Accurate Ionization Potentials and Electron Affinities of Acceptor Molecules I. Reference Data at the CCSD(T) Complete Basis Set Limit

Ryan M. Richard, Michael S. Marshall, O. Dolgounitcheva, J. V. Ortiz, Jean-Luc Bredas, Noa Marom, C. David Sherrill

Research output: Contribution to journalArticlepeer-review

76 Scopus citations


© 2016 American Chemical Society. In designing organic materials for electronics applications, particularly for organic photovoltaics (OPV), the ionization potential (IP) of the donor and the electron affinity (EA) of the acceptor play key roles. This makes OPV design an appealing application for computational chemistry since IPs and EAs are readily calculable from most electronic structure methods. Unfortunately reliable, high-accuracy wave function methods, such as coupled cluster theory with single, double, and perturbative triples [CCSD(T)] in the complete basis set (CBS) limit are too expensive for routine applications to this problem for any but the smallest of systems. One solution is to calibrate approximate, less computationally expensive methods against a database of high-accuracy IP/EA values; however, to our knowledge, no such database exists for systems related to OPV design. The present work is the first of a multipart study whose overarching goal is to determine which computational methods can be used to reliably compute IPs and EAs of electron acceptors. This part introduces a database of 24 known organic electron acceptors and provides high-accuracy vertical IP and EA values expected to be within ±0.03 eV of the true non-relativistic, vertical CCSD(T)/CBS limit. Convergence of IP and EA values toward the CBS limit is studied systematically for the Hartree-Fock, MP2 correlation, and beyond-MP2 coupled cluster contributions to the focal point estimates.
Original languageEnglish (US)
Pages (from-to)595-604
Number of pages10
JournalJournal of Chemical Theory and Computation
Issue number2
StatePublished - Jan 25 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This material is based upon work supported by the National Science Foundation (Grants No. CHE-1300497 and ACI-1147843). The computer resources of the Center for Computational Molecular Science and Technology are funded through a National Science Foundation CRIF Award (CHE-0946869). Computer time was provided by the National Energy Research Scientific Computing Center (NERSC), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-05CH11231.


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