Predictive Model of Charge Mobilities in Organic Semiconductor Small Molecules with Force-Matched Potentials

Varuni Dantanarayana, Tahereh Nematiaram, Daniel Vong, John E. Anthony, Alessandro Troisi, Kien Nguyen Cong, Nir Goldman, Roland Faller, Adam J. Moulé

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Charge mobility of crystalline organic semiconductors (OSC) is limited by local dynamic disorder. Recently, the charge mobility for several high mobility OSCs, including TIPS-pentacene, were accurately predicted from a density functional theory (DFT) simulation constrained by the crystal structure and the inelastic neutron scattering spectrum, which provide direct measures of the structure and the dynamic disorder in the length scale and energy range of interest. However, the computational expense required for calculating all of the atomic and molecular forces is prohibitive. Here we demonstrate the use of density functional tight binding (DFTB), a semiempirical quantum mechanical method that is 2 to 3 orders of magnitude more efficient than DFT. We show that force matching a many-body interaction potential to DFT derived forces yields highly accurate DFTB models capable of reproducing the low-frequency intricacies of experimental inelastic neutron scattering (INS) spectra and accurately predicting charge mobility. We subsequently predicted charge mobilities from our DFTB model of a number of previously unstudied structural analogues to TIPS-pentacene using dynamic disorder from DFTB and transient localization theory. The approach we establish here could provide a truly rapid simulation pathway for accurate materials properties prediction, in our vision applied to new OSCs with tailored properties.

Original languageEnglish
Pages (from-to)3494-3503
Number of pages10
JournalJournal of Chemical Theory and Computation
Volume16
Issue number6
DOIs
StatePublished - Jun 9 2020

Bibliographical note

Funding Information:
This research was supported by the Department of Energy, Basic Energy Sciences, Award DE-SC0010419, including salary for V.D. and A.J.M. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The INS spectrum was measured at the Spallation Neutron Source, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory, partly supported by LLNL under Contract DE-AC52-07NA27344. T.N. and A.T. acknowledge funding from ERC (Grant No. 862102).

Funding Information:
This research was supported by the Department of Energy, Basic Energy Sciences, Award DE-SC0010419 including salary for V.D. and A.J.M. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The INS spectrum was measured at the Spallation Neutron Source, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory, partly supported by LLNL under Contract DE-AC52-07NA27344. T.N. and A.T. acknowledge funding from ERC (Grant No. 862102).

Publisher Copyright:
Copyright © 2020 American Chemical Society.

ASJC Scopus subject areas

  • Computer Science Applications
  • Physical and Theoretical Chemistry

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