Self-consistent absorption correction for quantifying very noisy X-ray maps: group III nitride nanowires as an...

Energy-dispersive X-ray mapping in a scanning transmission electron microscope is a method to visualize the spatial distribution of chemical elements in a sample. Quantification of the signal intensities depends on proper background elimination and correction of the self-absorption and fluorescence of X-ray lines in the sample. The latter become particularly relevant for slightly thicker and rough samples, small take-off angles and low-energetic X-ray lines, for which we have recently introduced a self-consistent absorption correction based on effective k*-factors selected automatically from curves simulated as function of a K/L line intensity ratio of one of the heavier elements in the sample for ranges of different compositions. This has been shown to work well for thick and for rough samples. Correcting the background intensity to sub-pixel accuracy is necessary for reliable quantification of very noisy maps. In this study, we show how this self-consistent absorption correction method can be applied to InGaN and AlGaN layers in GaN nanowires, the net maps of which can be so noisy the layers can hardly be seen by the eye (a few counts per pixel) and the background is below a single count in each spectrum channel. The result indicates that background estimation for the Ga L-line intensity using fractional counts from an interpolation of maps from neighbouring X-ray lines of elements that are not actually present in the specimen is critical for quantification. The nanowires studied were between 66 and 375 nm thick.

Energy-dispersive X-ray mapping in a scanning transmission electron microscope is a method to visualize the spatial distribution of chemical elements in a sample. Quantification of the signal intensities depends on proper background elimination and correction of the self-absorption of X-ray lines in the sample. Here we show that our previously developed method of self-consistent effective absorption factors works well even with extremely noise elemental maps of a few net counts only where the human eye can hardly discern any pattern and the background signal is typically less than a single count in each spectrum channel. Correcting the background intensity to sub-pixel accuracy is then necessary for reliable quantification.