Sun Xi, Lin Wangqiang, Jiang Kun, Liang Heng, Chen Guanghui
Department of Chemistry and Key Laboratory for Preparation and Application of Ordered Structural Materials of Guangdong Province, Shantou University, Guangdong 515063, P. R. China.
Department of Natural Science, Shantou Polytechnic, Shantou 515041, Guangdong, China.
Phys Chem Chem Phys. 2023 Mar 22;25(12):8608-8623. doi: 10.1039/d2cp05410h.
As the by-products of catalytic cracking or alkane dehydrogenation, isobutene (2-methyl-propylene) and isobutane (2-methyl-propane) are important chemical feedstocks, but the separation of their mixture is a challenging issue in the petrochemical industry. Herein, we report the first example of large-scale computational screening of metal-organic frameworks (MOFs) with copper open metal sites (Cu-OMS) on the adsorptive separation of isobutene/isobutane using configuration-bias Monte Carlo (CBMC) simulations and machine learning among >330 000 MOFs data. We discovered that the optimal structural features governing the MOFs-based separation of isobutene/isobutane were density () and porosity (), with ranges of 0.2-0.5 g cm and 0.8-0.9, respectively. Furthermore, the key genes (metal nodes or linkers of frameworks) contributing to such adsorptive separation were data-mined by feature engineering of ML. These genes were cross-assembled into novel frameworks using a material-genomics strategy. The screened AVAKEP, XAHPON, HUNCIE, CuO-mof177-TDPAT_No730 and assembled CuO-BTC_B-core-4_No1 possessed high isobutene uptake and isobutene/isobutane selectivity of >19.5 mmol g and 4.7, with high thermal stability (as validated by molecular-dynamics simulations) overcoming the critical "trade-off" problem to some extent. The macroporous structures (pore-limiting diameter >12 Å) of these five promising frameworks with multi-layer adsorption on isobutene resulted in high isobutene loading, as validated by adsorption isotherms and CBMC simulations. The higher adsorption energy and heat of adsorption of isobutene than those of isobutane indicated that the thermodynamic equilibrium drove their selective adsorption. Generalized charge decomposition analysis and localized orbit locator calculations based on density functional theory wavefunctions suggested that high selectivity was due to complexation of feedback π bonds between isobutene and Cu-OMS, but also the strong π-π stacking interaction induced by the CC bond of isobutene with the multiple aromatic rings and unsaturated bonds of frameworks. Our theoretical results and data-driven approach may provide insights into the development of efficient MOF materials for the separation of isobutene/isobutane and other mixtures.
作为催化裂化或烷烃脱氢的副产物，异丁烯（2-甲基丙烯）和异丁烷（2-甲基丙烷）是重要的化学原料，但它们混合物的分离是石化行业中一个具有挑战性的问题。在此，我们报告了首例在超过330000种金属有机框架（MOF）数据中，利用构型偏置蒙特卡罗（CBMC）模拟和机器学习对具有铜开放金属位点（Cu-OMS）的MOF进行大规模计算筛选，用于异丁烯/异丁烷吸附分离的研究。我们发现，基于MOF的异丁烯/异丁烷分离的最佳结构特征是密度（）和孔隙率（），范围分别为0.2 - 0.5 g/cm³和0.8 - 0.9。此外，通过机器学习的特征工程挖掘出了有助于这种吸附分离的关键基因（框架的金属节点或连接体）。利用材料基因组学策略将这些基因交叉组装成新型框架。筛选出的AVAKEP、XAHPON、HUNCIE、CuO-mof177-TDPAT_No730和组装的CuO-BTC_B-core-4_No1具有高的异丁烯吸附量和大于19.5 mmol/g的异丁烯/异丁烷选择性以及4.7的选择性，并且具有高热稳定性（经分子动力学模拟验证），在一定程度上克服了关键的“权衡”问题。这五个有前景的框架的大孔结构（孔径限制直径>12 Å）对异丁烯具有多层吸附，导致高的异丁烯负载量，这已通过吸附等温线和CBMC模拟得到验证。异丁烯比异丁烷具有更高的吸附能和吸附热，表明热力学平衡驱动了它们的选择性吸附。基于密度泛函理论波函数的广义电荷分解分析和定域轨道定位器计算表明，高选择性是由于异丁烯与Cu-OMS之间反馈π键的络合作用，也是由于异丁烯的CC键与框架的多个芳香环和不饱和键之间的强π-π堆积相互作用。我们的理论结果和数据驱动方法可能为开发用于分离异丁烯/异丁烷及其他混合物的高效MOF材料提供见解。
