Boosting Output Performance of Sliding Mode Triboelectric Nanogenerator by Shielding Layer and Shrouded-Tribo-Area Optimized Ternary Electrification Layered Architecture.

Sliding mode triboelectric nanogenerator (S-TENG) is effective for low-frequency mechanical energy harvesting owing to their more efficient mechanical energy extraction capability and easy packaging. Ternary electrification layered (TEL) architecture is proven useful for improving the output performance of S-TENG. However, the bottleneck of electric output is the air breakdown on the interface of tribo-layers, which seriously restricts its further improvement. Herein, a strategy is adopted by designing a shielding layer to prevent air breakdown on the central surface of tribo-layers. And the negative effects of air breakdown on the edge of sliding layer are averted by increasing the shrouded area of tribo-layers on slider. Output charge of this shielding-layer and shrouded-tribo-area optimized ternary electrification layered triboelectric nanogenerator (SS-TEL-TENG) achieves 3.59-fold enhancement of traditional S-TENG and 1.76-fold enhancement of TEL-TENG. Furthermore, even at a very low speed of 30 rpm, output charge, current, and average power of the rotation-type SS-TEL-TENG reach 4.15 µC, 74.9 µA, and 25.4 mW (2.05 W m-2 Hz-1 ), respectively. With such high-power output, 4248 LEDs can be lighted brightly by SS-TEL-TENG directly. The high-performance SS-TEL-TENG demonstrated in this work will have great applications for powering ubiquitous sensor network in the Internet of Things (IoT).

Deep Learning Enabled Neck Motion Detection Using a Triboelectric Nanogenerator.

The state of neck motion reflects cervical health. To detect the motion state of the human neck is of important significance to healthcare intelligence. A practical neck motion detector should be wearable, flexible, power efficient, and low cost. Here, we report such a neck motion detector comprising a self-powered triboelectric sensor group and a deep learning block. Four flexible and stretchable silicon rubber based triboelectric sensors are integrated on a neck collar. With different neck motions, these four sensors lead-out voltage signals with different amplitudes and/or directions. Thus, the combination of these four signals can represent one motion state. Significantly, a carbon-doped silicon rubber layer is attached between the neck collar and the sensors to shield the external electric field (i.e., electrical changes at the skin surface) for a far more robust identification. Furthermore, a deep learning model based on the convolutional neural network is designed to recognize 11 classes of neck motion including eight directions of bending, two directions of twisting, and one resting state with an average recognition accuracy of 92.63%. This developed neck motion detector has promising applications in neck monitoring, rehabilitation, and control.

High performance floating self-excited sliding triboelectric nanogenerator for micro mechanical energy harvesting.

Non-contact triboelectric nanogenerator (TENG) enabled for both high conversion efficiency and durability is appropriate to harvest random micro energy owing to the advantage of low driving force. However, the low output (<10 µC m-2) of non-contact TENG caused by the drastic charge decay limits its application. Here, we propose a floating self-excited sliding TENG (FSS-TENG) by a self-excited amplification between rotator and stator to achieve self-increased charge density, and the air breakdown model of non-contact TENG is given for a maximum charge density. The charge density up to 71.53 µC m-2 is achieved, 5.46 times as that of the traditional floating TENG. Besides, the high output enables it to continuously power small electronics at 3 m s-1 weak wind. This work provides an effective strategy to address the low output of floating sliding TENG, and can be easily adapted to capture the varied micro mechanical energies anywhere.

Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real-Time Gesture Interaction.

In human-machine interaction, robotic hands are useful in many scenarios. To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction. Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. With a finger's traction movement of flexion or extension, the sensor can induce positive/negative pulse signals. Through counting the pulses in unit time, the degree, speed, and direction of finger motion can be judged in real-time. The magnetic array plays an important role in generating the quantifiable pulses. The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway, respectively, thus improve the durability, low speed signal amplitude, and stability of the system. This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural, intuitive, and real-time human-robotic interaction.

Wearable triboelectric sensors for biomedical monitoring and human-machine interface.

A growing advocacy of healthy and quality life makes wearable electronics spring up. Triboelectric nanogenerator (TENG) has developed as an energy harvesting technology and as an advanced sensor technology in wearable electronics. The triboelectric sensor (TS) is sensitive to the mechanical motion and driven by the motion itself. Therefore, TS is capable of monitoring certain vital signs and kinds of movements of human body. Based on these monitoring, novel human-machine interfaces (HMIs) can be established. In this review, a comprehensive overview of some key progresses in this field over last 5 years are presented. Several main aspects of biomedical monitoring based on TSs are classified: pulse/cardiac/micro-motion, respiration/airflow/vibration, and pressure/tactile/body movement. The major types of HMIs taking these biomedical monitoring as basis are introduced accordingly: eye movement, voice/auditory, gesture/joint movement, and touch/tactile based HMIs. Finally, the current limitations and future trends are put forward for biomedical monitoring and HMIs based on TSs.

High performance of filter capacitor based on nitrogen-doped carbon nanotube supercapacitor.

The high-performance filter capacitor is a hot research topic in the field of filter circuits for flexible and wearable devices, whereas traditional aluminum electrolytic capacitors still experience widespread problems in terms of large error factors and poor stability. To avoid these disadvantages, in this work, we have developed a liquid dual-layer supercapacitor (SC). When it is employed as the filter capacitor in a filter circuit, any waveform signal can be transformed into a linear signal. The maximum fluctuation of the output signal is less than 16 mV; the SC also demonstrates excellent filtering stability in a frequency range of 1 ∼ 100 000 Hz, as well as an amplitude window of 0 ∼ 10 V. In this framework, our filter SC demonstrates unparalleled processing properties, and can greatly improve the stability and extend the lifetime of the entire electronic circuit. The fact that the requirements of high-end electronic products can be fulfilled due to the contribution of this filter SC are particularly significant.

Author Correction: Boosting output performance of sliding mode triboelectric nanogenerator by charge space-accumulation effect.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Boosting output performance of sliding mode triboelectric nanogenerator by charge space-accumulation effect.

The sliding mode triboelectric nanogenerator (S-TENG) is an effective technology for in-plane low-frequency mechanical energy harvesting. However, as surface modification of tribo-materials and charge excitation strategies are not well applicable for this mode, output performance promotion of S-TENG has no breakthrough recently. Herein, we propose a new strategy by designing shielding layer and alternative blank-tribo-area enabled charge space-accumulation (CSA) for enormously improving the charge density of S-TENG. It is found that the shielding layer prevents the air breakdown on the interface of tribo-layers effectively and the blank-tribo-area with charge dissipation on its surface of tribo-material promotes charge accumulation. The charge space-accumulation mechanism is analyzed theoretically and verified by experiments. The charge density of CSA-S-TENG achieves a 2.3 fold enhancement (1.63 mC m-2) of normal S-TENG in ambient conditions. This work provides a deep understanding of the working mechanism of S-TENG and an effective strategy for promoting its output performance.

Direct Current Fabric Triboelectric Nanogenerator for Biomotion Energy Harvesting.

Triboelectric nanogenerators (TENGs) have demonstrated their promising potential in biomotion energy harvesting. A combination of the TENG and textile materials presents an effective approach toward smart fabric. However, most traditional fabric TENGs with an alternating current (AC) have to use a stiff, uncomfortable, and unfriendly rectifier bridge to obtain direct current (DC) to store and supply power for electronic devices. Here, a DC fabric TENG (DC F-TENG) with the most common plain structure is designed to harvest biomotion energy by tactfully taking advantage of the harmful and annoying electrostatic breakdown phenomenon of clothes. A small DC F-TENG (1.5 cm × 3.5 cm) can easily light up 416 serially connected light-emitting diodes. Furthermore, some yarn supercapacitors are fabricated and woven into the DC F-TENG to harvest and store energy and to power electronic devices, such as a hygrothermograph or a calculator, which shows great convenience and high efficiency in practice. This low-cost and efficient DC F-TENG which can directly generate DC energy without using the rectifier bridge by harvesting energy from unhealthy electrostatic breakdown has great potential as a lightweight, flexible, wearable, and comfortable energy-harvesting device in the future.

Integrated charge excitation triboelectric nanogenerator.

Performance of triboelectric nanogenerators is limited by low and unstable charge density on tribo-layers. An external-charge pumping method was recently developed and presents a promising and efficient strategy towards high-output triboelectric nanogenerators. However, integratibility and charge accumulation efficiency of the system is rather low. Inspired by the historical development of electromagnetic generators, here, we propose and realize a self-charge excitation triboelectric nanogenerator system towards high and stable output in analogy to the principle of traditional magnetic excitation generators. By rational design of the voltage-multiplying circuits, the completed external and self-charge excitation modes with stable and tailorable output over 1.25 mC m-2 in contact-separation mode have been realized in ambient condition. The realization of the charge excitation system in this work may provide a promising strategy for achieving high-output triboelectric nanogenerators towards practical applications.

Screen-Printed Washable Electronic Textiles as Self-Powered Touch/Gesture Tribo-Sensors for Intelligent Human-Machine Interaction.

Multifunctional electronic textiles (E-textiles) with embedded electric circuits hold great application prospects for future wearable electronics. However, most E-textiles still have critical challenges, including air permeability, satisfactory washability, and mass fabrication. In this work, we fabricate a washable E-textile that addresses all of the concerns and shows its application as a self-powered triboelectric gesture textile for intelligent human-machine interfacing. Utilizing conductive carbon nanotubes (CNTs) and screen-printing technology, this kind of E-textile embraces high conductivity (0.2 kΩ/sq), high air permeability (88.2 mm/s), and can be manufactured on common fabric at large scales. Due to the advantage of the interaction between the CNTs and the fabrics, the electrode shows excellent stability under harsh mechanical deformation and even after being washed. Moreover, based on a single-electrode mode triboelectric nanogenerator and electrode pattern design, our E-textile exhibits highly sensitive touch/gesture sensing performance and has potential applications for human-machine interfacing.

A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids.

The auditory system is the most efficient and straightforward communication strategy for connecting human beings and robots. Here, we designed a self-powered triboelectric auditory sensor (TAS) for constructing an electronic auditory system and an architecture for an external hearing aid in intelligent robotic applications. Based on newly developed triboelectric nanogenerator (TENG) technology, the TAS showed ultrahigh sensitivity (110 millivolts/decibel). A TAS with the broadband response from 100 to 5000 hertz was achieved by designing the annular or sectorial inner boundary architecture with systematic optimization. When incorporated with intelligent robotic devices, TAS demonstrated high-quality music recording and accurate voice recognition for realizing intelligent human-robot interaction. Furthermore, the tunable resonant frequency of TAS was achieved by adjusting the geometric design of inner boundary architecture, which could be used to amplify a specific sound wave naturally. On the basis of this unique property, we propose a hearing aid with the TENG technique, which can simplify the signal processing circuit and reduce the power consuming. This work expresses notable advantages of using TENG technology to build a new generation of auditory systems for meeting the challenges in social robotics.

Eye motion triggered self-powered mechnosensational communication system using triboelectric nanogenerator.

Mechnosensational human-machine interfaces (HMIs) can greatly extend communication channels between human and external devices in a natural way. The mechnosensational HMIs based on biopotential signals have been developing slowly owing to the low signal-to-noise ratio and poor stability. In eye motions, the corneal-retinal potential caused by hyperpolarization and depolarization is very weak. However, the mechanical micromotion of the skin around the corners of eyes has never been considered as a good trigger signal source. We report a novel triboelectric nanogenerator (TENG)-based micromotion sensor enabled by the coupling of triboelectricity and electrostatic induction. By using an indium tin oxide electrode and two opposite tribomaterials, the proposed flexible and transparent sensor is capable of effectively capturing eye blink motion with a super-high signal level (~750 mV) compared with the traditional electrooculogram approach (~1 mV). The sensor is fixed on a pair of glasses and applied in two real-time mechnosensational HMIs-the smart home control system and the wireless hands-free typing system with advantages of super-high sensitivity, stability, easy operation, and low cost. This TENG-based micromotion sensor is distinct and unique in its fundamental mechanism, which provides a novel design concept for intelligent sensor technique and shows great potential application in mechnosensational HMIs.

[Study on neurofeedback system based on electroencephalogram signals].

Neurofeedback, as an alternative treatment method of behavioral medicine, is a technique which translates the electroencephalogram (EEG) signals to styles as sounds or animation to help people understand their own physical status and learn to enhance or suppress certain EEG signals to regulate their own brain functions after several repeated trainings. This paper develops a neurofeedback system on the foundation of brain-computer interface technique. The EEG features are extracted through real-time signal process and then translated to feedback information. Two feedback screens are designed for relaxation training and attention training individually. The veracity and feasibility of the neurofeedback system are validated through system simulation and preliminary experiment.

A new method for detecting cerebral hemorrhage in rabbits by magnetic inductive phase shift.

Cerebral hemorrhage, which is an important clinical problem, is often monitored and studied using expensive devices, such as magnetic resonance imaging (MRI) and positron emission tomography (PET) that are unavailable in economically underdeveloped regions. Magnetic induction tomography (MIT) is a new type of non-contact, non-invasive, and low-cost detection technology, and exhibits prospects for wide application, especially for the detection of brain diseases. However, the previous studies on MIT have focused on laboratory models and rarely on in vivo applications because the induced signals produced by biological tissues are notably weak. Based on the symmetry between the two brain hemispheres and the fact that a local brain hemorrhage will not affect the contra-lateral hemisphere, a symmetric cancellation-type sensor detection system, which is characterized by one excitation coil and two receiving coils, was designed to improve the detection sensitivity of MIT. This method was subsequently used to detect the occurrence of cerebral hematomas in rabbits. The average phase drift induced by a 3-ml injection of autologous blood was 1.885°, which is a fivefold improvement compared with the traditional single excitation coil and single receiving coil method. The results indicate that this system has high sensitivity and anti-interference ability and high practical value.