Publication date: 11th March 2026
Solution-processed organic semiconductors based on non-fullerene acceptors (NFAs), such as Y6, exhibit outstanding performance in organic photovoltaics. However, their photophysical properties remain difficult to predict due to structural disorder and strongly anisotropic environments. In this work, we present a comprehensive multiscale QM/MM framework combined with polarizable embedding to investigate the electronic properties of Y6 across different environments.
Thin-film disordered structures are generated via an evaporation protocol using classical molecular dynamics, providing representative atomistic configurations of solution-processed Y6 film. These structures are subsequently employed in sequential QM/MM calculations to evaluate key properties, including redox potentials, optical and fundamental gaps, exciton binding energies, and UV-Vis absorption spectra. The explicit inclusion of environmental polarization enables a detailed description of anisotropic electrostatic effects beyond conventional continuum models.
In parallel, the same methodology is applied to representative Y6 configurations extracted from the single-crystal structure, enabling direct comparison between disordered thin films and well-defined crystalline arrangements. This dual approach provides insight into the role of intermolecular packing and electronic coupling in shaping excited-state characteristics.
Our results demonstrate that anisotropic polarization effects play a crucial role in modulating the electronic structure of Y6, significantly impacting quantities relevant to device performance. This study highlights the importance of combining multiscale modeling with explicit polarization to accurately describe emerging organic semiconductors and provides a transferable framework for systems where experimental dielectric information is limited.
We acknowledge the Carl Trygger Foundation (Grant No. CTS 23:2987) for the financial support. The computations were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC) at Linköping University, partially funded by the Swedish Research Council through Grant Agreement Nos. 2022-06725 and 2018-05973.
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