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Title: Benchmarking Semiempirical Methods To Compute Electrochemical Formal Potentials

Abstract

Computational methods to predict and tune electrochemical redox potentials are important for the development of energy technologies. Here, we benchmark several semiempirical models to compute reduction potentials of organic molecules, comparing approaches based on (1) energy differences between the S 0 and one-electron-reduced D 0 states of the isolated molecules and (2) an orbital energy shift approach based on tuning the charge-transfer triplet energy of the Ag 20-molecule complex; the second model enables explicit modeling of electrode–molecule interactions. For molecules in solution, the two models yield nearly identical results. Both PM7 and PM6 predict formal potentials with only a slight loss of accuracy compared to standard density functional theory models, and the results are robust across several choices of geometries and implicit solvent models. PM6 and PM7 show dramatically improved accuracy over older semiempirical Hamiltonians (MNDO, AM1, PM3, and INDO/S). However, our recently developed INDO parameters model the electronic properties of our Ag 20 model electrode much more accurately than does PM7. These results demonstrate the need for further development of semiempirical models to accurately model molecules on surfaces.

Authors:
ORCiD logo [1];  [1]; ORCiD logo [1]
  1. Northwestern Univ., Evanston, IL (United States). Dept. of Chemistry
Publication Date:
Research Org.:
Northwestern Univ., Evanston, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1464278
Alternate Identifier(s):
OSTI ID: 1508603
Grant/Contract Number:  
SC0004752
Resource Type:
Published Article
Journal Name:
Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory
Additional Journal Information:
Journal Volume: 122; Journal Issue: 33; Journal ID: ISSN 1089-5639
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 97 MATHEMATICS AND COMPUTING

Citation Formats

Gieseking, Rebecca L. M., Ratner, Mark A., and Schatz, George C. Benchmarking Semiempirical Methods To Compute Electrochemical Formal Potentials. United States: N. p., 2018. Web. doi:10.1021/acs.jpca.8b05143.
Gieseking, Rebecca L. M., Ratner, Mark A., & Schatz, George C. Benchmarking Semiempirical Methods To Compute Electrochemical Formal Potentials. United States. doi:10.1021/acs.jpca.8b05143.
Gieseking, Rebecca L. M., Ratner, Mark A., and Schatz, George C. Thu . "Benchmarking Semiempirical Methods To Compute Electrochemical Formal Potentials". United States. doi:10.1021/acs.jpca.8b05143.
@article{osti_1464278,
title = {Benchmarking Semiempirical Methods To Compute Electrochemical Formal Potentials},
author = {Gieseking, Rebecca L. M. and Ratner, Mark A. and Schatz, George C.},
abstractNote = {Computational methods to predict and tune electrochemical redox potentials are important for the development of energy technologies. Here, we benchmark several semiempirical models to compute reduction potentials of organic molecules, comparing approaches based on (1) energy differences between the S0 and one-electron-reduced D0 states of the isolated molecules and (2) an orbital energy shift approach based on tuning the charge-transfer triplet energy of the Ag20-molecule complex; the second model enables explicit modeling of electrode–molecule interactions. For molecules in solution, the two models yield nearly identical results. Both PM7 and PM6 predict formal potentials with only a slight loss of accuracy compared to standard density functional theory models, and the results are robust across several choices of geometries and implicit solvent models. PM6 and PM7 show dramatically improved accuracy over older semiempirical Hamiltonians (MNDO, AM1, PM3, and INDO/S). However, our recently developed INDO parameters model the electronic properties of our Ag20 model electrode much more accurately than does PM7. These results demonstrate the need for further development of semiempirical models to accurately model molecules on surfaces.},
doi = {10.1021/acs.jpca.8b05143},
journal = {Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory},
number = 33,
volume = 122,
place = {United States},
year = {2018},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1021/acs.jpca.8b05143

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