Optimization of Bi2O3/TS-1 preparation and photocatalytic reaction conditions for low concentration Erythromycin wastewater treatment based on artificial neural network

Technologies such as batteries, biomaterials and heterogeneous catalysts have functions that 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 rare1-5. Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches6-14 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 water15. The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm16-18. This autonomous search identified photocatalyst mixtures that were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous19,20 free-roaming robot21-24, automating the researcher rather than the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis.

Advanced oxidation processes via semiconductor photocatalysis for water treatment have been the subject of extensive research over the past three decades, producing many scientific reports focused on elucidating mechanisms and enhancing kinetics for the treatment of contaminants in water. Many of these reports imply that the ultimate goal of the research is to apply photocatalysis in municipal water treatment operations. However, this ignores immense technology transfer problems, perpetuating a widening gap between academic advocation and industrial application. In this Feature, we undertake a critical examination of the trajectory of photocatalytic water treatment research, assessing the viability of proposed applications and identifying those with the most promising future. Several strategies are proposed for scientists and engineers who aim to support research efforts to bring industrially relevant photocatalytic water treatment processes to fruition. Although the reassessed potential may not live up to initial academic hype, an unfavorable assessment in some areas does not preclude the transfer of photocatalysis for water treatment to other niche applications as the technology retains substantive and unique benefits.