(690c) Machine Learning-Driven Continuous Nanomanufacturing of Lead-Free Metal Halide Perovskite Nanocrystals

Colloidal metal halide perovskite (MHP) nanocrystals (NCs) are a class of advanced functional materials with versatile applications in photonic and energy devices owing to their excellent optoelectronic properties such as tunable emissions and high photoluminescence quantum yield (PLQY). However, the lead toxicity remains a challenge that significantly hinders their incorporation into printed technologies. Cesium copper halide perovskite NCs have lately come forth as a potential lead-free alternative with composition-tunable optical properties.^1,2 Cesium copper iodide (Cs₃Cu₂I₅) is a particular class of copper-based MHP NCs with a pure orthorhombic crystal structure. Incorporation of metal halide additives has been reported to boost the Cs₃Cu₂I₅ NCs PLQY and morphology uniformity.^3–5 Although cation-doped Cs₃Cu₂I₅ NCs have been successfully synthesized, their rapid formation kinetics may lead to inconsistencies among batches, posing challenges for fundamental research and practical applications. In this study, we developed an active learning (AL)-guided experimentation platform to autonomously synthesize metal cation-doped Cs₃Cu₂I₅ NCs in flow with improved optical properties and uniform size morphology. We utilized the process automation mode of the developed flow chemistry platform to investigate the effects of dopant/copper molar ratio, halide source precursor concentration, precursors injection ratio, reaction time, and temperature on the optical properties and size distribution of the in-flow synthesized doped Cs₃Cu₂I₅ NCs. In addition, we utilized the developed self-driving fluidic lab (SDFL) for accelerated parameter space mapping, synthetic route optimization, and autonomous nanomanufacturing of highest-performing cation-doped Cs₃Cu₂I₅ NCs with minimum experimental cost. The high-performing MHP NCs synthesized in this study could pave the way for large-scale adoption of nontoxic MHP NCs by printed clean energy technologies.

References:

(1) Li, Y.; Vashishtha, P.; Zhou, Z.; Li, Z.; Shivarudraiah, S. B.; Ma, C.; Liu, J.; Wong, K. S.; Su, H.; Halpert, J. E. Room Temperature Synthesis of Stable, Printable Cs₃Cu₂X₅ (X = I, Br/I, Br, Br/Cl, Cl) Colloidal Nanocrystals with Near-Unity Quantum Yield Green Emitters (X = Cl). Chem. Mater. 2020, 32 (13), 5515–5524. https://doi.org/10.1021/acs.chemmater.0c00280.

(2) Luo, Z.; Li, Q.; Zhang, L.; Wu, X.; Tan, L.; Zou, C.; Liu, Y.; Quan, Z. 0D Cs₃Cu₂X₅ (X = I, Br, and Cl) Nanocrystals: Colloidal Syntheses and Optical Properties. Small 2020, 16 (3), 1905226. https://doi.org/10.1002/smll.201905226.

(3) Lian, L.; Zheng, M.; Zhang, W.; Yin, L.; Du, X.; Zhang, P.; Zhang, X.; Gao, J.; Zhang, D.; Gao, L.; Niu, G.; Song, H.; Chen, R.; Lan, X.; Tang, J.; Zhang, J. Efficient and Reabsorption‐Free Radioluminescence in Cs₃Cu₂I₅ Nanocrystals with Self‐Trapped Excitons. Adv. Sci. 2020, 7 (11), 2000195. https://doi.org/10.1002/advs.202000195.

(4) Li, C.-X.; Cho, S.-B.; Kim, D.-H.; Park, I.-K. Monodisperse Lead-Free Perovskite Cs₃Cu₂I₅ Nanocrystals: Role of the Metal Halide Additive. Chem. Mater. 2022, 34 (15), 6921–6932. https://doi.org/10.1021/acs.chemmater.2c01318.

(5) Qu, K.; Lu, Y.; Ran, P.; Wang, K.; Zhang, N.; Xia, K.; Zhang, H.; Pi, X.; Hu, H.; Yang, Y. (Michael); He, Q.; Yin, J.; Pan, J. Zn (II)‐Doped Cesium Copper Halide Nanocrystals with High Quantum Yield and Colloidal Stability for High‐Resolution X‑Ray Imaging. Adv. Opt. Mater. 2023, 11 (7), 2202883. https://doi.org/10.1002/adom.202202883.