Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117576, Singapore.
Integrative Sciences and Engineering Programme, National University of Singapore, Singapore 119077, Singapore.
Environ Sci Technol. 2024 Sep 17;58(37):16465-16474. doi: 10.1021/acs.est.4c03854. Epub 2024 Sep 1.
Metal-organic frameworks (MOFs) represent a distinctive class of nanoporous materials with considerable potential across a wide range of applications. Recently, a handful of MOFs has been explored for the storage of environmentally hazardous fluorinated gases (Keasler et al. 2023, 381, 1455), yet the potential of over 100,000 MOFs for this specific application has not been thoroughly investigated, particularly due to the absence of an established force field. In this study, we develop an accurate force field for nonaversive hydrofluorocarbon vinylidene fluoride (VDF) and conduct high-throughput computational screening to identify top-performing MOFs with high VDF adsorption capacities. Quantitative structure-property relationships are analyzed via machine learning models on the combinations of geometric, chemical, and topological features, followed by feature importance analysis to probe the effects of these features on VDF adsorption. Finally, from detailed structural analysis via radial distribution functions and spatial densities, we elucidate the significance of different interaction modes between VDF and metal nodes in top-performing MOFs. By synergizing force-field development, computational screening, and machine learning, our findings provide microscopic insights into VDF adsorption in MOFs that will advance the development of new nanoporous materials for high-performance VDF storage or capture.
金属-有机骨架（MOFs）是一类具有独特性质的纳米多孔材料，在广泛的应用中具有巨大的潜力。最近，已经有一些 MOFs 被探索用于储存对环境有害的含氟气体（Keasler 等人，2023 年，381 卷，1455 页），然而，超过 100000 种 MOFs 用于这一特定应用的潜力尚未得到彻底研究，特别是由于缺乏已建立的力场。在这项研究中，我们为非侵袭性氢氟碳化物偏二氟乙烯（VDF）开发了一个精确的力场，并进行了高通量的计算筛选，以确定具有高 VDF 吸附能力的高性能 MOFs。通过机器学习模型对几何、化学和拓扑特征的组合进行定量结构-性质关系分析，然后进行特征重要性分析，以探究这些特征对 VDF 吸附的影响。最后，通过径向分布函数和空间密度的详细结构分析，我们阐明了 VDF 和金属节点之间不同相互作用模式在高性能 MOFs 中对 VDF 吸附的重要性。通过力场开发、计算筛选和机器学习的协同作用，我们的研究结果提供了对 MOFs 中 VDF 吸附的微观见解，这将推动用于高性能 VDF 储存或捕获的新型纳米多孔材料的发展。
