Multifunctional high entropy alloys enabled by severe lattice distortion
Since 2004, the design of high entropy alloys (HEAs) has generated significant interest
within the materials science community due to their exceptional structural and functional …
within the materials science community due to their exceptional structural and functional …
[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 …
to their unique design incorporating multi-principal elements and remarkable …
[HTML][HTML] Characterization of FeCoNiCr high-entropy alloys manufactured by powder metallurgy technique
This study explores the phase constitution, thermal behavior, magnetic characteristics, and
mechanical properties of FeCoNiCrCux high-entropy alloys (HEAs) produced via powder …
mechanical properties of FeCoNiCrCux high-entropy alloys (HEAs) produced via powder …
Interpretable machine learning workflow for evaluating and analyzing the performance of high-entropy gete-based thermoelectric materials
W Li, M Liu - ACS Applied Electronic Materials, 2023 - ACS Publications
To guide the development of high-performance thermoelectric materials, it is essential to
design appropriate material compositions and temperature environments. This study …
design appropriate material compositions and temperature environments. This study …
[HTML][HTML] Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations
Data science and material informatics are gaining traction in alloy design. This is due to
increasing infrastructure, computational capabilities and established open-source …
increasing infrastructure, computational capabilities and established open-source …
Machine learning–informed development of high entropy alloys with enhanced corrosion resistance
This study demonstrates the use of machine learning as a potential tool to efficiently develop
new biomedical alloys with improved corrosion resistance by exploring the whole …
new biomedical alloys with improved corrosion resistance by exploring the whole …
Interpretable Machine Learning to Discover Perovskites with High Spontaneous Polarization
Machine learning can accelerate the design of new materials by screening large quantities
of materials. We investigated the spontaneous polarization intensity of inorganic perovskite …
of materials. We investigated the spontaneous polarization intensity of inorganic perovskite …
Effective first-principle description of thermodynamics for BCC Nb-V system by involving the contributions of chemical order, lattice distortion and vibration
The thermodynamic properties of body-centered cubic Nb-V system are well described
using the integrated methodology of first-principle calculations, cluster expansion and Monte …
using the integrated methodology of first-principle calculations, cluster expansion and Monte …
Effects of Chemical Short-Range Order and Temperature on Basic Structure Parameters and Stacking Fault Energies in Multi-Principal Element Alloys
In the realm of advanced material science, multi-principal element alloys (MPEAs) have
emerged as a focal point due to their exceptional mechanical properties and adaptability for …
emerged as a focal point due to their exceptional mechanical properties and adaptability for …
[PDF][PDF] Results in Materials
DEP Klenam, TK Asumadu, M Vandadi, N Rahbar… - researchgate.net
Data science and material informatics are gaining traction in alloy design. This is due to
increasing infrastructure, computational capabilities and established open-source …
increasing infrastructure, computational capabilities and established open-source …