Boron coordination and three‐membered ring formation in sodium borate glasses: a machine‐learning molecular dynamics study

Author:

Kato Takeyuki1ORCID,Lodesani Federica2ORCID,Urata Shingo2ORCID

Affiliation:

1. Materials Integration Laboratories AGC Inc. Yokohama Kanagawa Japan

2. Innovative Technology Laboratories AGC Inc. Yokohama Kanagawa Japan

Abstract

AbstractClassical molecular dynamics (CMD) simulations that employ analytical force fields have been commonly utilized to investigate mechanical, chemical, and thermal properties of oxide glasses owing to their superior computational efficiency. Conversely, simple functional forms limit the accuracy in modeling complicated glass structures, specifically, in alkaline borate glasses, which exhibit boron coordination numbers that vary nonlinearly with changes in glass composition and temperature. Machine‐learning potentials (MLPs), which are trained using datasets on energy and force evaluated via the density functional theory (DFT), are garnering significant attention as a novel simulation technology for enhancing the accuracy in modeling materials. Therefore, this study applied a universal MLP, PreFerred Potential (PFP) (trade‐name: Matlantis), to model sodium borate glasses, and its accuracy was verified in reproducing boron coordination and ring structures by comparing its results to available experimental data. We found that PFP can quantitatively reproduce the boron coordination change with glass composition without any empirical correction, while the boron coordination in the melts at high temperatures is overestimated, even though the qualitative variation was better estimated than CMD simulations. Furthermore, the MLP could generate many 3‐rings, unlike the analytical force‐field. Accordingly, we demonstrated superior accuracy of the MLP in modeling alkaline borate glasses, while discussing the challenges faced in reproducing the elaborated microstructures in borate glasses.

Publisher

Wiley

Subject

Materials Chemistry,Ceramics and Composites

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3