Inverse Design of Tetracene Polymorphs with Enhanced Singlet Fission Performance by Property-Based Genetic Algorithm Optimization

ORAL

Abstract

The efficiency of solar cells may be improved by using singlet fission (SF), in which one singlet exciton splits into two triplet excitons. SF occurs in molecular crystals. A molecule may crystallize in more than one form, a phenomenon known as polymorphism. Crystal structure may affect SF performance. In the common form of tetracene, SF is experimentally known to be slightly endoergic. A second, metastable polymorph of tetracene has been found to exhibit better SF performance. Here, we conduct inverse design of the crystal packing of tetracene using a genetic algorithm (GA) with a fitness function tailored to simultaneously optimize the SF rate and the lattice energy. The property-based GA successfully generates more structures predicted to have higher SF rates and provides insight into packing motifs associated with improved SF performance. For the structures within the polymorph energy range, we use many-body perturbation theory within the GW approximaiton and the Bethe-Salpeter equaiton (GW+BSE) to evaluate the singlet and triplet exciton energies and the degree of charge transfer character of the singlet exciton wave-funciton. We find a putative polymorph predicted to have superior SF performance to the two forms of tetracene, whose structures have been determined experimentally. The putative structure has a lattice energy within 1.5 kJ/mol of the most stable common form of tetracene.

* This research was supported by the National Science Foundation (NSF) Division of Materials Research (DMR) through Grant DMR-2131944

Publication: Chem. Mater. 35, 1373 (2023) DOI: 10.1021/acs.chemmater.2c03444

Presenters

  • Siyu Gao

    Carnegie Mellon University

Authors

  • Noa Marom

    Carnegie Mellon University

  • Rithwik Tom

    Carnegie Mellon University

  • Siyu Gao

    Carnegie Mellon University

  • Imanuel Bier

    Carnegie Mellon University

  • Josef Michl

    University of Colorado, Boulder

  • Kaiji Zhao

    Carnegie Mellon University

  • Yi Yang

    Carnegie Mellon University

  • Eric A Buchanan

    University of Colorado, Boulder

  • Alexandr Zaykov

    Czech Academy of Sciences

  • Zdeněk Havlas

    Czech Academy of Sciences