skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation

Abstract

Automatic kinetic mechanism generation, virtual high-throughput screening, and automatic transition state search are currently trending applications requiring exploration of a large molecule space. Large-scale search requires fast and accurate estimation of molecules’ properties of interest, such as thermochemistry. Existing approaches are not satisfactory for large polycyclic molecules: considering the number of molecules being screened, quantum chemistry (even cheap density functional theory methods) can be computationally expensive, and group additivity, though fast, is not sufficiently accurate. Here, this paper provides a fast and moderately accurate alternative by proposing a polycyclic thermochemistry estimation method that extends the group additivity method with two additional algorithms: similarity match and bicyclic decomposition. It significantly reduces Hf(298 K) estimation error from over 60 kcal/mol (group additivity method) to around 5 kcal/mol, Cp(298 K) error from 9 to 1 cal/mol/K,and S(298 K) error from 70 to 7 cal/mol/K. This method also works well for heteroatomic polycyclics.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Massachusetts Institute of Technology, Cambridge, MA (United States). Dept. of Chemical Engineering
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory, Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC).
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1461668
Grant/Contract Number:  
SC0014901; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Chemical Kinetics
Additional Journal Information:
Journal Volume: 50; Journal Issue: 4; Journal ID: ISSN 0538-8066
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; polycyclics; thermochemistry; ring corrections

Citation Formats

Han, Kehang, Jamal, Adeel, Grambow, Colin A., Buras, Zachary J., and Green, William H. An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation. United States: N. p., 2018. Web. doi:10.1002/kin.21158.
Han, Kehang, Jamal, Adeel, Grambow, Colin A., Buras, Zachary J., & Green, William H. An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation. United States. doi:10.1002/kin.21158.
Han, Kehang, Jamal, Adeel, Grambow, Colin A., Buras, Zachary J., and Green, William H. Thu . "An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation". United States. doi:10.1002/kin.21158. https://www.osti.gov/servlets/purl/1461668.
@article{osti_1461668,
title = {An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation},
author = {Han, Kehang and Jamal, Adeel and Grambow, Colin A. and Buras, Zachary J. and Green, William H.},
abstractNote = {Automatic kinetic mechanism generation, virtual high-throughput screening, and automatic transition state search are currently trending applications requiring exploration of a large molecule space. Large-scale search requires fast and accurate estimation of molecules’ properties of interest, such as thermochemistry. Existing approaches are not satisfactory for large polycyclic molecules: considering the number of molecules being screened, quantum chemistry (even cheap density functional theory methods) can be computationally expensive, and group additivity, though fast, is not sufficiently accurate. Here, this paper provides a fast and moderately accurate alternative by proposing a polycyclic thermochemistry estimation method that extends the group additivity method with two additional algorithms: similarity match and bicyclic decomposition. It significantly reduces Hf(298 K) estimation error from over 60 kcal/mol (group additivity method) to around 5 kcal/mol, Cp(298 K) error from 9 to 1 cal/mol/K,and S(298 K) error from 70 to 7 cal/mol/K. This method also works well for heteroatomic polycyclics.},
doi = {10.1002/kin.21158},
journal = {International Journal of Chemical Kinetics},
number = 4,
volume = 50,
place = {United States},
year = {2018},
month = {2}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 1 work
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
journal, January 2012


THERM: Thermodynamic property estimation for gas phase radicals and molecules
journal, September 1991

  • Ritter, Edward R.; Bozzelli, Joseph W.
  • International Journal of Chemical Kinetics, Vol. 23, Issue 9
  • DOI: 10.1002/kin.550230903

Physicochemical Properties and Thermochemistry of Propellanes
journal, July 2008

  • Osmont, Antoine; Catoire, Laurent; Gökalp, Iskender
  • Energy & Fuels, Vol. 22, Issue 4
  • DOI: 10.1021/ef8000423

Quantum chemistry structures and properties of 134 kilo molecules
journal, August 2014

  • Ramakrishnan, Raghunathan; Dral, Pavlo O.; Rupp, Matthias
  • Scientific Data, Vol. 1, Issue 1
  • DOI: 10.1038/sdata.2014.22

Thermodynamic Parameters and Group Additivity Ring Corrections for Three- to Six-Membered Oxygen Heterocyclic Hydrocarbons
journal, March 1997

  • Lay, Tsan H.; Yamada, Takahiro; Tsai, Po-Lun
  • The Journal of Physical Chemistry A, Vol. 101, Issue 13
  • DOI: 10.1021/jp9629497

Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms
journal, June 2016

  • Gao, Connie W.; Allen, Joshua W.; Green, William H.
  • Computer Physics Communications, Vol. 203
  • DOI: 10.1016/j.cpc.2016.02.013

Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods
journal, August 2015

  • Suleimanov, Yury V.; Green, William H.
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 9
  • DOI: 10.1021/acs.jctc.5b00407

Deep Learning in Drug Discovery
journal, December 2015

  • Gawehn, Erik; Hiss, Jan A.; Schneider, Gisbert
  • Molecular Informatics, Vol. 35, Issue 1
  • DOI: 10.1002/minf.201501008

Ring perception. A new algorithm for directly finding the smallest set of smallest rings from a connection table
journal, September 1993

  • Fan, Bo Tao; Panaye, Annick; Doucet, Jean Pierre
  • Journal of Chemical Information and Modeling, Vol. 33, Issue 5
  • DOI: 10.1021/ci00015a002

Additivity rules for the estimation of thermochemical properties
journal, June 1969

  • Benson, Sidney W.; Cruickshank, F. R.; Golden, D. M.
  • Chemical Reviews, Vol. 69, Issue 3
  • DOI: 10.1021/cr60259a002

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
journal, April 2015

  • Ramakrishnan, Raghunathan; Dral, Pavlo O.; Rupp, Matthias
  • Journal of Chemical Theory and Computation, Vol. 11, Issue 5
  • DOI: 10.1021/acs.jctc.5b00099