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Robust Atomistic Modeling of Materials, Organometallic, and Biochemical Systems
Author(s) -
Spicher Sebastian,
Grimme Stefan
Publication year - 2020
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.202004239
Subject(s) - molecular dynamics , generality , field (mathematics) , force field (fiction) , computer science , nanotechnology , statistical physics , quantum , biological system , variety (cybernetics) , characterization (materials science) , chemical physics , computational science , biochemical engineering , chemistry , computational chemistry , materials science , physics , mathematics , psychology , artificial intelligence , pure mathematics , psychotherapist , biology , quantum mechanics , engineering
Abstract Modern chemistry seems to be unlimited in molecular size and elemental composition. Metal‐organic frameworks or biological macromolecules involve complex architectures and a large variety of elements. Yet, a general and broadly applicable theoretical method to describe the structures and interactions of molecules beyond the 1000‐atom size regime semi‐quantitatively is not self‐evident. For this purpose, a generic force field named GFN‐FF is presented, which is completely newly developed to enable fast structure optimizations and molecular‐dynamics simulations for basically any chemical structure consisting of elements up to radon. The freely available computer program requires only starting coordinates and elemental composition as input from which, fully automatically, all potential‐energy terms are constructed. GFN‐FF outperforms other force fields in terms of generality and accuracy, approaching the performance of much more elaborate quantum‐mechanical methods in many cases.