Graduate Thesis Or Dissertation
 

A Graph Grammar Representation of Metal-Organic Frameworks for Computational Synthesis and Exploration

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  • In this work, metal-organic frameworks (MOFs) are computationally represented, generated, and evaluated. The organic linker molecules are represented as graphs and use graph grammars where the atoms are represented by nodes and the bonds are represented by arcs. The grammar rules that dictate the graph generation process work on the principles of “recognize, choose, and apply” and are modelled off established molecular components and methods for creating linker molecules to ensure their feasibility. There are 14 rules for developing the backbone of the linker, 9 rules for functionalizing aromatic rings, and 1 rule for adding a carboxylate group. Starting with a carboxylate seed graph, the rules are randomly applied to generate a randomized linker. The arc and node information from this representation is used by the energy minimization function of the OpenBabel software to generate three-dimensional spatial information for the molecule. An original program written in Julia is used to translate the linkers into crystallographic information files, remove the carboxyl groups, and mark the former locations of the carboxyl groups with “X” symbols. The software Topologically Based Crystal Constructor combines the linkers with Zn4O nodes in a pcu topology to generate the MOF. This process is automated to generate one thousand randomized MOFs. These MOFs are then evaluated using the software Zeo++ to determine their pore diameter, surface area, accessible volume, void space, and density measurements. The results are analyzed using a histogram for each individual parameter and a scatterplot matrix of the pore diameters, surface areas, and accessible volumes. The histograms show vast ranges in the parameters, with some measurements being more than six standard deviations from the mean. The scatterplot matrix shows hundreds of unique combinations of the parameters within the high frequency regions. From this, it has been concluded the process has produced an expansive and diverse search space of MOFs. The work here can be used to build a repository of MOFs to guide future generation or for the intentional generation of MOFs for an interactive theoretical analysis.
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  • Simon Ensemble
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  • National Science Foundation, CMMI-166273
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