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High-quality, high-information datasets for universal atomistic machine learning
<p>The quality, consistency, and information content of training data is often what determines the practical value of machine-learning models for atomistic simulations.... -
Simultaneous learning of static and dynamic charges
<p>Long-range interactions and electric response are essential for accurate modeling of condensed-phase systems, but capturing them efficiently remains a challenge for... -
Simultaneous learning of static and dynamic charges
<p>Long-range interactions and electric response are essential for accurate modeling of condensed-phase systems, but capturing them efficiently remains a challenge for... -
Massive Atomic Diversity: a compact universal dataset for atomistic machine l...
<p>The development of machine-learning models for atomic-scale simulations has benefitted tremendously from the large databases of materials and molecular properties... -
Effect of residual stress and microstructure on mechanical properties of sput...
The combination of the high wear resistance and mechanical strength of W with the high thermal conductivity of Cu makes the Cu/W system an attractive candidate material for heat... -
Massive Atomic Diversity: a compact universal dataset for atomistic machine l...
<p>The development of machine-learning models for atomic-scale simulations has benefitted tremendously from the large databases of materials and molecular properties...
