A Computational and Experimental Approach to Understanding Ion-Induced Degradation in Perovskite Solar Cells
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zhu-aaronzhu-meng-eecs-2026-thesis.pdf
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7410ffee380f08c93abe1818c2416312
Author(s)
Zhu, Aaron Y.
Advisor(s)
Buonassisi, Tonio
Anthony, Brian
Date Issued
February 2026
Publisher
Massachusetts Institute of Technology
Abstract
Perovskite solar cells possess incredible potential for transforming the solar industry; however, the key obstacle perovskites face on the path to commercialization is long-term stability. Perovskites exhibit numerous degradation pathways, but the fundamental mechanisms governing these processes are not yet fully understood. In this work, a key degradation pathway hypothesized to dominate perovskite instability -- ion migration, particularly iodide migration -- is examined.
To develop a more cohesive understanding, this mechanism is probed by incorporating perspectives from various disciplines. Two complementary computational and experimental workflows are introduced. First, Bayesian optimization is combined with device simulations to fit current-voltage (JV) curves to empirical data over time, ultimately visualizing real-device degradation within the space of physical device parameters. Bridging solid-state physics and photoelectrochemistry, this approach provides insight into hypothesized ionic transport and defect generation mechanisms. Second, an experimental method to detect iodine migration via fluorescence quenching of an iodine-specific reporter layer is developed. This approach constitutes a novel, direct probe of the degradation mechanism and demonstrates potential as a high-throughput tool for further understanding and improving perovskite stability.
Together, these results provide multidisciplinary support for existing iodine migration hypotheses and establish two complementary tools that further enable mechanistic evaluation of ion-induced degradation. These workflows demonstrate how computational inference and direct experimental probes can be jointly applied to accelerate perovskite stability research.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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