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Miroslav Lebeda

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Preprint Oct 2026

Benchmarking Universal Machine-Learning Interatomic Potentials for Temperature-Dependent Elasticity of Binary and High-Entropy Refractory Carbides

Accurate prediction of temperature-dependent elasticity is important for assessing refractory carbides under high-temperature conditions, but the computational cost of ab initio molecular dynamics (AIMD) limits systematic investigations across compositions and temperatures. Universal machine-learning interatomic potent...

Miroslav Lebeda, Jan Drahokoupil, Šimon Svoboda et al. · 0 citations

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