Atomic spectrometry update: review of advances in X-ray fluorescence spectrometry and its special applications

Abstract

A highlight this year was the construction of elemental maps of microalgae cells at the organelle level using XRF-CT with a beam size of just 15 nm. These probably represent the highest ever spatial resolution achieved for XRF-CT images. An innovative approach for reconstruction algorithms used a deep convolutional neural network to correct for the self-absorption effects in the XRF-CT sinogram domain. Such corrections will enable the use of conventional tomographic reconstruction algorithms for XRF-CT analysis. A remarkable advantage of the proposed method was that it could correct for self-absorption effects without any prior knowledge of the scanning setups. A particularly innovative dual-energy X-ray-beam ptycho-fluorescence imaging method combined XRF spectrometry and X-ray ptychography scanning with simultaneous data-collection. To overcome the incompatibility of the different excitation and scanning conditions required for fast ptychography and high spatial resolution XRF spectrometry, two coaxial beams of different sizes were used on the sample simultaneously. In comparison to sequential scans, this combined approach has the potential to reduce the data collection time by a factor of 25. The very good performance of laboratory 2D-XRF spectrometry for the analysis of minute amounts of radioactive material has made it a potential alternative to TXRF spectrometry. Reconstruction algorithms are now capable of significantly enhancing imaging resolution in μXRF spectrometry. The forensic classification of incredibly small amounts of samples such as single fibres was accomplished using elemental profiles determined by TXRF spectrometry. Although characterisation of the low-Z matrix in milk and polymers by conventional TXRF spectrometry is challenging, it was successfully achieved by studying the Compton and Rayleigh scatter with both univariate and multivariate approaches. Portable XRF spectrometry is a well-established technique for a wide range of applications. Emphasis continues to be placed on improving calibration and reducing matrix and inter-element effects. The sample type remains a challenge for portable XRF analysis. Computer vision and statistical methods such as spectral angle mapper are being increasingly applied to maximise the information that can be extracted from the data. For example, an innovative approach exploited the elemental features from XRF spectra to improve the interpretation of molecular information provided by reflectance spectroscopy, and vice versa.