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2023
DOI: 10.1088/1402-4896/ad0186
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Possibility of using machine learning methods to reconstruct solid body parameters during laser-induced desorption analysis

A A Stepanenko,
D A Kashin,
Yu M Gasparyan

Abstract: The possibility of using machine learning methods for solving the inverse problem of the laser-induced desorption quadrupole mass-spectrometry (LID-QMS) diagnostic is studied. The formulation of the problem is given, and a general scheme of its solution is proposed. A test model of gas transport in a solid body is considered, which is used to construct a database of gas transport parameters in the sample. The application of the synthetic data and machine learning methods, viz. the interpolation technique, the … Show more

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Cited by 3 publications
(2 citation statements)
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“…To verify our numerical code, we performed a comparative run against the recently reported test TMAP7 data [85]. For the simulation, we used the one-dimensional model of tritium desorption.…”
Section: Appendix D Verification Of the Numerical Codementioning
confidence: 99%
See 1 more Smart Citation
“…To verify our numerical code, we performed a comparative run against the recently reported test TMAP7 data [85]. For the simulation, we used the one-dimensional model of tritium desorption.…”
Section: Appendix D Verification Of the Numerical Codementioning
confidence: 99%
“…To describe the tritium transport, equations (42), (43) were used. In accordance with [85], the particle trapping rate, E kT exp The spatial derivatives were discretized with the fourth-order central scheme. The numerical grid had 400 nodes.…”
Section: Appendix D Verification Of the Numerical Codementioning
confidence: 99%