Faculty of Chemistry, University of Warsaw; 1 Pasteura Street, Warsaw 02-093, Poland.
Department of Chemistry, McGill University; 801 Sherbrooke Street West, Montréal, Québec H3A 0B8, Canada.
J Am Chem Soc. 2023 Feb 15;145(6):3515-3525. doi: 10.1021/jacs.2c12095. Epub 2023 Jan 31.
First-principles crystal structure prediction (CSP) is the most powerful approach for materials discovery, enabling the prediction and evaluation of properties of new solid phases based only on a diagram of their underlying components. Here, we present the first CSP-based discovery of metal-organic frameworks (MOFs), offering a broader alternative to conventional techniques, which rely on geometry, intuition, and experimental screening. Phase landscapes were calculated for three systems involving flexible Cu(II) nodes, which could adopt a potentially limitless number of network topologies and are not amenable to conventional MOF design. The CSP procedure was validated experimentally through the synthesis of materials whose structures perfectly matched those found among the lowest-energy calculated structures and whose relevant properties, such as combustion energies, could immediately be evaluated from CSP-derived structures.
第一性原理晶体结构预测 (CSP) 是最强大的材料发现方法，仅基于其基础组件的图表即可预测和评估新固相的性质。在这里，我们首次提出了基于 CSP 的金属有机骨架 (MOF) 的发现，为传统技术提供了更广泛的选择，这些技术依赖于几何形状、直觉和实验筛选。为涉及柔性 Cu(II) 节点的三个系统计算了相图，这些节点可以采用潜在无限数量的网络拓扑结构，并且不适用于传统的 MOF 设计。CSP 程序通过合成材料进行了实验验证，这些材料的结构与计算出的最低能量结构中发现的结构完全匹配，并且其相关性质（例如燃烧能）可以立即从 CSP 衍生结构中进行评估。
