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(1) Research Design: The experiment used waste EPS as the raw material, dissolved in toluene to form a transparent solution, and then electrospun onto aluminum foil to create a nanofiber friction negative layer. The aluminum foil simultaneously served as the electrode and the friction positive layer. Both friction layers were supported by flexible PET, and the device adopted a vertical contact-separation mode, retaining an air gap to facilitate repeated contact. The smart sensor arranged the aluminum and EPS nanofibers in zones to create a pressable, positionable switch structure. Electrical tests were conducted using a programmable linear motor to apply periodic excitation, with an oscilloscope recording open-circuit voltage and short-circuit current to examine the effects of frequency, area, and load. Signals were sampled by a microcontroller, segmented with a sliding window, and features like mean, standard deviation, peak, minimum, and root mean square were extracted, then classified using a random forest for real-time recognition.
(2) Results: FTIR and Raman confirmed that EPS retained the characteristic aromatic and aliphatic structures of polystyrene, with the π-system in the benzene rings stabilizing surface electrons, explaining its negative triboelectric property. SEM showed that the nanofibers formed an interconnected network with uniform element distribution; AFM revealed a rough surface with nanoscale bumps, and KPFM indicated higher work function and surface potential, with enhanced electron affinity due to electrospinning-induced dipole orientation. In electrical tests, the nanofiber device outperformed film devices and also did better than PET, PDMS, and PTFE controls; output increased with area and frequency, peaking when load matched. Long-term continuous cycles, aging, and humidity-temperature tests showed the device was overall stable, with performance degradation under high humidity linked to moisture absorption and aluminum oxidation. AI classification reliably distinguished triggers.
(3) Extended Thinking: This work integrates recycled thermoplastics, nanofiber structure control, triboelectric energy harvesting, and machine learning signal recognition into a self-powered smart interface, highlighting the link between nanoscale electronic properties and macroscopic device performance. Its significance goes beyond energy harvesting demonstrations, offering an expandable path for high-value utilization of waste plastics and showcasing the potential of self-powered sensors in smart buildings, IoT nodes, human-machine interaction, and elevator control. Future work could focus on optimizing fiber morphology, surface chemistry, packaging, and electrode stability to improve high-humidity adaptability, explore multi-material composites and array designs to enhance signal robustness and system integration, and promote the development of sustainable smart electronic systems.
Original Link
DOI: 10.1002/advs.77972
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