Machine learning and artificial neural network accelerated computational discoveries in materials science

Y Hong, B Hou, H Jiang, J Zhang - Wiley Interdisciplinary …, 2020 - Wiley Online Library
Artificial intelligence (AI) has been referred to as the “fourth paradigm of science,” and as
part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically …

Structural changes in metallic glass-forming liquids on cooling and subsequent vitrification in relationship with their properties

DV Louzguine-Luzgin - Materials, 2022 - mdpi.com
The present review is related to the studies of structural changes observed in metallic glass-
forming liquids on cooling and subsequent vitrification in terms of radial distribution function …

Critical length scale controls adhesive wear mechanisms

R Aghababaei, DH Warner, JF Molinari - Nature communications, 2016 - nature.com
The adhesive wear process remains one of the least understood areas of mechanics. While
it has long been established that adhesive wear is a direct result of contacting surface …

Atomistic study of grain-boundary segregation and grain-boundary diffusion in Al-Mg alloys

RK Koju, Y Mishin - Acta Materialia, 2020 - Elsevier
Mg grain boundary (GB) segregation and GB diffusion can impact the processing and
properties of Al-Mg alloys. Yet, Mg GB diffusion in Al has not been measured experimentally …

The rise of neural networks for materials and chemical dynamics

M Kulichenko, JS Smith, B Nebgen, YW Li… - The Journal of …, 2021 - ACS Publications
Machine learning (ML) is quickly becoming a premier tool for modeling chemical processes
and materials. ML-based force fields, trained on large data sets of high-quality electron …

Atomistic modeling of interfaces and their impact on microstructure and properties

Y Mishin, M Asta, J Li - Acta Materialia, 2010 - Elsevier
Atomic-level modeling of materials provides fundamental insights into phase stability,
structure and properties of crystalline defects, and to physical mechanisms of many …

Learning grain-boundary segregation: from first principles to polycrystals

M Wagih, CA Schuh - Physical review letters, 2022 - APS
The segregation of solute atoms at grain boundaries (GBs) can strongly impact the structural
and functional properties of polycrystals. Yet, due to the limited availability of simulation tools …

Modified embedded atom method potential for Al, Si, Mg, Cu, and Fe alloys

B Jelinek, S Groh, MF Horstemeyer, J Houze… - Physical Review B …, 2012 - APS
A set of modified embedded-atom method (MEAM) potentials for the interactions between Al,
Si, Mg, Cu, and Fe was developed from a combination of each element's MEAM potential in …

Development of suitable interatomic potentials for simulation of liquid and amorphous Cu–Zr alloys

MI Mendelev, MJ Kramer, RT Ott, DJ Sordelet… - Philosophical …, 2009 - Taylor & Francis
We present a new semi-empirical potential suitable for molecular dynamics simulations of
liquid and amorphous Cu–Zr alloys. To provide input data for developing the potential, new …

[HTML][HTML] Development of an interatomic potential for the simulation of defects, plasticity, and phase transformations in titanium

MI Mendelev, TL Underwood… - The Journal of chemical …, 2016 - pubs.aip.org
New interatomic potentials describing defects, plasticity, and high temperature phase
transitions for Ti are presented. Fitting the martensitic hcp-bcc phase transformation …