Molecular single crystal materials have demonstrated their elasticity and flexibility recently, highlighting potential applications in flexible electronics. Mechanical strain has significant impact on charge mobility within these crystals. However, the mechanism underlying the dependence of charge mobility on mechanical strain remains elusive. To address this, we combined molecular dynamics, machine learning and Marcus charge transport theory to determine the strain-mobility relationship, in which the machine learning model was applied to accurately predict electronic coupling from molecular structures under the influence of dynamic disorder. Our simulation results of pentacene reveal that a 5% tensile strain along the a-axis enhances charge mobility by 55% along the b-axis, and a 5% tensile strain along the b-axis reduces mobility by 33% in the b-axis. Topological analysis shows that tensile strain along the a-axis reduces intermolecular distance, enhancing the effective charge transport network, while b-axis strain increases these distances, hindering charge transport. Crucially, our simulation indicates that strain along the b-axis significantly enhances the translational and rotational motion of pentacene molecules, thereby broadening the distribution of electronic couplings. The time correlation function of electronic coupling further reveals that strain modifies the temporal characteristics of dynamic disorder, with b-axis strain inducing stronger low-frequency coupling fluctuations which further limit charge transport. Consequently, charge mobility prediction that neglects dynamic disorder can be inaccurate. This study highlights the strain-dependent charge mobility in molecular single crystals and clarifies the boundaries of applicability for fixed electronic coupling models.
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Chen et al. (2026) studied this question.
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