Accelerated Discovery of Luminescent Compositions in Ternary Halide Perovskite Nanocrystals

Yehonadav Bekenstein^a, Shai Levy^b, Lotte Kortstee^a, Georgy Dosovitskiy^a, Emma H. Massasa^a, Yaron Kauffmann^a, Juan Maria García-Lastra^a, Ivano E. Castelli^b

^aDepartment of Materials Science and Engineering and The Solid-State Institute, Technion-Israel Institute of Technology, 32000 Haifa, Israel

^bDepartment of Energy Conversion and Storage (DTU Energy), Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark

Proceedings of Emerging Light Emitting Materials 2026 (EMLEM26)

Kallithea, Greece, 2026 September 20th - 23rd

Organizers: Grigorios Itskos and Maksym Kovalenko

Invited Speaker, Yehonadav Bekenstein, presentation 048
Publication date: 8th July 2026

For nearly a century, alloy design has been governed by emperical rules (the Hume Rothery), which ascribe strict miscibility limits based on ionic radii and lattice strain. Halide perovskites appeared to conform rigidly to these principles, where chloride iodide alloys were found to be fundamentally unstable, limiting the accessible composition space and stable band-gap engineering.

Here, we demonstrate that these empirical miscibility rules collapse for colloidal quantum dots, where surface energy can counter destabilizing volumetric terms.

Our work flow consists of an automated high-throughput colloidal synthesis enbale us to measure the optical properties and thus map solid solution stability across 3,000 halide perovskite anion exchanged alloyed reactions. We show that nanocrystal size and thus the surface energy is crtical in reshaping perovskite miscibility boundaries. Smaller nanocrystals suppress halide segregation and the associated interfacial defect formation, producing homogeneous ternary alloys that are strictly forbidden in the bulk and are bright.

This approch portrays miscibility as a tunable design parameter and establishes nanoscale miscibility engineering as a synthetic strategy for stabilizing metastable compositions. We have integrated this high-throughput workflow into a fully operational self-driving laboratory governed by the Bayesian optimization algorithm. This autonomous platform bridges the gap between our digital predictions and physical reality, accelerating the discovery and precise synthesis of new, complex perovskite nanocrystal architectures.

Acknowledgements:

W. Hume-Rothery, J. Inst. Metals, 35, 295 (1926).
R. D. Shannon, Acta Cryst. A, 32, 751–767 (1976).
N. Livakas, S. Toso, Y. P. Ivanov, T. Das, S. Chakraborty, G. Divitini, L. Manna, J. Am. Chem. Soc., 145, 20442–20450 (2023).
S. Levy, L. Kortstee, G. Dosovitskiy, E. H. Massasa, Y. Kauffmann, J. M. García-Lastra, I. E. Castelli, Y. Bekenstein, arXiv:2601.06880 (2026).

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