[HTML][HTML] Current application status of multi-scale simulation and machine learning in research on high-entropy alloys

D Jiang, L Xie, L Wang - Journal of Materials Research and Technology, 2023 - Elsevier
High-entropy alloys (HEAs) have garnered significant attention across various fields owing
to their unique design incorporating multi-principal elements and remarkable …

[HTML][HTML] Recent progress in high-entropy alloys: A focused review of preparation processes and properties

B Yu, Y Ren, Y Zeng, W Ma, K Morita, S Zhan… - Journal of Materials …, 2024 - Elsevier
In recent years, high-entropy alloys (HEAs) have attracted tremendous attention in various
fields. With multiple-principal elements and multiple core effects, giving them different …

Unraveling the deformation behavior of the Fe45Co25Ni10V20 high entropy alloy

YX Li, RK Nutor, QK Zhao, XP Zhang, QP Cao… - International Journal of …, 2023 - Elsevier
Here we report on the tensile deformation behavior of a face-centered cubic (FCC)-
structured Fe 45 Co 25 Ni 10 V 20 high-entropy alloy at cryogenic temperature (77 K). The …

Nanoprecipitate and stacking fault-induced high strength and ductility in a multiscale heterostructured high-entropy alloy

L Liu, Y Zhang, Z Zhang, J Li, W Jiang, L Sun - International Journal of …, 2024 - Elsevier
Two-phase high-entropy alloys (HEAs) have high strength due to the contribution of
interface-dependent strengthening, but the deformation incompatibility between the two …

[HTML][HTML] A neural network model for high entropy alloy design

J Wang, H Kwon, HS Kim, BJ Lee - npj Computational Materials, 2023 - nature.com
A neural network model is developed to search vast compositional space of high entropy
alloys (HEAs). The model predicts the mechanical properties of HEAs better than several …

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 …

Effect of short-range ordering and grain boundary segregation on shear deformation of CoCrFeNi high-entropy alloys with Al addition

R Babicheva, A Jarlöv, H Zheng, S Dmitriev… - Computational Materials …, 2022 - Elsevier
A method combining molecular dynamics (MD) and Monte Carlo (MC) simulation is used to
analyze the short-range ordering and grain boundary (GB) segregation in the bi-crystals of …

Investigation on the effect of cutting edge rounded arc radius on the subsurface damage of FeCoNiCrAl0. 6 high entropy alloy based on molecular dynamics …

P Zhang, Y Sun, S Wang, Y Gao, X Yue - Journal of Manufacturing …, 2024 - Elsevier
This investigation delves into the nanomachining mechanisms of the FeCoNiCrAl0. 6 high
entropy alloy, with an emphasis on the influence of the cutting edge's rounded arc radius …

Simultaneously optimizing the strength and ductility of high-entropy alloys by magnetic field-assisted additive manufacturing

S Guo, S Sui, M Wang, Q Wang, R Tang, A Guo… - Journal of Alloys and …, 2023 - Elsevier
The mechanical properties of many metallic materials have been optimized by magnetic
field-assisted additive manufacturing, however, there is still a gap in high-entropy alloys …

An efficient scheme for accelerating the calculation of stacking fault energy in multi-principal element alloys

H Sun, Z Ding, H Sun, J Zhou, JC Ren, Q Hu… - Journal of Materials …, 2024 - Elsevier
Abstract We present the High-Throughput Computing and Statistical Analysis (HCSA)
scheme, which efficiently and accurately predicts the stacking fault energies (SFEs) of multi …