Structural and excited-state properties of oligoacene crystals from first principles

TL;DR

This study employs advanced computational methods to accurately predict the structure and excited state properties of oligoacene crystals, crucial for optoelectronic applications, by combining DFT with vdW corrections and MBPT.

Contribution

It demonstrates that combining vdW-inclusive DFT with MBPT can reliably predict both lattice constants and excited states of oligoacene crystals, advancing first-principles modeling of organic materials.

Findings

vdW methods predict lattice constants within 1% of experiments

MBPT yields excitation energies within a few tenths of an eV when using optimized geometries

Trends in excitation energies across the acene series are elucidated

Abstract

Molecular crystals are a prototypical class of van der Waals (vdW) bound organic materials with excited state properties relevant for optoelectronics applications. Predicting the structure and excited state properties of molecular crystals presents a challenge for electronic structure theory, as standard approximations to density functional theory (DFT) do not capture long range vdW dispersion interactions and do not yield excited state properties. In this work, we use a combination of DFT including vdW forces) using both non local correlation functionals and pair wise correction methods (together with many body perturbation theory (MBPT) to study the geometry and excited states, respectively, of the entire series of oligoacene crystals, from benzene to hexacene. We find that vdW methods can predict lattice constants within 1 percent of the experimental measurements, on par with the previously reported accuracy of pairwise approximations for the same systems. We further find that excitation energies are sensitive to geometry, but if optimized geometries are used MBPT can yield excited state properties within a few tenths of an eV from experiment. We elucidate trends in MBPT computed charged and neutral excitation energies across the acene series and discuss the role of common approximations used in MBPT.