Spectral Safari: a Tour Through the Zoo of Perovskite Solar Cell Impedance Spectra from the Perspective of the Drift-Diffusion Model
Will Clarke a, Petra Cameron b, Giles Richardson a
a School of Mathematical Sciences, University of Southampton, Southampton, United Kingdom
b Dept. of Chemistry & Centre for Sustainable Chemical Technologies, University of Bath, UK, Claverton Down, Bath BA2 7AY, Reino Unido, United Kingdom
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Spring 2025 Conference (MATSUSSpring25)
Numerical device modelling and SIMulation of SOLar cells and Light Emitting Diodes: methodologies and applications - #SIMUSOLED
Sevilla, Spain, 2025 March 3rd - 7th
Organizers: Juan A. Anta and Sandra Jenatsch
Invited Speaker, Will Clarke, presentation 397
DOI: https://doi.org/10.29363/nanoge.matsusspring.2025.397
Publication date: 16th December 2024

We present a tour through the many and varied impedance spectra observed in perovskite solar cells, including loops, mid-frequency features, and the so-called ‘giant’ and ‘negative’ capacitances. Beginning with single-arc spectra, progressing through double- and triple-arcs, and finishing with discussion of the effects of degradation, we classify observed spectra into generic types, named for animals resembling their Nyquist plot. Remarkably, all of these spectral ‘animals’ can be faithfully replicated using the well-established ionic-electronic drift-diffusion model with a single mobile ion species, eliminating the need for speculative physics.  Perovskite solar cell spectra often defy traditional interpretations, prompting increasingly intricate equivalent circuit models comprising elements without a sensible physical meaning. However, our animal-inspired framework offers a simpler, more intuitive approach to spectral analysis. This ‘spotter’s guide’ allows researchers to identify spectral features and their underlying physical origins based only shape recognition from a safe distance, unlocking insights without the need to venture into the wilds of computational modelling.

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