Computational Materials Science, volume 208, pages 111326
Ultimate sensitivity of radial distribution functions to architecture of PtCu bimetallic nanoparticles
Avakyan Leon A.
1
,
Tolchina D
1
,
Barkovski V
1
,
Belenov Sergey
2
,
Alekseenko A. A.
2
,
Shaginyan A
1
,
Srabionyan V. V.
1
,
Guterman V. E.
2
,
Bugaev L
1
Publication type: Journal Article
Publication date: 2022-06-01
Journal:
Computational Materials Science
Quartile SCImago
Q1
Quartile WOS
Q3
Impact factor: 3.3
ISSN: 09270256
General Chemistry
General Physics and Astronomy
General Materials Science
Mechanics of Materials
Computational Mathematics
General Computer Science
Abstract
Bimetallic nanoparticles containing platinum and another d-metal are highly perspective catalysts with stability and activity superior to a single-metal platinum materials. It is known that the improvement of catalytic properties depends both from the composition and from the structural arrangement of atoms in bimetallic nanoparticles. This leads to importance of the experimental determination of the nanoparticles architecture (random solid solution, Janus, core–shell or “gradient”) for the search of novel bimetallic systems. We considered the platinum–copper nanoparticles synthesized by simultaneous or multistage sequential depositions of metals. The insight of the architecture of bimetallic PtCu nanoparticles was obtained by the study of radial distribution functions (RDFs) of metal atoms. The RDFs were obtained both theoretically, using molecular dynamics simulations, and experimentally, from the analysis of the extended X-ray absorption fine structure (EXAFS) spectra at Pt L 3 - and Cu K- edges. Machine learning (ML) algorithms revealed the outstanding sensitivity of the theoretical RDFs to the architecture of the bimetallic nanoparticles: the correct architecture can be determined with 99 % confidence in terms of F1 score. The application of the variety of ML classification methods to the experimental RDFs showed the benefit K-Neighbors classification method.
Citations by journals
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Energies
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Energies
1 publication, 50%
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Biochar
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Biochar
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Citations by publishers
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Multidisciplinary Digital Publishing Institute (MDPI)
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Multidisciplinary Digital Publishing Institute (MDPI)
1 publication, 50%
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Springer Nature
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Springer Nature
1 publication, 50%
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1
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Avakyan L. A. et al. Ultimate sensitivity of radial distribution functions to architecture of PtCu bimetallic nanoparticles // Computational Materials Science. 2022. Vol. 208. p. 111326.
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Avakyan L. A., Tolchina D., Barkovski V., Belenov S., Alekseenko A. A., Shaginyan A., Srabionyan V. V., Guterman V. E., Bugaev L. Ultimate sensitivity of radial distribution functions to architecture of PtCu bimetallic nanoparticles // Computational Materials Science. 2022. Vol. 208. p. 111326.
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TY - JOUR
DO - 10.1016/j.commatsci.2022.111326
UR - https://doi.org/10.1016%2Fj.commatsci.2022.111326
TI - Ultimate sensitivity of radial distribution functions to architecture of PtCu bimetallic nanoparticles
T2 - Computational Materials Science
AU - Avakyan, Leon A.
AU - Tolchina, D
AU - Barkovski, V
AU - Belenov, Sergey
AU - Alekseenko, A. A.
AU - Shaginyan, A
AU - Srabionyan, V. V.
AU - Guterman, V. E.
AU - Bugaev, L
PY - 2022
DA - 2022/06/01 00:00:00
PB - Elsevier
SP - 111326
VL - 208
SN - 0927-0256
ER -
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@article{2022_Avakyan,
author = {Leon A. Avakyan and D Tolchina and V Barkovski and Sergey Belenov and A. A. Alekseenko and A Shaginyan and V. V. Srabionyan and V. E. Guterman and L Bugaev},
title = {Ultimate sensitivity of radial distribution functions to architecture of PtCu bimetallic nanoparticles},
journal = {Computational Materials Science},
year = {2022},
volume = {208},
publisher = {Elsevier},
month = {jun},
url = {https://doi.org/10.1016%2Fj.commatsci.2022.111326},
pages = {111326},
doi = {10.1016/j.commatsci.2022.111326}
}