Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

DFT-Based Permutationally Invariant Polynomial Potentials Capture the Twists and Turns of C14H30

Published

Author(s)

Chen Qu, Paul Houston, Thomas C. Allison, Barry Schneider, Joel Bowman

Abstract

Hydrocarbons are ubiquitous as fuels, solvents, lubricants, and as the principal components of plastics and fibers, yet our ability to predict their dynamical properties is limited to force-field mechanics. Here, we report two machine-learned potential energy surfaces (PESs) for the linear 44-atom hydrocarbon C14H30 using an extensive data set of roughly 250,000 DFT (B3LYP) energies for a large variety of configurations, obtained using MM3 direct-dynamics calculations at 500 K, 1000 K and 2500 K. The surfaces, based on Permutationally Invariant Polynomials (PIPs) and using both a many-body expansion approach and a fragmented-basis approach produce precise fits for energies and forces and also produce excellent out-of-sample agreement with direct DFT calculations for torsional and dihedral angle potentials. Going beyond precision, the PESs are used in molecular dynamics calculations that demonstrate the robustness of the PESs for a large range of conformations. The many-body PIPs PES, although more compute intensive than the fragmented-basis one, is directly transferable for other linear hydrocarbons.
Citation
Journal of Chemical Theory and Computation

Keywords

permutationally invariant polynomials, potential energy surface, computational chemistry

Citation

qu, C. , Houston, P. , Allison, T. , Schneider, B. and Bowman, J. (2024), DFT-Based Permutationally Invariant Polynomial Potentials Capture the Twists and Turns of C14H30, Journal of Chemical Theory and Computation (Accessed October 7, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 23, 2024, Updated September 18, 2024