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    Molecular adsorption and diffusion properties of polymeric and microporous materials via quartz crystal microbalance techniques

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    VENKATASUBRAMANIAN-DISSERTATION-2013.pdf (3.563Mb)
    Date
    2013-06-05
    Author
    Venkatasubramanian, Anandram
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    Abstract
    Nanoporous molecular sieve materials like metal organic frameworks (MOFs) and metal oxide nanotubes (AlSiNTs) have found a wide range of technological applications in catalysis, separations, and ion exchange due to their salient features over other contemporary sensing materials. As a result, these materials can function as a chemical recognition layer that relies on analyte adsorption and they have shown to selectively adsorb specific gas molecules from mixtures. The characterization of gas adsorption in these materials is performed predominantly by commercial gravimetric equipment, whose capital and operating costs are generally high and require relatively large amounts of sample. Thus, it is desirable to obtain a reliable measure of the gas transport properties of these materials over a substantial range of pressure and temperature by non-gravimetric methods. The objective of this thesis is to investigate the adsorption and diffusion characteristics of recently-identified nanoporous materials through the development and use of a high-pressure/high-temperature quartz crystal microbalance (QCM) device. In this regard, this thesis is divided into four main objectives, viz. (1) Design and development of high temperature/ high pressure QCM device, (2) Measurement and analysis of adsorption characteristics in nanoporous materials, (3) Diffusion measurement and analysis in polymer thin films and (4) Diffusion measurement and analysis in MOF crystals. The results obtained in Objectives 2-4 will allow us to make important recommendations regarding the use of specific nanoporous materials in molecular separation applications and also lead to significant understanding of gas uptake thermodynamics in nanoporous materials via the application of analytical models to the experimental data.
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    http://hdl.handle.net/1853/52167
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    • Georgia Tech Theses and Dissertations [22398]
    • School of Mechanical Engineering Theses and Dissertations [3831]

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