Mechanism and Machine Led Catalyst Discovery for a Circular Economy

该计划的愿景是发现新的（脱）氢化反应催化剂，并利用它们来解决循环经济的两个最重要的挑战：(a)可再生塑料的闭环生产，以及(b)二氧化碳的利用。该项目的第一个目标是发现新的有机金属催化剂/催化过程，以首次展示可再生塑料（聚酯、聚酰胺、聚碳酸酯和聚氨酯）的闭环生产。合成将通过可再生二醇/（和）二胺/（和）甲醇的脱氢偶联进行，回收过程将通过逆反应进行，即塑料的催化氢化解聚。该工艺还将用于开发基于甘油/聚酯偶对的高效可再生储氢材料。该计划的第二个目标是发现新的有机金属催化剂，用于逆向水煤气变换反应（CO2 + H2 = CO + H2O），将“废”CO2转化为有价值的化学原料- CO。催化剂设计将基于Ni和Fe的双金属配合物，灵感来自[Ni-Fe]-一氧化碳脱氢酶（CODHase）酶。催化剂的发现将通过双管齐下的方法协同进行——(i)使用有机金属化学工具箱进行机制研究，例如键激活、催化研究、动力学和DFT计算；（ii）使用数据科学和机器学习预测催化剂设计，其中使用自动（脱）氢化反应器生成合适质量的数据集。总体而言，该项目将整合有机金属化学和数据科学的方法，从根本上发现新的催化剂，提供必要的化学技术，使人类通过可持续性、环境和经济效益实现循环经济的繁荣。

The vision of this program is to discover new catalysts for (de)hydrogenation reactions and utilize them to solve two of the most important challenges of the circular economy: (a) closed-loop production of renewable plastics, and (b) CO2 utilization. The first goal of this program is to discover new organometallic catalysts/catalytic processes to demonstrate the closed-loop production of renewable plastics (polyesters, polyamides, polycarbonates, and polyurethanes) for the first time. The synthesis will be carried via the dehydrogenative coupling of renewable diols/(and) diamines/(and) methanol and the recycling process will be carried via the reverse reaction i.e. catalytic hydrogenative depolymerisation ofplastics. The discovered process will also be demonstrated for its application in developing an efficient and renewable hydrogen storage material based on glycerol/polyester couple. The second goal of this program is to discover new organometallic catalysts for the reverse water gas shift reaction (CO2 + H2 = CO + H2O) that will convert "waste" CO2 to the valuable chemical feedstock - CO. The catalyst design will be based on bimetallic complexes of Ni, and Fe inspired by the [Ni-Fe]-carbon monoxide dehydrogenase (CODHase) enzyme. The catalyst discoveries will be carried out synergistically using a two-pronged approach - (i) carrying mechanistic studies using the toolbox of organometallic chemistry e.g. bond activation, catalytic studies, kinetics, and DFT computation, and (ii) predicting catalyst design using data science and machine learning for which datasets of suitable quality will be generated using automated (de)hydrogenation reactors. Overall, this program will integrate the approaches of organometallic chemistry and data science to discover fundamentally new catalysts to provide the chemical technologies necessary to allow humanity to prosper through the sustainability, environmental, and economic benefits of making the circular economy a reality.