上海科技大学姜珊团队利用电子晶体学和计算智能确定共价有机框架结构。相关研究成果发表在2024年12月2日出版的《美国化学会杂志》。

新材料的结构表征往往带来巨大的挑战，特别是在难以获得单晶结构的情况下，这是共价有机框架（COFs）的常见困难。尽管如此，理解原子结构至关重要，因为它提供了对有机构建块的排列和连接的见解，为建立结构-功能关系的相关性和揭示材料特性提供了机会。

该研究中，研究人员提出了一种确定COFs结构的方法，这是电子晶体学和计算智能（COF+）的集成。通过应用已有的化学知识并采用粒子群优化（PSO）进行试验结构生成，克服了现有的局限性，从而为COF结构确定的进步铺平了道路。

研究人员已经在四个具有代表性的COFs上成功实现了这项技术，每个COF都有其独特的特性。这些例子突显了人们在应对与COF结构确定相关的挑战方面的方法的准确性和有效性。此外，我该方法揭示了具有不同拓扑结构或互穿结构的新结构候选者，这些结构在化学上是可行的。

这一发现证明了改算法在不受拓扑因素影响的情况下构建试验COF结构的能力。COF结构的新方法代表了该领域的重大进步，并为探索COF材料的性能和应用开辟了新的途径。

附：英文原文

Title: Determining Covalent Organic Framework Structures Using Electron Crystallography and Computational Intelligence

Author: Xiangyu Zhang, Junyi Hu, Huiyu Liu, Tu Sun, Zidi Wang, Yingbo Zhao, Yue-Biao Zhang, Ping Huai, Yanhang Ma, Shan Jiang

Issue&Volume: December 2, 2024

Abstract: The structural characterization of new materials often poses immense challenges, especially when obtaining single-crystal structures is difficult, which is a common difficulty with covalent organic frameworks (COFs). Despite this, understanding the atomic structure is crucial as it provides insights into the arrangement and connectivity of organic building blocks, offering the opportunity to establish the correlation of structure–function relationships and unravel material properties. In this study, we present an approach for determining the structures of COFs, an integration of electron crystallography and computational intelligence (COF+). By applying established chemistry knowledge and employing particle swarm optimization (PSO) for trial structure generation, we overcome existing limitations, thus paving the way for advancements in COF structural determination. We have successfully implemented this technique on four representative COFs, each with unique characteristics. These examples underline the accuracy and efficacy of our approach in addressing the challenges tied to COF structural determination. Furthermore, our approach has revealed new structure candidates with different topologies or interpenetrations that are chemically feasible. This discovery demonstrates the capability of our algorithm in constructing trial COF structures without being influenced by topological factors. Our new approach to COF structure determination represents a significant advancement in the field and opens new avenues for exploring the properties and applications of COF materials.

DOI: 10.1021/jacs.4c12757

Source: https://pubs.acs.org/doi/abs/10.1021/jacs.4c12757