Processing Spectra

Calculating Lineshape from Data

Angle Resolved XPS Data and Peak Models

Angle Resolved XPS (ARXPS) performed using a combination of lens optics and tilting the sample with respect to the axis for the analyser yield a wealth of data from the same sample. These data are used to illustrate charge correction via range calibration and further refined using calibration based on a component peak. Once energy calibrated these data are processed to form a data set where data bins in each spectrum are equivalent in a vector sense. These vectors are processed using Principal Component Analysis and Vector Manipulation to extract peak models for SiO2, Si2O3 and elemental Si which illustrate the nature of the native oxide layer on a silicon wafer. Once obtained the peak model is propagated to spectra over a range of angles.

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            Auger Peaks and Determination of Chemical State

Cu oxide sputtered using an argon ion gun creates from a nominally Cu 2+ material a range of sub-oxide and metallic copper within the same sample. A linescan of measurements is performed by stepping the stage position before acquiring a sequence of spectra to include Cu 2p, Cu 3p, Cu Auger and valance band spectra. These stage positions move from a predominantly Cu (0) location to a predominantly Cu 2+ location via a sequence of stage position increments which trace a path over the edge of the sputtered zone with the Cu 2+ material. These data are analysed using calculated lineshapes for Auger spectra corresponding to Cu (0), ion beam induced Cu sub-oxide and original Cu 2+ material. The analysis involves merging spectra to form irregular spaced energy spectra, calculation of difference spectra, PCA as a means of understanding tends within the data set and also PCA as a noise reduction tool.

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Background Subtracted Data

            Exporting ASCII form of Background Subtracted Data

A peak model prepared for an S 2p doublet complete with loss peaks associated with WS2 2D material is exported to a spreadsheet program. The exported data appear as columns of ASCII values corresponding to the background subtracted data together with each component peak and synthetic envelope resulting from fitting the peak model to the S 2p spectrum. The example illustrates the process of creating background subtracted data, copying processed data to a new VAMAS block and extracting an energy interval as a separate VAMAS block from which the final form of the peak model is exported through the clipboard.

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Energy Calibration

Charge Correction and Why Charge Correction is Required in XPS

A series of measurements from an insulating powder is used to illustrate charge compensation during measurements and how charge correction is performed in CasaXPS. The energy scale is calibrated by using the binding energy for an O 1s peak to establish the binding energy scale for five measurements from the same material. An example of manually calibrating a measurement is illustrated within the video as well as a demonstration of how energy calibration can be performed automatically for a set of measurements.

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Binding Energy Calibration and the Influence of Charge Compensation on Spectra

Binding energy calibration and the implications of charge compensation for the shapes of photoemission peaks are examined using PVEE C 1s spectra.

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Range Calibration Option

A set of 10 measurements are simultaneously calibrated using the C 1s narrow scan spectrum from each measurement to calibrate other narrow scan spectra from the same measurement. The measured C 1s peak position is determined using an energy interval over which the maximum intensity identifies the un-calibrated binding energy for the as-measured spectra and an offset energy required to place the C 1s peak maximum at 285 eV is computed and applied en-masse to these 10 independent sets of spectra within a single VAMAS file.

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Energy Calibration based on Fermi Edge Position

A row of spectra are energy calibrated based on the position of a Fermi edge. A Step Down background type representing an approximation to a Fermi edge (in the form of a complementary error function) is automatically fitted to an edge in the valance band spectra of aluminium. The position for the Fermi edge, as measured by the intersection of two straight lines computed from the fitted Step Down background type, is extracted and used to estimate an energy offset required to locate the edge position at 0 eV. Spectra corresponding to the same measurement as the valance band spectrum as calibrated by applying the same offset as is required to calibrate the Fermi edge.

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Energy Calibration and Data Scaling using a Defined Peak Maximum Intensity

Energy calibration and data scaling is performed for a set of measurements where the energy offset and intensity scale factor for each measurement is calculated from a specified set of spectra, then applied to all spectra measured under the same conditions. The VAMAS file consists of a set of VAMAS blocks organised as rows of high resolution spectra measured under the same conditions. N 1s spectra from each measurement are used to calculate a binding energy calibration and also a scale factor. These two adjustments are applied to VAMAS blocks in the same rows of high resolution spectra collected as part of the same measurement as the N 1s data.

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Spectrum Calculator

Summing Spectra with Identical Acquisition Parameters

Data acquired in parallel saved as separate VAMAS blocks can be combined to form new VAMAS blocks by summing intensities on an acquisition channel by acquisition channel basis. The example illustrated in this video demonstrates two methods for summing columns of VAMAS blocks representing slices within a 2D detector corresponding to two photoemission peaks with an outcome of two VAMAS blocks for C 1s and Fe 2p spectra. Options on the Spectrum Processing dialog window Test Data property page are used to form these two new VAMAS blocks from hundreds of individual VAMAS blocks in the original data file. Profiling of the signal as a function of detector slice index is used to select a subset from the total set of VAMAS blocks.

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Summing Spectra using the Expression Calculator

A set of spectra are summed using the shortcut format sum vb<a> : vb<b> : inc to define the VAMAS blocks for which a sum is required.

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A data set containing nine acquisition regions split over more than 400 detector slices is used to illustrate how to energy calibrate four sets of spectra derived from this one measurement and then sum these energy calibrated spectra to obtain a smaller FWHM than is obtained by a direct sum based on raw acquisition data channels.

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Normalising Data for Export as ASCII Tables

Exported data in the form of ASCII tables is performed using the processed data. A normalised form of data can therefore be exported by first processing VAMAS block data using the Spectrum Processing Calculator Property Page, where spectral intensities can be adjusted with respect to a specific energy or at a peak maximum to ensure all data appear using a common intensity scaling factor.

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Normalising and Scaling Data

Normalised spectra are scaled using a common factor to convert a set of spectra with a range of intensities to VAMAS blocks with a common intensity range. These new VAMAS blocks contain spectra which permit a display of these data overlaid in a display tile and also in preparation for further manipulation via the Spectrum Processing Calculator Property Page. The example used illustrates how to divide a set of gold spectra by a reference spectrum representing the idealised gold spectrum from an XPS instrument. The resulting traces provide insight into the transmission characteristics for the instruments in questions.

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Principal Component Analysis

Gathering Spectra from Regions defined on VAMAS blocks within a VAMAS File

Survey spectra from graphene oxide (GO) and reduced graphene oxide (rGO) are used to illustrate how to extract signal between and including O 1s and C 1s photoemission peaks from the original survey data. After constructing a file containing only the part of these spectra corresponding to O 1s and C 1s, the resulting data are processed using PCA noise reduction to form a set of spectra with significantly improved signal to noise characteristics. The results of processing these signal enhanced spectra are presented as a peak model fitted to the set of survey spectra allowing a decomposition of the sample into proportions of GO and rGO.

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Image Calculator

Calculating an Image using Colour Scale Thresholds to Define an Expression

Auger and SEM images are used to illustrate how contrast within an image can be enhanced and adjusted in terms of display settings. Once an appropriate pair of threshold values is established, the image calculation is used to clip intensities above and below threshold to obtain an image consisting of pixel values within the threshold range previously prepared for visual inspection of an image.

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Managing VAMAS Blocks within a VAMAS File

VAMAS Block Order and Re-ordering VAMAS blocks

Data within a VAMAS file are organised using VAMAS blocks, where each VAMAS block maintains the context for data within the VAMAS block. When loaded into CasaXPS VAMAS blocks appear as an array of rectangles with Block Id strings used as labels. The order for these labelled rectangles is determined by the order for VAMAS blocks within the VAMAS file and the values assigned to VAMAS block fields. Rows of VAMAS blocks are ordered by the experimental variable value while columns of VAMAS blocks are determined by element/transition VAMAS block fields. These VAMAS block fields can be adjusted within CasaXPS as a means of reordering the arrangement of VAMAS blocks in the right-hand pane of CasaXPS.

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Linear Least Squares (LLS)

Linear Least Squares applied to Cerium Oxide I

A cerium oxide sample is measured by splitting the acquisition time over many VAMAS blocks for a set of narrow scan spectra. Expanding the data set, by recording rapid scans and saving each rapid narrow scan as a separate VAMAS block, results in 50 spectra per narrow scan region. Short dwell-times per acquisition bin produces many spectra with poor signal to noise, but taken as a whole and when summed to create a single spectrum per photoemission line, the signal-to-noise for these summed spectra is typical of measurements performed by XPS. PCA and LLS are used to overcome low counts per bin for these individual spectra leading to hybrid backgrounds calculated from LLS solutions as well as signal enhanced spectra for each Ce 3d VAMAS block in the experiment.

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Linear Least Squares applied to Cerium Oxide II

A cerium oxide sample is measured over an extended acquisition time by repeatedly measuring the same set of Ce 3d narrow scans using an acquisition time typical for obtaining reasonable signal to noise in a spectrum. The intension is to induce reduction from Ce 4+ to a lower oxidation state and by repeatedly measuring the same narrow scan spectrum have a history of the way these spectra evolve, and to make use of this evolution to calculate spectral shapes characteristic of Ce 4+ and Ce 3+ materials. The computed spectra for Ce 4+ and Ce 3+ are compared to spectra measured from standard materials. These computed Ce 3d spectral forms are then used within a LLS calculation to demonstrate the suitability of these calculated spectra for all spectra within the data set.

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