Can ML simulate carbon nanotube growth? 🧬🚀 Discover how the new DeepCNT-22 force field, based on DeePMD, enables precise large-scale simulations. Learn more about this breakthrough in nanomaterials!
🚀 New Insights from DeePMD-kit! 🚀
Check out the latest Nature Chemistry article where DeePMD-kit reveals a dual-gated mechanism of proton transport in water, advancing our understanding of this vital process.
🔗 Read more: doi.org/10.1038/s41557…#DeepModeling#DeePMD#AI4S
🚀Machine learning potential model was generated for the Pt-TiO2 system using DeePMD-kit. This model studies the effect of atomic isolation walls on catalyst stability and illustrates noble metal particle sintering on TiO2-supported Pt particles.
doi.org/10.1016/j.jcat…
🧬 Exciting news! Researchers Xi Cheng, Liuqing Wen, and Dingyan Wang introduced DeepGlycanSite, a deep learning model for accurate carbohydrate-binding site prediction on proteins.
nature.com/articles/s4146…#deepmodeling#unimol#opensource