Multiscale Modelling of Interface Passivation Mechanisms for Perovskite Solar Cells
James McQueen a b, Vikram Vikram a, Amit Kumar b, Henry Snaith b, Saiful Islam a, Sebastian Bonilla a
a Department of Materials, University of Oxford; Oxford, UK
b Department of Physics, Clarendon Laboratory, University of Oxford, Oxford OX1 3PU, U.K
Proceedings of International Conference on Hybrid and Organic Photovoltaics (HOPV26)
Uppsala, Sweden, 2026 May 18th - 20th
Organizers: Gerrit Boschloo, Ellen Moons, Feng Gao and Anders Hagfeldt
Oral, James McQueen, presentation 121
Publication date: 11th March 2026

There is not yet a consensus on the most effective interface passivation technique to suppress non-radiative recombination and unwanted phase transitions in perovskite solar cells. A range of approaches have been demonstrated, including 2D/3D heterojunctions, organic cations, and molecular layers. However, identifying the most successful technique experimentally has proven challenging, given the difficulty in characterising the underlying atomistic mechanisms driving improvements. Herein, we exploit computational modelling techniques at a range of length-scales to overcome this barrier.

In this work, we apply finite-element device simulations to quantify the interfacial losses present in an industrially relevant perovskite-on-TOPCon architecture. We have developed a state-of-the-art perovskite-silicon tandem device model including transfer matrix method and raytracing optics, carrier tunnelling, and ion migration, coupled with a widely used drift-diffusion solver[1] to do so. We then move down the length-scales to ab-initio modelling of an experimentally demonstrated novel passivation scheme. This elucidates the atomistic mechanisms driving observed improvements in device performance and stability. Finally, we introduce the established passivation mechanism back into the device simulation to quantify the maximum possible performance improvement, setting a final target for the fully optimised interface passivation. A clear strategy for ameliorating the most critical interface identified by the device model hence emerges. Our methodology uniquely provides deep physical insight, whilst remaining broadly applicable to a range of device architectures.

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