Data-Driven design of Bio-inspired Photocatalysts

该项目的目标是从树叶等自然系统中汲取灵感，设计出高效、无毒、可持续的二氧化碳减排光催化剂。这将使用逆设计方法进行，即在合成之前利用计算建模来设计具有所需硅性能集的材料。这缩小了需要实验探索的化学空间的范围，因此与更传统的方法相比，大大简化了材料发现的过程。该项目旨在同时解决两个问题，即大气中的二氧化碳和公共空间的消毒。2019年二氧化碳水平为409.8 0.1 ppm，过去60年的浓度年增长率比以前自然观察到的快100倍左右。二氧化碳水平的上升对全球变暖、海洋酸化和气候变化起到了重要作用。因此，碳捕获和二氧化碳转化的方法近年来获得了极大的兴趣。同样，在2019冠状病毒病大流行之后，人们越来越重视公共空间的卫生，以防止病原体的传播。该项目旨在通过设计受自然启发的光催化剂来解决这两个问题，将二氧化碳还原为乙醇，一种有效的消毒剂。

The goal of this project is to design efficient, non-toxic and sustainable photocatalysts for CO2 reduction, taking inspiration from natural systems, such as leaves. This would be carried out using an inverse design approach whereby computational modelling is utilised to design a material with a desired set of properties in-silico prior to synthesis. This narrows the area of chemical space needing to be explored experimentally and thus streamlines the process of material discovery significantly compared to more conventional methods. This project aims to tackle two problems simultaneously, that of CO2 in the atmosphere and that of disinfection of communal spaces. CO2 levels were 409.8 0.1 ppm in 2019 with the annual rate of concentration increase over the last 60 years about 100 times faster than previously observed naturally. Rising CO2 levels are contributing significantly towards global warming, ocean acidification and climate change. As such, methods for carbon capture and CO2 conversion have garnered significant interest in recent years. Likewise, in the wake of the COVID-19 pandemic increasing focus is being placed on the sanitisation of communal spaces to prevent the spread of pathogens. This project aims to address both issues by designing nature-inspired photocatalysts for the reduction of CO2 to ethanol, an effective disinfectant.