钙钛矿太阳能电池的退化与修复机制：物理研究与数据驱动人工智能分析

该博士项目旨在研究钙钛矿太阳能电池的性能下降及恢复机制，这些电池具有实现高效光伏应用的前景。 该研究结合控制实验、漂移-扩散建模与数据驱动分析，旨在揭示各种因素对稳定性与恢复机制的影响，从而构建预测模型以延长太阳能电池的寿命。

Job description: Project description: Perovskite solar cells, with their strong light absorption and tunable bandgap, offer exceptional potential for high-efficiency photovoltaics, both as single-junction devices and in perovskite-silicon tandems. However, operational stability remains a major barrier to industrial deployment. This PhD project aims to understand the physical mechanisms behind performance degradation and recovery, analyzing how illumination, temperature, and electrical bias influence these processes. The approach combines controlled experiments, physical modeling (via drift-diffusion models), and data-driven analysis (physics-informed AI). Periodic current density-voltage (JV) measurements track the evolution of electrical properties (open-circuit voltage, short-circuit current, fill factor) to identify ageing pathways. Targeted experiments, including interface treatments and varied operating conditions, will test hypotheses about dominant mechanisms. Key objectives: Identify degradation mechanisms at different ageing stages. Understand how operating conditions influence recovery. Develop predictive models to anticipate cell responses to new scenarios. This work will help prioritize interface improvements, evaluate recovery strategies, and design more stable perovskite devices.

所需个人背景与技能要求： "[会员信息]"