Detection of explosive gas leaks such as hydrogen (H2) becomes key element in the wake of counter-terrorism threats, introduction of hydrogen powered vehicles and use of hydrogen as a fuel for space explorations. In recent years, a significant interest has developed on metal oxide nanostructured sensors for the detection of hydrogen gas. Gas sensors properties such as sensitivity, selectivity and response time can be enhanced by tailoring the size, the shape, the structure and the surface of the nanostructures. Sensor properties (sensitivity, selectivity and response time) are largely modulated by operating temperature of the device. Issues like instability of nanostructures at high temperature, risk of hydrogen explosion and high energy consumption are driving the research towards detection of hydrogen at low temperatures. At low temperatures adsorption of O2- species on the sensor surface instead of O- (since O- species reacts easily with hydrogen) result in need of higher activation energy for hydrogen and adsorbed species interaction. This makes hydrogen detection at room temperature a challenging task. Higher surface area to volume ratio (resulting higher reaction sites), enhanced electronic properties by varying size, shape and doping foreign impurities (by modulating space charge region) makes nanocrystalline materials ideal candidate for room temperature gas sensing applications. In the present work various morphologies of nanostructured tin oxide (SnO2) and indium (In) doped SnO2 and titanium oxide (titania, TiO2) were synthesized using sol-gel, hydrothermal, thermal evaporation techniques and successfully integrated with the micro-electromechanical devices H2 at ppm-level (as low as 100ppm) has been successfully detected at room temperature using the SnO2 nanoparticles, SnO2 (nanowires) and TiO2 (nanotubes) based MEMS sensors. While sensor based on indium doped tin oxide showed the highest sensitivity (S =Ra/Rg= 80000) and minimal response time (10sec.). Highly porous SnO2 nanoparticles thin film (synthesized using template assisted) showed response time of about 25 seconds and sensitivity 4. The one dimensional tin oxide nanostructures (nanowires) based sensor showed a sensitivity of 4 and response time of 20 sec. Effect of aspect ratio of the nanowires on diffusion of hydrogen molecules in the tin oxide nanowires, effect of catalyst adsorption on nanowire surface and corresponding effect on sensor properties has been studied in detail. Nanotubes of TiO2 prepared using hydrothermal synthesis showed a sensitivity 30 with response time as low as 20 seconds where as, TiO2 nanotubes synthesized using anodization showed poor sensitivity. The difference is mainly attributed to the issues related to integration of the anodized nanotubes with the MEMS devices. The effect of MEMS device architecture modulation, such as, finger spacing, number and length of fingers and electrode materials were studied. It has been found that faster sensor response (~ 10 sec) was observed for smaller finger spacing. A diffusion model is proposed for elucidating the effect of inter-electrode distance variation on conductance change of a nano-micro integrated hydrogen sensor for room temperature operation. Both theoretical and experimental results showed a faster response upon exposure to hydrogen when sensor electrode gap was smaller. Also, a linear increase in the sensor sensitivity from 500 to 80000 was observed on increasing the electrode spacing from 2 to 20 μm. The improvement in sensitivity is attributed to the higher reactive sites available for the gaseous species to react on the sensor surface. This phenomenon also correlated to surface adsorbed oxygen vacancies (O-) and the rate of change of surface adsorbed oxygen vacancies. This dissertation studied in detail dimensionality aspects of materials as well as device in detecting hydrogen at room temperature.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4140 |
| Date | 01 January 2007 |
| Creators | Deshpande, Sameer Arun |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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