Computational characterization of zeolite porous networks: an automated approach

被引:175
作者
First, Eric L. [1 ]
Gounaris, Chrysanthos E. [1 ]
Wei, James [1 ]
Floudas, Christodoulos A. [1 ]
机构
[1] Princeton Univ, Dept Chem & Biol Engn, Princeton, NJ 08544 USA
基金
美国国家科学基金会;
关键词
DIFFUSION;
D O I
10.1039/c1cp21731c
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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/).
引用
收藏
页码:17339 / 17358
页数:20
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