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Cited by 890

The DOI matches its Crossref record; 192 of the 192 references it cites were found in a registry or an index.

Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry**

Open access
Bursch, Markus, Mewes, Jan‐Michael, Hansen, Andreas, Grimme, Stefan·2022·Angewandte Chemie International Edition

Abstract

Nowadays, many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. The lion's share of these quantum‐chemical calculations applies density functional theory (DFT) evaluated in atomic‐orbital basis sets. This work provides best‐practice guidance on the numerous methodological and technical aspects of DFT calculations in three parts: Firstly, we set the stage and introduce a step‐by‐step decision tree to choose a computational protocol that models the experiment as closely as possible. Secondly, we present a recommendation matrix to guide the choice of functional and basis set depending on the task at hand. A particular focus is on achieving an optimal balance between accuracy, robustness, and efficiency through multi‐level approaches. Finally, we discuss selected representative examples to illustrate the recommended protocols and the effect of methodological choices.

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Metadata

Authors
Bursch, M., Mewes, J., Hansen, A., & Grimme, S.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2022-09-14
Volume
61
Issue
42
Pages
e202205735-e202205735
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W4295779282
Cited by
890
References
192
FWCI
69.53
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry**. https://app.cochat.ai/papers/10.1002/anie.202205735
The paper
Bursch, M., Mewes, J., Hansen, A., & Grimme, S. (2022). Best‐Practice DFT Protocols for Basic Molecular Computational Chemistry**. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.202205735

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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