Advancing Reverse Electrowetting‐on‐Dielectric from Planar to Rough Surface Electrodes for High Power Density Energy Harvesting. Issue 3 (7th January 2022) - Adhikari, Pashupati R.; Patwary, Adnan B.; Kakaraparty, Karthik; Gunti, Avinash; Reid, Russell C.; Mahbub, Ifana
Abstract : Reverse electrowetting‐on‐dielectric (REWOD)‐based energy harvesting has been studied over the last decade as a novel technique of harvesting energy by actuating liquid droplet(s) utilizing applied mechanical modulation. Much prior research in REWOD has relied on planar electrodes, which by its geometry possess a limited surface area. In addition, most of the prior REWOD works have applied a high bias voltage to enhance the output power that compromises the concept of self‐powering wearable motion sensors in human health monitoring applications. In order to enhance the REWOD power density resulting from an increased electrode–electrolyte interfacial area, high surface area electrodes are required. Herein, electrical and multiphysics‐based modeling approaches of REWOD energy harvester using structured rough surface electrodes are presented. By enhancing the overall available surface area, an increase in the overall capacitance is achieved. COMSOL and MATLAB‐based models are also developed, and the empirical results are compared with the models to validate the performance. Root mean square (RMS) power density is calculated using the RMS voltage across an optimal load impedance. For the proposed rough electrode REWOD energy harvester, maximum power density of 3.18 μW cm −2 is achieved at 5 Hz frequency, which is ≈4 times higher than that of the planar electrodes. Abstract : Low‐frequency motion (1–5 Hz) energy harvesting based on reverse electrowetting‐on‐dielectric is presented using structured high surface area rough electrodes. The energy harvester is capable of generating up to 3.18 μW cm −2 of power density without external bias voltage, making the harvester suitable to power up wearable motion sensors. Empirical results are validated and supported with developed mathematical models.