Advancing the mechanical performance of glasses: perspectives and challenges

L Wondraczek, E Bouchbinder, A Ehrlicher… - Advanced …, 2022 - Wiley Online Library
Glasses are materials that lack a crystalline microstructure and long‐range atomic order.
Instead, they feature heterogeneity and disorder on superstructural scales, which have …

Machine learning for glass science and engineering: A review

H Liu, Z Fu, K Yang, X Xu, M Bauchy - Journal of Non-Crystalline Solids, 2021 - Elsevier
The design of new glasses is often plagued by poorly efficient Edisonian “trial-and-error”
discovery approaches. As an alternative route, the Materials Genome Initiative has largely …

Development of boron oxide potentials for computer simulations of multicomponent oxide glasses

L Deng, J Du - Journal of the American Ceramic Society, 2019 - Wiley Online Library
Molecular dynamics and related atomistic computer simulations are effective ways in
studying the structures and structure–property relations of glass materials. However …

A review on Machine learning aspect in physics and mechanics of glasses

J Singh, S Singh - Materials Science and Engineering: B, 2022 - Elsevier
The glass science and technology is a rapidly develo** field which is focused on
development of new glasses with excellent properties. Glasses are the non-crystalline …

Experimental method to quantify the ring size distribution in silicate glasses and simulation validation thereof

Q Zhou, Y Shi, B Deng, J Neuefeind, M Bauchy - Science advances, 2021 - science.org
Silicate glasses have no long-range order and exhibit a short-range order that is often fairly
similar to that of their crystalline counterparts. Hence, the out-of-equilibrium nature of …

Molecular dynamics simulation and luminescence properties of Eu3+ doped molybdenum gadolinium borate glasses for red emission

R Rajaramakrishna, P Nijapai, P Kidkhunthod… - Journal of Alloys and …, 2020 - Elsevier
The contribution reports on molecular dynamics simulation were used to understand, at the
molecular level, the interaction of molybdenum, gadolinium and europium ions with …

Deciphering the atomic genome of glasses by topological constraint theory and molecular dynamics: a review

M Bauchy - Computational Materials Science, 2019 - Elsevier
From telescope lenses to optical fibers and smartphone screens, glasses have been key
enablers in human history. Unlike crystalline materials, glasses can virtually feature any …

Predicting Young's modulus of oxide glasses with sparse datasets using machine learning

S Bishnoi, S Singh, R Ravinder, M Bauchy… - Journal of non …, 2019 - Elsevier
Abstract Machine learning (ML) methods are becoming popular tools for predicting and
designing novel materials. In particular, neural network (NN) is a promising ML method …

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

R Bhattoo, S Bishnoi, M Zaki, NMA Krishnan - Acta materialia, 2023 - Elsevier
Despite the use of inorganic glasses for more than 4500 years, the composition–property
relationships in these materials remain poorly understood. Here, exploiting largescale …

[PDF][PDF] Interatomic potentials for describing impurity atoms of light elements in fcc metals.

GM Poletaev, IV Zorya, RY Rakitin, MA Iliina - Materials Physics & …, 2019 - ipme.ru
Parameters of Morse potentials for describing the interactions of atoms of light elements C,
N, O with atoms of fcc metals Al, Ag, Ni are found. This set of three metals is unique in that …