Revised M06-L functional for improved accuracy on chemical reaction barrier heights, noncovalent interactions, and solid-state physics

Ying Wang, Xinsheng Jin, Haoyu S. Yu, Donald G Truhlar, Xiao He

Research output: Contribution to journalArticlepeer-review

136 Scopus citations


We present the revM06-L functional, which we designed by optimizing against a larger database than had been used for Minnesota 2006 local functional (M06-L) and by using smoothness restraints. The optimization strategy reduced the number of parameters from 34 to 31 because we removed some large terms that increased the required size of the quadrature grid and the number of self-consistent-field iterations. The mean unsigned error (MUE) of revM06-L on 422 chemical energies is 3.07 kcal/mol, which is improved from 3.57 kcal/mol calculated by M06-L. The MUE of revM06-L for the chemical reaction barrier height database (BH76) is 1.98 kcal/mol, which is improved by more than a factor of 2 with respect to the M06-L functional. The revM06-L functional gives the best result among local functionals tested for the noncovalent interaction database (NC51), with an MUE of only 0.36 kcal/mol, and the MUE of revM06-L for the solid-state lattice constant database (LC17) is half that for M06-L. The revM06-L functional also yields smoother potential curves, and it predicts more-accurate results than M06-L for seven out of eight diversified test sets not used for parameterization. We conclude that the revM06-L functional is well suited for a broad range of applications in chemistry and condensed-matter physics.

Original languageEnglish (US)
Pages (from-to)8487-8492
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number32
StatePublished - Aug 8 2017

Bibliographical note

Funding Information:
We thank Pragya Verma for helpful assistance. This work was supported by the National Natural Science Foundation of China (Grants 21303057 and 21673074), Ministry of Science and Technology of China (Grant 2016YFA0501700), Specialized Research Fund for the Doctoral Program of Higher Education (Grant 20130076120019), Youth Top-Notch Talent Support Program of Shanghai, New York University–East China Normal University (NYU–ECNU) Center for Computational Chemistry at NYU Shanghai, and US Department of Energy, Basic Energy Sciences (Award DE-SC0012702 to the Inorganometallic Catalysis Design Center).

Publisher Copyright:
© 2017, National Academy of Sciences. All rights reserved.


  • Chemical energetics
  • Chemical structures
  • Kohn−Sham density functional theory
  • Molecular thermochemistry
  • Solid-state physics


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