Publication date: 21st July 2025
For semiconductors, precise tuning of the bandgap holds the key to unlocking technologies. For halide perovskites, such tunability is possible by alloying halides into effective solid solutions. But what are the stability boundaries of such a mixture? In metallurgy, Hume-Rothery rules ascribe the radius ratio of cations to anions as a guiding principle for stability, which also holds for oxide-perovskites. We use lead halide perovskite nanocrystals as a model system to experimentally validate the boundaries of crystal stability and contrast it with the fundamental theories. We base the experiment on the ability to conduct halide exchange post-synthetically, effectively tuning their composition from single-halide into ternary solid solution alloys. The halide composition determines the band-gap, and a spectroscopic readout is used to interrogate the resulting crystals. To map such a vast space of composition and sizes, thousands of exchange reactions were conducted. To execute such vast experimental task a high-throughput robotic anion exchange and spectroscopic process was developed. We mapped the size-dependent behavior across the ternary halide composition of these materials by synthesizing and spectroscopically characterizing over 3000 successful experiments. The resulting maps allow for the first time to point to a stable ternary CsPb(ClₓBryIz)₃ halide perovskite domain. We showcase the stabilizing effect surface energy has on ternary solid solution compositions, and that smaller nanocrystals demonstrate a smaller miscibility gap. The vision is to extend our understanding of sable perovskite compositions also to bulk, influencing the design of future optoelectronic devices.
We thank Noa Goeli and Noa Zilberman for their help in this research as part of their undergraduate project. We thank Jessica Nachamie for her help in data analysis. We gratefully thank Dr. Yaron Kauffmann for his help with STEM measurements.
Funding: This project is supported by the European Union’s Horizon 2020 research and innovation program under grant agreement No 949682- ERC. We thankfully acknowledge RES resources provided by Barcelona Supercomputer Center in MareNostrum5 to project QHS-2025-1-0036. Additionally, we acknowledge support from the Novo Nordisk Foundation Data Science Research Infrastructure 2022 Grant under No. NNF22OC0078009: “A high-performance computing infrastructure for data-driven research on sustainable energy materials”.
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