Investigation of the Laser Radiation Focusing Effect on the Sensitivity of Analysis of the Hydrogen Isotope Content in Plasma-Deposited Layers by Laser-Induced Desorption

Krat, S.; Kharina, A. P.; Sorokin, I. A.; Kostyushin, V. A.; Vovchenko, E. D.; Kurnaev, V.А.

doi:10.1134/s1063778820110058

Cited by 3 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…the necessity to check the conditions of thermodynamic equilibrium and plume opacity, and require only the registration of the particle flow, released from the target. The main difficulty of the LID-QMS technique lies in the rather limited amount of diagnostic data: the desorption flux time signals [23,29,30] and/or the total amount of hydrogen desorbed in one laser pulse [21,31,32]. Such a constraint, coupled with a large number of parameters characterizing the process of gas desorption from a solid (the presence of traps of various types with different concentrations and binding energies, the presence of energy barriers for hydrogen transport in the volume and on the surface of the material, the presence of oxidized layers, etc.…”

Section: Introductionmentioning

confidence: 99%

Possibility of using machine learning methods to reconstruct solid body parameters during laser-induced desorption analysis

Stepanenko,

Kashin,

Gasparyan

2023

Phys. Scr.

View full text Add to dashboard Cite

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 method of K nearest neighbors, and the neural networks, for solving the LID-QMS inverse problem is investigated. The advantages and disadvantages of each approach are discussed.

show abstract