Cover Image

Surface segregation in high-entropy alloys from alchemical machine learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mazitov, Arslan, Springer, Maximilian A., Lopanitsyna, Nataliya, Fraux, Guillaume, De, Sandip, Ceriotti, Michele
Format:	Preprint
Published:	2023
Subjects:	Materials Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning
by: Mazitov, Arslan, et al.
Published: (2025)

High-quality, high-information datasets for universal atomistic machine learning
by: Malosso, Cesare, et al.
Published: (2026)

PET-MAD, a lightweight universal interatomic potential for advanced materials modeling
by: Mazitov, Arslan, et al.
Published: (2025)

A universal machine learning model for the electronic density of states
by: How, Wei Bin, et al.
Published: (2025)

GAP-DFT: A graph-based alchemical perturbation density functional theory for catalytic high-entropy alloys
by: Hendy, Mohamed, et al.
Published: (2024)

Capturing short-range order in high-entropy alloys with machine learning potentials
by: Cao, Yifan, et al.
Published: (2024)

Composition based machine learning to predict phases & strength of refractory high entropy alloys
by: Iyengar, M. Sreenidhi, et al.
Published: (2025)

Pushing the limits of unconstrained machine-learned interatomic potentials
by: Bigi, Filippo, et al.
Published: (2026)

Interpolation and differentiation of alchemical degrees of freedom in machine learning interatomic potentials
by: Nam, Juno, et al.
Published: (2024)

Rapid modeling of segregation-driven metal-oxide adhesion in high-entropy alloys using macroscopic atom model
by: Boakye, Dennis, et al.
Published: (2026)

Fine-tuning of universal machine-learning interatomic potentials for 2D high-entropy alloys
by: Zhou, Chun, et al.
Published: (2026)

Accelerating ab initio melting property calculations with machine learning: Application to the high entropy alloy TaVCrW
by: Zhu, Li-Fang, et al.
Published: (2024)

Machine learning accelerated discovery of corrosion-resistant high-entropy alloys
by: Zeng, Cheng, et al.
Published: (2023)

Atomistic insights into Cu segregation effects on irradiation-induced defect dynamics in medium-entropy alloys
by: Rahman, Kazi Tawseef, et al.
Published: (2024)

Errors that matter: Uncertainty-aware universal machine-learning potentials calibrated on experiments
by: Kellner, Matthias, et al.
Published: (2026)

How unconstrained machine-learning models learn physical symmetries
by: Domina, Michelangelo, et al.
Published: (2026)

Adaptive energy reference for machine-learning models of the electronic density of states
by: How, Wei Bin, et al.
Published: (2024)

Utilizing a machine-learned potential to explore enhanced radiation tolerance in the MoNbTaVW high-entropy alloy
by: Liu, Jiahui, et al.
Published: (2024)

Reconstructions and Dynamics of $β$-Lithium Thiophosphate Surfaces
by: Türk, Hanna, et al.
Published: (2025)

Comparing the latent features of universal machine-learning interatomic potentials
by: Chorna, Sofiia, et al.
Published: (2025)

Efficient first principles based modeling via machine learning: from simple representations to high entropy materials
by: Li, Kangming, et al.
Published: (2024)

Threshold displacement energies in refractory high-entropy alloys
by: Byggmästar, Jesper, et al.
Published: (2024)

Surface segregation of liquid metal plasma-facing component alloys: A ReaxFF investigation
by: Munshi, Md Adnan Mahathir, et al.
Published: (2026)

Revealing the impact of chemical short-range order on radiation damage in MoNbTaVW high-entropy alloys using a machine-learning potential
by: Liu, Jiahui, et al.
Published: (2025)

Grain boundary interstitial segregation in substitutional binary alloys
by: Zhang, Zuoyong, et al.
Published: (2025)

Machine-learned accelerated discovery of oxidation-resistant NiCoCrAl high-entropy alloys
by: Boakye, Dennis, et al.
Published: (2025)

Cocktail effect on superconductivity in hexagonal high-entropy alloys
by: Liu, Bin, et al.
Published: (2024)

Fractal structure, depinning, and hysteresis of dislocations in high-entropy alloys
by: Le, Hoa Thi, et al.
Published: (2024)

Smooth, exact rotational symmetrization for deep learning on point clouds
by: Pozdnyakov, Sergey N., et al.
Published: (2023)

Predicting co-segregation in multicomponent alloys with solute-solute interactions
by: Zhang, Zuoyong, et al.
Published: (2026)

The hidden sustainability bottleneck in high-entropy alloy design
by: Nominé, Alexandre, et al.
Published: (2025)

Thermodynamic surface reconstruction governs catalytic behavior in high-entropy alloys
by: Kim, Taegyeong, et al.
Published: (2026)

Spontaneous formation of Frenkel defects in high-entropy-alloys-type compound
by: Ishikawa, Rikuya, et al.
Published: (2024)

Investigating into mechanisms of high temperature strength of refractory high-entropy alloys
by: Seetharaman, Sai Anandhi, et al.
Published: (2025)

Exploring mechanical and thermal properties of high-entropy ceramics via general machine learning potentials
by: Liu, Yiwen, et al.
Published: (2024)

Charting the thermodynamic stability of hybrid perovskite alloys with machine learning
by: Laakso, Jarno, et al.
Published: (2026)

Order-disorder duality of high entropy alloys extends non-linear optics
by: Milichko, Valentin A., et al.
Published: (2025)

Additively manufacturable high-strength aluminum alloys with thermally stable microstructures enabled by hybrid machine learning-based design
by: Taheri-Mousavi, S. Mohadeseh, et al.
Published: (2024)

Spin Hall effect in the high-resistivity high-entropy alloy AlCrMoW
by: Yadav, Jyoti, et al.
Published: (2025)

Micromechanics reveal strain rate dependent transition between dislocation mechanisms in a dual phase high entropy alloy
by: Kalácska, Szilvia, et al.
Published: (2024)