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

被引：0

作者：

Vakhrushev, A. A. ^{[1
,2
]}

Matveev, A. V. ^{[2
]}

Nartova, A. V. ^{[1
,2
]}

机构：

[1] Russian Acad Sci, Boreskov Inst Catalysis, Fed Res Ctr, Siberian Branch, Novosibirsk 630090, Russia

[2] Novosibirsk State Univ, Novosibirsk 630090, Russia

来源：

KINETICS AND CATALYSIS | 2024年 / 65卷 / 06期

基金：

俄罗斯科学基金会;

关键词：

deep machine learning; XPS; automatic spectral analysis; convolutional neural network; heterogeneous catalysts; MASS-SPECTROMETRY; XPS;

D O I：

10.1134/S0023158424602687

中图分类号：

O64 [物理化学（理论化学）、化学物理学];

学科分类号：

070304 ; 081704 ;

摘要：

AbstractA 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).

引用

页码：788 / 796

页数：9

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