The ever-growing Internet of Things is promoting more data acquisition, data exchange and fewer human interactions, engendering a higher demand for sensors and therefore power. While in most cases it is possible to directly connect these sensors to the power grid, it will not always be feasible with emerging technologies, especially in remote areas where human access is limited.
Moisture-Electric Energy Transformation (MEET) devices are components that use moisture as a “fuel” to generate electrical power. Upon contact with moisture, a potential difference results from a diffusion mechanism, allowing charge to be stored locally in capacitors or rechargeable batteries to be utilized for useful work.
The focus of the present work was to investigate the potential of Cold Gas Dynamic Spray (CGDS) as an additive manufacturing (AM) process for the fabrication of MEET devices. Following a layer-by-layer approach, MEET devices were successfully built by CGDS, by combining aluminum (electrode material) and an in-situ composite of polyether ether ketone (PEEK) and alumina (diffusion medium).
The main challenges of this work were the determination of the spray parameters of PEEK and the investigation of the MEET capability of the manufactured devices. On the other hand, the main contributions of this work were the demonstration of the viability of CGDS in the deposition of PEEK/Al2O3 on aluminum 6061-T6 substrates, as well as the potential of PEEK as a MEET-capable material. The diffusion mechanisms that govern power generation were also hypothesized, explained and summarized.
Initial tests of a MEET device of 66 mm x 34 mm indicate an uninterrupted power generation cycle of over 30 hours, and a maximum output voltage of 268 mV with a 6.8 MΩ load. The output power and power per unit area of the device were computed to be 10.63 nW and 4.736 µW/m2 respectively. The output current and current density were evaluated to 39.53 nA and 17.62 µA/m2.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/40052 |
| Date | 10 January 2020 |
| Creators | Daoud, Amir |
| Contributors | Jodoin, Bertrand |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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