Nanocrystalline, nanoporous, and heterogeneous functional materials have a range of unique physical and chemical properties at the nanoscale that make them useful in various fields such as gas storage, sensing, catalysis, and construction. However, these materials have complex and varied internal structures make them difficult to analyze using traditional methods. In this work, advanced tools were presented that combine several existing algorithms and techniques to enable efficient and accurate analysis of the structures of these materials. The tools were tested on well-studied systems (TiO2 nanoparticles) and novel materials (multiple metal organic frameworks), and the results showed that they produced accurate and reliable results. These results have contributed to important scientific discoveries, some of which are highlighted in this thesis.
First, an automated platform for x-ray scattering experiments and a streaming data pipeline were developed to determine pair distribution functions, which were used to study nanocrystalline, nanoporous, and heterogeneous functional materials. A systematic workflow was then proposed and tested to analyze the phases and morphologies of metal oxide nanoparticles. Using the data pipeline and workflow, the effects of temperature on phases, morphologies, and structure order during the synthesis of titanium oxide (bronze) nanoparticles were demonstrated. Specific tools were then designed to analyze the structures of nanoporous materials based on the disorder in their complex structures. The turbostratic disorder in zirconium phosphates was analyzed, and the potential to tune disorders using phosphoric acid concentration was demonstrated. In addition, the glass transition in metal-organic frameworks was detected, and a reminiscent correlation between metal sites in the glass state was discovered. Furthermore, evidence of polar solvent-induced lattice arrangement in an aluminum metal-organic framework was found using the analysis of pair distribution functions. Finally, a simple but effective algorithm was proposed to study the grain distribution and mosaicity in heterogeneous crystalline materials, moving beyond the study of homogeneous systems.
Overall, these studies aim to enable faster and more comprehensive analysis of the disordered structures in nanocrystalline, nanoporous, and heterogeneous materials, which could have applications in fields including photocatalysis, optical or gas sensing, radioactive waste storage, and metallurgical industry.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/yz5p-es51 |
| Date | January 2023 |
| Creators | Tao, Songsheng |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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