Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.
Phys Chem Chem Phys. 2011 Oct 14;13(38):17339-58. doi: 10.1039/c1cp21731c. Epub 2011 Aug 31.
An automated method has been developed to fully characterize the three-dimensional structure of zeolite porous networks. The proposed optimization-based approach starts with the crystallographic coordinates of a structure and identifies all portals, channels, and cages in a unit cell, as well as their connectivity. We apply our algorithms to known zeolites, hypothetical zeolites, and zeolite-like structures and use the characterizations to calculate important quantities such as pore size distribution, accessible volume, surface area, and largest cavity and pore limiting diameters. We aggregate this data over many framework types to gain insights about zeolite selectivity. Finally, we develop a continuous-time Markov chain model to estimate the probability of occupancy of adsorption sites throughout the porous network. ZEOMICS, an online database of structure characterizations and web tool for the automated approach is freely available to the scientific community (http://helios.princeton.edu/zeomics/).
已经开发出一种自动化方法来全面描述沸石多孔网络的三维结构。所提出的基于优化的方法从结构的晶体坐标开始，并确定单元晶胞中的所有门户、通道和笼，以及它们的连接性。我们将我们的算法应用于已知沸石、假设沸石和沸石样结构，并使用这些特征来计算重要的数量，如孔径分布、可及体积、表面积和最大空腔和孔限制直径。我们将这些数据汇总到许多骨架类型中，以了解沸石的选择性。最后，我们开发了一个连续时间马尔可夫链模型来估计整个多孔网络中吸附位点的占有率概率。ZEOMICS 是一个结构特征数据库和自动化方法的网络工具，向科学界免费提供(http://helios.princeton.edu/zeomics/)。
