Research [ASAP] Dynamic Training Enhances Machine Learning Potentials for Long-Lasting Molecular Dynamics LikeLiked Date: July 22, 2025 Less than 1 MinRead Views: 11 Journal of Chemical Information and Modeling DOI: 10.1021/acs.jcim.5c01180 Source: http://dx.doi.org/10.1021/acs.jcim.5c01180 Tags:Materials Industry FacebookTwitterLinkedinWhatsAppTelegramEmail ALT-Lab-Ad-1ALT-Lab-Ad-2ALT-Lab-Ad-3ALT-Lab-Ad-4ALT-Lab-Ad-5ALT-Lab-Ad-6ALT-Lab-Ad-7ALT-Lab-Ad-8ALT-Lab-Ad-9ALT-Lab-Ad-10ALT-Lab-Ad-11ALT-Lab-Ad-12ALT-Lab-Ad-13 Recent Articles Integration of metabolic and bioprocess engineering for the production of β-ketoadipic acid from glucose and xylose by Pseudomonas putida Research August 14, 2025 Electrocatalytic oxidation of biomass-derived chemicals using non-precious metal catalysts: design strategies, performance characteristics and perspectives Research August 14, 2025 Health was supposed to be central to the UN plastics treaty. Now it’s up for debate. Environmental News August 13, 2025 Cross Post: Impacts of Budget Reconciliation and Colorado Farms: Hurt for Farmers and Farm Communities, and the Need for a New Farm Bill Food & Agriculture August 13, 2025 House in Nishitanabe / FujiwaraMuro Architects Built Environment August 13, 2025 Animal Ag News 8/13 Food & Agriculture August 13, 2025 Arkion Life Sciences Announces Promotions Food & Agriculture August 13, 2025 Visualizing the World’s AI Compute Hubs Finance & investments August 13, 2025 Advancing Energy Storage Through Science and Real-World Solutions Research August 13, 2025 Mapped: Farmland by State in 2025 Finance & investments August 13, 2025 Load more
