A Graph Random Walk Method for Calculating Time-of-Flight Charge Mobility in Organic Semiconductors from Multiscale Simulations

TL;DR

This paper introduces a graph random walk method to efficiently compute charge carrier time-of-flight in complex organic semiconductors, providing a numerically stable alternative to traditional kinetic Monte Carlo simulations.

Contribution

The paper presents a novel graph-based random walk approach that directly calculates charge transport times, avoiding the numerical challenges of existing methods like KMC and master equations.

Findings

GRW method accurately matches master equation results

It reduces computational complexity and sampling issues

Validated on multiscale simulated materials with varying disorder

Abstract

We present a graph random walk (GRW) method for the study of charge transport properties of complex molecular materials in the time-of-flight regime. The molecules forming the material are represented by the vertices of a directed weighted graph, and the charge carriers are random walkers. The edge weights are rates for elementary jumping processes for a charge carrier to move along the edge and are determined from a combination of the energies of the involved vertices and an interaction strength. Exclusions are built into the random walk to account for the Pauli exclusion principle. In time-of-flight experiments, charge carriers are injected into the material and the time until they reach a collecting electrode is recorded. Our approach allows direct evaluation of the expected hitting time of the collecting nodes in terms of a sparse, linear system, avoiding numerically cumbersome and potentially fluctuations-prone methods based on explicit time evolution from solutions of a high-dimensional Master Equation or from kinetic Monte Carlo (KMC). We validate the GRW approach by numerical studies of charge dynamics of single and multiple carriers in diffusive and drift-diffusive regimes using a surrogate lattice model of a realistic material whose properties have been simulated within a multiscale model framework combining quantum-mechanical and molecular-mechanics methods. The surrogate model allows varying types and strengths of energetic disorder from the reference baseline. Comparison with results from the Master Equation confirms the theoretical equivalence of both approaches also in numerical implementations. We further show that KMC results show substantial deviations due to inadequate sampling. All in all, we find that the GRW method provides a powerful alternative to the more commonly used methods without sampling issues and with the benefit of making use of sparse matrix methods.