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IMOMM: A new integrated ab initio + molecular mechanics geometry optimization scheme of equilibrium structures and transition states

Maseras, Feliu, Morokuma, Keiji·1995·Journal of Computational Chemistry

Abstract

A new computational scheme integrating ab initio and molecular mechanics descriptions in different parts of the same molecule is presented. In contrast with previous approaches, this method is especially designed to allow the introduction of molecular mechanics corrections in full geometry optimizations concerning problems usually studied through ab initio calculations on model systems. The scheme proposed in this article intends to solve some of the systematic error associated with modeling through the use of molecular mechanics corrections. This method, which does not require any new parameter, evaluates explicitly the energy derivatives with respect to geometrical parameters and therefore has a straightforward application to geometry optimization. Examples of its performance on two simple cases are provided: the equilibrium geometry of cyclopropene and the energy barriers on S N 2 reactions of alkyl chloride systems. Results are in satisfactory agreement with those of full ab initio calculations in both cases. © 1995 by John Wiley & Sons, Inc.

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Metadata

Authors
Maseras, F., & Morokuma, K.
Venue
Journal of Computational Chemistry
Publisher
Wiley
Published
1995-09
Volume
16
Issue
9
Pages
1170-1179
ISSN
  • 0192-8651 (ISSN-L)
  • 1096-987X
OpenAlex
W1965378620
Cited by
1,721
References
0
FWCI
17.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: IMOMM: A new integrated ab initio + molecular mechanics geometry optimization scheme of equilibrium structures and transition states. https://app.cochat.ai/papers/10.1002/jcc.540160911
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Maseras, F., & Morokuma, K. (1995). IMOMM: A new integrated ab initio + molecular mechanics geometry optimization scheme of equilibrium structures and transition states. Journal of Computational Chemistry. https://doi.org/10.1002/jcc.540160911

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.