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Title: Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics

Abstract

In this study, the photofragmentation dynamics of tetranitromethane (TNM) is explored by a spin-unrestricted time-dependent excited-state molecular dynamics (u-TDESMD) algorithm based on Rabi oscillations and principles similar to trajectory surface hopping, with a midintensity field approximation. The leading order process is represented by the molecule undergoing cyclic excitations and de-excitations. During excitation cycles, the nuclear kinetic energy is accumulated to overcome the dissociation barriers in the reactant and a sequence of intermediates. The dissociation pathway includes the ejection of NO2 groups followed by the formation of NO and CO. The simulated mass spectra at the ab initio level, based on the bond length in possible fragments, are extracted from simulation trajectories. Finally, the recently developed methodology has the potential to model and monitor photoreactions with open-shell intermediates and radicals.

Authors:
 [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Univ. of South Dakota, Vermillion, SD (United States). Dept. of Chemistry; North Dakota State Univ., Fargo, ND (United States). Dept. of Chemistry and Biochemistry
  2. North Dakota State Univ., Fargo, ND (United States). Dept. of Coatings and Polymeric Materials
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1483859
Grant/Contract Number:  
AC02-05CH11231; SC0001717
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physical Chemistry Letters
Additional Journal Information:
Journal Volume: 8; Journal Issue: 14; Journal ID: ISSN 1948-7185
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Han, Yulun, Rasulev, Bakhtiyor, and Kilin, Dmitri S. Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics. United States: N. p., 2017. Web. doi:10.1021/acs.jpclett.7b01330.
Han, Yulun, Rasulev, Bakhtiyor, & Kilin, Dmitri S. Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics. United States. https://doi.org/10.1021/acs.jpclett.7b01330
Han, Yulun, Rasulev, Bakhtiyor, and Kilin, Dmitri S. Fri . "Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics". United States. https://doi.org/10.1021/acs.jpclett.7b01330. https://www.osti.gov/servlets/purl/1483859.
@article{osti_1483859,
title = {Photofragmentation of Tetranitromethane: Spin-Unrestricted Time-Dependent Excited-State Molecular Dynamics},
author = {Han, Yulun and Rasulev, Bakhtiyor and Kilin, Dmitri S.},
abstractNote = {In this study, the photofragmentation dynamics of tetranitromethane (TNM) is explored by a spin-unrestricted time-dependent excited-state molecular dynamics (u-TDESMD) algorithm based on Rabi oscillations and principles similar to trajectory surface hopping, with a midintensity field approximation. The leading order process is represented by the molecule undergoing cyclic excitations and de-excitations. During excitation cycles, the nuclear kinetic energy is accumulated to overcome the dissociation barriers in the reactant and a sequence of intermediates. The dissociation pathway includes the ejection of NO2 groups followed by the formation of NO and CO. The simulated mass spectra at the ab initio level, based on the bond length in possible fragments, are extracted from simulation trajectories. Finally, the recently developed methodology has the potential to model and monitor photoreactions with open-shell intermediates and radicals.},
doi = {10.1021/acs.jpclett.7b01330},
journal = {Journal of Physical Chemistry Letters},
number = 14,
volume = 8,
place = {United States},
year = {Fri Jun 16 00:00:00 EDT 2017},
month = {Fri Jun 16 00:00:00 EDT 2017}
}

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