Understanding the compositional control on electrical, mechanical, optical, and physical properties of inorganic glasses with interpretable machine learning-Reference-Cited by-同舟云学术

Understanding the compositional control on electrical, mechanical, optical, and physical properties of inorganic glasses with interpretable machine learning

Published:2023-01 Issue: Volume:242 Page:118439
ISSN:1359-6454
Container-title:Acta Materialia
language:en
Short-container-title:Acta Materialia

Author:

Bhattoo Ravinder,Bishnoi Suresh,Zaki Mohd^ORCID,Krishnan N. M. Anoop

Publisher

Elsevier BV

Subject

Metals and Alloys,Polymers and Plastics,Ceramics and Composites,Electronic, Optical and Magnetic Materials

Reference58 articles.

1. Grand challenges in glass science;Mauro;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. Fundamentals of Inorganic Glasses;Varshneya,2019

4. The atomic arrangement in glass;Zachariasen;J. Am. Chem. Soc.,1932

5. Bioactive glasses—structure and properties;Brauer;Angew. Chem. Int. Ed.,2015

Cited by 21 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. Prediction of optical properties of oxide glass combined with autoencoder and machine learning;Journal of Non-Crystalline Solids;2024-10

2. Designing high-performance ion-exchangeable glasses with multi-objective optimization and machine learning;Ceramics International;2024-08

3. Enhancing glass-forming ability and mechanical properties of barium-calcium-aluminate glasses through ZnO inclusion;Journal of Non-Crystalline Solids;2024-07

4. Refractive-index Prediction for High-refractive-index Optical Glasses Based on the B₂O₃-La₂O₃-Ta₂O~~5-SiO₂ System Using Machine Learning;CURR OPT PHOTONICS;2024~~

~~5. Enhancing glass property predictions through ab initio‐derived descriptors;Journal of the American Ceramic Society;2024-05-23~~