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1. Introduction

Today several instruments for fast spectra recording are available. In most cases the difficulty
is to process and analyze the data quickly in a reliable way. The Maud program, in one of its
many undocumented features, can be used to process a list of analyses in batch mode from the
console without requiring the interface. This is useful to process quickly similar spectra or launch
a slow/time consuming refinement in a remote computer without recurring to the interface that
would need to open a session involving the remote display setting.

The overall procedure is to prepare the analysis locally using the interface or to prepare a starting point for a series of spectra
(one common starting point) also using the interface, then to prepare an instruction file in CIF like
format to specify the analyses, the spectra and the kind of refinement to conduct and finally to run
Maud in batch mode providing the instruction file previously prepared. The program will run and
process one analysis at time and prepare an output file extracting some key information (either the
default or some to be specified) in a format suitable to be imported in spreadsheet or graphical
programs to analyze the results.
As an example we will show the procedure to analyze a series of ball milled Cu-Fe mixed powders
in which two different phases may form with a different composition. By an automatic Rietveld
analysis performed in batch mode we will extract information about phase content [2, 1], crystallite
and microstrain for each sample/spectrum. The analysis is further complicated from the fact that
the powders milled at higher energy show the presence of planar defects [5] and texture arising
from sample preparation and the platelet like shape of the grains [3].

2 Analysis and procedure
In this section we will present the procedure to analyze 25 spectra of Cu-Fe different samples. The
spectra has been collected by a Philips X-pert system in Le Mans at the LPEC laboratory of the
1
University du Maine, thanks to A. Gibaud.
2.1 Analysis preparation through the interface
We start the Maud program and load all the datafiles together to check their integrity and to prepare
a common starting analysis file. A plot of all spectra and their differences is available in Figure 1.

We load the two possible phases, bcc iron and fcc copper, from the Maud database. By computing
the spectra once and comparing them visually with the experimental spectra we may notice that
for some samples, milled at longer time, an alloyed fcc phase form (out of equilibrium) and the
bcc iron disappears. Unluckily we could not use the copper rich phase cell parameter to monitor
the Fe content in it as the cell parameter tends to growth as a result probably of oxygen entrapping.
In a first attempt we discovered the spectra were affected by texture, anisotropic crystallite sizes
and microstrain as well as planar defects (especially on the Cu like phase). So we decide here
to include also texture and anisotropic/planar defects effects in the analysis. For both the bcc
and fcc phases we select in the proper panel the Popa model for anisotropic broadening [4], the
Warren model for planar defects and the harmonic model for texture (specifying cylindrical sample
symmetry and Lmax = 6 in the options; it is required by the experiment geometry).
Next step was to adjust the cell parameters for both bcc and fcc phases in order to get a mean
starting value good for all spectra (especially for the fcc); and to adjust the crystallite value to a
good starting point (around 200 angstrom) obtaining peak shapes a little sharper than in the less
broadened spectrum. The background constant parameter was also adjusted to the value of the
spectrum with the lower background. Actually only the cell parameter adjustment is critical, the
background one is even not necessary.
Finally we remove all the spectra (we will specify which datafile to use for each analysis later in an
instruction file) and save the analysis containing everything except the spectrum/a. For the purpose
of this article we save the analysis with the name: FeCustart.par.
2.2 Preparation of the instruction file and batch processing
To run Maud in batch we need to write an instruction file containing the list of analyses to execute
one at time. The file is in CIF format but containing some terms not available in the official CIF
dictionary, but that Maud recognize. All the analyses to be performed are specified through the
loop CIF instruction. The first term of the loop must be the one specifying the starting analysis
file to be loaded (full path in unix convention) and then the others to instruct Maud for the kind
of analysis to perform, iterations and eventually datafile to load and name of the file were to save
the analysis. Additional keywords can be used to append specific results to a file for spreadsheet
analysis. The simplest instruction file is something containing the following:
First example (paths for windows):
loop
riet analysis file
riet analysis iteration number
2
´//C:/mypathfortheanalysis/analysis1.par´ 5
´//C:/mypathfortheanalysis/analysis2.par´ 3
´//C:/mypathfortheanalysis/analysis3.par´ 7
The analysis1.par (or 2 or 3) are some analyses files prepared with Maud, containing also
the datafile/spectrum, already set for the parameters to be refined and saved just ready for the refinement step. Maud will load each analysis, starts the refinement with the number of iterations
specified and save the analysis with the refined parameters under the same name. The analyses can
be loaded at end in Maud (with the interface) to see the result of the refinement.
In the case of the Cu-Fe we need to perform some more steps: first we start from one common analysis point (the FeCustart.par analysis file) but we want to specify different datafiles; second
we want to perform a full automatic analysis in which Maud performs different cycles deciding
which parameters to refine at each step and third we will specify the name of each analysis for the
saving process and a file name were to append some selected results in a tab/column format for
subsequent easy loading in a spreadsheet program.
Cu-Fe example:
loop
riet analysis file
riet analysis iteration number
riet analysis wizard index
riet analysis fileToSave
riet meas datafile name
riet append simple result to
´//mypath/FeCustart.par´ 7 13 ´//mypath/FECU1010.par´ ´//mypath/FECU1010.UDF´
´//mypath/FECUresults.txt´
´//mypath/FeCustart.par´ 7 13 ´//mypath/FECU1011.par´ ´//mypath/FECU1011.UDF´
´//mypath/FECUresults.txt´
…………(lines with all the other 23 datafiles omitted for brevity)
´//mypath/FeCustart.par´ 7 13 ´//mypath/FECU1038.par´ ´//mypath/FECU1038.UDF´
´//mypath/FECUresults.txt´
With this instruction file (that we save under the name: fecu.ins) we specify for example that
as a first analysis, Maud has to load the FeCustart.par file, then to load in the analysis the
FECU1010.UDF datafile, to perform the automatic analysis number 13 (in the wizard panel of
Maud the automatic analysis number 13 is the texture analysis; we need to refine also the texture
parameters along with phase analysis and microstructure) and to use 7 iterations for each cycle (the
texture automatic analysis is composed by 4 cycles) to ensure sufficient convergence. At the end
the analysis is saved with the name FECU1010.par and simple selected results will be appended
in the file FECUresults.txt. The simple results saved in the spreadsheet like file are some of
the most used parameters and results. It is possible to specify the parameters we want in output
using the CIF word riet append result to (in addition or as an alternative), but in the
preparation of the starting analysis file in the Maud interface, the parameters to be added to the
results must be specified by turning to true the switch in the output column of the parameter list
window or panel.
Now to run Maud in batch in the console (
where the Maud.jar is located the following:
DOS (everything in the same line): java -mx512M -cp
“Maud.jar;lib\miscLib.jar;lib\JSgInfo.jar;lib\jgaec.jar;lib\ij.jar”
it.unitn.ing.rista.MaudText -f fecu.ins
Unix (everything in the same line): java -mx512M -cp
Maud.jar:lib/miscLib.jar:lib/JSgInfo.jar:lib/jgaec.jar:lib/ij.jar
it.unitn.ing.rista.MaudText -f fecu.ins
For Mac OS X, it is advised to use the generic Unix Maud installation (or to change the path to
the jar files). Before to run Maud in batch mode it is important to run Maud interactive (with the
interface) at least once to create and extract the databases, examples and preferences folder.

2.3 Analysis of results
After running Maud in batch mode, we can check quickly the results by loading the results file
FECUresults.txt in a spreadsheet program. The results are arranged in rows and separated
by tabs. The first row contains the column titles, each subsequent row a different analysis. The
Rwp value for each analysis is reported in the second column and the biggest value found was
5.6% as an indication of the success of the analysis. As an example we report in Figure 2 the
graphical correlation of the copper-rich phase percentage and its mean crystallite value as found
in the analysis versus the sample number. The files and examples used in this articles will be
uploaded in a tutorial in the Maud web page along with some additional files with the batch mode
commands for an easier use.

3 How to get Maud 2.0 and further informations
For this analysis we need Maud version 2.037 or later and it can be freely downloaded from the
Maud web page at http://www.ing.unitn.it/ maud for the preferred platform. There are two archives
for Windows and Mac OS X plus a generic unix version that can be used for Linux, Solaris or
every unix based system with a Java 2 virtual machine installed. The new version 2.0 has a new
interface focused on reducing the effort of a new user and simplifying the most common tasks.
Some particularity of the new version respect to the previous one are (most of them to provide
some useful routines for ab-initio structure solution):
• Different minimization/search algorithms selectable: Marquardt least squares, Evolutionary
algorithm, Simulated annealing, Metadynamic search algorithm. As an example the evolutionary algorithm can be used in the early steps of the refinement to select the proper starting
solution and the Marquardt to drive it to convergence.
4
• Possibility to use crystallites and microstrain distributions for peak shape description instead
of analytical fixed shape functions.
• Maximum Entropy Electron Map full pattern fitting. An electron map can be used for fitting
instead of atoms.
• Full pattern fitting by a list of peaks. Either an arbitrary list of peaks (each one with its own
position, intensity and shape), or simply a list of structure factors to be imported, instead of
a list of atoms.
• Indexing directly on the pattern, selecting the Le Bail fit and the evolutionary algorithm for
the cell search. This may be used to improve a difficult indexing or a partly done one.
• Introduction of fragments. So fragment search can be done directly on the pattern or on a
list of extracted structure factors.
• Energy minimization. At the moment only the simple repulsion energy is completed. Other
energy principles are under completition.
• Spectra integration from image plate or CCD transmission/reflection 2D images. Center,
tilting errors and distance from sample can be refined in the spectra fitting.
Bugs and errors should be reported to the author through the bug reporter web page; questions in
the Maud forum accessible from the Maud web page.
In a future article we will report the instructions on how to modify/extend the program by little Java programming or provide a new alternative model/plugin for the instrument or the structure/microstructure or datafiles importing.
References
[1] D. L. Bish and S. A. Howard. J. Appl. Cryst., 21, 86–91, 1988.
[2] R. J. Hill and C. J. Howard. J. Appl. Cryst., 20, 467–474, 1987.
[3] L. Lutterotti and S. Gialanella. Acta Mater., 46(1), 101–110, 1998.
[4] N. C. Popa. J. Appl. Cryst., 31, 176–180, 1998.
[5] B. E. Warren. X-ray Diffraction. Addison-Wesley, Reading, MA, 1969

Author: Luca Lutterotti
Dipartimento di Ingegneria dei Materiali e delle Tecnologie Industriali
Universita di Trento, 38050 Trento, Italy `
E-mail: Luca.Lutterotti@ing.unitn.it
WWW: http://www.ing.unitn.it/ maud

Our XRD interpretation includes: 
1. Phase determination 
2. Determination of diffracted planes
 3- Calculation of crystalline size and microstrain
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XRD is a non-destructive test method used to analyze the structure of crystalline materials. XRD analysis, by way of the study of the crystal structure, is used to identify the crystalline phases present in a material and thereby reveal The chemical composition information. JCPDS does not exist now. It has not existed since 1978. It is now known as ICDD. These particular files have never been, are not, and never will be free; it a commercial only database. There are other free databases, however. Vikas has given you a starting point.

Powder Diffraction File is a trademark of the “JCPDS (Joint Committee on Powder Diffraction Standards)-International Centre for Diffraction Data”.In 1978, the name of the organization was changed to the “International Centre for Diffraction Data” in order to highlight the global commitment of this scientific endeavor. Here, you need to purchase the database.

Some free databases are collected:

1. COD (Crystallography Open Database):

COD is an open-access database, and you can freely obtain all data contained in it. You can download cif files and then you can use mercury to plot structure models and save reflection list and xrd calculated pattern.http://www.crystallography.net/cod/search.html

2. The American Mineralogist Crystal Structure Database:

This site is an interface to a crystal structure database that includes every structure published in the American Mineralogist, The Canadian Mineralogist, European Journal of Mineralogy and Physics and Chemistry of Minerals, as well as selected datasets from other journals. The database is maintained under the care of the Mineralogical Society of America and the Mineralogical Association of Canada, and financed by the National Science Foundation.http://rruff.geo.arizona.edu/AMS/amcsd.php

3. DASH: (Cambridge Structural Database System (CSDS)):DASH is a versatile and interactive package for solving crystal structures from powder diffraction data. DASH solves structures by simulated annealing of structural models to indexed diffraction data and features a helpful wizard to guide you through the entire structure solution process.https://www.ccdc.cam.ac.uk/solutions/csd-materials/components/dash/

Some of Paid databases:

1. The International Centre for Diffraction Data® (ICDD®):

ICDD (JCPDS is now called ICDD) is a non-profit scientific organization dedicated to collecting, editing, publishing, and distributing powder diffraction data for the identification of materials. The membership of the ICDD consists of worldwide representation from academe, government, and industry. The Powder Diffraction File™ (PDF®) is the only crystallographic database that is specifically designed for material identification and characterization. It is an analysis system that is comprised of crystallographic and diffraction data. The only crystallographic database organization in the world with its Quality Management System ISO 9001:2015 certified by DEKRA.http://www.icdd.com/

2. HighScore Plus:The ideal tool for crystallographic analysis and more. Whether you are interested in improved process control, or doing research and development, understanding your materials starts very often with understanding the powder diffraction pattern. After identification of all phases present in your sample with Malvern Panalytical’s HighScore, this all-in-one software suite with the Plus option continues to support you with your analysis. Whether your focus is on quantification with or without the Rietveld method, profile fitting, or pattern treatment; HighScore Plus is the solution and helps you performing your daily analyses.https://www.malvernpanalytical.com/en/products/category/software/x-ray-diffraction-software/highscore-with-plus-option

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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

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What is XPS?

XPS is a surface-sensitive technique based on the photoelectric effect, which occurs when atoms or molecules are irradiated by photons of suitable energy, resulting in the ejection of electrons. The kinetic energy of the ejected electrons depends upon the elemental core level from which they originated.

Using this information, XPS data can be used to determine the elemental composition of the surface and, in most cases, the bonding environment of the elements.

The schematic figure shown to the right, illustrates the XPS procedure, where x-rays are used to excite and eject photoelectrons from a sodium chloride molecule on a substrate.

XPS detects and quantifies the ejected photoelectrons, which are proportional to the amount present in the uppermost layers of the surface.

To understand more about these uppermost layers, further details on the XPS penetration depth and attenuation length of the X-ray photons are required.

Normal XPS can provide information from the top 10nm (approximately) layer of the surface.

Schematic diagram of photoelectron emission from a sodium atom under x-ray exposure, and (right) example of XPS survey scan spectra of sodium chloride with the Na1s electron XPS peak highlighted in the spectra.

Image provided courtesy of Thermo Fisher Scientific.

Theoretically, XPS should be able to detect all elements. However, helium (He) does not readily form solid compounds and its 1s orbital has a tiny cross-section for photoemission.

Hydrogen (H) also has a tiny cross-section and suffers from having to share its only electron in forming compounds, which then resides in a valence-like orbital, the energy of which varies from compound to compound.

Features of the Thermo Fisher ESCALAB 250Xi XPS instrument

The Thermo Fisher Scientific ESCALAB 250Xi is the most recent advancement in the ESCALAB series.

The instrument is an optimised multi-method platform that is expandable and comes with excellent flexibility and configurability. Its cutting edge technology is driven by smart software and hardware.

Equipped with a micro-focusing X-ray monochromator designed to deliver optimum XPS performance, the instrument ensures maximum sample throughput.

The multi-technique capability and availability of a range of preparation chambers and devices provides the solution to any surface analytical problem.

ESCALAB 250Xi XPS instrumentESCALAB standard sample loading chamber

Some notable features of the instrument include:

• High sensitivity spectroscopy
• Small area XPS
• Depth profiling capability with MAGCIS (Monatomic & Gas Cluster Ion Source)
• Ion scattering spectroscopy (ISS)
• Reflected electron energy loss spectroscopy (REELS)
• Micro-focused X-ray spot
• Efficient Charge Neutralisation
• Angle Resolved Spectroscopy
• Ultra-high sensitivity and energy resolution

XPS analysis sample requirement

XPS is a surface analytical technique that can be used to study the surface properties of a range of sample types. This includes both inorganic and organic (ex-situ and samples suitable to be placed under ultra-high vacuum) materials, polymers, semiconductors, metals, composite materials, geological and archaeological samples, ceramics, and glasses amongst others.

• The ideal dimension for an XPS analysis sample is 1cm X 1cm, with a maximum of 0.5cm thickness. Samples with lengths up to 5cm and widths up to 2.2cm can also be analysed. Samples below 0.5cm x 0.5cm dimension are difficult to mount on the sample stage. XPS analysis depends on the spot size. Ideally we can measure surface areas (spots) greater than 300µm X 300µm, as the smallest X-ray spot/exposure area is 200µm X 200µm for general analysis in our instrument. Please let us know your sample size and type in advance.
• Powder samples can also be measured using XPS. However, please discuss this with us in advance.
• Sample handling is crucial for XPS analysis. As XPS measures the top few atomic layers on the surface (different for depth profiling), it is very easy to contaminate samples with fingerprints. Ideally, XPS samples should be shipped and transferred inside a Wafer Carrier Box used in the semiconductor industry. However, any sealed container that doesn’t alter surface chemistry should be sufficient. Samples stored in zip-lock polymer bags are not ideal.

XPS Instrument Analysis Chamber view.

Image provided courtesy of Thermo Fisher Scientific.

Applications of XPS

XPS surface analysis can provide answers to a wide range of research problems. The following are examples of research questions addressed using XPS by researchers at the University of Brighton and elsewhere.

What material did we make / purchase?

XPS can provide data about the elemental distribution on the surface of a sample.

The limit of detection is 0.1 atomic per cent or better. In the figure (right), two XPS survey scans of gold coated QCM crystals are shown – the inset is a zoomed-in version of the Ti2p area of the spectra.

The two crystals are from two separate purchased batches. As can be seen, batch one (red) contains around 23 atomic per cent of titanium, making the crystal not fit for purpose, while batch two (green) is ‘pure’ as claimed by the manufacturer.

Survey scan spectra of two different batch QCM crystals. (S. Ray, unpublished data)

How thick is the coating/contamination on a surface?

XPS can measure precisely the thickness (below 10nm) of the surface adsorbed layer. This is useful in understanding the nature of surface contamination, and also in studying biomolecular adsorption on implants.

The spectra (right) is a comparison of XPS and Ellipsometric Thickness measurements of three different proteins adsorbed on hydrophobic surfaces, showing extremely close agreement.

XPS and Ellipsometric Thickness measurement comparison of three different proteins adsorbed on hydrophobic surfaces.

What chemical states are present on my surface?

XPS can identify and quantify the nature of the chemical states on a surface, and can help in visualising the surface functionalisation, essential for applications including bio-chemical sensors and chemical conjugations.

In the example (below left image), the experimental verification of graphene oxide reduction is shown, while the right image illustrates the success of a pluoronics (triblock copolymer) coating on reduced graphene oxide.

XPS C1s narrow scan spectra of (left) reduced graphene oxide and (right) pluronics coated reduced graphene oxide (S. Ray, unpublished data)

How can we analyse and quantify contamination or doping in our sample?

XPS can reveal surface or just below-surface contamination, and can successfully quantify any organic and inorganic contaminants and/or doping.

One example of doping quantification would be analysing the nitrogen doping effect on the properties of graphene. From the XPS spectra (right), the amount and bonding nature of nitrogen with graphene could be quantified.

Image on left: Nitrogen (N1s) narrow scan spectra and peak deconvolution to find the nature of nitrogen bonded to graphene (S. Ray, unpublished data).

Can XPS measure the thickness of coatings on nanoparticles?

In his 2017 publication, Professor David Castner (University of Washington) states, “Single particle information from electron microscopy combined with XPS sensitivity in determining composition make a powerful combination for nanoparticle analysis” ( Powell et al., 2017, J. Physical. Chemistry C).

XPS can measure precisely the thickness of single layer or multiple layers of coatings on nano-micro particles. Currently there are numerous situations where nanoparticles are used (e.g. in targeted drug delivery, sunscreens, and antimicrobial socks).

To functionalise these particles according to their target use, a proper understanding of the coating on the nanoparticles is required. In the case of multifunction nanoparticle use for targeted drug delivery, quantification of the single, double or triple layers is necessary.

XPS can help in understanding many other questions, including:

• What is the effect of heat, aging, chemical treatment, or real world use on my samples?
• What coating is on the surface?
• What is wrong inside my thick film?
• Are the thicknesses of film layers correct?
• Is the surface chemistry of a sample uniform?

Accessing the Surface Analysis Laboratory

If you have queries about how XPS can help in your research and/or industrial project, please do not hesitate to get in touch by telephone or email. We are happy to discuss your research requirements and provide quotations as necessary.

We particularly welcome proposals for joint research funding applications.

We also offer an analysis-only service, but can also provide full interpretation of results on request. XPS analysis costs can be charged per sample, per day/half-day or according to your needs.

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Introduction

X-Ray photoelectron spectroscopy (XPS), also known as electron spectroscopy for chemical analysis (ESCA), is one of the most widely used surface techniques in materials science and chemistry. It allows the determination of atomic composition of the sample in a non-destructive manner, as well as other chemical information, such as binding constants, oxidation states and speciation. The sample under study is subjected to irradiation by a high energy X-ray source. The X-rays penetrate only 5 – 20 Å into the sample, allowing for surface specific, rather than bulk chemical, analysis. As an atom absorbs the X-rays, the energy of the X-ray will cause a K-shell electron to be ejected, as illustrated by Figure 1.13.11.13.1. The K-shell is the lowest energy shell of the atom. The ejected electron has a kinetic energy (KE) that is related to the energy of the incident beam (hν), the electron binding energy (BE), and the work function of the spectrometer (φ) (1.13.11.13.1). Thus, the binding energy of the electron can be calculated.

BE = hν − KE − ψs(1.13.1)(1.13.1)BE = hν − KE − ψs

Table 1.13.11.13.1 shows the binding energy of the ejected electron, and the orbital from which the electron is ejected, which is characteristic of each element. The number of electrons detected with a specific binding energy is proportional to the number of corresponding atoms in the sample. This then provides the percent of each atom in the sample.

The chemical environment and oxidation state of the atom can be determined through the shifts of the peaks within the range expected (Table 1.13.21.13.2). If the electrons are shielded then it is easier, or requires less energy, to remove them from the atom, i.e., the binding energy is low. The corresponding peaks will shift to a lower energy in the expected range. If the core electrons are not shielded as much, such as the atom being in a high oxidation state, then just the opposite occurs. Similar effects occur with electronegative or electropositive elements in the chemical environment of the atom in question. By synthesizing compounds with known structures, patterns can be formed by using XPS and structures of unknown compounds can be determined.

Sample preparation is important for XPS. Although the technique was originally developed for use with thin, flat films, XPS can be used with powders. In order to use XPS with powders, a different method of sample preparation is required. One of the more common methods is to press the powder into a high purity indium foil. A different approach is to dissolve the powder in a quickly evaporating solvent, if possible, which can then be drop-casted onto a substrate. Using sticky carbon tape to adhere the powder to a disc or pressing the sample into a tablet are an option as well. Each of these sample preparations are designed to make the powder compact, as powder not attached to the substrate will contaminate the vacuum chamber. The sample also needs to be completely dry. If it is not, solvent present in the sample can destroy the necessary high vacuum and contaminate the machine, affecting the data of the current and future samples.

Analyzing Functionalized Surfaces

Depth Profiling

When analyzing a sample (Figure 1.13.21.13.2 a) by XPS, questions often arise that deal with layers of the sample. For example, is the sample homogenous, with a consistent composition throughout, or layered, with certain elements or components residing in specific places in the sample? (Figure 1.13.21.13.2 b,c). A simple way to determine the answer to this question is to perform a depth analysis. By sputtering away the sample, data can be collected at different depths within the sample. It should be noted that sputtering is a destructive process. Within the XPS instrument, the sample is subjected to an Ar⁺ ion beam that etches the surface. This creates a hole in the surface, allowing the X-rays to hit layers that would not have otherwise been analyzed. However, it should be realized that different surfaces and layers may be etched at different rates, meaning the same amount of etching does not occur during the same amount of time, depending on the element or compound currently being sputtered.

It is important to note that hydrocarbons sputter very easily and can contaminate the high vacuum of the XPS instrument and thus later samples. They can also migrate to a recently sputtered (and hence unfunctionalized) surface after a short amount of time, so it is imperative to sputter and take a measurement quickly, otherwise the sputtering may appear to have had no effect.

Functionalized Films

When running XPS, it is important that the sample is prepared correctly. If it is not, there is a high chance of ruining not only data acquisition, but the instrument as well. With organic functionalization, it is very important to ensure the surface functional group (or as is the case with many functionalized nanoparticles, the surfactant) is immobile on the surface of the substrate. If it is removed easily in the vacuum chamber, it not only will give erroneous data, but it will contaminate the machine, which may then contaminate future samples. This is particularly important when studying thiol functionalization of gold samples, as thiol groups bond strongly with the gold. If there is any loose thiol group contaminating the machine, the thiol will attach itself to any gold sample subsequently placed in the instrument, providing erroneous data. Fortunately, with the above exception, preparing samples that have been functionalized is not much different than standard preparation procedures. However, methods for analysis may have to be modified in order to obtain good, consistent data.

A common method for the analysis of surface modified material is angle resolved X-ray photoelectron spectroscopy (ARXPS). ARXPS is a non-destructive alternative to sputtering, as it relies upon using a series of small angles to analyze the top layer of the sample, giving a better picture of the surface than standard XPS. ARXPS allows for the analysis of the topmost layer of atoms to be analyzed, as opposed to standard XPS, which will analyze a few layers of atoms into the sample, as illustrated in Figure 1.13.31.13.3. ARXPS is often used to analyze surface contaminations, such as oxidation, and surface modification or passivation. Though the methodology and limitations are beyond the scope of this module, it is important to remember that, like normal XPS, ARXPS assumes homogeneous layers are present in samples, which can give erroneous data, should the layers be heterogeneous.

Limitations of XPS

There are many limitations to XPS that are not based on the samples or preparation, but on the machine itself. One such limitation is that XPS cannot detect hydrogen or helium. This, of course, leads to a ratio of elements in the sample that is not entirely accurate, as there is always some amount of hydrogen. It is a common fallacy to assume the percent of atoms obtained from XPS data are completely accurate due to this presence of undetected hydrogen (Table 1.13.11.13.1).

It is possible to indirectly measure the amount of hydrogen in a sample using XPS, but it is not very accurate and has to be done in a roundabout, often time consuming manner. If the sample contains hydrogen with a partial positive charge (i.e. OH), the sample can be washed in sodium naphthalenide (C₁₀H₈Na). This replaces this hydrogen with sodium, which can then be measured. The sodium to oxygen ratio that is obtained infers the hydrogen to oxygen ratio, assuming that all the hydrogen atoms have reacted.

XPS can only give an average measurement, as the electrons lower down in the sample will lose more energy as they pass other atoms while the electrons on the surface retain their original kinetic energy. The electrons from lower layers can also undergo inelastic or elastic scattering, seen in Figure 1.13.41.13.4. This scattering may have a significant impact on data at higher angles of emission. The beam itself is also relatively wide, with the smallest width ranging from 10 – 200 μm, lending to the observed average composition inside the beam area. Due to this, XPS cannot differentiate sections of elements if the sections are smaller than the size of the beam.

Sample reaction or degredation are important considerations. Caution should be exercised when analyzing polymers, as they are often chemically active and X-rays will provide energy to start degrading the polymer, altering the properties of the sample. One method found to help overcome this particular limitation is to use angle-resolved X-ray photoelectron spectroscopy (ARXPS). XPS can often reduce certain metal salts, such as Cu²⁺. This reduction will give peaks that indicate a certain set of properties or chemical environments when it could be completely different. It needs to be understood that charges can build up on the surface of the sample due to a number of reasons, specifically due to the loss of electrons during the XPS experiment. The charge on the surface will interact with the electrons escaping from the sample, affecting the data obtained. If the charge collecting is positive, the electrons that have been knocked off will be attracted to the charge, slowing the electrons. The detector will pick up a lower kinetic energy of the electrons, and thus calculate a different binding energy than the one expected, giving peaks which could be labeled with an incorrect oxidation state or chemical environment. To overcome this, the spectra must be charge referenced by one of the following methods: using the naturally occurring graphite peak as a reference, sputtering with gold and using the gold peak as a reference or flooding the sample with the ion gun and waiting until the desired peak stops shifting.

Limitations with Surfactants and Sputtering

While it is known that sputtering is destructive, there are a few other limitations that are not often considered. As mentioned above, the beam of X-rays is relatively large, giving an average composition in the analysis. Sputtering has the same limitation. If the surfactant or layers are not homogeneous, then when the sputtering is finished and detection begins, the analysis will show a homogeneous section, due to the size of both the beam and sputtered area, while it is actually separate sections of elements.

The chemistry of the compounds can be changed with sputtering, as it removes atoms that were bonded, changing the oxidation state of a metal or the hybridization of a non-metal. It can also introduce charges if the sample is non-conducting or supported on a non-conducting surface.

Using XPS to Analyze Metal Nanoparticles

Introduction

X-ray photoelectron spectroscopy (XPS) is a surface technique developed for use with thin films. More recently, however, it has been used to analyze the chemical and elemental composition of nanoparticles. The complication of nanoparticles is that they are neither flat nor larger than the diameter of the beam, creating issues when using the data obtained at face value. Samples of nanoparticles will often be large aggregates of particles. This creates problems with the analysis acquisition, as there can be a variety of cross-sections, as seen in Figure 1.13.51.13.5. This acquisition problem is also compounded by the fact that the surfactant may not be completely covering the particle, as the curvature of the particle creates defects and divots. Even if it is possible to create a monolayer of particles on a support, other issues are still present. The background support will be analyzed with the particle, due to their small size and the size of the beam and the depth at which it can penetrate.

Many other factors can introduce changes in nanoparticles and their properties. There can be probe, environmental, proximity, and sample preparation effects. The dynamics of particles can wildly vary depending on the reactivity of the particle itself. Sputtering can also be a problem. The beam used to sputter will be roughly the same size or larger than the particles. This means that what appears in the data is not a section of particle, but an average composition of several particles.

Each of these issues needs to be taken into account and preventative measures need to be used so the data is the best representation possible.

Sample Preparation

Sample preparation of nanoparticles is very important when using XPS. Certain particles, such as iron oxides without surfactants, will interact readily with oxygen in the air. This causes the particles to gain a layer of oxygen contamination. When the particles are then analyzed, oxygen appears where it should not and the oxidation state of the metal may be changed. As shown by these particles, which call for handling, mounting and analysis without exposure to air, knowing the reactivity of the nanoparticles in the sample is very important even before starting analysis. If the reactivity of the nanoparticle is known, such as the reactivity of oxygen and iron, then preventative steps can be taken in sample preparation in order to obtain the best analysis possible.

When preparing a sample for XPS, a powder form is often used. This preparation, however, will lead to aggregation of nanoparticles. If analysis is performed on such a sample, the data obtained will be an average of composition of each nanoparticle. If composition of a single particle is what is desired, then this average composition will not be sufficient. Fortunately, there are other methods of sample preparation. Samples can be supported on a substrate, which will allow for analysis of single particles. A pictorial representation in Figure 1.13.61.13.6 shows the different types of samples that can occur with nanoparticles.

Analysis Limitations

Nanoparticles are dynamic; their properties can change when exposed to new chemical environments, leading to a new set of applications. It is the dynamics of nanoparticles that makes them so useful and is one of the reasons why scientists strive to understand their properties. However, it is this dynamic ability that makes analysis difficult to do properly. Nanoparticles are easily damaged and can change properties over time or with exposure to air, light or any other environment, chemical or otherwise. Surface analysis is often difficult because of the high rate of contamination. Once the particles are inserted into XPS, even more limitations appear.

Probe Effects

There are often artifacts introduced from the simple mechanism of conducting the analysis. When XPS is used to analyze the relatively large surface of thin films, there is small change in temperature as energy is transferred. The thin films, however, are large enough that this small change in energy has to significant change to its properties. A nanoparticle is much smaller. Even a small amount of energy can drastically change the shape of particles, in turn changing the properties, giving a much different set of data than expected.

The electron beam itself can affect how the particles are supported on a substrate. Theoretically, nanoparticles would be considered separate from each other and any other chemical environments, such as solvents or substrates. This, however, is not possible, as the particles must be suspended in a solution or placed on a substrate when attempting analysis. The chemical environment around the particle will have some amount of interaction with the particle. This interaction will change characteristics of the nanoparticles, such as oxidation states or partial charges, which will then shift the peaks observed. If particles can be separated and suspended on a substrate, the supporting material will also be analyzed due to the fact that the X-ray beam is larger than the size of each individual particle. If the substrate is made of porous materials, it can adsorb gases and those will be detected along with the substrate and the particle, giving erroneous data.

Environmental Effects

Nanoparticles will often react, or at least interact, with their environments. If the particles are highly reactive, there will often be induced charges in the near environment of the particle. Gold nanoparticles have a well-documented ability to undergo plasmon interactions with each other. When XPS is performed on these particles, the charges will change the kinetic energy of the electrons, shifting the apparent binding energy. When working with nanoparticles that are well known for creating charges, it is often best to use an ion gun or a coating of gold. The purpose of the ion gun or gold coating is to try to move peaks back to their appropriate energies. If the peaks do not move, then the chance of there being no induced charge is high and thus the obtained data is fairly reliable.

Proximity Effects

The proximity of the particles to each other will cause interactions between the particles. If there is a charge accumulation near one particle, and that particle is in close proximity with other particles, the charge will become enhanced as it spreads, affecting the signal strength and the binding energies of the electrons. While the knowledge of charge enhancement could be useful to potential applications, it is not beneficial if knowledge of the various properties of individual particles is sought.

Less isolated (i.e., less crowded) particles will have different properties as compared to more isolated particles. A good example of this is the plasmon effect in gold nanoparticles. The closer gold nanoparticles are to each other, the more likely they will induce the plasmon effect. This can change the properties of the particles, such as oxidation states and partial charges. These changes will then shift peaks seen in XPS spectra. These proximity effects are often introduced in the sample preparation. This, of course, shows why it is important to prepare samples correctly to get desired results.

Conclusions

Unfortunately there is no good general procedure for all nanoparticles samples. There are too many variables within each sample to create a basic procedure. A scientist wanting to use XPS to analyze nanoparticles must first understand the drawbacks and limitations of using their sample as well as how to counteract the artifacts that will be introduced in order to properly use XPS.

One must never make the assumption that nanoparticles are flat. This assumption will only lead to a misrepresentation of the particles. Once the curvature and stacking of the particles, as well as their interactions with each other are taken into account, XPS can be run.

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Principle

X-ray Photoelectron Spectroscopy (XPS) or Electron Spectroscopy for Chemical Analysis (ESCA) is a technique which analyzes the elements constituting the sample surface, its composition, and chemical bonding state by irradiating x-rays on the sample surface, and measuring the kinetic energy of the photoelectrons emitted from the sample surface. XPS instrument using Al Kα rays can generally obtain information on elements within a few nms of the sample surface.

Additionally, the change in bond energy (chemical shift) caused by the electron state surrounding the atoms to be analyzed, such as atomic valence charges and interatomic distances, tend to be greater than the chemical shift observed in AES, which makes the relative ease with which the state of chemical bonds can be identified another advantage of XPS.

Charge compensation mechanism (dual beam charge neutralization)

XPS is used for element/chemical state analysis for a wide range of solid samples from conductive to insulating materials. However, with insulating material samples, a positive charge occurs in the x-ray irradiated area due to the generation of photoelectrons. A spectrum measured in a positively charged state shifts to the high bond energy side (low kinetic energy side) compared to its actual position, making it difficult to grasp the correct energy position. Thus, with insulating material samples, charge neutralization is necessary during measurement. The dual beam technique, which irradiates a low energy electron beam and an ion beam simultaneously, is a neutralization method which stabilizes uneven charges on the surface in a self-repairing way, and is capable of stable charge neutralization for a wide range of insulating materials. It is also an essential feature for microscopic area analysis.

X-ray photoelectron spectroscopy (XPS Analysis) also called Electron
Spectroscopy for Chemical Analysis (ESCA) is a chemical surface
analysis method. XPS measures the chemical composition of the outermost
100 Å of a sample. Measurements can be made at greater depths by
ion sputter etching to remove surface layers.

All elements except for H and He can be detected at concentrations above 0.05 to 1.0 atom %, depending on the element. In addition, chemical bonding information can be determined from detailed analysis. Conductive and nonconductive samples can be measured and the technique is well suited for polymeric materials. The sampled area varies from 1 mm down to 30 µm in diameter.

X-ray Photoelectron Spectroscopy Analysis (XPS)

In XPS, also known as Electron Spectroscopy for Chemical Analysis (ESCA), X-rays bombard a sample creating ionized atoms and ejecting free electrons. The energies of these free electrons are related to their binding energies in the original atom. By measuring these characteristic energies, XPS Analysis identifies the chemical elements present in the sample. XPS provides both elemental and, to a certain extent, chemical information in the top 3-30 atomic layers (10-100Å) in solid samples. The sensitivity varies between 0.01-1 atom% dependent upon the element. It can do nondestructive depth profiling to 100 Å and detect all elements except H and He. Ion sputtering combined with XPS is used to accomplish deeper profiling. XPS is especially good for obtaining elemental surface composition of unknown materials, including conductors and insulators.

Critical problem solving with surface analysis is enhanced by reducing the probe area when using XPS Analysis. Small-spot XPS instruments probe for composition, chemistry, and contamination in 0.01 mm2 areas. It also makes XPS sputter depth profiles a reality.

One of the primary reasons for using XPS Surface Analysis to analyze samples is its inherent high surface sensitivity. This results from the fact that nearly all of the electrons which are used for analysis escape from only the outermost four to five atomic layers of the material. This high surface sensitivity permits the easy detection of most surface concentrated elements that would be undetectable by bulk or quasi-bulk techniques, e.g. XRD, XRF, EDS or Electron Microprobe. Remember, chemistry begins at the surface.

Imagine that a sample surface is contaminated by 20% coverage of Si from a silicone lubricant. Using XPS Analysis, the Si atoms represent ~6% of the atoms present in the 4-atom deep sampling volume. However, by using one of the bulk or quasi-bulk techniques, the Si atoms now represent ~0.03% or less of the >1 µm deep sampling volume. Given that surface Si concentrations as low as 0.10.% can be detected, the advantage of XPS over bulk techniques is readily apparent.

One very important reason for using XPS Surface Aanlysis is that it is nondestructive. XPS uses very soft (low energy) x-rays that produce minimum energy input to the sample during analysis. Electron beam analysis techniques concentrate a high amount of energy in a small region and can be very destructive toward organic materials or other thermally sensitive compounds. Bulk analysis techniques often require that the sample be powdered and placed in a matrix material introducing a high probability of altering or entirely losing some surface species.

In addition to providing a detailed elemental surface composition, XPS Analysis provides even more information about the detected elements. Changes in the chemical environment or oxidation state of an atom can cause corresponding changes in the energies of the electrons that are ejected and analyzed. These energy shifts or “chemical shifts” have been well studied and tabulated for many different compounds. By measuring these shifts, it is possible in most cases to accurately assign the chemical environment of a given element.

Another important advantage of XPS over electron beam techniques, i.e. AES, Electron Microprobe, etc., is its ability to analyze insulating specimens with relative ease. Since the analysis beam (x-rays) does not consist of charged particles, the insulating specimen is not required to conduct away any charge buildup due to incidence of the analysis beam itself. The specimen is only required to conduct away enough charge to compensate for the small number of electrons which were ejected from the sample. This small positive charge buildup is easily compensated for by use of a “flood gun”, which directs low energy electrons to the sample surface.

In addition to the inherent advantages of using XPS generally, the small-spot instrument that Rocky Mountain Laboratories’ employs has a number of special features that give an enormous edge over other instruments. The sample transfer and sample chamber configuration allows the analysis of samples a s large as 3.75″ diameter x 0.375″ high. Or, many specimens may be mounted and measured by software automation, if they are of uniform size and shape. The minimum size is limited only by the size of the smallest x-ray beam (50 µm), which has been used to analyze a single 10 µm organic fiber.

The largest x-ray spot (image of the x-ray beam on the sample) is 1-2 mm and is used primarily for rapid data acquisition during survey scans. The smallest x-ray spot is most often used for analysis of small heterogeneous features on a larger sample or simply for analysis of a very small sample. Because the x-ray spot is smaller than in other XPS instruments, remarkably rapid and precise depth profiles are now routine, since both raster size and beam voltage of the ion etching gun can be greatly reduced.

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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

Show caption

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). Details

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

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)

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X-ray diffraction (XRD) is a technique used in materials science for determining the atomic and molecular structure of a material. This is done by irradiating a sample of the material with incident X-rays and then measuring the intensities and scattering angles of the X-rays that are scattered by the material. The intensity of the scattered X-rays are plotted as a function of the scattering angle, and the structure of the material is determined from the analysis of the location, in angle, and the intensities of scattered intensity peaks. Beyond being able to measure the average positions of the atoms in the crystal, information on how the actual structure deviates from the ideal one, resulting for example from internal stress or from defects, can be determined.

The diffraction of the X-rays, that is central to the XRD method, is a subset of the general X-ray scattering phenomena. XRD, which is generally used to mean can wide-angle X-ray diffraction (WAXD), falls under several methods that use the elastically scattered X-ray waves. Other elastic scattering based X-ray techniques include small angle X-ray scattering (SAXS), where the X-rays are incident on the sample over the small angular range of 0.1-10⁰typically). SAXS measures structural correlations of the scale of several nanometers or larger (such as crystal superstructures), and X-ray reflectivity that measures the thickness, roughness, and density of thin films. WAXD covers an angular range beyond 10⁰.

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JoVE Science Education Database. Materials Engineering. X-ray Diffraction. JoVE, Cambridge, MA, (2020).

PRINCIPLES

Relationship between diffracted peak positions and crystal structure:

When light waves of sufficiently small wavelength are incident upon a crystal lattice, they diffract from the lattice points. At certain angles of incidence, the diffracted parallel waves constructively interfere and create detectable peaks in intensity. W.H. Bragg identified the relationship illustrated in Figure 1 and derived a corresponding equation:

nλ = 2d_hkl sin θ [1]

Here λ is the wavelength of the X-rays used, d_hkl is the spacing between a particular set of planes with (hkl) Miller indices*, and θ is the angle of incidence at which a diffraction peak is measured. Finally, n is an integer that represents the ‘harmonic order’ of the diffraction. At n=1, for example, we have the first harmonic, meaning that the path of X-rays diffracted through the crystal (equivalent to 2d_hkl sin ) is exactly 1λ, while at n=2, the diffracted path is 2λ. We can typically assume n=1, and, in general, n=1 for θ < sin^-1(2λ/d_h’k’l’), where h’k’l’ are the Miller indices of the planes that show the first peak (at the lowest 2θ value) in a diffraction experiment. Miller indices are a set of three integers that constitute a notation system for identifying directions and planes within crystals. For directions, the [h k l]Miller indices represent the normalized difference in the respective x, y and z coordinates (in a Cartesian coordinate system) of two points along the direction. For planes, the Miller indices (h k l) of a plane are simply the h k l values of the direction perpendicular to the plane.

In a typical XRD experiment in reflection mode, the X-ray source is fixed in position and the sample is rotated with respect to the X-ray beam over θ. A detector picks up the diffracted beam and has to keep up with the sample rotation by rotating at twice the rate (i.e. for a given sample angle of θ, the detector angle is 2θ). The geometry of the experiment is schematically shown in Figure 1.

Figure 1: Illustration of Bragg’s Law.

When a peak in intensity is observed, equation 1 is necessarily satisfied. Consequently, we can calculate d-spacings based on the angles at which these peaks are observed. By calculating the d-spacings of multiple peaks, the crystal class and the crystal structure parameters material sample can be identified using a database such as the Hanawalt Search Manual or database libraries available with the XRD software being used.

We will be assuming that the sample being investigated is not a single crystal. If the sample were a single crystal with a particular (h*k*l*) plane parallel to the sample surface, it would need to be rotated until the Bragg condition for the (h*k*l*) is satisfied in order to see a peak in diffracted intensity (for n=1) with potentially higher harmonic (h*k*l*)peaks (e.g. for n=2) also detectable at higher angles. At all other angles there would be no peaks in a single crystal sample. Instead, let’s assume that the sample is either polycrystalline or that it is a powder, with a statistically significant number of crystalline grains or powder particles illuminated by the incident X-ray beam. Under this assumption, the sample consists of randomly oriented grains, with a similar statistical probability for all possible lattice planes to diffract.

The relationships between the d_hkl and the unit cell parameters are shown below in Equations 2-7 for the 7 crystal classes, cubic, tetragonal, hexagonal, rhombohedral, orthorhombic, monoclinic and triclinic. The unit cell parameters consist of lengths of(a,b,c) and the angles between (α, β, γ) the edges of the unit cells for the 7 crystal classes (Figure 1x shows the example of one of the crystal classes: the tetragonal structure where a=b≠c, and α=β=γ=90⁰). Using multiple diffracted peak positions (i.e. several distinct d_hkl values), the values of the unit cell parameters can be solved uniquely.

Figure 2: The tetragonal structure as one of the seven crystal classes.

Cubic (a = b = c; α = β = γ = 90⁰):

  [2]

Tetragonal (a = b ≠ c; α = β = γ = 90⁰):

  [3]

Hexagonal (a = b ≠ c; α = β = 90⁰; γ = 120⁰):

  [4]

Orthorhombic (a ≠ b ≠ c; α = β = γ = 90⁰):

  [5]

Rhombohedral (a = b ≠ c; α = β = γ = 90⁰):

  [6]

Monoclinic (a ≠ b ≠ c; α = γ = 90⁰≠ β):

  [7]

Triclinic (a ≠ b ≠ c; α ≠ β ≠ γ ≠ 90⁰): 

        [8] 

Relationship between diffracted peak intensities and crystal structure:

Next we examine the factors that contribute to the intensity in an XRD pattern. The factors can be broken down as 1) the contribution to scattering that results directly from the unique structural aspects of the material (the specific types and locations of scattering atoms in the structure) and 2) those that are not specific to the material. In the former, there are two factors: the ‘absorption factor’ and the ‘structure factor’. The absorption factor primarily depends on the ability of the material to absorb X-rays on their way in and out. This factor does not have a θ dependence as long as the samples are not thin (the sample should be > 3 times thicker than the attenuation length of the X-rays). In other words, the contribution by the absorption factor to the intensity of different peaks is constant. The ‘structure factor’ directly affects the intensity of specific peaks as a direct result of the structure. The remaining factors, the ‘multiplicity’, which accounts for all the planes that belong to the same family because they are symmetrically related, and the ‘Lorentz-Polarization’ factor, which comes from the geometry of the XRD experiment, also affect the relative intensity of the peaks but they are not specific to a material and can easily be accounted for with analytical expressions (i.e. XRD analysis software can remove them with analytical functions).

Figure 3: Three diffraction ray paths, of which rays 11′ and 22′ satisfy the Bragg condition, while ray 33′ results from scattering by an atom (red circle) at an arbitrary position.

As the only factor that carries the unique structural contribution of a material to the relative intensities of XRD peaks, the structure factor is very important and requires a closer look. In Figure 2, let us assume that the 1^st order Bragg diffraction condition (remember, that this corresponds to n=1) is satisfied between ray_11′ and ray_22′ which are scattered on two atomic planes in the h00 direction (using the Miller indices notation described earlier) separated by a distance d. Under this condition, the difference in path length between ray_11′ and ray_22′ is δ_{(22′-11′)} = SA + AR = λ. The phase shift between the diffracted rays 1 and 2 is, therefore, Φ_22′-11′ = (δ_{(22′-11′)}/λ) 2π = 2π (assuming a cubic symmetry and, therefore, d = a/h in the h00 direction].

With a few steps in analytical geometry, it can be shown that the phase shift, Φ_{(33′-11′)}, with ray 3 diffracted by an arbitrary plane of atoms that are spaced an arbitrary distance x, is given by: Φ_{(33′-11′)} = 2πhu, where u=x/a (a is the unit cell parameter in the (h00) direction.) Taking the two other orthogonal directions, (0k0) and (00l), and v=y/a and w=z/a as fractional coordinates in the y- and z-directions, the expression for the phase shift extends to Φ = 2π(hu+kv+lw). Now, the X-ray wave scattered by the j-th atom in a unit cell will have a scattering amplitude of f_j and a phase of Φ_j, such that the function describing it is . The structure factor we seek, therefore, is the sum of all the scattering functions due to all the unique atoms in a unit cell. This structure factor, F, is given as:

  [9]

and the intensity factor contributed by the structure factor is I = F².

Based on the positions (u,v,w) of atoms on particular planes (h,k,l), there is the possibility of interference between scattered waves that is constructive, destructive, or in-between, and this interference directly affects the amplitude of the XRD peaks representing the (hkl) planes.

Now, a plot of intensity, I, versus 2θ is what is measured in an XRD experiment. The determination of the of crystal type and the associated unit cell parameters (a, b, c, α, β, and γ) can be arrived at analytically by observing systematic presence/absence of peaks, using the equations 2-9, comparing values against databases, using deduction and a process of elimination. Nowadays, this is process is fairly automated by a variety of software linked to crystal structure databases.

PROCEDURE

The following procedure applies to a specific XRD instrument and its associated software, and there may be some variations when other instruments are used.

1. We will examine a Ni powder sample on a Panalytical Alpha-1 XRD instrument.
2. First, choose the mask to fix the beam size according to your sample diameter. The beam must not have a footprint larger than the sample at the smallest θ value (typically ~ 7⁰-10⁰). For a sample of width ε, the beam size should be < ε sinθ.
3. Load the sample in the sample spinner stage and lock the sample into position. The sample spinner helps to spatially randomize the exposure of the sample to the X-ray source.
4. Choose the angle range for your XRD scan. For example 15-90 degrees is a typical range.
5. Choose a step size, i.e. the increment in 2θ, and integration (counting) time. Generally a 0.05 degree step size and 4 seconds integration is the default for a wide angle scan.
6. Once all the peak positions are determined through this initial scan, subsequent scans can focus on a narrower scan range around specific peaks using a smaller step size in angle if higher resolution data from those peaks are desired.

RESULTS

In Figure 4 we see the XRD peaks for the Ni powder sample. Note that the peaks that are observed (e.g. {111}, {200}) are for those that have either all even or all odd combinations of h, k, and l. Ni is face-centered cubic (FCC), and in all FCC structures, the peaks corresponding to {hkl} planes where h, k, and l are mixtures of even and odd integers, are absent due to the destructive interference of the scattered X-rays. Peaks corresponding to planes, such as {210} and {211} are missing. This phenomenon is called the systematic presence and absence rules, and they provide an analytical tool for assessing the crystal structure of the sample.

Figure 4: An XRD scan of Ni with a face-centered cubic structure is shown.

APPLICATIONS AND SUMMARY

This is a demonstration of a standard XRD experiment. The material examined in this experiment was in a powder form, but XRD works equally well with solid piece of material as long as the sample has a flat surface that can be set parallel to the plane of the sample stage.

XRD is a fairly ubiquitous method for determining the presence (or absence) of crystallographic order in materials. Beyond the standard application of determining the crystal structure, XRD is often used to obtain a variety of other structural information such as:

1. Whether or not the structure of a material is amorphous (characterized by a broad hump in the diffraction intensity and a lack of discernable crystallographic peaks),
2. Whether the sample is a composite material consisting of multiple crystallographic phases and, if so, determine the fraction of each phase,
3. Determining whether a material is an amorphous/crystalline composite
4. Determining the grain/particle size of the material,
5. Determining the degree of texture (preferred orientation of grains) in material

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X-Ray photoelectron spectroscopy (XPS), also known as electron spectroscopy for chemical analysis (ESCA) is a non-destructive technique used to analyze the surface of a material. The XPS will measure the elemental composition, chemical state as well as the electronic state, thickness measurements of overlayers (up to 8nm), and will give you the empirical formula of the material that is being analyzed. This instrument will only detect elements with an atomic number higher of 3 and higher since hydrogen and helium atoms are very small and the probability of detecting them is almost zero. Also, it can only analyze depths ranging from 1 to 10nm, for this reason it only gives analysis of the surface. Preparation of the samples is minimal if any; you can analyze samples “as receive” or can clean the surface to eliminate any contaminates that might be present. Some examples that can be analyzed using the XPS are elements, metal alloys, semiconductors polymers, ceramics, and inorganic compounds. Other examples include paints, inks, viscous oils, wood and papers.

Physics of XPS

The XPS functions by irradiating a surface with a beam of x-rays which are usually monochromatic Al Ka (1486.6eV) or non-monochromatic Mg Ka (1253.6eV) in an ultra-high vacuum. When the x-ray photons hit the sample, they transfer this energy to core electrons and are emitted from the initial state with a kinetic energy which is being measured (Figure 1). It will also count the number of photoelectrons that are being ejected from the surface with the cylindrical mirror detector analyzer. With this information you can obtain an XPS spectrum which plots the number of electrons detected vs. the binding energy of the electrons detected (Figure 2). Since each element will produce a characteristic peak at characteristic binding energies, the element at the surface can be identified and because the number of electrons in each peak is directly related to the amount of the element, the elemental composition within the area that is being analyzed can be calculated. There are tables with the kinetic energies as well as binding energies already in the system that will help identify the elements present in the surface of the material. 
The binding energy of each emitted electron can be calculated using the equation below since the energy of the x-rays being emitted is known. 
E_binding = E_photon– (E_kinetic + F)
E_binding is the binding energy of the electron, E_photon is the energy of the x-ray photons, E_kinetic is the kinetic energy that is measured by the XPS, and F is the work function of the spectrometer. 
Figure 1. XPS, sample is being irradiated by x-rays which will then emit core electrons which are then detected and data is collected to obtain a spectrum. 

References

• X-Ray Photoelectron Spectroscopy, In National Physical Laboratory, Retrieved October 29, 2012 form http://www.npl.co.uk/science-technology/surface-and-nanoanalysis/surface-and-nanoanalysis-basics/introduction-to-xps-x-ray-photoelectron-spectroscopy
• XPS Works, Actinide Research Quarterly, Retrieved October 29, 2012 form http://arq.lanl.gov/source/orgs/nmt/nmtdo/AQarchive/04summer/XPS.html
• X-Ray Photoelectron Spectroscopy, In Wikipedia, Retrieved October 29, 2012 from http://en.wikipedia.org/wiki/X-ray_photoelectron_spectroscopy
  Torres, D., X-Ray Photoelectron Spectroscopy (XPS),The University of Texas at El Paso, Retrieved October 29, 2012 
  

Example Of XPS

XPS depth profiling study on the passive oxide film of carbon steel in saturated calcium hydroxide solution and the effect of the chloride on the film properties

By: P.Ghods, O.B. Isgor, J.R. Brown, F. Benseabaa, D. Kingston

Introduction

The purpose of the paper presented was to use XPS in order to characterize the passive oxide layer that forms on carbon steel rebar in concrete pore solutions when it is passivated in calcium hydroxide solutions. Since there is very few information on the compositional characteristics of the passive oxide film before and after it has been exposed to this high alkaline environments, they decided to use XPS since it will give the depth profiling of the surface.

Preparation of Specimens

An analysis was conducted on the cross-sections of four carbon steel rebar specimens, which were 8-mm long each. The size designation for the rebar was #10M. The specimens where then hot-mounted and polished to 0.05µm and used isopropyl alcohol in order to prevent oxidation. The epoxy was then removed and three samples were submerged into saturate calcium hydroxide (CH) solution (99.6% CH in distilled water). The first sample (CH-2) was taken out after 2 days and the second one, CH-9, after 9 days. The third sample (CH-Cl) after 9 days, was then submerged in to a 0.05M chloride solution for 14 more days. This was done in order for the chlorides to react with the passivation film. The three specimens after they were taken out of the solution were placed in a jar containing isopropyl alcohol until the use of XPS was needed. The final specimen, AE, was exposed to indoor air at room temperature for 10 minutes to allow oxidation of the steel surface.

XPS Procedures

In this experiment, they used a PerkinElmer PHI-5700-2 XPS spectrometer that used an achromatic Al Ka x-ray source. It contained an electronic ultra-high vacuum chamber with pressure of 10-6 Pa and was operated at 15kV. The work function was calibrated using ultra-pure gold metal. The information was obtained by using a spherical capacitor analyzer, which was at an angle of 54? with the x-ray source, and the x-ray source was at an angle of 90? with the specimen surface. The analyzed area was 800µm.
In order to collect low-energy spectra, they did a survey scan which had the following conditions: energy range=1400eV, analyzer pass energy= 187.8eV, step size= 0.25 and a sweep time of 180s. In order to obtain high-resolution spectra, they used 10 or 20eV spectral windows at an analyzer pass energy of 29.3eV and 0.1eV steps. The spectra was for oxygen (O 1s), carbon (C1s), iron (Fe 2p), chlorine (Cl 2P), calcium (Ca 2p), and sodium (Na 1s). They collected and processed all survey and high-resolution spectra using PHI Access XPS operating software.

XPS Data Analysis

To figure out the sampling depth (d) which is the thickness of the layer, they used the equation below,
d= 3?cos?
where ? is the decreasing length and ? is the take -off angle with respect to the surface normal, which would be zero for this case. To find the kinetic energy the equation below was used,
Ek=hv- Eb
Where Ek is the kinetic energy, h is Planck’s constant, v is frequency, and Eb is the binding energy. Table 2 below shows the calculation of the sampling depth for iron oxide. The average sampling depth was of 8.5nm. 

Curve fitting had to be done to the high-resolution spectra in order to get the minimum number of peaks that will result in an optimum fit. This was done using Casa XPS software and setting a few constraints in order to get the optimal fitting. Constrains included, setting peak positions to the average reported data in literature, peak positions were set constant for all depths, the full width at half maximum (FHWM) were set to the FHWM of the photoelectron core level of each element, Sheirley background corrections algorithms were used, peaks were calibrated to hydrocarbon signal set at 285eV, and semi-quantitative composition data was collected by using XPS elemental sensitivity factors. The curves that were fitted were for Fe 2p, O 1s, C 1s, and Ca 2p spectra. The curve parameters used are shown below in Table 3.

Results and Discussions

The XPS depth profiles for all four elements and for the four specimens analyzed are shown in Fig. 5 below. The graph for iron shows that as depth increases, so does the concentration, as for the oxygen curve, there will be an increase in concentration and around 2.5nm in depth it will decrease. In the carbon curves, the concentration is high at the surface which is most likely due to contamination during preparation, but then remains constant throughout the rest of the analysis. For the calcium curves, most of the samples had a constant concentration as the depth increased except for the sample which was only exposed to air which did not contain large amounts of calcium. The reason for small amounts of calcium present in the AE specimen was because there were particles embedded on the surface during polishing. As for the constant concentrations of calcium in the rest of the sample, SEM and EDS was used and showed that it was due to CH and CaCl precipitates at the surface. It was concluded that because the precipitates contained the same elements (C,O, Ca) that were analyzed by the XPS, their spectra would not be used to study the atomic structure of the oxide film. Only the Fe 2p spectrum would be used to characterize the oxide film.

Analyzing the Fe 2p spectra at different depths for the CH-2 sample, a few observations were made. First, the five components were identified to be, iron (Fe), cementite (Fe3C), magnetite (Fe3O4), hematite/ferrihydrite (Fe2O3/ FeOOH), and Fe2O3 satellite structure; their peak position were also identified as seen in the image (Fig.8). Another observation made was that the Fe peak increased in intensity with ion sputtering which means that the Fe component comes from the substrate. Also, the sputtering shifted the Fe 2P signal to the left which indicates that the oxide film is thin no matter what the exposure time was. 
The effect of exposure conditions on the thickness of the oxide film was also analyzed. Results showed that the AE specimen had a thicker iron oxide layer than the other samples and that the CH-Cl spectrum was the one with the thinnest oxide layers (See spectra below). The reason for the AE sample having a thicker layer can be due to porosity and also because the oxide layer of the CH specimens might have dissolved in the solution. The conclusion made for the CH-Cl curve was that chloride reduces the thickness of the oxide film. It was also concluded that since the spectrum for the different exposure times were almost the same, the exposure time does not affect the thickness as much. The ratio of the iron oxide to the metallic iron concentration at different sputtering depth was analyzed and results showed that above a sputtering depth of 5nm, the ratio remained constant. This meant that the iron oxide film was about 5nm in thickness. To confirm this, they used several equations and the thickness of the oxide layers to be 5.7, 4.1, 4.1, 3.6nm for AE, CH-2, CH-9, CH-Cl respectively. Other observations made where that the concentration of Fe3+ relative to Fe2+ decreased with depth in the oxide film and that longer exposure times will increase the concentration of Fe2+ relative to Fe3+.

Conclusion

In this experiment, they used the XPS depth profiling in order to characterize the oxide film of carbon steel when it was saturated in calcium hydroxide (CH) solutions and also what the effect of chloride (CH-Cl) could be on the film. Samples where carefully prepared and placed in CH and CH-Cl solutions for different amounts of time. Then they were analyzed using the XPS. 
After obtaining the spectra of the specimens studied and analyzing them, they were able to make valuable conclusions. The first finding was that the carbon steel contained precipitates of calcium hydroxide and calcium carbonate so several spectra were not used for analysis. The study was only done for the Fe 2p spectrum. With the XPS depth profiles, they were able to determine the thickness of the iron oxide film to be about 4nm. The spectra for the four different specimens studies also showed that there was almost no difference between them meaning that there was no effect on exposure time to the CH solutions. Analyzing the spectra also showed that the exposure to chloride reduced the thickness of the oxide film. Another conclusion made was that there were higher concentrations of Fe2+ at the substrate and at the surface it was mostly composite of Fe3+. The longer the specimens were exposed to the CH solution, the larger the Fe2+ concentration. As seen with this experiment, the XPS is a valuable instrument that can tell us a lot about a material.

References

• Mark C. Biesinger, Brian R. Hart, Russell Polack, Brad A. Kobe, Roger St.C. Smart, Analysis of mineral surface chemistry in flotation separation using imaging XPS, Minerals Engineering, Volume 20, Issue 2, February 2007, Pages 152-162, ISSN 0892-6875, 10.1016/j.mineng.2006.08.006.
  (http://www.sciencedirect.com/science/article/pii/S0892687506002093)