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Title: Advanced Potential Energy Surfaces for Molecular Simulation

Journal Article · · Journal of Physical Chemistry. B, Condensed Matter, Materials, Surfaces, Interfaces and Biophysical Chemistry
 [1];  [2];  [3];  [4];  [5];  [4];  [6];  [7];  [8];  [7];  [9];  [9];  [3];  [4];  [9];  [10];  [11];  [3];  [12];  [13] more »;  [14] « less
  1. Univ. of California, Berkeley, CA (United States). Dept. of Chemical and Biomolecular Engineering
  2. Bates College, Lewiston, ME (United States). Dept. of Mathematics
  3. Univ. of Southampton (United Kingdom). School of Chemistry
  4. Univ. of California, Berkeley, CA (United States). Dept. of Chemistry
  5. Univ. of Southampton (United Kingdom). School of Chemistry; Gdansk Univ. of Technology, Gdansk (Poland). Faculty of Applied Physics and Mathematics
  6. New York Univ. (NYU), NY (United States). Dept. of Chemistry
  7. Rutgers Univ., Piscataway, NJ (United States). Dept. of Chemistry and Chemical Biology
  8. National Inst. of Health (NIH), Bethesda, MD (United States). Lab. of Computational Biology, National Heart, Lung and Blood Inst.
  9. Stanford Univ., CA (United States). Dept. of Chemistry
  10. Washington Univ., St. Louis, MO (United States). Dept. Chemistry
  11. Q-Chem Inc., Pleasanton, CA (United States)
  12. Science and Technology Facilities Council (STFC), Daresbury (United Kingdom). Daresbury Lab.
  13. New York Univ. (NYU), NY (United States). Courant Inst. of Mathematical Science, and Dept. of Chemistry; NYU-ECNU, Center for Computational Chemistry at NYU, Shanghai (China)
  14. Univ. of California, Berkeley, CA (United States). Dept. of Chemistry, Dept. of Chemical and Biomolecular Engineering, and Dept. of Bioengineering

Advanced potential energy surfaces are defined as theoretical models that explicitly include many-body effects that transcend the standard fixed-charge, pairwise-additive paradigm typically used in molecular simulation. However, several factors relating to their software implementation have precluded their widespread use in condensed-phase simulations: the computational cost of the theoretical models, a paucity of approximate models and algorithmic improvements that can ameliorate their cost, underdeveloped interfaces and limited dissemination in computational code bases that are widely used in the computational chemistry community, and software implementations that have not kept pace with modern high-performance computing (HPC) architectures, such as multicore CPUs and modern graphics processing units (GPUs). Here in this Feature Article we review recent progress made in these areas, including well-defined polarization approximations and new multipole electrostatic formulations, novel methods for solving the mutual polarization equations and increasing the MD time step, combining linear-scaling electronic structure methods with new QM/MM methods that account for mutual polarization between the two regions, and the greatly improved software deployment of these models and methods onto GPU and CPU hardware platforms. Finally, we have now approached an era where multipole-based polarizable force fields can be routinely used to obtain computational results comparable to state-of-the-art density functional theory while reaching sampling statistics that are acceptable when compared to that obtained from simpler fixed partial charge force fields.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22), Scientific User Facilities Division (SC-22.3 )
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1478341
Journal Information:
Journal of Physical Chemistry. B, Condensed Matter, Materials, Surfaces, Interfaces and Biophysical Chemistry, Vol. 120, Issue 37; ISSN 1520-6106
Publisher:
American Chemical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 63 works
Citation information provided by
Web of Science

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