(651e) Autonomous Nanomanufacturing of CsPbBr3 Nanoplatelets

Colloidal metal halide perovskite (MHP) nanocrystals (NCs) have made breakthroughs in a wide range of device applications including displays, light-emitting diodes, and photovoltaics due to their high photoluminescence quantum yield (PLQY) and narrow emission linewidth. The defect tolerance nature of MHP NCs with lower energy bandgaps has resulted in the synthesis of high-performing NCs with high PLQYs (95%+) and narrow emission linewidth [1]. However, as the energy bandgap increases, the surface defects of MHP NCs become more prominent and result in a decrease in their PLQY. In recent years, many reports have attempted to produce high bandgap MHP NCs with the highest PLQY, but have not seen great success compared to lower bandgap MHPs. Conventional synthesis of MHP NCs is performed in batch reactors, but fast formation kinetics can cause irreproducible NCs for both industrial applications and academic research. Continuous flow chemistry adapts to the fast formation kinetics due to the fast, controllable, and reproducible axial and radial mixing occurring in the flow reactors. Along with adapting to the fast formation kinetics, continuous flow chemistry allows for continuous experimentation, in-situ characterization, and reaction miniaturization (lower chemical consumption and waste generation than batch experimentation) [2].

The high-dimensional synthesis space of MHP NCs complicates the process of discovering the best-in-class high-band gap NCs. Self-driving labs (SDLs) with autonomous closed-loop experimentation have gained traction in the past five years for their effectiveness in navigating extremely complex and high-dimensional parameter spaces in a timely manner [3]. Combining both machine learning (ML)-guided experimentation with continuous flow chemistry can decrease chemical consumption and time-to-solution (i.e., identifying the highest-performing MHP NC) by orders of magnitude compared to manual experimentation.

In this work, we present the smart nanomanufacturing of MHP NCs. Specifically, we focus on the autonomous synthesis of high-performing Cesium Lead Bromide (CsPbBr₃) nanoplatelets by leveraging an SDL for rapid discovery of their manufacturing route. First, we characterize, validate, and benchmark both the hardware and ML agent of the developed SDL. We then employ autonomous experimentation for the rapid discovery of the synthesis route for high energy bandgap CsPbBr₃ nanoplatelets for multiple monolayer thicknesses.

References:

[1] Protesescu, L.; Yakunin, S.; Bodnarchuk, M. I.; Krieg, F.; Caputo, R.; Hendon, C. H.; Yang, R. X.; Walsh, A.; Kovalenko, M. V. Nanocrystals of Cesium Lead Halide Perovskites (CsPbX 3 , X = Cl, Br, and I): Novel Optoelectronic Materials Showing Bright Emission with Wide Color Gamut. Nano Lett. 2015, 15 (6), 3692–3696. https://doi.org/10.1021/nl5048779.

[2] Sadeghi, S.; Bateni, F.; Kim, T.; Yong Son, D.; A. Bennett, J.; Orouji, N.; S. Punati, V.; Stark, C.; D. Cerra, T.; Awad, R.; Delgado-Licona, F.; Xu, J.; Mukhin, N.; Dickerson, H.; G. Reyes, K.; Abolhasani, M. Autonomous Nanomanufacturing of Lead-Free Metal Halide Perovskite Nanocrystals Using a Self-Driving Fluidic Lab. Nanoscale 2024, 16 (2), 580–591. https://doi.org/10.1039/D3NR05034C.

[3] Abolhasani, M.; Kumacheva, E. The Rise of Self-Driving Labs in Chemical and Materials Sciences. Nat. Synth. 2023, 2 (6), 483–492. https://doi.org/10.1038/s44160-022-00231-0.