Accurate prediction of materials phase diagrams from first principles remains a central challenge in computational materials science. Machine-learning interatomic potentials can provide near-DFT ...
Combinatorial synthesis and high-throughput characterization have become powerful tools to accelerate the discovery and design of novel materials. Correctly extracting information about the ...
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