A Python Implementation of a Drift-Diffusion Model to Capture Ion Migration in Perovskite Solar Cells

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A Python Implementation of a Drift-Diffusion Model to Capture Ion Migration in Perovskite Solar Cells

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2021-06

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Charge carrier dynamics and ion migration are attributed to the current-voltage hysteresis in perovskite solar cells (PSCs). This study implements a drift-diffusion model in Python to simulate the characteristic current-voltage scans for realistic device architectures. The novel work in this research involve the integration of a transfer-matrix optical model to the drift-diffusion model with ion migration, the implementation of a Radau 5th order solver to the method of lines, and a demonstration that standard Python libraries can handle stiff systems of differential algebraic equations. A comparative analysis with published works was conducted to validate the algorithm. It was found that the simulation was able to capture fast carrier dynamics under a variety of experimental conditions. Lastly, it is shown that the model captures physically relevant trends in PSCs.

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University of Minnesota M.S.Ch.E. thesis. June 2021. Major: Chemical Engineering. Advisor: Zhihua Xu. 1 computer file (PDF); ix, 116 pages.

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Anderson, Nathan. (2021). A Python Implementation of a Drift-Diffusion Model to Capture Ion Migration in Perovskite Solar Cells. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/224495.

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