Ionization Energies, Electron Affinities, and Polarization Energies of Organic Molecular Crystals: Quantitative Estimations from a Polarizable Continuum Model (PCM)–Tuned Range-Separated Density Functional Approach
Type
ArticleAuthors
Sun, Haitao
Ryno, Sean
Zhong, Cheng
Ravva, Mahesh Kumar

Sun, Zhenrong
Körzdörfer, Thomas
Bredas, Jean-Luc

KAUST Department
KAUST Solar Center (KSC)Laboratory for Computational and Theoretical Chemistry of Advanced Materials
Material Science and Engineering Program
Physical Science and Engineering (PSE) Division
Date
2016-05-26Online Publication Date
2016-05-26Print Publication Date
2016-06-14Permanent link to this record
http://hdl.handle.net/10754/610565
Metadata
Show full item recordAbstract
We propose a new methodology for the first-principles description of the electronic properties relevant for charge transport in organic molecular crystals. This methodology, which is based on the combination of a non-empirical, optimally tuned range-separated hybrid functional with the polarizable continuum model, is applied to a series of eight representative molecular semiconductor crystals. We show that it provides ionization energies, electron affinities, and transport gaps in very good agreement with experimental values as well as with the results of many-body perturbation theory within the GW approximation at a fraction of the computational costs. Hence, this approach represents an easily applicable and computationally efficient tool to estimate the gas-to-crystal-phase shifts of the frontier-orbital quasiparticle energies in organic electronic materials.Citation
Ionization Energies, Electron Affinities, and Polarization Energies of Organic Molecular Crystals: Quantitative Estimations from a Polarizable Continuum Model (PCM)–Tuned Range-Separated Density Functional Approach 2016 Journal of Chemical Theory and ComputationSponsors
The authors thank Prof. S. Kümmel for helpful discussions about the combination of the optimal tuning procedure with polarizable continuum solvation models. This work has been supported by King Abdullah University of Science and Technology (KAUST). We acknowledge the KAUST IT Research Computing Team for providing computational and storage resources.Publisher
American Chemical Society (ACS)PubMed ID
27183355Additional Links
http://pubs.acs.org/doi/abs/10.1021/acs.jctc.6b00225ae974a485f413a2113503eed53cd6c53
10.1021/acs.jctc.6b00225
Scopus Count
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