A lattice model approach to the morphology formation from ternary mixtures during the evaporation of one component

TL;DR

This study models the morphology formation in ternary mixtures during solvent evaporation using a lattice-based approach, providing insights into phase separation relevant for organic solar cell fabrication.

Contribution

It introduces a generalized lattice model with Monte Carlo simulations to analyze morphology formation in ternary mixtures during evaporation, linking parameters to phase separation.

Findings

Model reproduces key experimental morphological features

Parameters influence phase separation regions

Qualitative analysis of formed configurations

Abstract

Stimulated by experimental evidence in the field of solution--born thin films, we study the morphology formation in a three state lattice system subjected to the evaporation of one component. The practical problem that we address is the understanding of the parameters that govern morphology formation from a ternary mixture upon evaporation, as is the case in the fabrication of thin films from solution for organic photovoltaics. We use, as a tool, a generalized version of the Potts and Blume-Capel models in 2D, with the Monte Carlo Kawasaki-Metropolis algorithm, to simulate the phase behaviour of a ternary mixture upon evaporation of one of its components. The components with spin $+1$, $-1$ and $0$ in the Blume-Capel dynamics correspond to the electron--acceptor, electron--donor and solvent molecules, respectively, in a ternary mixture used in the preparation of the active layer films in an organic solar cell. Further, we introduce parameters that account for the relative composition of the mixture, temperature, and interaction between the species in the system. We identify the parameter regions that are prone to facilitate the phase separation. Furthermore, we study qualitatively the types of formed configurations. We show that even a relatively simple model, as the present one, can generate key morphological features, similar to those observed in experiments, which proves the method valuable for the study of complex systems.