A mobile robotic chemist

Article

关键词: AUTOMATED OPTIMIZATION;    DISCOVERY;    HYDROGEN;    DESIGN;   

DOI  :  10.1038/s41586-020-2442-2

来源: SCIE

【 摘 要 】

Technologies such as batteries, biomaterials and heterogeneous catalysts have functionsthat are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare(1-5). Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches(6-14)but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water(15). The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm(16-18). This autonomous search identified photocatalyst mixturesthat were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous(19,20)free-roaming robot(21-24), automating the researcher ratherthan the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis.

【 授权许可】

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