Prediction and screening of glass properties based on high-throughput molecular dynamics simulations and machine learning-Reference-Cited by-同舟云学术

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Prediction and screening of glass properties based on high-throughput molecular dynamics simulations and machine learning

Published:2022-12 Issue: Volume:597 Page:121927
ISSN:0022-3093
Container-title:Journal of Non-Crystalline Solids
language:en
Short-container-title:Journal of Non-Crystalline Solids

Author:

Yang Yong,Han Jiang,Zhai Hua,Chen Jiarui,Jiang Qi,Chen Shuyong,Li Bao,Cao Xin

Publisher

Elsevier BV

Subject

Materials Chemistry,Condensed Matter Physics,Ceramics and Composites,Electronic, Optical and Magnetic Materials

Reference59 articles.

1. Glass science in the United States: current status and future directions;Mauro;Int. J. Appl. Glass Sci.,2014

2. Two centuries of glass research: historical trends, current status, and grand challenges for the future;Mauro;Int. J. Appl. Glass Sci.,2014

3. The glassy state of matter: its definition and ultimate fate;Zanotto;J. Non-Cryst. Solids,2017

4. How many non-crystalline solids can be made from all the elements of the periodic table?;Zanotto;J. Non-Cryst. Solids,2004

5. Topological optimization of cementitious binders: advances and challenges;Liu;Cem. Concr. Compos.,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Structural, mechanical, thermal, optical, and gamma rays attenuation properties of a developed sodium aluminum zinc lead borate glass;Radiation Physics and Chemistry;2024-05

2. The optimization of evaporation rate in graphene-water system by machine learning algorithm;Journal of Applied Physics;2024-04-03

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