Self-Powered Non-Contact Motion Vector Sensor for Multifunctional Human-Machine Interface

Multi-receptor skin with highly sensitive tele-perception somatosensory

The limitations and complexity of traditional noncontact sensors in terms of sensitivity and threshold settings pose great challenges to extend the traditional five human senses. Here, we propose tele-perception to enhance human perception and cognition beyond these conventional noncontact sensors. Our bionic multi-receptor skin employs structured doping of inorganic nanoparticles to enhance the local electric field, coupled with advanced deep learning algorithms, achieving a ΔV/Δd sensitivity of 14.2, surpassing benchmarks. This enables precise remote control of surveillance systems and robotic manipulators. Our long short-term memory-based adaptive pulse identification achieves 99.56% accuracy in material identification with accelerated processing speeds. In addition, we demonstrate the feasibility of using a two-dimensional (2D) sensor matrix to integrate real object scan data into a convolutional neural network to accurately discriminate the shape and material of 3D objects. This promises transformative advances in human-computer interaction and neuromorphic computing.

A self-powered droplet sensor based on a triboelectric nanogenerator toward the concentration of green tea polyphenols

Self-powered liquid droplet sensors based on triboelectric nanogenerators have attracted extensive attention in the field of biochemical sensing applications. Numerous research studies have investigated the effects of factors such as molecular species, molecular concentration, molecular charge, and molecular dipole moment in solution on the output electrical signals of the sensor. In this study, we prepared a self-powered droplet sensor using conductive copper film tape, polytetrafluoroethylene, and conductive aluminum foil tape. The sensor can continuously output pulsed electrical signals with minimal environmental impact. In comparison with other types of sensors, this sensor boasts a rapid response time of 10 ms and excellent sensitivity. The relationship between the friction-induced output current and voltage of the droplets and the concentration of green tea polyphenols (GTPs) was studied using the self-powered liquid droplet sensor with five different green tea samples. It was found that GTPs were the main factor contributing to the changes in output electrical signals in green tea water droplets. Fluorescence spectroscopy was used to reveal that the magnitude of the output current was inversely proportional to the concentration of GTPs in green tea. These results demonstrate the potential application of self-powered liquid droplet sensors in biochemical sensing applications based on concentration-dependent output signals.

Effective Charging of Commercial Lithium Cell by Triboelectric Nanogenerator with Ultrahigh Voltage Energy Management

It is an increasingly mature application solution that triboelectric nanogenerator (TENG) supplies power to electronic devices through its power management system (PMS). However, the previous PMS is able to manage a limited voltage magnitude and the energy storage elements are limited to capacitors. This work proposes an ultrahigh voltage PMS (UV-PMS) to realize the charging of commercial lithium cells (LCs) by TENG. The design of UV-PMS enables energy management of TENGs with ultrahigh open-circuit voltages up to 3500 V and boosts the peak charging current from 30.9 µA to 2.77 mA, an increase of 89.64 times. With the introduction of UV-PMS, the effective charging capacity of LC charged by a TENG at a working frequency of 1.5 Hz for 1 h comes to 429.7 µAh, making a 75.3 times enhancement compared to charging by TENG directly. The maximum charging power comes to 1.56 mW. The energy storage efficiency is above 97% and the overall charge efficiency can be maintained at 81.2%. This work provides a reliable strategy for TENG to store energy in LC, and has promising applications in energy storage, LC's life, and self-powered systems.

High Sensitivity Triboelectric Based Flexible Self-Powered Tactile Sensor with Bionic Fingerprint Ring Structure

Flexible self-powered tactile sensors, with applications spanning wearable electronics, human-machine interaction, prosthetics, and soft robotics, offer real-time feedback on tactile interactions in diverse environments. Despite advances in their structural development, challenges persist in sensitivity and robustness, particularly when additional functionalities, such as high transparency and stretchability. In this study, we present a novel approach integrating a bionic fingerprint ring structure with a PVDF-HFP/AgNWs composite fiber electrode membrane, fabricated via 3D printing technology and electrospinning, respectively, yielding a triboelectric nanogenerator (TENG)-based self-powered tactile sensor. The sensor demonstrates high sensitivity (5.84 V/kPa in the 0-10 kPa range) and rapid response time (10 ms), attributed to the microring texture on its surface, and exhibits exceptional robustness, maintaining electrical output integrity even after 24,000 cycles of loading. These findings highlight the potential of the microring structures in addressing critical challenges in flexible sensor technology.

Facile Electret-Based Self-Powered Soft Sensor for Noncontact Positioning and Information Translation

Noncontact sensors have demonstrated significant potential in human-machine interactions (HMIs) in terms of hygiene and less wear and tear. The development of soft, stable, and simply structured noncontact sensors is highly desired for their practical applications in HMIs. This work reports on electret-based self-powered noncontact sensors that are soft, transparent, stable, and easy to manufacture. The sensors contain a three-layer structure with a thickness of 0.34 mm that is fabricated by simply stacking a polymeric electret layer, an electrode layer, and a substrate layer together. The fabricated sensors show high charge-retention capability, keeping over 98% of the initial surface potential even after 90 h, and can accurately and repeatedly sense external approaching objects with impressive durability. The intensity of the detected signal shows a strong dependence on the distance between the object and the sensor, capable of sensing a distance as small as 2 mm. Furthermore, the sensors can report stable signals in response to external objects over 3000 cycles. By virtue of the signal dependence on distance, an intelligent noncontact positioning system is developed that can precisely detect the location of an approaching object. Finally, by integrating with eyeglasses, the transparent sensor successfully captures the movements of blinks for information translation. This work may contribute to the development of stable and easily manufactured noncontact soft sensors for HMI applications, for instance, assisting with communication for locked-in syndrome patients.

Largely Improving the Output Performance of Stretchable Triboelectric Nanogenerators via Thermo-Compressive Technology

Stretchable triboelectric nanogenerators (TENGs) are widely applied in wearable and implantable electronics, smart medical devices, and soft robots. However, it is still a challenge to produce stretchable TENGs with both exceptional elasticity and output performance, which limits their application scope. In this work, high-performance stretchable TENGs are developed through a thermo-compression (TC) fabrication process. In particular, a poly(vinylidene fluoride) film is compactly bound to the elastic thermoplastic polyurethane substrate, which inherits excellent stretchability with a strain of up to 815%. Furthermore, owing to the large surface area, tight contact, and effective vertical transport of tribo-induced charges between the coupled fibrous tribo-layer and soft substrate, the TC composite film-based TENGs exhibit a greater output (2-4 times) than unlaminated film-based TENGs. Additionally, the broad universality of this method is proven using various tribo- and substrate materials. The proposed technology provides a novel and effective approach to conjointly boost the output and stretchability of TENGs, showing encouraging application prospects in self-powered wearable and flexible electronics.

Harvesting Inertial Energy and Powering Wearable Devices: A Review

Amidst the swift progression of microelectronics and Internet of Things technology, wearable devices are gradually gaining ground in the domains of human health monitoring. Recently, human bioenergy harvesting has emerged as a plausible alternative to batteries. This paper delves into harvesting human inertial energy that stimulates inertial masses through human motion and then transmutes the motion of the inertial masses into electrical energy. The inertial energy harvester is better suited for low-frequency and irregular human motion. This review first identifies the sources of human motion excitation that are compatible with inertial energy harvesters and then provides a summary of the operating principles and the comparisons of the commonly used energy conversion mechanisms, including electromagnetic, piezoelectric, and triboelectric transducers. The review thoroughly summarizes the latest advancements in human inertial energy-harvesting technology that are categorized and grouped based on their excitation sources and mechanical modulation methods. In addition, the review outlines the applications of inertial energy harvesters in powering wearable devices, medical health monitoring, and as mobile power sources. Finally, the challenges faced by inertial energy-harvesting technologies are discussed, and the review provides a perspective on the potential developments in the field.

A Flexible Self-Powered Noncontact Sensor with an Ultrawide Sensing Range for Human-Machine Interactions in Harsh Environments

Noncontact human-machine interactions (HMIs) provide a hygienic and intelligent approach to communicate between humans and machines. However, current noncontact HMIs are generally hampered by the interaction distance, and they lack the adaptability to environmental interference such as high humidity conditions. Here, we explore a self-powered electret-based noncontact sensor (ENS) with moisture-resisting ability and ultrawide sensing range exceeding 2.5 m. A megascopic air-bubble structure is designed to enhance charge-storage stability and charge-recovery ability of the ENS based on the heterocharge-synergy effect in electrets. Besides, multilayer electret films are introduced to strengthen the electric field by utilizing the electrostatic field superposition effect. Thanks to the above improved performances of the ENS, we demonstrate various noncontact HMI applications in harsh environments, including noncontact appliances, a moving trajectory and accidental fall tracking system, and a real-time machine learning-assisted gesture recognition system with accuracy as high as 99.21%. This research expands the way for noncontact sensor design and may further broaden applications in noncontact HMIs.

A Flexible Tribotronic Artificial Synapse with Bioinspired Neurosensory Behavior

As key components of artificial afferent nervous systems, synaptic devices can mimic the physiological synaptic behaviors, which have attracted extensive attentions. Here, a flexible tribotronic artificial synapse (TAS) with bioinspired neurosensory behavior is developed. The triboelectric potential generated by the external contact electrification is used as the ion-gel-gate voltage of the organic thin film transistor, which can tune the carriers transport through the migration/accumulation of ions. The TAS successfully demonstrates a series of synaptic behaviors by external stimuli, such as excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memory process from sensory memory to short-term memory and long-term memory. Moreover, the synaptic behaviors remained stable under the strain condition with a bending radius of 20 mm, and the TAS still exhibits excellent durability after 1000 bending cycles. Finally, Pavlovian conditioning has been successfully mimicked by applying force and vibration as food and bell, respectively. This work demonstrates a bioinspired flexible artificial synapse that will help to facilitate the development of artificial afferent nervous systems, which is great significance to the practical application of artificial limbs, robotics, and bionics in future.