Machine learning assisted design of FeCoNiCrMn high-entropy alloys with ultra-low hydrogen diffusion coefficients

XY Zhou, JH Zhu, Y Wu, XS Yang, T Lookman, HH Wu - Acta Materialia, 2022 - Elsevier
The broad compositional space of high entropy alloys (HEA) is conducive to the design of
HEAs with targeted performance. Herein, a data-driven and machine learning (ML) assisted …

Exploration of V–Cr–Fe–Co–Ni high-entropy alloys with high yield strength: A combination of machine learning and molecular dynamics simulation

L Chen, A Jarlöv, HL Seet, MLS Nai, Y Li… - Computational Materials …, 2023 - Elsevier
Improving the strength of Cr–Fe–Co–Ni high-entropy alloys is a key issue in expanding their
applicability. Herein, a framework combining machine learning and molecular dynamics is …

Machine learning guided appraisal and exploration of phase design for high entropy alloys

Z Zhou, Y Zhou, Q He, Z Ding, F Li… - npj Computational …, 2019 - nature.com
High entropy alloys (HEAs) and compositionally complex alloys (CCAs) have recently
attracted great research interest because of their remarkable mechanical and physical …

A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness

C Yang, C Ren, Y Jia, G Wang, M Li, W Lu - Acta Materialia, 2022 - Elsevier
Trapped by time-consuming traditional trial-and-error methods and vast untapped
composition space, efficiently discovering novel high entropy alloys (HEAs) with exceptional …

Revisit the VEC rule in high entropy alloys (HEAs) with high-throughput CALPHAD approach and its applications for material design-A case study with Al–Co–Cr–Fe …

S Yang, J Lu, F Xing, L Zhang, Y Zhong - Acta Materialia, 2020 - Elsevier
Valence electron concentration (VEC) was treated as a useful parameter to predict solid
solution phases, and the VEC rule was proposed for high entropy alloys (HEAs). However …

Machine learning accelerated design of non-equiatomic refractory high entropy alloys based on first principles calculation

Y Gao, S Bai, K Chong, C Liu, Y Cao, Y Zou - Vacuum, 2023 - Elsevier
Abstract The properties of High Entropy Alloys (HEAs) strongly depend on the composition
and content of elements. However, it was difficult to obtain the optimized element …

[HTML][HTML] Molecular dynamics simulation and machine learning of mechanical response in non-equiatomic FeCrNiCoMn high-entropy alloy

L Zhang, K Qian, J Huang, M Liu, Y Shibuta - Journal of Materials Research …, 2021 - Elsevier
High-entropy alloys (HEAs) have attracted a wide range of academic interest for their
promising properties as structural materials, among which the equiatomic FeCrNiCoMn …

Review and outlook on high-entropy alloys for hydrogen storage

F Marques, M Balcerzak, F Winkelmann… - Energy & …, 2021 - pubs.rsc.org
Recently, a new class of alloys, namely, high-entropy alloys (HEAs), started to be
investigated for hydrogen storage as they can form metal hydrides. Considering that the …

A focused review on machine learning aided high-throughput methods in high entropy alloy

L Qiao, Y Liu, J Zhu - Journal of Alloys and Compounds, 2021 - Elsevier
High-entropy alloys (HEAs) have attracted tremendous attention in various fields due to
unique microstructures and many excellent properties. For particular applications, an in …

[HTML][HTML] Machine learning assisted modelling and design of solid solution hardened high entropy alloys

X Huang, C Jin, C Zhang, H Zhang, H Fu - Materials & Design, 2021 - Elsevier
High entropy alloys (HEAs) are considered as a way to unlock the unlimited potentials of
materials during material design, where solid solution hardening (SSH) is one of the major …