Data driven approaches to quantifying charge transport in semiconducting systems

Charge transport in molecular solids, such as semiconducting polymers, is strongly affected by packing

and structural order over several length scales. We describe a computationally scalable methodology

using graph theory to explore the influence of molecular ordering on charge mobility. This model

accurately reproduces the analytical results for transport in nematic and isotropic systems, as well as

experimental results of the dependence of the charge carrier mobility on orientation correlation length

for polymers. This approach can be deployed both on continuum/experimental data as well as MD

simulation data. We illustrate with examples including (a) modeling how defect distribution (correlated

and uncorrelated) in semiconducting polymers can modify the mobility, and (b) quantifying the

resilience of charge transport. This work enables rapid (and computationally extensible) evaluation of

charge mobility semiconducting polymer devices. This work is collaborative work with the Risko group

(U Kentucky) and the Chabinyc group (UC Santa Barbara).