Towards High-Performance Multi-Junction Perovskite Solar Cells: Fabrication, Interlayer Design, and Characterisation

Abstract

Metal halide perovskites have emerged as a leading class of materials in the development of next-generation optoelectronic technologies. Their exceptional properties, including high absorption coefficients, long carrier diffusion lengths, and tuneable bandgaps, have driven remarkable progress, particularly in the field of photovoltaics. Metal halide perovskites are particularly attractive for multi-junction photovoltaics because their bandgaps can be finely tuned. By stacking materials with different bandgaps, it becomes possible to capture a broader range of the solar spectrum. This has led to the development of perovskite-on-silicon tandems, perovskite-perovskite tandems, and even triple-junction devices, some of which have already outperformed the efficiency of their individual single junction components. This thesis explores the use of halide perovskites in multi-junction solar cells. After outlining the motivation for this work in Chapter 2, I introduce the fabrication of single junction wide and low bandgap devices, alongside their subcells within an all-perovskite tandem device, in Chapter 3. This includes the exploration of local device optimisation strategies and the identification of performance and stability limitations arising from current interlayer materials. In Chapter 4, I introduce a new interconnecting layer engineered to improve optical transparency, reduce non-radiative recombination losses, and enhance operational stability. I demonstrate its successful integration into a range of device architectures, including all- perovskite tandem solar cells, triple-junction perovskite solar cells, and substrate-structured all-perovskite tandem solar cells. These results collectively confirm the versatility and broad applicability of this new interconnecting layer across multiple multi-junction platforms. Finally, in Chapter 6, I present a study focused on tandem-relevant wide bandgap single junction devices that combines hyperspectral photoluminescence imaging with voltage- dependent photoluminescence microscopy. This approach enables mapping of different parameters obtained by optical techniques. Machine learning techniques are employed to analyse the complex relationships between parameters, offering insights into device degradation mechanisms and performance-limiting factors. Together, these investigations contribute to advancing the design, understanding, and practical implementation of high-efficiency perovskite-based multi-junction solar cells.