Researches at the Terasaki Institute for Biomedical Innovation (TIBI) have used artificial intelligence (AI) to improve the design and production of nanofibers for wearable nanofiber acoustic energy harvesters (NAEH) that are used for the design and production of wearable nanofibers. These mini-machines absorb environmental sound energy and turn it into electricity, which can power the lifeline of hearing aids among other exciting applications.
Humans are already getting energy from natural sources that are being wasted in the environment. Innovations such as solar panels and wind turbines permit us to collect sun and wind energy into electricity that we can store and use for different purposes. Furthermore, sound is also changed to acoustic energy in the case of amplifying technologies such as microphones, which can then be readdressed to wearable IoT sensors that a patient can wear for monitoring health.
At the moment, there is a burgeoning concern with piezoelectric nanogenerators, which are tools for the conversion of mechanical vibrations, stress, or strain into electrical power as micro-acoustic energy harvesters. Piezoelectric nanogenerators are mechanical-to-electrical energy conversion devices that can use sound waves as power. The transformation of sound energy to electricity, however, is a restriction of high-frequency emitters, which are capable of converting only high-frequency sound waves while the majority of sounds are at low frequencies. In addition, the selection of the best materials, structural design, and fabrication methods is a difficult task in producing piezoelectric nanogenerators.
In a report that was published in Nano Research, the TIBI scientists conquered these difficulties in the study. They decided to use the first end of that double acting approach by electing the correct materials and decided to synthesize the plaque using piezoelectric polyvinylfluoride (PVDF). This PVDF nanocapture had the advantage of being energy efficient.
They piggybacked the original PVDF solution with polyurethane (PU) in order to make it more flexible and they did the electrospinning technique, which is a technique for creating ultrathin fibers, to produce the composite PVDF/PU nanofibers.
For the next part, they used AI techniques in order to optimize the fabrication parameters implicated in electrospinning the PVDF/PU nanofibers. These parameters mentioned, applied voltages, the duration of electrospinning time, and the number of drum rotations. Through this AI. The team succeeded in the proper setting of the values which made their that PVDF/PU nanofibers could make more power from solar cell.
Industry the nanoacoustic energy harvester came of the new in terms of its principal who is PVDF/PU nanofibers. The researchers performed the following materials by cutting the PVDF/PU nanofiber mat finished with a nanofibrous mat and attaching it to aluminum mesh layers as the working electrodes. Then the whole setup was placed in two flexible frames.
It was ascertained through the trials that the overachieved AI-made PVDF/PU NAEHs surpassed the conventional NAEHs. The devices that derived from the AI process showed the power density level more than 2.5 times higher and an energy conversion efficiency (66% compared to 42%) as well. In addition to this, these optimized NAEHs performed excellently over a wide range of low-frequency background noise, a sound stream that is normally encountered at a normal pace. The acceptance of excellent sound recognition and high-resolution word distinction was also.
“The AI optimization model that we have been using has cut down the time trial and error significantly and done a perfect job with the end product,” Dr. Ali Khademhosseini, TIBI director and CEO, mentioned. “The idea of this kind of approach may have a significant impact on the manufacturing of medical devices on a practical scale.” Summing up, the scientists at TIBI used AI in a great way, which in turn will improve nanofiber creation and production that is a significant advancement
in the field of energy harvesting by sound waves.
Reference: Enhancing nanofibrous acoustic energy harvesters with artificial intelligence