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20192026
most citedMachine learning materials physics: Integrable deep neural networks enable scale bridging by learning free energy functions

113 citations · 114 across the 6 of their papers we have counts for

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11 papers · 1 filter

cond-mat.mtrl-sci2026

Cracking the case: fluctuations enhance ductility in refractory alloys

Manura Liyanage, Julia Chmielewska, Tijmen Vermeij +4

Refractory body-centered cubic (BCC) alloys are attractive candidates for structural applications at extreme temperatures, yet combining room-temperature ductility with high-temper…

cond-mat.mtrl-sci2026

pyeCE: A Python Implementation of the Embedded Cluster Expansion

Yann L. Müller, Claire A. Paetsch, Anirudh Raju Natarajan

The cluster expansion is a widely used approach for predicting the finite-temperature thermodynamics of alloys from zero-kelvin first-principles calculations, but its conventional…

cond-mat.mtrl-sci2026

Synthesizability, hardness, and stacking order in multicomponent transition metal carbides from machine-learned potentials

Xin Liu, Anirudh Raju Natarajan

Multicomponent transition metal carbides are promising for extreme-environment applications, but identifying compositions that are both synthesizable and hard remains challenging.…

cond-mat.mtrl-sci20261 cited

Diffusion coefficients of multi-principal element alloys from first principles

Damien K. J. Lee, Anirudh Raju Natarajan

Vacancy-mediated diffusion in multi-principal element alloys (MPEAs) remains poorly understood. Existing computational methods face challenges in connecting electronic structure to…

cond-mat.mtrl-sci2026

Machine learning interatomic potentials for solid-state precipitation

Lorenzo Piersante, Anirudh Raju Natarajan

Machine learning interatomic potentials (MLIPs) are routinely used to model diverse atomistic phenomena, yet parameterizing them to accurately capture solid-state phase transformat…

cond-mat.mtrl-sci2026

Thermodynamic and electronic properties of rutile SnGeO alloys from first principles

Yann L. Müller, Alp Umut Kurbay, Xiao Zhang +2

Rutile SnGeO alloys are promising materials for high-power electronic applications due to their dopability and tunable ultra-wide band gaps. We use first-principl…