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Title: Quantifying Energetic and Entropic Pathways in Molecular Systems

Abstract

When examining dynamics occurring at nonzero temperatures, both energy and entropy must be taken into account to describe activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called state predictive information bottleneck (SPIB) to find nonlinear reaction coordinates for three systems of varying complexity. SPIB is able to correctly predict an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Lastly, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy, energy, and enthalpy barriers in physical systems, which can then be used to enhance the understanding and sampling of different activated mechanisms.

Authors:
 [1]; ORCiD logo [1]; ORCiD logo [1]
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  1. Univ. of Maryland, College Park, MD (United States)
Publication Date:
Research Org.:
Univ. of Maryland, College Park, MD (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1991216
Grant/Contract Number:  
SC0021009
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry. B
Additional Journal Information:
Journal Volume: 126; Journal Issue: 21; Journal ID: ISSN 1520-6106
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Chemical reactions; Computer simulations; Entropy; Free energy; Vesicles

Citation Formats

Beyerle, Eric R., Mehdi, Shams, and Tiwary, Pratyush. Quantifying Energetic and Entropic Pathways in Molecular Systems. United States: N. p., 2022. Web. doi:10.1021/acs.jpcb.2c01782.
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Beyerle, Eric R., Mehdi, Shams, & Tiwary, Pratyush. Quantifying Energetic and Entropic Pathways in Molecular Systems. United States. https://doi.org/10.1021/acs.jpcb.2c01782
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Beyerle, Eric R., Mehdi, Shams, and Tiwary, Pratyush. Mon . "Quantifying Energetic and Entropic Pathways in Molecular Systems". United States. https://doi.org/10.1021/acs.jpcb.2c01782. https://www.osti.gov/servlets/purl/1991216.
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@article{osti_1991216,
title = {Quantifying Energetic and Entropic Pathways in Molecular Systems},
author = {Beyerle, Eric R. and Mehdi, Shams and Tiwary, Pratyush},
abstractNote = {When examining dynamics occurring at nonzero temperatures, both energy and entropy must be taken into account to describe activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called state predictive information bottleneck (SPIB) to find nonlinear reaction coordinates for three systems of varying complexity. SPIB is able to correctly predict an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Lastly, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy, energy, and enthalpy barriers in physical systems, which can then be used to enhance the understanding and sampling of different activated mechanisms.},
doi = {10.1021/acs.jpcb.2c01782},
journal = {Journal of Physical Chemistry. B},
number = 21,
volume = 126,
place = {United States},
year = {Mon May 23 00:00:00 EDT 2022},
month = {Mon May 23 00:00:00 EDT 2022}
}
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