Scripta Materialia, volume 186, pages 14-18

Accelerated modeling of interfacial phases in the Ni-Bi system with machine learning interatomic potential

Korolev Vadim ¹

Mitrofanov Artem ¹

Kucherinenko Yaroslav ²

Nevolin Yurii ¹

Krotov Vladimir ¹

Protsenko P. ¹

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Department of Chemistry, Lomonosov Moscow State University, Moscow 119991, Russia. |

Department of Geology, Lomonosov Moscow State University, Moscow 119991, Russia |

Publication type: Journal Article

Publication date: 2020-09-01

Elsevier

Journal: Scripta Materialia

Quartile SCImago

Quartile WOS

Impact factor: 6

ISSN: 13596462

DOI: 10.1016/j.scriptamat.2020.03.057

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Metals and Alloys

Condensed Matter Physics

General Materials Science

Mechanical Engineering

Mechanics of Materials

Abstract

Abstract High-performance modeling of interfacial phases is a challenge because of the low scalability of first-principle methods. Here we present a data-driven approach based on using the machine learning potential to address this problem. The developed model quantitatively reproduces the formation energy of Bi films on selected Ni grain boundaries. This scheme allows us to model arbitrary grain boundaries, preserving chemical accuracy of the reference method. The suitability of the interatomic potential is also confirmed by the construction of a grain boundary phase diagram. This approach opens the door for the accelerated study of the full configurational space of interfacial phases.

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MRS Communications	MRS Communications, 1, 20% MRS Communications 1 publication, 20%
Acta Materialia	Acta Materialia, 1, 20% Acta Materialia 1 publication, 20%
International Journal of Mechanical System Dynamics	International Journal of Mechanical System Dynamics, 1, 20% International Journal of Mechanical System Dynamics 1 publication, 20%
Journal of Materials Chemistry A	Journal of Materials Chemistry A, 1, 20% Journal of Materials Chemistry A 1 publication, 20%
Physical Review Materials	Physical Review Materials, 1, 20% Physical Review Materials 1 publication, 20%
	1

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Cambridge University Press	Cambridge University Press, 1, 20% Cambridge University Press 1 publication, 20%
Elsevier	Elsevier, 1, 20% Elsevier 1 publication, 20%
Wiley	Wiley, 1, 20% Wiley 1 publication, 20%
Royal Society of Chemistry (RSC)	Royal Society of Chemistry (RSC), 1, 20% Royal Society of Chemistry (RSC) 1 publication, 20%
American Physical Society (APS)	American Physical Society (APS), 1, 20% American Physical Society (APS) 1 publication, 20%
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Korolev V. et al. Accelerated modeling of interfacial phases in the Ni-Bi system with machine learning interatomic potential // Scripta Materialia. 2020. Vol. 186. pp. 14-18.

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Korolev V., Mitrofanov A., Kucherinenko Y., Nevolin Y., Krotov V., Protsenko P. Accelerated modeling of interfacial phases in the Ni-Bi system with machine learning interatomic potential // Scripta Materialia. 2020. Vol. 186. pp. 14-18.

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RIS Copy

TY - JOUR

DO - 10.1016/j.scriptamat.2020.03.057

UR - https://doi.org/10.1016%2Fj.scriptamat.2020.03.057

TI - Accelerated modeling of interfacial phases in the Ni-Bi system with machine learning interatomic potential

T2 - Scripta Materialia

AU - Korolev, Vadim

AU - Mitrofanov, Artem

AU - Kucherinenko, Yaroslav

AU - Nevolin, Yurii

AU - Krotov, Vladimir

AU - Protsenko, P.

PY - 2020

DA - 2020/09/01 00:00:00

PB - Elsevier

SP - 14-18

VL - 186

SN - 1359-6462

ER -

BibTex

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BibTex Copy

@article{2020_Korolev,

author = {Vadim Korolev and Artem Mitrofanov and Yaroslav Kucherinenko and Yurii Nevolin and Vladimir Krotov and P. Protsenko},

title = {Accelerated modeling of interfacial phases in the Ni-Bi system with machine learning interatomic potential},

journal = {Scripta Materialia},

year = {2020},

volume = {186},

publisher = {Elsevier},

month = {sep},

url = {https://doi.org/10.1016%2Fj.scriptamat.2020.03.057},

pages = {14--18},

doi = {10.1016/j.scriptamat.2020.03.057}

}

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Publisher

Elsevier

Journal

Scripta Materialia

Quartile SCImago

Quartile WOS

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ISSN

13596462 (Print)

Labs

Laboratory of Intelligent Chemical Design

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