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

D Jiang, L **e, 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] Enhancing the mechanical properties of high-entropy alloys through severe plastic deformation: A review

M Naseri, AO Moghadam, M Anandkumar… - Journal of Alloys and …, 2024 - Elsevier
High-entropy alloys (HEAs) are one of the breakthroughs in the past decade in alloy
development that have the potential to exhibit outstanding physical, mechanical, and …

Review on applications of artificial neural networks to develop high entropy alloys: A state-of-the-art technique

SK Dewangan, C Nagarjuna, R Jain… - Materials Today …, 2023 - Elsevier
Compared to conventional alloys, multicomponent high-entropy alloys (HEAs) have
received considerable attention in recent years owing to their exceptional phase stability …

Large language models as molecular design engines

D Bhattacharya, HJ Cassady, MA Hickner… - Journal of Chemical …, 2024 - ACS Publications
The design of small molecules is crucial for technological applications ranging from drug
discovery to energy storage. Due to the vast design space available to modern synthetic …

Review on cellular automata for microstructure simulation of metallic materials

Y Zhi, Y Jiang, D Ke, X Hu, X Liu - Materials, 2024 - mdpi.com
The cellular automata (CA) method has played an important role in the research and
development of metallic materials. CA can interpret the microstructure changes of materials …

[HTML][HTML] Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

X Mi, L Dai, X **g, J She, B Holmedal, A Tang… - Journal of Magnesium …, 2024 - Elsevier
Magnesium (Mg), being the lightest structural metal, holds immense potential for widespread
applications in various fields. The development of high-performance and cost-effective Mg …

Tribo-informatics analysis of in-situ TiC reinforced ZA27 alloy: Microstructural insights and wear performance modeling by machine learning

KA Sheikh, MM Khan - Tribology International, 2024 - Elsevier
The study examines the performance of ZA27 alloy reinforced with in-situ TiC under high-
stress abrasive wear conditions. The ZA27+ 10 wt% TiC composite demonstrates superior …

[HTML][HTML] Designing unique and high-performance Al alloys via machine learning: Mitigating data bias through active learning

M Hu, Q Tan, R Knibbe, M Xu, G Liang, J Zhou… - Computational Materials …, 2024 - Elsevier
Data-driven modelling, such as machine learning (ML), has great potential to streamline the
complexity involved in designing new alloys. However, such powerful predictive models …

Recent machine learning-driven investigations into high entropy alloys: a comprehensive review

Y Yan, X Hu, Y Liao, Y Zhou, W He, T Zhou - Journal of Alloys and …, 2024 - Elsevier
The exploration of high entropy alloys (HEAs) primarily relies on trial-and-error experiments
and multiscale modelling, which are time-consuming and resource-intensive. Recently …

[HTML][HTML] Estimating the lattice thermal conductivity of AlCoCrNiFe high-entropy alloy using machine learning

J Lu, X Huang, Y Yue - Journal of Applied Physics, 2024 - pubs.aip.org
The lattice thermal conductivity stands as a pivotal thermos-physical parameter of high-
entropy alloys; nonetheless, achieving precise predictions of the lattice thermal conductivity …