Poster De Conférence Année : 2023

Advanced Characterization and Degradation Analysis of Perovskite Solar Cells using Machine Learning and Bayesian Optimization

Résumé

Context & Scale • Poor stability is a major barrier to the commercialization of perovskite solar cells. • With so many factors to consider, it often takes years to understand performance bottlenecks and optimize the design process. • We combine physics modeling, machine learning, and experimentation to better understand the complex relationship between device performance and underlying properties. → Gain insights into performance and degradation → Reduce the need for time-consuming and laborious characterization techniques → Flexible & scalable approach

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Dates et versions

hal-04297081 , version 1 (21-11-2023)

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Identifiants

  • HAL Id : hal-04297081 , version 1

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Joseph Chakar, Arthur Julien, Karim Medjoubi, Jorge Posada, Jean-François Guillemoles, et al.. Advanced Characterization and Degradation Analysis of Perovskite Solar Cells using Machine Learning and Bayesian Optimization. IEEE PVSC 2023, Jun 2023, San Juan, Puerto Rico. . ⟨hal-04297081⟩
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