identical. Deviations from linearity are attributable to the effects of interactions in the system.

Figure 7 shows the Henkel plot corresponding to Figure 6 and Figure 8 illustrates the forward and reverse SFD’s obtained from differentiation of the IRM and DCD curves. Clearly the SFDs are not identical. The extent to which interactions exist in the system are revealed by these types of ΔM vs H curves. A larger interaction yields a larger ΔM peak. The use of this type of analysis is becoming increasingly common in the investigation of interaction effects in particulate and thin film media. A strong correlation exists between the form of these interaction effects, and the degree of dispersion of the particles.

Hysteresis Loop for Hard Disk Magnetic Film

Figure 9 shows a hysteresis loop for hard disk CoPt magnetic film deposited on a rigid disk substrate. Critical M(H) loop parameters are indicated in the figure.

Figures 10 and 11 show the hysteresis loop and derivative curve, respectively, for a hard disk film sample.

Summary

Selecting a VSM and Future Requirements

There are a number of considerations that come into play when selecting an appropriate VSM. These include; the types of materials that are to be measured, i.e., both intrinsic magnetic characteristics and physical properties and dimensions are important, required magnetic field strength, accessible temperature range, available measurement options, ease-of- use which is largely dictated by the software interface, etc.

Current research trends in magnetic media include the development of perpendicular recording media, magneto-optical materials, the development of pseudo-contact recording techniques, the use of magnetoresistive (i.e., GMR and CMR) multi-layer films for read heads, the use of alternative substrate materials (e.g., glass), and patterned media. Additionally, the superparamagnetic limit is being approached as magnetic film thicknesses are decreased. This trend will force VSM manufacturers to enhance the sensitivity characteristics of their VSM’s.

This paper has discussed some of the more important magnetic properties of magnetic media, their relation to the recording process, and their determination utilizing a Vibrating Sample Magnetometer measurement methodology. The wide spread use of magnetic media materials for audio, video, and data storage systems results in a continual research effort to increase storage densities, and decrease access time.

Advances made possible by materials science, combined with the development of commercially available computer automated characterization tools, such as the VSM will certainly result in significant advances in this area.

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What is EDS?

Energy-dispersive X-ray spectroscopy (also known as EDS, EDX, or EDXA) is a powerful technique that enables the user to analyze the elemental composition of a desired sample. The major operating principle that allows EDS to function is the capacity of high energy electromagnetic radiation (X-rays) to eject ‘core’ electrons (electrons that are not in the outermost shell) from an atom. This principle is known as Moseley’s Law, which determined that there was a direct correlation between the frequency of light released and the atomic number of the atom.

Removing these electrons from the system will leave behind a hole that a higher energy electron can fill in, and it will release energy as it relaxes. The energy released during this relaxation process is unique to each element on the periodic table, and as such bombarding a sample with X-rays can be used to identify what elements are present, as well as what proportion they are present in.

Shown below is an example of how EDS works. The letters K, L, and M refer to the n value that electrons in that shell have (K electrons, closest to the nucleus, are n=1 electrons), while α and β indicate the size of the transition. The relaxation from M to L or L to K are therefore described as Lα or Kα, while going from M to K would be a Kβ transition. The means that are used for describing these processes as a whole are known as Siegbahn notation.

How is data collected?

EDS functions with a series of three major parts: an emitter, a collector, and an analyzer. These parts are additionally typically equipped on an electron microscope such as SEM or TEM. The combination of these three pieces enables analysis of both how many X-rays are released, as well as what their energy is (in comparison to the energy of the initial X-rays that were emitted).

The EDS data is presented as a graph with KeV on the x-axis and peak intensity on the y-axis. The peak location on the x-axis are converted into the atoms that the energy changes represent by a computer program.

Figure. EDS chart from a research group that was analyzing the composition of shrimp and the associated bacteria that associate with these minerals. The EDS helped support the researcher’s case that the endosymbiotic bacteria living on these shrimp actually do influence the iron oxide composition in these minerals. This is evident by the peaks at 0.5 and 6.5 KeV.² 

What are some drawbacks of EDS?

Although EDS is an extremely useful technique, there are a number of difficulties involved with the process which hinder its utility. First, EDS is generally not a particularly sensitive technique. If the concentration of an element in the sample is too low, the amount of energy given off by X-rays after hitting the sample will be insufficient to adequately measure its proportion. Second, EDS generally does not work for elements with a low atomic number. Hydrogen and helium both only have an n=1 shell, meaning there aren’t core electrons to be removed that can allow for X-ray emission. Lithium and beryllium, meanwhile, have sufficiently low atomic numbers that the energy of X-rays given off by Li or Be samples is insufficient for measurement, and often times they cannot be tested as a result.

One additional difficulty associated with the technique is the thickness of the sample. Sample thickness can bring energy levels closer together, thus making electrons easier to move to outer energy levels, which can in turn cause deviation in the results. Another error source is overlapping emitted x-rays, which can alter the KeV readings. Additionally, X-rays are not particularly effective at penetrating beyond several nanometers in samples, which means that only surface layers can be efficiently measured by the technique. As such, if there is a discrepancy between the outer and inner material layers, it will not necessarily appear in EDS.

Work Cited

1. https://en.wikipedia.org/wiki/Energy-dispersive_X-ray_spectroscopy
2. https://cfamm.ucr.edu/documents/eds-intro.pdf
3. L. Corbari, M.-A. Cambon-Bonavita, G. J. Long, F. Grandjean, M. Zbinden, F. Gaill, and P. Compere “Iron oxide deposits associated with the ectosymbiotic bacteria in the hydrothermal vent shrimp Rimicaris exoculata” Biogeosciences 2008, 5, 1295–1310.

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1. XPST

XPST is a program package for the analysis of X-ray Photoelectron Spectroscopy (XPS) data. It includes various graphical interfaces as well as commandline functions to facilitate the workup of XPS data.

When a XPST fit project is started, a corresponding subfolder with all required data is generated and saved within the Igor experiment. You can generate fit templates and you can export entire fit projects to share them with your co-workers. As a special feature, a flexible multiplet function was implemented to facilitate a convenient analysis of complex spectra. XPST can handle any number of peaks.

There is also a youtube channel with tutorials.

Several changes in the newest version of XPST were made according to this book about programming Igor.

Installation

XPST was initially developed with Igor 5, but a major revision was made with Igor 7. XPST works also nicely with Igor 8. The Igor 7/8 version is not compatible with Igor 6. If you still run Igor 6, you have to download a previous release.

• Unpack the .zip file
• Copy/Move the folder ‘XPST’ to the folder ‘Igor Procedures’ in Igor’s main folder
• Copy/Move the folder ‘XPSTHelp’ to the folder ‘Igor Help Files’ in Igor’s main folder
• Restart Igor

Before you upgrade to a newer version of XPST, please remove all files associated with your old version from Igor’s folders.
 

Stay in touch …

If you want to stay informed about updates or other issues, just send a blank mail to: xpst_update@freenet.de
This is not a support contact – it only serves to keep you informed about changes.
You can sign off anytime you want using the same address.
 

More functions …

Besides the graphical interfaces, XPST comes with several commandline functions. For example:

• WhereIs() …. returns the absolute path of a selected wave (so it can be easily found)
• WaveOverlap() …. computes the overlap of two selected waves and saves it to a new wave
• CursorCut() …. cuts out regions from a selected wave

Limitations

• Data with ‘kinetic energy’ as x-axis (in waveform format or not) can not be analyzed with the Fit Assistant. Only a positive ‘binding energy’ scale works – however, this should be the most common case. If there is a strong demand for kinetic energies, it could be implemented in future versions.

See: https://www.wavemetrics.com/project/XPStools

2. CasaXPS

CasaXPS processing software offers powerful analysis techniques for both spectral and imaging data. The system originally designed for XPS and Auger data now offers features covering a wide range of analytical techniques including ToF SIMS, dynamic SIMS and many more.

Features in CasaXPS include:

·         Full quantification including transmission correction.

·         Configurable quantification reports.

·         Background type ranging from the standard Linear, Shirley and Tougaard to user-defined cubic-spline approximations.

·         Asymmetric and symmetric line-shapes: Doniach-Sunjic, Voigt, Gaussian-Lorentzian and line-shapes defined from data.

·         Easy-to-use propagation of processing, annotation and peak models to other data.

·         Batch processing for repetitive tasks, including configurable processing, display layout with automatic printing and report generation.

·         State-of-the-art image processing for XPS spectromicroscopy offering quantified chemical-state XPS images.

See: http://www.casaxps.com/

3. Originlab

Origin provides powerful and versatile tools such as Peak Analyzer, Quick Peaks Gadget, Integration Gadget, etc. for baseline correction, peak detection, peak integration and peak fitting.

Origin provides baseline detection and subtraction. Key features include:

• Create baseline with many baseline modes
  • Commonly used baseline types such as Constant, Straight line, Use Existing Dataset, End Points Weighted, Min&Max
  • Automatically find anchor points for baseline, modify the points, create baseline by interpolation or fitting
  • Create baseline for XPS using Shirley or Tougaard method and adjust corresponding parameters to optimize
  • Create baseline using Asymmetric Least Squares (ALS) Smoothing method and adjust corresponding parameters to optimize
• Subtract baseline

Origin allows you to search for peaks including hidden (“convoluted”) peaks and filter out unwanted peaks or manually add or remove peaks.

• Savitzky-Golay smoothing on the spectrum before peak finding

In Origin, you can integrate data with multiple peaks, to obtain peak areas, FWHM and other peak characteristics. Baseline subtraction is supported before peak integration. 

Available options include: 

• Directly select desired data range on graph
• Instantly view results of peak area and FWHM
• Subtract baseline from peak data
• Auto detect peak positions
• Auto determine peak widths for overlapped peaks
• Individually set peak widths
• Fit peaks and obtain fitted peak areas

Origin provides many tools to perform peak fitting: 

• Quick Peaks Gadget  : Visually correct baseline, find and fit peaks
• Multiple Peak Fit: Manually pick peak positions and fit peaks with same function. No baseline correction
• Peak Analyzer: Correct baseline, find peaks and fit by Peak Analyzer wizard
• Nonlinear Curve Fit Dialog: Fit multiple peaks with replicas in the nonlinear curve fit dialog

Available options for peak fitting include:

• Fit peaks with built-in or user-defined functions
• Fit multiple peaks with different functions
• Control fitting process using bounds and constraints
• Fix or share peak parameters
• Vary baseline parameters along with peak fitting

See: https://www.originlab.com/index.aspx?go=Products/Origin/DataAnalysis/PeakAnalysis#Peak_Fitting_PRO

4. XPSPEAK

Free, fully featured, software for the analysis of XPS spectra written by Raymund Kwok.XPSPeak is a XPS Peak Fitting Program.The portable app creates a sandbox folder in its current location, where it stores all its settings and temporary files. Can be downloaded from the US, UK or Hong Kong.

See: https://xpspeak.software.informer.com/4.1/

5. Unifit

See: https://home.uni-leipzig.de/unifit/downloads.htm