Simulating nanocrystal-based solar cells: A lead sulfide case study.

Nanocrystal-based solar cells are promising candidates for next generation photovoltaic applications; however, the most recent improvements to the device chemistry and architecture have been mostly trial-and-error based advancements. Due to complex interdependencies among parameters, determining factors that limit overall solar cell efficiency are not trivial. Furthermore, many of the underlying chemical and physical parameters of nanocrystal-based solar cells have only recently been understood and quantified. Here, we show that this new understanding of interfaces, transport, and origin of trap states in nanocrystal-based semiconductors can be integrated into simulation tools, based on 1D drift-diffusion models. Using input parameters measured in independent experiments, we find excellent agreement between experimentally measured and simulated PbS nanocrystal solar cell behavior without having to fit any parameters. We then use this simulation to understand the impact of interfaces, charge carrier mobility, and trap-assisted recombination on nanocrystal performance. We find that careful engineering of the interface between the nanocrystals and the current collector is crucial for an optimal open-circuit voltage. We also show that in the regime of trap-state densities found in PbS nanocrystal solar cells (∼1017 cm-3), device performance exhibits strong dependence on the trap state density, explaining the sensitivity of power conversion efficiency to small changes in nanocrystal synthesis and nanocrystal thin-film deposition that has been reported in the literature. Based on these findings, we propose a systematic approach to nanocrystal solar cell optimization. Our method for incorporating parameters into simulations presented and validated here can be adopted to speed up the understanding and development of all types of nanocrystal-based solar cells.