Li Wenliang, Pang Yujia, Zhang Jingping
Faculty of Chemistry, Northeast Normal University, Changchun, China.
J Mol Model. 2014 Jul;20(7):2346. doi: 10.1007/s00894-014-2346-x. Epub 2014 Jul 1.
The selectivity of indoor pollution gases (including formaldehyde, benzene, and toluene) over N2 on a set of 37 covalent organic frameworks (COFs) was modeled by combining classical grand canonical Monte Carlo (GCMC) methods and periodic density functional theory with dispersion correction (DFT-D2). The pore volume, pore size, and the isosteric heat (Q st) of gases on COFs were investigated to explore the origin of the high selectivity of pollution gases over N2. We found that the size match between the pore of the COFs and the corresponding pollution gases is the key factor for high selectivity. Additionally, the Q st for the investigated four gases follows the order of toluene > benzene > formaldehyde > N2, which is consistent with the order of selectivity. Furthermore, the favorite sites and interaction energies of pollution gases on COFs were calculated by the periodic DFT-D2 method. Our simulation procedure offers an alternative approach with which to evaluate or design the best candidate porous materials in capture pollution gases.
通过结合经典巨正则蒙特卡罗（GCMC）方法和带色散校正的周期性密度泛函理论（DFT-D2），对一组37种共价有机框架（COF）材料上室内污染气体（包括甲醛、苯和甲苯）相对于N₂的选择性进行了建模。研究了COF材料上气体的孔体积、孔径和等量吸附热（Qst），以探究污染气体相对于N₂具有高选择性的原因。我们发现，COF材料的孔与相应污染气体之间的尺寸匹配是实现高选择性的关键因素。此外，所研究的四种气体的Qst顺序为甲苯＞苯＞甲醛＞N₂，这与选择性顺序一致。此外，采用周期性DFT-D2方法计算了污染气体在COF材料上的优先吸附位点和相互作用能。我们的模拟过程提供了一种替代方法，用于评估或设计捕获污染气体的最佳候选多孔材料。
