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When does a functional correctly describe both the structure and the energy of the transition state?

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Abstract

Requiring that several properties are well reproduced is a severe test on density functional approximations. This can be assessed through the estimation of joint and conditional success probabilities. An example is provided for a small set of molecules, for properties characterizing the transition states (geometries and energies).

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Acknowledgements

Henry Chermette was an early fighter on the path of density functional approximations. Applying them carefully was one of his main concerns. It is thus our pleasure to dedicate our paper to him. This work was supported by the Ministry of Science and Technology (2013CB834606, 2011CB808505), and National Natural Science Foundation of China (91027044, 21133004).

Author information

Authors and Affiliations

  1. Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, Shanghai, 200433, China

    Neil Qiang Su & Xin Xu

  2. CNRS, UMR8000, Laboratoire de Chimie Physique, F-91405, Orsay, France

    Pascal Pernot

  3. Univ. Paris-Sud, UMR8000, Laboratoire de Chimie Physique, F-91405, Orsay, France

    Pascal Pernot

  4. CNRS, UMR7616, Laboratoire de Chimie Théorique, F-75005, Paris, France

    Andreas Savin

  5. UPMC Univ Paris 06, UMR7616, Laboratoire de Chimie Théorique, F-75005, Paris, France

    Andreas Savin

Authors
  1. Neil Qiang Su
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  2. Pascal Pernot
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  3. Xin Xu
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  4. Andreas Savin
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Corresponding author

Correspondence to Andreas Savin.

Additional information

This paper belongs to Topical Collection Festschrift in Honor of Henry Chermette

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Appendix

Appendix

Table 1 The acronyms for 33 representative density functional approximations
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Su, N.Q., Pernot, P., Xu, X. et al. When does a functional correctly describe both the structure and the energy of the transition state?. J Mol Model 23, 65 (2017). https://doi.org/10.1007/s00894-017-3229-8

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  • DOI: https://doi.org/10.1007/s00894-017-3229-8

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