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Abstract:

In this thesis, design and operation strategies for chemical-looping combustion (CLC) and chemical-looping gasification (CLG) are investigated to improve the sustainability of energy generation. In this work, a nonlinear model predictive control scheme is implemented for large-scale packed bed CLC, and is used to determine control actions which increase the energy generation and carbon capture effectiveness of the process. In addition, a reactor network model is developed for biomass-fueled CLC and CLG and is used to determine reactor designs which improve the gasification efficiency of CLG and the carbon capture effectiveness of CLC.

To monitor the progress of manure fermentation and control gas pollutants from manure lagoon released into the atmosphere, a sensor that can detect components of biogas in a reliable manner is necessary. Any sensor requires a sensing material that responds to one specific gas analyte. Polyaniline (PANI), PPy and PDMS are found to have affinity for ammonia and/or methane.

They were tested with gas chromatography using formaldehyde. PANI showed better sorption. SnO2, ZnO, SDS, TiO2 and HCl were selected as dopants for PANI. PANI was synthesized with varying dopant levels for GC testing. When tested with the MEMS sensor, both PANI with SnO2 and ZnO sorbed methane at ambient temperature. PANI-5% ZnO was proven to be the most suitable sensing material for methane detection, showing the highest signal at 50 ppm methane levels.