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Abstract The optimal synthesis of advanced nanomaterials with numerous reaction parameters, stages, and routes, poses one of the most complex challenges of modern colloidal science, and current strategies often fail to meet the demands of these combinatorially large systems. In response, an Artificial Chemist is presented: the integration of machine‐learning‐based experiment selection and high‐efficiency autonomous flow chemistry. With the self‐driving Artificial Chemist, made‐to‐measure inorganic perovskite quantum dots (QDs) in flow are autonomously synthesized, and their quantum yield and composition polydispersity at target bandgaps, spanning 1.9 to 2.9 eV, are simultaneously tuned. Utilizing the Artificial Chemist, eleven precision‐tailored QD synthesis compositions are obtained without any prior knowledge, within 30 h, using less than 210 mL of total starting QD solutions, and without user selection of experiments. Using the knowledge generated from these studies, the Artificial Chemist is pre‐trained to use a new batch of precursors and further accelerate the synthetic path discovery of QD compositions, by at least twofold. The knowledge‐transfer strategy further enhances the optoelectronic properties of the in‐flow synthesized QDs (within the same resources as the no‐prior‐knowledge experiments) and mitigates the issues of batch‐to‐batch precursor variability, resulting in QDs averaging within 1 meV from their target peak emission energy.
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This content will become publicly available on September 1, 2026
Regulating the Growth of Cesium Lead Bromide Quantum Dots at a Liquid/Liquid Interface Constrained in a Micropipette
Abstract: Colloidal all‐inorganic lead halide perovskite quantum dots (QDs) are high‐performance light‐emitting materials with size‐dependent optical properties and can be readily synthesized by mixing ionic precursors. However, the low formation energy of the perovskite lattice makes their growth too fast to control under regular reaction conditions. Diffusion‐regulated CsPbBr3 perovskite QD growth is reported on a nanometer‐sized liquid/liquid (L/L) interface supported in a micropipette tip without long‐chain organic ligands. The precursors are divided into two immiscible solutions across the L/L interface to avoid additional nucleation, and the QD growth kinetics are regulated by the constrained cationic diffusion field depending on the size of the micropipette tip. QDs with unprecedentedly small sizes (2.7 nm) are obtained due to the slowed‐down growth rates. The synthesis approach demonstrates the potential of micro‐controlled colloidal QD synthesis for mechanistic studies and micro‐fabrications.
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- Award ID(s):
- 2316919
- PAR ID:
- 10639815
- Publisher / Repository:
- Wiley-VCH GmbH
- Date Published:
- Journal Name:
- Small Methods
- Volume:
- 9
- Issue:
- 9
- ISSN:
- 2366-9608
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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