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Cited by 266

The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.

A computational chemist's guide to accurate thermochemistry for organic molecules

Open access
Karton, Amir·2016·WIREs Computational Molecular Science
DOI 10.1002/wcms.1249
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Abstract

Composite ab initio methods are multistep theoretical procedures specifically designed to obtain highly accurate thermochemical and kinetic data with confident sub‐kcal mol−1 or sub‐kJ mol−1 accuracy. These procedures include all energetic terms that contribute to the molecular binding energies at these levels of accuracy (e.g., CCSD(T), post‐CCSD(T), core–valence, relativistic, spin‐orbit, Born–Oppenheimer, and zero‐point vibrational energy corrections). Basis‐set extrapolations (and other basis‐set acceleration techniques) are used for obtaining these terms at sufficiently high levels of accuracy. Major advances in computer hardware and theoretical methodologies over the past two decades have enabled the application of these procedures to medium‐sized organic systems (e.g., ranging from benzene and hexane to amino acids and DNA bases). With these advances, there has been a proliferation in the number of developed composite ab initio methods. We give an overview of the accuracy and applicability of the various types of composite ab initio methods that were developed in recent years. General recommendations to guide selection of the most suitable method for a given problem are presented, with a special emphasis on organic molecules. WIREs Comput Mol Sci 2016, 6:292–310. doi: 10.1002/wcms.1249 This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry > Thermochemistry

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Metadata

Authors
Karton, A.
Venue
WIREs Computational Molecular Science
Publisher
Wiley
Published
2016-02-15
Volume
6
Issue
3
Pages
292-310
ISSN
  • 1759-0876 (ISSN-L)
  • 1759-0884
DOI
10.1002/wcms.1249
OpenAlex
W2285001074
Cited by
266
References
95
FWCI
13.49
Type
journal article
Language
en
Open access
green

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