Wu Xiaoyu, Jiang Jianwen
Department of Chemical and Biomolecular Engineering, National University of Singapore 117576 Singapore
Chem Sci. 2024 Sep 25;15(40):16467-79. doi: 10.1039/d4sc05616g.
Digital discoveries of metal-organic frameworks (MOFs) have been significantly advanced by the reverse topological approach (RTA). The node-and-linker assembly strategy allows predictable reticulations predefined by coordination templates; however, reticular equivalents lead to substantial combinatorial explosion due to the infinite design space of building units (BUs). Here, we develop a fine-tuned RTA for the structure prediction of MOFs by integrating precise topological constraints and leveraging reticular chemistry, thus transcending traditional exhaustive trial-and-error assembly. From an extensive array of chemically realistic BUs, we subsequently design a database of 94 823 precision-engineered MOFs (PE-MOFs) and further optimize their structures. The PE-MOFs are assessed for post-combustion CO capture in the presence of HO and top-performing candidates are identified by integrating three stability criteria (activation, water and thermal stabilities). This study highlights the potential of synergizing PE with the RTA to enhance efficiency and precision for computational design of MOFs and beyond.
金属有机框架(MOF)的数字化发现通过反向拓扑方法(RTA)取得了显著进展。节点-连接体组装策略允许通过配位模板进行可预测的网状化;然而,由于构建单元(BU)的无限设计空间,网状等效物会导致大量的组合爆炸。在此,我们通过整合精确的拓扑约束并利用网状化学,开发了一种用于MOF结构预测的微调RTA,从而超越了传统的穷举试错组装法。从大量化学上合理的构建单元中,我们随后设计了一个包含94823个精确工程化MOF(PE-MOF)的数据库,并进一步优化它们的结构。在存在水的情况下评估PE-MOF的燃烧后二氧化碳捕获性能,并通过整合三个稳定性标准(活化稳定性、水稳定性和热稳定性)来确定表现最佳的候选物。这项研究突出了将PE与RTA协同以提高MOF及其他材料计算设计的效率和精度的潜力。