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 …

Modeling the mechanics of amorphous solids at different length scale and time scale

D Rodney, A Tanguy… - Modelling and Simulation …, 2011 - iopscience.iop.org
We review the recent literature on the simulation of the structure and deformation of
amorphous solids, including oxide and metallic glasses. We consider simulations at different …

Electron-beam-assisted superplastic sha** of nanoscale amorphous silica

K Zheng, C Wang, YQ Cheng, Y Yue, X Han… - Nature …, 2010 - nature.com
Glasses are usually shaped through the viscous flow of a liquid before its solidification, as
practiced in glass blowing. At or near room temperature (RT), oxide glasses are known to be …

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 …

Type label framework for bonded force fields in LAMMPS

JR Gissinger, I Nikiforov, Y Afshar… - The Journal of …, 2024 - ACS Publications
New functionality is added to the LAMMPS molecular simulation package, which increases
the versatility with which LAMMPS can interface with supporting software and manipulate …

Polarization effects in ionic solids and melts

M Salanne, PA Madden - Molecular Physics, 2011 - Taylor & Francis
Ionic solids and melts are compounds in which the interactions are dominated by
electrostatic effects. However, the polarization of the ions also plays an important role in …

[HTML][HTML] Interatomic potentials for oxide glasses: Past, present, and future

A Pedone, M Bertani, L Brugnoli, A Pallini - Journal of Non-Crystalline …, 2022 - Elsevier
The continuous development and improvement of interatomic potential models for oxide
glasses have made classical molecular dynamics a powerful computational technique …

Deep machine learning interatomic potential for liquid silica

IA Balyakin, SV Rempel, RE Ryltsev, AA Rempel - Physical Review E, 2020 - APS
The use of machine learning to develop neural network potentials (NNP) representing the
interatomic potential energy surface allows us to achieve an optimal balance between …

A machine-learned interatomic potential for silica and its relation to empirical models

LC Erhard, J Rohrer, K Albe, VL Deringer - npj Computational Materials, 2022 - nature.com
Silica (SiO2) is an abundant material with a wide range of applications. Despite much
progress, the atomistic modelling of the different forms of silica has remained a challenge …

[HTML][HTML] New optimization scheme to obtain interaction potentials for oxide glasses

S Sundararaman, L Huang, S Ispas… - The Journal of Chemical …, 2018 - pubs.aip.org
We propose a new scheme to parameterize effective potentials that can be used to simulate
atomic systems such as oxide glasses. As input data for the optimization, we use the radial …