Rollable Magnetoelectric Energy Harvester as a Wireless IoT Sensor

Parasitic magnetic noise arising from an electrical power transmission system is the most abundant form of waste energy in our daily life. In this work, a flexible and rollable magneto-mechano-electric nanogenerator (MMENG)-based wireless Internet of Things (IoT) sensor has been demonstrated to capture and utilize the environmental magnetic noise in the absence of a direct current magnetic field. Free-standing magnetoelectric composites are fabricated by combining magnetostrictive nickel ferrite (NiFe2O4) nanoparticles (similar to 9 nm diameter) and piezoelectric polyvinylidene-co-trifluoroethylene polymer. The magneto-elctric 0-3-type nanocomposites possess maximum magnetoelectric voltage coefficient (alpha) of 11.43 mV/cm Oe. Even, without a magnetic bias field, 99% of the maximum a value is observed due to the self-bias effect. The magnetoelectric voltage generation capability under a low-frequency (50-60 Hz) alternating current magnetic field, validated by theoretical simulation, enables the nanocomposite to design efficient MMENG for harvesting a low-frequency stray magnetic field from the power cable of home appliances, such as electric kettle and microwave oven. As a result, the MMENG generates a peak-to-peak open circuit voltage of 1.4 V and output power density of 0.05 mu W/cm(3) and successfully operates a commercial capacitor under the weak (similar to 1.7 X 10(-3) T) and low-frequency (similar to 50 Hz) stray magnetic field arising from the power cable of electric kettle. Additionally, under the rolled condition around the power cable, the MMENG generates a slightly improved peak-to-peak open circuit voltage of 1.5 V. Finally, the harvested electrical signal has been wirelessly transmitted to a smart phone to demonstrate the possibility of position monitoring system construction. This cost-effective and easy to integrate approach with tailored size and shape of device configuration is expected to be explored in next-generation self-powered IoT sensors including implantable biomedical devices and human health monitoring sensory systems.