One of the most popular and straightforward methods for non-destructive multi-element material analysis is X-ray fluorescence (XRF) spectroscopy. In the last few years, the method has advanced remarkably and shown to be helpful in several disciplines, including geology, environment, materials science, and archaeology. The technique has proven successful in industry in addition to research applications, particularly in preserving the purity of ultra-pure grade chemicals, reagents, and products. These practical applications of XRF provide a wealth of knowledge and understanding for scientists and industrial users. Due to recent developments in science and technology, we decided to compile this section as a resource that provides sufficient information for scientists and industrial users to design and set up modern XRF experiments for use in a wide range of practical applications. This compilation aims to keep you updated and aware of the latest advancements in XRF. We have also briefly discussed the application of machine learning and artificial intelligence which has the potential to expand the capabilities of XRF analysis.

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X-Ray Fluorescence Spectroscopy: Introduction, Latest Developments and Applications

  • Neslihan Ekinci,
  • Ahmet Furkan Ekinci,
  • Yasser Rammah,
  • Neha Sharma,
  • Vivek K. Singh

摘要

One of the most popular and straightforward methods for non-destructive multi-element material analysis is X-ray fluorescence (XRF) spectroscopy. In the last few years, the method has advanced remarkably and shown to be helpful in several disciplines, including geology, environment, materials science, and archaeology. The technique has proven successful in industry in addition to research applications, particularly in preserving the purity of ultra-pure grade chemicals, reagents, and products. These practical applications of XRF provide a wealth of knowledge and understanding for scientists and industrial users. Due to recent developments in science and technology, we decided to compile this section as a resource that provides sufficient information for scientists and industrial users to design and set up modern XRF experiments for use in a wide range of practical applications. This compilation aims to keep you updated and aware of the latest advancements in XRF. We have also briefly discussed the application of machine learning and artificial intelligence which has the potential to expand the capabilities of XRF analysis.