Abstract

Hybrid organic-inorganic halide perovskites have emerged as a disruptive new class of materials, exhibiting optimum properties for a broad range of optoelectronic applications, most notably for photovoltaics. The first report of highly efficient organic-inorganic perovskite solar cells in 2012 marked a new era for photovoltaics research, reporting a power conversion efficiency of over 10%. Only five years after this discovery, perovskite photovoltaic devices have reached a certified efficiency of 22.7%, making them the first solution processable technology to surpass thin film and multi-crystalline silicon solar cells. The remarkable development of perovskite solar cells is due to the ideal optoelectronic properties of organic-inorganic lead-halide perovskites. The prototypical compound, methylammonium lead iodide, CH3NH3PbI3 is a direct band gap semiconductor with a band gap in the visible, high charge carrier mobility, long diffusion length and low excitonic binding energy. Due to these ideal properties, CH3NH3PbI3 is also drawing interest across many other applications beyond photovoltaics, such as light emitting devices, lasers, photocatalysts and transistors. The continued progress of metal-halide perovskite optoelectronics relies not only on a detailed understanding of the electronic and optical properties of materials in this class, but also on the development of practical strategies to tune their properties by controlling parameters such as chemical composition. In this context, ab initio computational modelling can play a key role in providing a physical interpretation of experimental measurements, and guiding the design of novel halide perovskites with tailored properties. In this chapter we will present an account of the contributions to this fast developing field of research from our computational modelling group.

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