How does the nanomorphology affect charge generation, recombination, and transport in organic solar cells?
Carsten Deibel a, Fabio Le Piane a, Mario Vozza b, Francesco Mercuri b, Chen Wang a, Maria Saladina a, Roderick MacKenzie c
a Chemnitz University of Technology, Germany, Reichenhainer Straße, 70, Chemnitz, Germany
b Consiglio Nazionale delle Ricerche (CNR), Istituto per lo Studio dei Materiali Nanostrutturati (ISMN), via Gobetti, 101, Bologna, 40129, Italy
c Department of Engineering, Durham University, Lower Mount Joy, South Road, United Kingdom
Proceedings of MATSUS Spring 2026 Conference (MATSUSSpring26)
B2 Strategies to push the efficiency and stability limits of organic photovoltaics at a multiscale
Barcelona, Spain, 2026 March 23rd - 27th
Organizers: Ignasi Burgués and Maria Saladina
Invited Speaker, Carsten Deibel, presentation 245
Publication date: 15th December 2025

In novel printed organic solar cells, the device performance depends heavily on the donor–acceptor nanomorphology. We focus on two ways nanomorphology affects organic solar cells. First, we study domain connectivity by gradually diluting the donor material, an aspect of functional morphology that is linked to the tortuosity of charge transport. We observe how this affects charge generation, transport, and recombination in a state-of-the-art model system. Second, we investigate a different approach of linking nanomorphology to performance. Instead of using simple 1-dimensional drift–diffusion simulations, we now combine complex 3-dimensional simulations of realistic bulk heterojunction morphologies with machine learning. This approach has two goals. First, to find realistic solar cell parameters based on 3D models rather than effective ones based on 1D fits. Second, since 3D fitting is very time-consuming, machine learning lets us quickly predict solar cell performance and morphology from limited experimental data, reducing computation time from days to seconds.

We thank the Deutsche Forschungsgemeinschaft (DFG) for funding this work (Research Unit FOR 5387 POPULAR, Project No. 461909888).

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