Dresden 2026 – scientific programme

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HL: Fachverband Halbleiterphysik

HL 4: Perovskite and Photovoltaics: Synthesis and Performance

HL 4.2: Talk

Monday, March 9, 2026, 10:00–10:15, POT/0251

Impact of Antisolvents on Halide Perovskite Nanocrystal Synthesis — •Tim Julius Hashagen, Leo Luber, and Alexander Skyrme Urban — Nanospectroscopy Group, Nano-Institute Munich, Department of Physics, Ludwig-Maximilians-Universität München, Königinstraße 10, 80539 Munich, Germany

Lead halide perovskite nanocrystals (NCs) offer highly tunable optical properties and high photoluminescence efficiencies, making them promising for optoelectronic and photocatalytic applications. Their synthesis, however, is extremely sensitive to the choice of antisolvent, which governs nucleation and growth kinetics and thereby the structural and optical quality of the resulting NCs. [1] In this work, we systematically investigate how structural and chemical variations among antisolvents affect the formation of CsPbBr2 NCs. By tuning precursor compositions and antisolvent identities, we identify clear trends in crystallization behavior and photoluminescence characteristics. These experimental results are combined with a Gaussian Process regression model that encodes antisolvent geometry to predict NC emission wavelengths.[2] The model performs accurately for well-represented antisolvent classes but still faces challenges when extrapolating to sparsely sampled or previously unseen antisolvents. Our combined experimental and data-driven approach highlights the decisive role of antisolvent molecular structure in NC synthesis and demonstrates a pathway toward predictive control over perovskite nanocrystal properties.

[1]K. Frank et al., Nat. Commun. 2024, 15, 8952.

[2]N. A. Henke et al., Adv. Mater. 2025, e09472.

Keywords: Lead Halide Perovskites; Nanocrystals; Machine Learning