Machine learning for high-entropy alloys: Progress, challenges and opportunities
High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional
mechanical properties and the vast compositional space for new HEAs. However …
mechanical properties and the vast compositional space for new HEAs. However …
Machine-learning informed prediction of high-entropy solid solution formation: Beyond the Hume-Rothery rules
The empirical rules for the prediction of solid solution formation proposed so far in the
literature usually have very compromised predictability. Some rules with seemingly good …
literature usually have very compromised predictability. Some rules with seemingly good …
An overview of modeling the stacking faults in lightweight and high-entropy alloys: Theory and application
Z Pei - Materials Science and Engineering: A, 2018 - Elsevier
Modeling stacking faults in lightweight and medium-to high-entropy alloys is an exciting and
fast developing field. Stacking faults and associated defects play a key role in understanding …
fast developing field. Stacking faults and associated defects play a key role in understanding …
Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: A data-driven approach
High entropy alloys (HEAs) are a series of novel materials that demonstrate many
exceptional mechanical properties. To understand the origin of these attractive properties, it …
exceptional mechanical properties. To understand the origin of these attractive properties, it …
Robust data-driven approach for predicting the configurational energy of high entropy alloys
High entropy alloys (HEAs) are promising next-generation materials due to their various
excellent properties. To understand these properties, it's necessary to characterize the …
excellent properties. To understand these properties, it's necessary to characterize the …
Statistics of the NiCoCr medium-entropy alloy: Novel aspects of an old puzzle
We study the K-state phenomenon in the NiCoCr medium-entropy alloy using first-principles
techniques jointly with the efficient Wang–Landau Monte Carlo and simulated annealing …
techniques jointly with the efficient Wang–Landau Monte Carlo and simulated annealing …
Dopant arrangements in Y-doped BaZrO 3 under processing conditions and their impact on proton conduction: a large-scale first-principles thermodynamics study
Y-doped BaZrO3 is an ion conductor under intense research for application in medium
temperature solid oxide fuel cells. The conductivity is maximized at∼ 20% doping, and the …
temperature solid oxide fuel cells. The conductivity is maximized at∼ 20% doping, and the …
Properties of α-brass nanoparticles. 1. Neural network potential energy surface
J Weinreich, A Römer, ML Paleico… - The Journal of Physical …, 2020 - ACS Publications
Binary metal clusters are of high interest for applications in heterogeneous catalysis and
have received much attention in recent years. To gain insights into their structure and …
have received much attention in recent years. To gain insights into their structure and …
Machine learning assisted design of new ductile high-entropy alloys: Application to Al-Cr-Nb-Ti-V-Zr system
The search for new high-entropy alloys (HEAs) with desired properties is an urgent problem
that is hardly solvable experimentally due to the extremely large number of possible alloy …
that is hardly solvable experimentally due to the extremely large number of possible alloy …
Effective optimization of atomic decoration in giant and superstructurally ordered crystals with machine learning
FT Cerasoli, D Donadio - The Journal of Chemical Physics, 2024 - pubs.aip.org
Crystals with complicated geometry are often observed with mixed chemical occupancy
among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar …
among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar …