Self-Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow
Self-Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow
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DOI：
10.1002/aisy.202000245
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发表时间：
2021-02-01
影响因子：
7.4
通讯作者：
Abolhasani, Milad
中科院分区：
文献类型：
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作者：
Abdel-Latif, Kameel;Epps, Robert W.;Abolhasani, Milad
确定新兴的无机卤化铅钙钛矿量子点（LHP QD）的最佳配方及其庞大的胶体合成宇宙和多个合成/合成后处理参数对于材料和时间密集型批量合成策略来说是一项具有挑战性的任务。在本文中，介绍了一种模块化微流体合成策略，该策略与人工智能（AI）引导的决策代理集成，用于通过具有10个单独控制的合成参数和超过2x 10（7）的可访问参数空间的LHP QD的复杂胶体合成宇宙进行智能导航。利用开发的自主微流体实验策略在一个全球性的学习框架内，LHP量子点的最佳配方是快速确定通过两步胶体合成和合成后的卤化物交换反应，为10个不同的发射颜色在不到40分钟，每个所需的峰值发射能量。使用两个串联的微流体反应器能够通过在线卤化物交换反应实现LHP QD的连续带隙工程化，而不需要中间洗涤步骤。在三相流形式内使用惰性气体使得能够成功地将卤化物盐前体自同步连续递送到含有LHP QD的移动液滴中，从而加速闭环制剂优化和具有所需光电性质的LHP QD的端到端连续制造。
Identifying the optimal formulation of emerging inorganic lead halide perovskite quantum dots (LHP QDs) with their vast colloidal synthesis universe and multiple synthesis/postsynthesis processing parameters is a challenging undertaking for material- and time-intensive, batch synthesis strategies. Herein, a modular microfluidic synthesis strategy, integrated with an artificial intelligence (AI)-guided decision-making agent for intelligent navigation through the complex colloidal synthesis universe of LHP QDs with 10 individually controlled synthesis parameters and an accessible parameter space exceeding 2x10(7), is introduced. Utilizing the developed autonomous microfluidic experimentation strategy within a global learning framework, the optimal formulation of LHP QDs is rapidly identified through a two-step colloidal synthesis and postsynthesis halide exchange reaction, for 10 different emission colors in less than 40min per desired peak emission energy. Using two in-series microfluidic reactors enables continuous bandgap engineering of LHP QDs via in-line halide exchange reactions without the need for an intermediate washing step. Using an inert gas within a three-phase flow format enables successful, self-synchronized continuous delivery of halide salt precursor into moving droplets containing LHP QDs, resulting in accelerated closed-loop formulation optimization and end-to-end continuous manufacturing of LHP QDs with desired optoelectronic properties.