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Analytical nuclear gradients for the range-separated many-body dispersion model of noncovalent interactions

Journal Article · · Chemical Science
DOI:https://doi.org/10.1039/c5sc03234b· OSTI ID:1467449
 [1];  [2];  [3];  [4];  [2]
  1. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry and Chemical Biology; Harvard University
  2. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry and Chemical Biology
  3. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry; Cornell Univ., Ithaca, NY (United States). Dept. of Chemistry and Chemical Biology
  4. Harvard Univ., Cambridge, MA (United States). Dept. of Chemistry; Princeton Univ., NJ (United States). Princeton Inst. for the Science and Technology of Materials, Dept. of Physics, and Program in Applied and Computational Mathematics
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An accurate treatment of the long-range electron correlation energy, including van der Waals (vdW) or dispersion interactions, is essential for describing the structure, dynamics, and function of a wide variety of systems. Among the most accurate models for including dispersion into density functional theory (DFT) is the range-separated many-body dispersion (MBD) method [A. Ambrosetti et al., J. Chem. Phys., 2014, 140, 18A508], in which the correlation energy is modeled at short-range by a semi-local density functional and at long-range by a model system of coupled quantum harmonic oscillators. In this work, we develop analytical gradients of the MBD energy with respect to nuclear coordinates, including all implicit coordinate dependencies arising from the partitioning of the charge density into Hirshfeld effective volumes. To demonstrate the efficiency and accuracy of these MBD gradients for geometry optimizations of systems with intermolecular and intramolecular interactions, we optimized conformers of the benzene dimer and isolated small peptides with aromatic side-chains. We find excellent agreement with the wavefunction theory reference geometries of these systems (at a fraction of the computational cost) and find that MBD consistently outperforms the popular TS and D3(BJ) dispersion corrections. To demonstrate the performance of the MBD model on a larger system with supramolecular interactions, we optimized the C60@C60H28 buckyball catcher host–guest complex. In our analysis, we also find that neglecting the implicit nuclear coordinate dependence arising from the charge density partitioning, as has been done in prior numerical treatments, leads to an unacceptable error in the MBD forces, with relative errors of ~20% (on average) that can extend well beyond 100%.

Research Organization:
Princeton Univ., NJ (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Grant/Contract Number:
SC0008626
OSTI ID:
1467449
Journal Information:
Chemical Science, Journal Name: Chemical Science Journal Issue: 3 Vol. 7; ISSN 2041-6520; ISSN CSHCBM
Publisher:
Royal Society of ChemistryCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (14)

First-principles modeling of molecular crystals: structures and stabilities, temperature and pressure: First-principles modeling of molecular crystals
  • Hoja, Johannes; Reilly, Anthony M.; Tkatchenko, Alexandre
  • Wiley Interdisciplinary Reviews: Computational Molecular Science, Vol. 7, Issue 1 https://doi.org/10.1002/wcms.1294
journal December 2016
First-principles stability ranking of molecular crystal polymorphs with the DFT+MBD approach journal January 2018
Theory and practice of modeling van der Waals interactions in electronic-structure calculations journal January 2019
Communication: Charge-population based dispersion interactions for molecules and materials journal April 2016
Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning journal June 2018
Geometry optimisations with a nonlocal density-functional theory method based on a double Hirshfeld partitioning journal July 2018
Isotope effects in liquid water via deep potential molecular dynamics journal October 2019
Advanced capabilities for materials modelling with Quantum ESPRESSO journal October 2017
Reliable and practical computational description of molecular crystal polymorphs journal January 2019
Advanced capabilities for materials modelling with Quantum ESPRESSO text January 2017
Communication: Charge-Population Based Dispersion Interactions for Molecules and Materials text January 2016
Advanced capabilities for materials modelling with Quantum ESPRESSO text January 2017
Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning text January 2017
Isotope Effects in Liquid Water via Deep Potential Molecular Dynamics text January 2019

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