XPS Image Acquisition in Minutes Using SnapMap

Thermo Scientific™ K-Alpha™ and Nexsa™ XPS systems are integrated with SnapMap technology that provides the surface analyst the ability to create high resolution, large area, XPS images within minutes. In order to realize this, the sample stage is shifted through the stationary X-ray beam so that the X-ray spot is effectively rastered across the chosen area of the sample surface. The stage movement is synchronized with the high performance spectrometer which continuously gathers snapshot XPS spectra during rastering. This process results in the production of a high resolution XPS image of the sample surface with each pixel point representing an individual snapshot XPS spectrum. Contrary to scanning the X-ray beam, the stage raster method maintains the analysis area constant during the analysis, making sure that all areas of the image have the same definition.

SnapMap in operation.

Figure 1. SnapMap in operation.

The Avantage software, supplied with all Thermo Fisher Scientific XPS instruments, provides many options in the processing of SnapMap data. Positional data can be extracted from the image to identify areas of interest or key features and defined as analysis points. It is also possible to interrogate or average the spectra from individual pixel points for chemical information. In addition, mathematical processes such as TFA (target factor analysis), PCA (principal component analysis), and NLSF (non-linear least squares fitting) can be used to manipulate the image to extract important spectral information from the images.

Using SnapMap

An extraordinarily useful tool in the arsenal of surface analyst is the SnapMap rapid image acquisition feature, which is common to both K-Alpha and Nexsa XPS instruments. The feature is easily integrated into a usual analytical workflow with minimal cost in experimental time, and that is far outweighed by the benefits offered by the technique.

In most cases, the patented reflex optics of the K-Alpha and Nexsa manage the definition of the area under investigation, but despite this it is challenging to locate sample features that are difficult to see optically. Fortunately, this problem can be solved by the SnapMap technology. Attaining a SnapMap of an element specific to the feature, or using a mid-range peak such as 01s for an unknown sample, will enable the user to identify its position. By using SnapMap, features as small as 10 μm can be easily identified.

The only restriction to the resolution of SnapMap images is the size of the X-ray spot used to produce the map. This means that the 10 μm X-ray spot of Nexsa provides superior image resolution without any loss of image clarity over large areas of the sample surface. This is represented in Figure 2.

SnapMap XPS images

Figure 2. SnapMap XPS images of varied image size of an Au grid deposited onto a Si wafer.

The Avantage software offers users the freedom to describe the position of experiments from imaging data or using the reflex optics. This implies that the location where specific features are present in SnapMap images can be directly fed back into the Avantage experiment tree as an analysis position.

As shown by Figure 3, assigning points for analysis using SnapMap data helps the user to guarantee ultimate sample alignment and also helps in the selection of X-ray spot size depending on the feature size. This means that the analyst can be sure that XPS signal is sampled from the selected feature only. In addition, the micro-focused X-ray spot of the Nexsa system enables features as small as 10 μm to be detected and analyzed by XPS in isolation. This can include the acquisition of high resolution XPS spectra or survey scans, XPS depth profiling using the Thermo Scientific™ MAGCIS™ ion source, or by additional processing of the SnapMap data.

Experimental work flow using SnapMap.

Figure 3. Experimental work flow using SnapMap.

Processing SnapMap Data

Each pixel point in a SnapMap image represents a spectrum in the sense that the data can be processed in the same manner as traditional XPS spectra. In addition, various mathematical data processing options such as PCA, TFA, and NLSF are provided by Avantage, These options can all be used to extract useful information from SnapMap datasets and enhance the quality of the final image. Multiple elemental SnapMaps enables the user to deduce positional information about specific features of sample surface areas with a very high accuracy. Shown in Figure 4 is the SnapMap processing available in Avantage.

In the example, PCA is employed on raw SnapMap data in order to extract the common peak shapes detected in the spectra at each pixel of three SnapMaps. The software automatically re-plots the SnapMaps to demonstrate the relative intensity of the common peak shapes, or principal components by position. It is possible to display these processed SnapMaps simultaneously in an image overlay plot offering relative intensities of each of the different elements present in the sample by position.

Summary

Incorporating SnapMap rapid imaging to the experimental workflow can help the surface analyst in the identification and ultimate experimental alignment of specific or even optically invisible features on the surface of a sample. Using the rapidly acquired SnapMap as a starting point, features as small as 10 μm in diameter can be picked out and analyzed rapidly and efficiently using the Nexsa system.

Three different elemental SnapMaps of an “α”

Figure 4. Three different elemental SnapMaps of an “α” printed on a Ti substrate processed using PCA and an overlay of the images.

In addition to being an alignment tool, SnapMap images contain XPS snapshot spectra at each pixel point and thus can be processed and analyzed using many of the same methods applied to traditional XPS spectra. By integrating the data processing options of Avantage with the micro-focused X-ray spot of the Nexsa system, the user gains the ability to create high resolution XPS images of large areas of a samples surface within minutes.

This information has been sourced, reviewed and adapted from materials provided by Thermo Fisher Scientific – Materials & Structural Analysis.

For more information on this source, please visit Thermo Fisher Scientific – Materials & Structural Analysis.

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