Parametrization
of Extended Gaussian Disorder Models
from Microscopic Charge Transport Simulations
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Abstract
Simulations of organic semiconducting
devices using drift-diffusion
equations are vital for the understanding of their functionality as
well as for the optimization of their performance. Input parameters
for these equations are usually determined from experiments and do
not provide a direct link to the chemical structures and material
morphology. Here we demonstrate how such a parametrization can be
performed by using atomic-scale (microscopic) simulations. To do this,
a stochastic network model, parametrized on atomistic simulations,
is used to tabulate charge mobility in a wide density range. After
accounting for finite-size effects at small charge densities, the
data is fitted to the uncorrelated and correlated extended Gaussian
disorder models. Surprisingly, the uncorrelated model reproduces the
results of microscopic simulations better than the correlated one,
compensating for spatial correlations present in a microscopic system
by a large lattice constant. The proposed method retains the link
to the material morphology and the underlying chemistry and can be
used to formulate structure–property relationships or optimize
devices prior to compound synthesis