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NN-xTB: density functional accuracy at semi empirical speed with neural network extended tight binding
Abstract Accurate prediction of molecular structure, energetics, and reactivity requires quantum chemistry methods that remain too costly for large-scale and high-throughput modeling. Semi-empirical tight-binding approaches are much faster, but their largely element-fixed parameters under-resolve local chemical-environment effects, limiting accuracy.
AliSim-HPC: parallel sequence simulator for phylogenetics
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Novel Computer Architectures and Quantum Chemistry
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Phys. Chem. A 2020, 124, 23 Mark S. Gordon*, Giuseppe Barca, Sarom S. Leang Sarom S. Leang EP Analytics, 12121 Scripps Summit Drive, Suite 130, San Diego, California 92131, United States , David Poole David Poole Department of Chemistry and Ames Laboratory, Iowa State University, Ames, Iowa 50011, United States , Alistair P. Rendell* Alistair P.
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