Investigation of ZnGeP2 crystals by Raman spectroscopy and machine learning

A. I. Knyazkova; D. A. Vrazhnov; Y. V. Kistenev; O. A. Romanovskii

doi:10.1117/12.2692886

17 October 2023 Investigation of ZnGeP2 crystals by Raman spectroscopy and machine learning

A. I. Knyazkova, D. A. Vrazhnov, Y. V. Kistenev, O. A. Romanovskii

Proceedings Volume 12780, 29th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 127801I (2023) https://doi.org/10.1117/12.2692886
Event: XXIX International Symposium "Atmospheric and Ocean Optics, Atmospheric Physics", 2023, Moscow, Russian Federation

Abstract

ZnGeP2 crystals with different thermal spraying of the chemical elements on the crystal surface studied in this work. The Raman spectra of the crystals were obtained using the inVia Reflex system with an excitation wavelength of 785 nm. Good separation between ZnGeP2 and Ca/Mg samples by first principal component points to the significant differences in corresponding Raman spectral features. Proposed machine learning pipeline include principal component analysis and support vector machine with non-linear radial based function kernel. High area under curve values also reflects good pairwise separability of the samples.

Citation Download Citation

A. I. Knyazkova, D. A. Vrazhnov, Y. V. Kistenev, and O. A. Romanovskii "Investigation of ZnGeP2 crystals by Raman spectroscopy and machine learning", Proc. SPIE 12780, 29th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 127801I (17 October 2023); https://doi.org/10.1117/12.2692886

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