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Abstract Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicability. Here, we present a promising approach for constructing a unified general-purpose MLP for numerous elements, demonstrated through a model (UNEP-v1) for 16 elemental metals and their alloys. To achieve a complete representation of the chemical space, we show, via principal component analysis and diverse test datasets, that employing one-component and two-component systems suffices. Our unified UNEP-v1 model exhibits superior performance across various physical properties compared to a widely used embedded-atom method potential, while maintaining remarkable efficiency. We demonstrate our approach’s effectiveness through reproducing experimentally observed chemical order and stable phases, and large-scale simulations of plasticity and primary radiation damage in MoTaVW alloys.

Longfeng A, derived from the cross of Bo A/(Zhenshan 97B/Bo B F1//Bo B/Gui 2 F1), is a new high-quality indica CMS line with soft-grain characteristics in cooking rice. The CMS line is characterized by good agronomic traits, complete pollen sterility, stale fertility, favorable outcrossing habits, high combining ability and good grain quality. It was technically identified by Guangxi Crop Variety Appraisal Committee in June, 2013. [ABSTRACT FROM AUTHOR]