Scattering of monochromatic X-rays at different incident radiation angles provides quantitative information on physical and chemical properties of plastics. (February 2021)

• Record Type: Journal Article
• Authors: Aidene, Soraya; Semenov, Valentin; Kirsanov, Denis; Kirsanov, Dmitry; Panchuk, Vitaly
• Is Part Of: Measurement. Volume 172(2021)
• Publication Date: 2021-02
• Subjects: X-ray fluorescence spectroscopy -- X-ray scattering -- Multivariate regression -- Plastics; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2020.108888
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: X-Ray scattered radiation and machine learning for plastic material characterization. Quantification of carbon, hydrogen and physical properties. Impact of measuring conditions on the results. Broadening the scope of XRF analysis in standard measurements. Abstract: X-ray fluorescence spectroscopy (XRF) is a powerful tool of elemental analysis; however in most of the experimental set-ups it does not allow quantification of the light elements (with atomic number below 11). The use of scattering X-ray radiation as a source of useful analytical information is getting more and more popular in X-ray studies. The common trend in this field is in using the standard XRF instrumentation, where polychromatic incident X-ray radiation and fixed geometry are employed. In this study we explore the opportunity of obtaining valuable physical and chemical information on plastic samples using monochromatic radiation and varying incident radiation angles. The use of machine learning techniques for multivariate regression modeling of scattering radiation spectra allows quantification of certain physical and chemical properties in commercial plastic samples which are normally not available from standard XRF measurements.