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Embedding Methods for Quantum Chemistry: Applications from Materials to Life Sciences
Author(s) -
Leighton O. Jones,
Martín A. Mosquera,
George C. Schatz,
Mark A. Ratner
Publication year - 2020
Publication title -
journal of the american chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.115
H-Index - 612
eISSN - 1520-5126
pISSN - 0002-7863
DOI - 10.1021/jacs.9b10780
Subject(s) - embedding , chemistry , scaling , perspective (graphical) , underpinning , field (mathematics) , nanotechnology , macro , biochemical engineering , quantum , management science , theoretical computer science , computer science , artificial intelligence , quantum mechanics , physics , engineering , mathematics , civil engineering , geometry , materials science , pure mathematics , programming language
Quantum mechanical embedding methods hold the promise to transform not just the way calculations are performed, but to significantly reduce computational costs and improve scaling for macro-molecular systems containing hundreds if not thousands of atoms. The field of embedding has grown increasingly broad with many approaches of different intersecting flavors. In this perspective, we lay out the methods into two streams: QM:MM and QM:QM, showcasing the advantages and disadvantages of both. We provide a review of the literature, the underpinning theories including our contributions, and we highlight current applications with select examples spanning both materials and life sciences. We conclude with prospects and future outlook on embedding, and our view on the use of universal test case scenarios for cross-comparisons of the many available (and future) embedding theories.

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