Identifying Perovskite Solar Cell Degradation Mechanisms From A Digital Twin
Alison Walker a, Kjeld Jensen b, Petra Cameron c, Giles Richardson d, Will Clarke e
a Department of Physics University of Bath, BA2 7AY, UK
b Department of Mathematical Sciences, University of Bath
c Department of Chemistry, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
d School of Mathematical Sciences, University of Southampton, Southampton, United Kingdom
e School of Mathematics & Physics, University of Portsmouth
Proceedings of International Conference on Hybrid and Organic Photovoltaics (HOPV25)
Roma, Italy, 2025 May 12th - 14th
Organizers: Filippo De Angelis, Francesca Brunetti and Claudia Barolo
Invited Speaker Session, Alison Walker, presentation 043
Publication date: 17th February 2025

Achieving long term operational stability of perovskite cells under real-world conditions continues to be a major concern. Many mechanisms have been shown to cause degradation, recent examples being exposure to both water and oxygen [1], screening of the internal field driving charge extraction through ion migration [2] and interfacial recombination at the SnOx/bathocuproine interface in the hole blocking layer [3].

Here, we show how degradation mechanisms in a solar cell can be identified from experimental measurements by creating a digital twin, a virtual representation of an object designed to produce an accurate reflection of a physical object [https://www.ibm.com/think/topics/what-is-a-digital-twin]. Through simulations performed in real time, our digital twin can analyse performance changes due to degradation under operation and suggests potential mitigations. Our digital twin is a combination of the device transport model IonMonger [4] and machine learning [5]. It can be used to test hypotheses about the physical processes responsible for degradation. These processes include the role of mobile iodide vacancies in influencing charge transport across the interface through charge accumulation/depletion at interfaces, trap assisted recombination at the interfaces, and contributions of other impurities. The TOC Figure shows example results from our digital twin along with perovskite solar cells fabricated in the Cameron lab https://people.bath.ac.uk/chppjc/research.html.

TOC Figure Left: Perovskite solar cells fabricated in the Cameron lab. Right: Illustrative example joint distributions of two IonMonger input parameters for a degrading device as derived by Bayesian Parameter Estimation.

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