DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field-Reference-Cited by-同舟云学术

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DL_FFLUX: A Parallel, Quantum Chemical Topology Force Field

Published:2021-10-07 Issue:11 Volume:17 Page:7043-7055
ISSN:1549-9618
Container-title:Journal of Chemical Theory and Computation
language:en
Short-container-title:J. Chem. Theory Comput.

Author:

Symons Benjamin C. B.¹²,Bane Michael K.³⁴^ORCID,Popelier Paul L. A.¹²^ORCID

Affiliation:

1. Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, Great Britain

2. Department of Chemistry, University of Manchester, Oxford Road, Manchester M13 9PL, Great Britain

3. High End Compute LTD, 23 Welby Street, Manchester M13 0EL, Great Britain

4. Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M15 6BH, Great Britain

Funder

Engineering and Physical Sciences Research Council

Publisher

American Chemical Society (ACS)

Subject

Physical and Theoretical Chemistry,Computer Science Applications

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.1c00595

Reference57 articles.

1. Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment

2. Systematic Validation of Protein Force Fields against Experimental Data

3. ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

4. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

5. General-Purpose Machine Learning Potentials Capturing Nonlocal Charge Transfer

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1. Ichor: A Python library for computational chemistry data management and machine learning force field development;Journal of Computational Chemistry;2024-08-31

2. Quantum Topological Atomic Properties of 44K molecules;Scientific Data;2024-08-29

3. Going beyond the Ordered Bulk: A Perspective on the Use of the Cambridge Structural Database for Predictive Materials Design;Crystal Growth & Design;2024-08-19

4. Incorporating Noncovalent Interactions in Transfer Learning Gaussian Process Regression Models for Molecular Simulations;Journal of Chemical Theory and Computation;2024-07-09

5. Exchange‐correlation effects in interatomic energies for pure density functionals and their application to the molecular energy prediction;Journal of Computational Chemistry;2024-06-07

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