This work explores the use of computational methods to aid in the design of Metal Organic Frameworks (MOFs) for use as CO2 scrubbers in carbon capture and storage applications. One of the main challenges in this field is in identifying important MOF design characteristics which optimize the complex interactions governing surface adsorption. We approach this in a high-throughput manner, determining properties important to CO2 adsorption from generating and sampling a large materials search space.
The utilization of MOFs as potential carbon scrubbing agents is a recent phenomenon, as such, many of the computational tools necessary to perform high-throughput screening of MOFs and subsequent analysis are either underdeveloped or non-existent. A large portion of this work therefore involved the development of novel tools designed specifically for this task. The chapters in this work are contiguous with the goal of designing MOFs for CO¬2 capture, and somewhat chronological in order and complexity, meaning as time and expertise progressed, more advanced tools were developed and utilized for the purposes of computational MOF discovery.
Initial work towards MOF design involved the detailed analysis of two experimental structures; CALF-15 and CALF-16 using classical molecular dynamics, grand canonical Monte Carlo simulations, and DFT to determine the structural features which promote CO2 adsorption. An unprecedented level of agreement was found between theory and experiment, as we are able to capture, with simulation, the X-ray resolved binding sites of CO2 in the confined pores of CALF-15. Molecular simulation was then used to provide a detailed breakdown of the energy contributions from nearby functional groups in both CALF-15 and CALF-16.
A large database of hypothetical MOF structures is constructed for the purposes of screening for CO2 adsorption. The database contains 1.3 million hypothetical structures, generated with an algorithm which snaps together rigid molecular building blocks extracted from existing MOF crystal structures. The algorithm for constructing the hypothetical MOFs and the building blocks themselves were all developed in-house to form the resulting database. The topological, chemical, and physical features of these MOFs are compared to recently developed materials databases to demonstrate the larger structural and chemical space sampled by our database.
In order to rapidly and accurately describe the electrostatic interactions of CO2 in the hypothetical database of MOFs, parameters were developed for use with the charge equilibration method. This method assigns partial charges on the framework atoms based on a set of parameters assigned to each atom type. An evolutionary algorithm was used to optimize the charge equilibration parameters on a set of 543 hypothetical MOFs such that the partial charges generated would reproduce each MOFs DFT-derived electrostatic potential. Validation of these parameters was performed by comparing the CO2 adsorption from the charge equilibration method vs DFT-derived charges on a separate set of 693 MOFs. Our parameter set were found to reproduce DFT-derived CO2 adsorption extremely well using only a fraction of the time, making this method ideal for rapid and accurate high-throughput MOF screening.
A database of 325,000 MOFs was then screened for CO2 capture and storage applications. From this study we identify important binding pockets for CO2 in MOFs using a binding site analysis tool. This tool uses a pattern recognition method to compare the 3-D configurations of thousands of pore structures surrounding strong CO2 adsorption sites, and present common features found amongst them.
For the purposes of developing larger databases which sample a more diverse materials space, a novel MOF construction tool is devloped which builds MOFs based on abstract graphs. The graph theoretical foundations of this method are discussed and several examples of MOF construction are presented to demonstrate its use. Notably, not only can it build existing MOFs with complicated geometries, but it can sample a wide range of unique structures not yet discovered by experimental means.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/32532 |
| Date | January 2015 |
| Creators | Boyd, Peter G. |
| Contributors | Woo, Tommy |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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