Accurate coarse-graining of small organic molecules in melts and thin films using density-dependent potentials

TL;DR

This paper introduces a density-dependent coarse-graining method for small organic molecules that accurately models inhomogeneous systems like thin films, improving simulation fidelity at interfaces.

Contribution

The authors develop a novel coarse-graining approach incorporating local-density-dependent potentials to better simulate inhomogeneous organic systems.

Findings

Accurately reproduces bulk densities and radial distribution functions.

Successfully captures molecular orientations at liquid-vacuum interfaces.

Enhances the predictive power of molecular simulations for organic thin films.

Abstract

Conjugated organic molecules play a central role in a wide range of optoelectronic devices, including organic light-emitting diodes, organic field-effect transistors, and organic solar cells. A major bottleneck in the computational design of these materials is the discrepancy between simulation and experimental time and length scales. Coarse-graining (CG) offers a promising solution to bridge this gap by reducing redundant degrees of freedom and smoothing the potential energy landscape, thereby significantly accelerating molecular dynamics simulations. However, standard CG models are typically parameterized from homogeneous bulk simulations and assume density-independent effective interactions. As a consequence, they often fail to replicate inhomogeneous systems, such as (free-standing) thin films, due to an incorrect representation of liquid-vacuum interfacial properties. In this work, we develop a CG parametrization strategy that incorporates local-density-dependent potentials to capture material heterogeneities. We evaluate the methodology by simulating free-standing films and comparing interfacial orientational order parameters between all-atom and CG simulations. The resulting CG models accurately reproduce bulk densities and radial distribution functions as well as molecular orientations at the liquid-vacuum interface. This work paves the way for reliable, computation-driven predictions of atomically resolved interfacial ordering in organic molecular systems.