Accelerated Prediction of Phase Behavior for Block Copolymer Libraries Using a Molecularly Informed Field Theory.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of the American Chemical Society"
DOI: 10.1021/jacs.4c11258
Abstract: Solution formulations involving polymers are the basis for a wide range of products spanning consumer care, therapeutics, lubricants, adhesives, and coatings. These multicomponent systems typically show rich self-assembly and phase behavior that are sensitive to… read more here.
Keywords: field; accelerated prediction; phase behavior; block ... See more keywords
Machine-learning accelerated prediction of two-dimensional conventional superconductors.
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DOI: 10.1039/d4mh01753f
Abstract: We perform a large scale search for two-dimensional (2D) superconductors, by using electron-phonon calculations with density-functional perturbation theory combined with machine learning models. In total, we screened over 140 000 2D compounds from the Alexandria database.… read more here.
Keywords: accelerated prediction; machine; learning accelerated; machine learning ... See more keywords
Machine learning accelerated prediction of Ce-based ternary compounds involving antagonistic pairs
Sign Up to like & getrecommendations! Published in 2024 at "Physical Review Materials"
DOI: 10.1103/physrevmaterials.9.053803
Abstract: The discovery of novel quantum materials within ternary phase spaces containing antagonistic pairs such as Fe with Bi, Pb, In, and Ag, presents significant challenges yet holds great potential. In this work, we investigate the… read more here.
Keywords: accelerated prediction; antagonistic pairs; ternary compounds; learning accelerated ... See more keywords