Advancements in Stable Solution-Processed Photovoltaic Materials: Exploration of New High-Bandgap Materials and Degradation Kinetics of Low-bandgap Perovskites - Meng, Yuhuan (My University, 2024)
Solution-processed tandem solar cells are distinguished by their high theoretical power conversion efficiency (PCE), attributed to minimized thermalization losses, and their low manufacturing costs. These attributes align well with the objectives of the SunShot 2030 Goals, which aim for a levelized cost of energy (LCOE) of $0.03/kWh for photovoltaic (PV) systems. Within the spectrum of materials suitable for the absorber layers in these cells, organic-inorganic lead-based hybrid perovskites (HPs) are particularly prominent due to their low production costs, adjustable bandgaps, and superior PV properties. These materials have undergone extensive investigation over the past decade. Despite their advantages, the widespread commercial deployment of HPs is hindered by serious concerns regarding environmental and health risks associated with their lead content, along with their vulnerability to degradation from exposure to moisture, oxygen, and light. Moreover, the field lacks a standardized methodology for assessing the lifetime of perovskite solar cells, which complicates the comparative evaluations of stability and longevity under diverse accelerated testing conditions noted in existing literature. My research primarily addresses these two critical issues in the context of solution-processed photovoltaic materials by: (1) exploring the use of bismuth rudorffites, a new class of stable, environmentally-friendly, high bandgap materials, as potential substitutes for HPs; and (2) investigating the degradation mechanisms of mixed tin-lead perovskite, a potential material for the bottom cell, to develop a comprehensive kinetic model. This model aims to accurately predict the degradation rates, thereby enhancing the prediction of the lifetimes of these solar cells.First, I determined the main loss mechanisms of the performance of the solar cells by using BiI3, a lead-free direct wide-bandgap solution-processable semiconductor that could be an alternative to lead-based perovskites in tandem or multijunction solar cells, as the absorber. Based on that, I demonstrated that lithium doping of BiI3 can increase the diffusion length of BiI3 to improve the performance of BiI¬3 solar cells. Although the deep understanding of the main loss mechanisms of this work paves the way for future optimization of BiI3 solar cells, the power conversion efficiency is still very low compared with perovskite solar cells. I believe it is very difficult to use BiI3 to replace HPs as high bandgap absorber for solution-processed tandem solar cells. Second, to accurately predict the lifetime of perovskite solar cells, I concentrated on extensively studying the degradation kinetics of FA0.75Cs0.25Pb0.5Sn0.5I3, the most representative compound of mixed Sn-Pb perovskites, by in-situ measurements of optical transmittance (T), photoluminescence (PL), and diffusion length (LD). I proposed the different degradation mechanisms for dry oxidation and water-accelerated oxidation pathways and built a kinetic model to the rate of oxygen-induced degradation, the most dominant degradation mechanism, as a function of temperature, oxygen, and moisture levels. The degradation rate equation derived from this model is crucial for constructing the machine learning model that predicts the decay in diffusion length (LD). Third, I explored the influence of iodine (I2), a significant byproduct for the degradation of perovskite materials. I proposed the detailed degradation mechanism of iodine-induced degradation for mixed Sn-Pb perovskite materials and developed a rate model to predict its degradation rate. Additionally, I investigated the impact of I2 on the oxygen-induced degradation. The results not only confirmed the existence of reverse reactions in oxygen-induced degradation but also led to the creation of a comprehensive rate model to predict how the absorber degrades under various concentrations of I2 vapor in 0% RH air at different temperatures. Lastly, in collaboration with my colleague, we construct a machine learning model to predict the lifetime of FA0.75Cs0.25Pb0.5Sn0.5I3 solar cells with ~29.9% test error. The rate model integral to this predictive model highlights the critical role of degradation kinetics studies. Collectively, the work included in this dissertation demonstrates considerable progress toward the commercialization of solution-process tandem solar cells: (i) it reaffirms perovskite materials as the superior absorber candidates for these systems due to their exceptional optoelectronic properties; (ii) it emphasizes the importance of a quantitative analysis of perovskite material degradation for accurately predicting the lifetime of perovskite solar cells. This work not only deepens our understanding of their degradation pathways but also paves the way for the reliability study of solution-processed tandem solar cells.
Thesis (Ph.D.)--University of Washington, 2024
Keywords: Bismuth Triiodide; Machine Learning; Mixed Sn-Pb Perovskite Materials; Perovskite Solar Cells; Stability; Chemical engineering; Molecular engineering