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Methods of electrostatic conversion are available for harvesting energy where there are ambient vibrations. However, most of the previous work in the literature has addressed applications with high frequencies. In this study, we are not only implementing an electret-based energy harvester for low-frequency applications but also evaluating the effect of parameters, including vibration rates, accelerations, electret surface potential, e.g. on the efficiency of electrostatic energy harvesting (EH). A prototype system, with the size of 4 × 28 cm 3 , was built and constructed to accomplish experimental analysis, and the corona triode process was used to prepare electrets by charging Teflon FEP films. In the electret surface potential range of 300-1800 V, vibration frequency range of 2-45 Hz, and acceleration range of 0.1-1.0 g, the effect of parameters on the EH efficiency was experimentally tested. To predict and maximize the performance of the system, a mathematical response surface model (RSM), validated experimentally < 9.5% error. The maximum peak-peak voltage output of 318 V was predicted using this model for the electret surface potential of −1800 V, and vibration frequency of 16 Hz. Moreover, harvested energy was ∼ 900 µJ (∼0.8 µJ per mechanical cycle) in a minute though low frequencies (<20 Hz), which can be easily enhanced to more than 1 mJ with system optimization. We suggest our device can be used in numerous low-frequency applications, and our predictive model can also be used to optimize the efficiency of other electrostatic energy harvesters based on electrets.

Objective. Free-floating implantable neural interfaces are an emerging powerful paradigm for mapping and modulation of brain activity. Minuscule wirelessly-powered devices have the potential to provide minimally-invasive interactions with neurons in chronic research and medical applications. However, these devices face a seemingly simple problem—how can they be placed into nervous tissue rapidly, efficiently and in an essentially arbitrary location? Approach. We introduce a novel injection tool and describe a controlled injection approach that minimizes damage to the tissue. Main results. To validate the needle injectable tool and the presented delivery approach, we evaluate the spatial precision and rotational alignment of the microdevices injected into agarose, brain, and sciatic nerve with the aid of tissue clearing and MRI imaging. In this research, we limited the number of injections into the brain to four per rat as we are using microdevices that are designed for an adult head size on a rat model. We then present immunohistology data to assess the damage caused by the needle. Significance. By virtue of its simplicity, the proposed injection method can be used to inject microdevices of all sizes and shapes and will do so in a fast, minimally-invasive, and cost-effective manner. As a result, the introduced technique can be broadly used to accelerate the validation of these next-generation types of electrodes in animal models.

This study demonstrates an energy harvester that combines a piezoelectric nanogenerator and an electret-based electrostatic generator. The device consists of an in-house fabricated nanocomposite (polydimethylsiloxane/barium titanate/carbon nanotube) as a piezoelectric layer and a monocharged Teflon fluorinated ethylene propylene as an electret electrostatic layer. The mechanical impedance of the structure can be altered easily by changing the nanocomposite monomer/cross-linker ratio and optimizing various mechanical energy sources. The energy harvester's performance was characterized by performing measurements with different frequencies (5–20 Hz) under applied dynamic loading. A total volumetric power density of ∼8.8 μW cm−3 and a total stored energy of ∼50.2 μJ min−1 were obtained. These findings indicate that this versatile, lightweight, and low-cost energy harvester can be employed as a power supply source for microelectronics in applications, such as wearables.

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