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Application of a Convolutional Neural Network for Automated Analysis of X-ray Photoelectron Spectra of Heterogeneous Catalysts Научная публикация

Журнал Kinetics and Catalysis
ISSN: 0023-1584 , E-ISSN: 1608-3210
Вых. Данные Год: 2024, Том: 65, Номер: 6, Страницы: 788–796 Страниц : 9 DOI: 10.1134/S0023158424602687
Ключевые слова deep machine learning, XPS, automatic spectral analysis, convolutional neural network, heterogeneous catalysts
Авторы Vakhrushev A.A. 1,2 , Matveev A.V. 2 , Nartova A.V. 1,2
Организации
1 Federal Research Center, Boreskov Institute of Catalysis, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090 Russia
2 Novosibirsk State University, Novosibirsk, 630090 Russia

Информация о финансировании (1)

1 Российский научный фонд 24-63-00037

Реферат: A convolutional neural network was used to solve the problem of segmentation of XPS spectra. The developed combination of recognition using a machine learning model and a post-processing algorithm provided fast automatic analysis of XPS data. The results of determining the positions and areas of peaks were in good agreement with both the results of manual analysis and handbook values. The proposed approach was applied to analyze the XPS spectra of heterogeneous catalysts (Pd/Al2O3 and Sr2TiO4) and chemical compounds used in the preparation of catalysts (AgCl and TiO2).
Библиографическая ссылка: Vakhrushev A.A. , Matveev A.V. , Nartova A.V.
Application of a Convolutional Neural Network for Automated Analysis of X-ray Photoelectron Spectra of Heterogeneous Catalysts
Kinetics and Catalysis. 2024. V.65. N6. P.788–796. DOI: 10.1134/S0023158424602687 WOS Scopus РИНЦ CAPlus OpenAlex
Даты:
Поступила в редакцию: 6 окт. 2024 г.
Опубликована в печати: 1 дек. 2024 г.
Принята к публикации: 3 дек. 2024 г.
Идентификаторы БД:
Web of science: WOS:001432561900008
Scopus: 2-s2.0-85218443581
РИНЦ: 80381333
Chemical Abstracts: 2025:474202
OpenAlex: W4407893965
Цитирование в БД: Пока нет цитирований
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