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Abstract Excessive exercise is an etiological factor of intervertebral disc degeneration (IVDD). Engineered extracellular vesicles (EVs) exhibit excellent therapeutic potential for disease-modifying treatments. Herein, we fabricate an exercise self-powered triboelectric-responsive microneedle (MN) assay with the sustainable release of optogenetically engineered EVs for IVDD repair. Mechanically, exercise promotes cytosolic DNA sensing-mediated inflammatory activation in senescent nucleus pulposus (NP) cells (the master cell population for IVD homeostasis maintenance), which accelerates IVDD. TREX1 serves as a crucial nuclease, and disassembly of TRAM1-TREX1 complex disrupts the subcellular localization of TREX1, triggering TREX1-dependent genomic DNA damage during NP cell senescence. Optogenetically engineered EVs deliver TRAM1 protein into senescent NP cells, which effectively reconstructs the elimination function of TREX1. Triboelectric nanogenerator (TENG) harvests mechanical energy and triggers the controllable release of engineered EVs. Notably, an optogenetically engineered EV-based targeting treatment strategy is used for the treatment of IVDD, showing promising clinical potential for the treatment of degeneration-associated disorders.

Acoustics, as a branch of modern science, holds pivotal significance in advancing sustainable energy and sensing technologies. Despite its potential, the current limitations still persist in acoustic energy harvesting efficiency and acoustic information sensing technology. Triboelectric nanogenerator (TENG), leveraging the coupled mechanisms of contact electrification and electrostatic induction, offer a promising avenue for the development of energy harvesting and sound sensing applications. Its high sensitivity, broad material choices, and versatile structural designs make it particularly suited for this purpose. In this review, we introduce the theoretical foundation of TENGs in acoustics and present a comprehensive overview of triboelectric acoustic transducers, spanning from low-frequency sound to ultrasonic. Furthermore, we summarize the research advancements in triboelectric acoustic devices for sound/auditory sensing, highlighting their integration with machine learning for intelligent voice recognition. These innovative endeavors provide novel solutions across diverse fields such as energy supplementation, biomedicine, wireless communication, human-machine interaction (HMI), and marine localization. Lastly, we discuss the existing challenges and future directions in this domain, proposing strategies to propel the practical deployment of triboelectric technology in acoustics and outlining emerging research directions.

Abstract This study is nationwide multicenter epidemiological research, aimed at investigating the distribution changes and seasonal patterns of various airborne allergens among preschool children with allergic rhinitis (AR) in different regions of China, and analyzing the clinical correlation between sensitization to various airborne allergens and AR symptoms in children. Information on children was collected through standard questionnaires, and total IgE (tIgE) and specific IgE (sIgE) for 11 inhalant allergens were tested. The results showed that dust mites are the primary allergens for preschool AR children (39%). Among pollen allergens, Amb a had the highest positivity rate (8.1%), followed by Art v (7.8%). The sensitization rates for two mites peaked in May (46.9% and 40.6%). Art v peaked in August (21.5%), while Amb a had peaks in May (12.7%) and August (17.8%). The sensitization peaks for various tree pollens mainly occurred in August. In the Eastern monsoon region, the sensitization rate to mites was significantly higher than in the Northwest arid and semi-arid regions; whereas, for pollen allergens, the sensitization rates to Amb a, Pla a, Pin a, Pop d, and Bet v were significantly higher in the Northwest arid and semi-arid regions than in the Eastern monsoon region. The correlation among various tree pollens, specifically between Pla a, Pin r, Pop d, and Bet v was strong (0.63 ~ 0.79), with a cross-overlapping percentage of 53.9%. Children with multiple pollen sensitizations had higher cumulative nasal symptom scores than those negative for pollen (P

Facial paralysis refers to the abnormal behavior of facial muscles caused by a disorder of the facial nerve, mainly manifested as facial asymmetry. In recent years, deep learning has found extensive applications in facial paralysis detection research. However, most existing methods are constrained to assessing the severity of facial paralysis, thereby concealing crucial symptoms within black-box models. Compared to the severity of facial paralysis, the symptoms of facial paralysis are of greater significance to both physicians and patients. To address this issue, this paper proposes a facial paralysis symptom detection model based on facial action units (AUs). To enhance the accuracy of AU intensity prediction, a novel Difference Ensemble Method (DEM) is introduced. This method leverages differential information between frames within the same video to improve the accuracy of predictions for the current frame. Building upon the predicted AU intensity sequences for keyframes in a video, an interpretable model for detecting facial paralysis symptoms is designed. This model employs an active means to describe the asymmetry in facial muscle strength and utilizes co-occurrence matrices to detect synkinesis. It is noteworthy that DEM is exclusively trained on a dataset of normal faces but exhibits excellent performance when transferred to a facial paralysis dataset. Additionally, DEM exhibits higher accuracy in predicting AU intensity compared to existing methods. The F1 scores for detecting facial muscle function in the eyebrow, eye, and mouth regions with our proposed model are 80.0%, 79.23%, and 90.91%, respectively. To demonstrate the model’s performance, a synkinesis detection experiment is conducted, further validating its applicability in facial paralysis detection.

Ulcerative colitis (UC), a subtype of inflammatory bowel disease, manifests with symptoms such as abdominal pain, diarrhea, and mucopurulent, bloody stools. The pathogenesis of UC is not fully understood. At present, the incidence of UC has increased significantly around the world. Conventional therapeutic arsenals are relatively limited, with often poor efficacy and many adverse effects. In contrast, traditional Chinese medicine (TCM) holds promise due to their notable effectiveness, reduced recurrence rates, and minimal side effects. In recent years, significant progress has been made in the basic research on TCM for UC treatment. It has been found that the inhibition of ferroptosis through the intervention of TCM can significantly promote intestinal mucosal healing and reverse UC. The mechanism of action involves multiple targets and pathways.Aim of the reviewThis review summarizes the experimental studies on the targeted regulation of ferroptosis by TCM and its impact on UC in recent years, aiming to provide theoretical basis for the prevention, treatment, and further drug development for UC.ResultsFerroptosis disrupts antioxidant mechanisms in intestinal epithelial cells, damages the intestinal mucosa, and participates in the pathological process of UC. TCM acts on various pathways such as Nrf2/HO-1 and GSH/GPX4, blocking the pathological progression of ferroptosis in intestinal epithelial cells, inhibiting pathological damage to the intestinal mucosa, and thereby alleviating UC.ConclusionThe diverse array of TCM single herbs, extracts and herbal formulas facilitates selective and innovative research and development of new TCM methods for targeting UC treatment. Although progress has been made in studying TCM compound formulas, single herbs, and extracts, there are still many issues in clinical and basic experimental designs, necessitating further in-depth scientific exploration and research.

Oxidative stress (OS) is a key factor in the generation of various pathophysiological conditions. Nuclear factor erythroid 2 (NF-E2)-related factor 2 (Nrf2) is a major transcriptional regulator of antioxidant reactions. Heme oxygenase-1 (HO-1), a gene regulated by Nrf2, is one of the most critical cytoprotective molecules. In recent years, Nrf2/HO-1 has received widespread attention as a major regulatory pathway for intracellular defense against oxidative stress. It is considered as a potential target for the treatment of inflammatory bowel disease (IBD). This review highlights the mechanism of action and therapeutic significance of Nrf2/HO-1 in IBD and IBD complications (intestinal fibrosis and colorectal cancer (CRC)), as well as the potential of phytochemicals targeting Nrf2/HO-1 in the treatment of IBD. The results suggest that the therapeutic effects of Nrf2/HO-1 on IBD mainly involve the following aspects: (1) Controlling of oxidative stress to reduce intestinal inflammation and injury; (2) Regulation of intestinal flora to repair the intestinal mucosal barrier; and (3) Prevention of ferroptosis in intestinal epithelial cells. However, due to the complex role of Nrf2/HO-1, a more nuanced understanding of the exact mechanisms involved in Nrf2/HO-1 is the way forward for the treatment of IBD in the future.

Highlights Construction of a viscoelastic composite nacre with a ripple-like layered architecture through supramolecular interactions. Outstanding self-adhesion, self-healing and scrape-resistant mechanical and thermal properties. Utility as an integrated heat spreader and TIMs for “chameleon-like” thermal management of planar soft electronics.

Highlights The porous-reinforcement microstructure is constructed by the self-assembly of silicone rubber adhering to the porous framework of the PU sponge. With the excellent performance both for tiny pressure and large mechanical stimuli, the flexible triboelectric patch can be used to monitor pulse wave and plantar pressure. A remote healthcare system for real-time physiological signal monitoring is proposed.

The surface electromyography (sEMG) signals contain a large amount of physiological information reflecting the body’s motor intention. The use of sEMG signals for gesture recognition has received a lot of attention in both robotics and rehabilitation fields. Most of the current studies on gesture recognition based on sEMG signals obtain discrete gestures by classification, ignoring the continuous natural motion. In this paper, a continuous gesture recognition and force estimation method is proposed based on sEMG signals. To establish a foundation for this approach, sEMG sensors are thoughtfully positioned on the forearm’s surface, guided by considerations of physiological structure and muscular function. The finger curvature is proposed to describe the gesture state, and the gesture changes at different moments can be represented by the set of finger curvatures of different fingers, thus achieving continuous gesture recognition. Muscle force estimation was performed while recognizing gestures under different force partterns. A multi-stream convolutional neural network (MSCNN) is used to model finger curvature with sEMG to achieve gesture recognition, and Long short-term memory (LSTM) is used for muscle force estimation due to it is able to capture the temporal relationship during muscle force generation. The experimental results show that the average Pearson correlation coefficient (CC) and root-meansquare error (RMSE) of gesture recognition are 0.84 and 0.11, respectively, and the coefficient of determination $(R^{2}) $ of muscle force estimation is 0.92. The whole scheme achieves the simultaneous estimation of gesture and muscle force, which can well meet the needs in the field of prosthetic control and rehabilitation assistance.

With the arrival of intelligent terminals, triboelectric nanogenerators, as a new kind of energy converter, are considered one of the most important technologies for the next generation of intelligent electronics. As a self-powered sensor, it can greatly reduce the power consumption of the entire sensing system by transforming external mechanical energy to electricity. However, the fabrication method of triboelectric sensors largely determines their functionality and performance. This review provides an overview of various methods used to fabricate triboelectric sensors, with a focus on the processes of micro-electro-mechanical systems technology, three-dimensional printing, textile methods, template-assisted methods, and material synthesis methods for manufacturing. The working mechanisms and suitable application scenarios of various methods are outlined. Subsequently, the advantages and disadvantages of various methods are summarized, and reference schemes for the subsequent application of these methods are included. Finally, the opportunities and challenges faced by different methods are discussed, as well as their potential for application in various intelligent systems in the Internet of Things.

Abstract Traditional triboelectric tactile sensors based on solid–solid interface have illustrated promising application prospects through optimization approach. However, the poor sensitivity and reliability caused by hard contact-electrification still poses challenges for the practical applications. In this work, a liquid–solid interface ferrofluid-based triboelectric tactile sensor (FTTS) with ultrahigh sensitivity is proposed. Relying on the fluidity and magnetism of ferrofluid, the topography of microstructure can be flexibly adjusted by directly employing ferrofluid as triboelectric material and controlling the position of outward magnet. To date, an ultrahigh sensitivity of 21.48 kPa−1 for the triboelectric sensors can be achieved due to the high spike microstructure, low Young’s modulus of ferrofluid and efficient solid–liquid interface contact-electrification. The detection limit of FTTS of 1.25 Pa with a wide detection range to 390 kPa was also obtained. In addition, the oleophobic property between ferrofluid and poly-tetra-fluoro-ethylene triboelectric layer can greatly reduce the wear and tear, resulting in the great improvement of stability. Finally, a strategy for personalized password lock with high security level has been demonstrated, illustrating a great perspective for practical application in smart home, artificial intelligence, Internet of things, etc.

In this study, a picosecond (ps) laser was employed to produce micro-textures on ductile iron in linearly processing leading to significantly higher processing efficiency. The fabrication efficiency was increased about 1331 times as compared to the more common spot-by-spot texturing method. The ps laser induced graphene (LIG) structures were simultaneously fabricated in dimples, which further enhanced the surface tribological properties. The surface micro-textures were produced by forming micro-dimples on the substrate via the laser ablation process. The dimple diameter and area density were regulated by varying the key laser processing parameters, and were experimentally correlated to the tribological properties of the ductile iron substrate. To understand deeper into the wear reduction mechanism of the micro-dimples, simulation models based on the Reynold equation were established, which analyze the flow field pressure distribution and demonstrate the hydrodynamic lubrication effect of the micro-textures. The ball-on disk friction test showed that the area density of the micro-textures had a significant influence on the friction and wear properties. The micro-texture with the area density of 20% and the average dimple diameter of 36 μm showed the highest volume wear rate reduction of 70% and the friction coefficient reduction of 20% respectively. The results indicated that the simultaneous laser in-situ generation of graphene micro-textures is an effective way of enhancing tribological properties on the ductile iron surface. It enhances the hardness of textured surfaces, thermal diffusion, debris capture ability, and fluid dynamic lubrication effect.

Metal borides/borates are promising candidates to become high-performance alkaline oxygen evolution reaction catalysts. This study reports an in-situ phase composition modulation approach to fabricate boride/borate-based catalysts.

Abstract Triboelectric sensors emerged as a new promising sensor several years ago for their high sensitivity, low cost, and zero power consumption. Its capability of realizing various sensing without consuming external power offers a new strategy for promoting the internet of healthcare. Several triboelectric sensors have been used for healthcare monitoring. Such as eye fatigue, pulse, blood pressure, human motion, etc. Various healthcare monitoring devices on the human body help build the internet of healthcare. In this perspective, first, the introduction of triboelectric sensors is proposed. Then, the current healthcare electronics enabled by the triboelectric sensor are discussed. Third, future requirements for the triboelectric sensor are proposed. Finally, future methods for the triboelectric sensor to build the internet of healthcare are discussed.

Miniaturizing efficient triboelectric nanogenerators remains a challenge. Here, the authors propose a MEMS-based micro triboelectric device for acoustic energy transfer and signal communication which is capable of generating the voltage signal of 16.8 mV and 12.7 mV through oil and sound-attenuation medium respectively with 63kPa at 1 MHz ultrasound input.

Abstract Photoelectrochemical hydrogen generation is a promising approach to address the environmental pollution and energy crisis. In this work, we present a hybridized mechanical and solar energy-driven self-powered hydrogen production system. A rotatory disc-shaped triboelectric nanogenerator was employed to harvest mechanical energy from water and functions as a sufficient external power source. WO3/BiVO4 heterojunction photoanode was synthesized in a PEC water-splitting cell to produce H2. After transformation and rectification, the peak current reaches 0.1 mA at the rotation speed of 60 rpm. In this case, the H2 evolution process only occurs with sunlight irradiation. When the rotation speed is over 130 rpm, the peak photocurrent and peak dark current have nearly equal value. Direct electrolysis of water is almost simultaneous with photoelectrocatalysis of water. It is worth noting that the hydrogen production rate increases to 5.45 and 7.27 μL min−1 without or with light illumination at 160 rpm. The corresponding energy conversion efficiency is calculated to be 2.43% and 2.59%, respectively. All the results demonstrate such a self-powered system can successfully achieve the PEC hydrogen generation, exhibiting promising possibility of energy conversion.

Abstract Potassium ion hybrid capacitors (PIHCs) have attracted considerable interest due to their low cost, competitive power/energy densities, and ultra‐long lifespan. However, the more sluggish insertion kinetics of battery‐type anodes than capacitor‐type cathodes in PIHCs seriously limits their practical application. Therefore, developing advanced anodes with high capacitor and suitable K+ intercalation is imperative and significant. A novel core–shell structure of NiCo oxide/NiCo oxyphosphide (NCOP) nanowires are designed and constructed in this study via efficient and facile strategy. Combining the merits of the core–shell structure and the massive active sites in the oxyphosphide layer, the as‐prepared NCOP composites manifest highly reversible capacitors and outstanding rate capability. Meanwhile, the insertion and conversion potassium storage mechanisms of the NCOP are successfully revealed through in situ X‐ray diffraction and density functional theory calculations, respectively. Furthermore, the PIHC was assembled with NCOP anode and borocarbonitride cathode, which displays a large energy density and high‐power density, along with an exceptional capacity retention of ≈90% over 10 000 cycles at 1.0 A g−1. This work provides the anion regulation strategy for modifying the transition metal oxide and constructing the advancing electrode materials for next‐generation energy storage and beyond.

Abstract Electronic skin (e‐skin), new generation of flexible wearable electronic devices, has characteristics including flexibility, thinness, biocompatibility with broad application prospects, and a crucial place in future wearable electronics. With the increasing demand for wearable sensor systems, the realization of multifunctional e‐skin with low power consumption or even autonomous energy is urgently needed. The latest progress of multifunctional self‐powered e‐skin for applications in physiological health, human–machine interaction (HMI), virtual reality (VR), and artificial intelligence (AI) is presented here. Various energy conversion effects for the driving energy problem of multifunctional e‐skin are summarized. An overview of various types of self‐powered e‐skins, including single‐effect e‐skins and multifunctional coupling‐effects e‐skin systems is provided, where the aspects of material preparation, device assembly, and output signal analysis of the self‐powered multifunctional e‐skin are described. In the end, the existing problems and prospects in this field are also discussed.

The sensitivity and selectivity profiles of gas sensors are always changed by sensor drifting, sensor aging, and the surroundings (e.g., temperature and humidity changes), which lead to a serious decline in gas recognition accuracy or even invalidation. To address this issue, the practical solution is to retrain the network to maintain performance, leveraging its rapid, incremental online learning capacity. In this paper, we develop a bio-inspired spiking neural network (SNN) to recognize nine types of flammable and toxic gases, which supports few-shot class-incremental learning, and can be retrained quickly with a new gas at a low accuracy cost. Compared with gas recognition approaches such as support vector machine (SVM), k-nearest neighbor (KNN), principal component analysis (PCA) +SVM, PCA+KNN, and artificial neural network (ANN), our network achieves the highest accuracy of 98.75% in five-fold cross-validation for identifying nine types of gases, each with five different concentrations. In particular, the proposed network has a 5.09% higher accuracy than that of other gas recognition algorithms, which validates its robustness and effectiveness for real-life fire scenarios.

Abstract Stem cell senescence contributes to stem cell exhaustion and drives various aging‐associated disorders. However, strategies to rejuvenate senescent stem cells are limited. The present study proposes an approach based on triboelectric stimulation to rejuvenate senescent bone marrow mesenchymal stromal cells (BMSCs) by fabricating a pulsed triboelectric nanogenerator (P‐TENG) that can produce stable pulsed current output unaffected by the triggered frequency. The senescence phenotypes of aged BMSCs are reversed by triboelectric stimulation at 30 µA at 1.5 Hz. Triboelectric stimulation enhances the proliferation of aged BMSCs and increases their pluripotency and differentiation capacity. Additionally, mechanistic investigations reveal that pulsed triboelectric stimulation by P‐TENG rejuvenates senescent BMSCs by enhancing MDM2‐dependent p53 degradation, which is demonstrated by loss‐of‐function studies of MDM2 and p53. Overall, this study identifies a new approach for the rejuvenation of senescent BMSCs and describes a promising therapeutic intervention for many diseases associated with aged BMSCs.

Abstract Continuous deforming always leads to the performance degradation of a flexible triboelectric nanogenerator due to the Young’s modulus mismatch of different functional layers. In this work, we fabricated a fiber-shaped stretchable and tailorable triboelectric nanogenerator (FST–TENG) based on the geometric construction of a steel wire as electrode and ingenious selection of silicone rubber as triboelectric layer. Owing to the great robustness and continuous conductivity, the FST–TENGs demonstrate high stability, stretchability, and even tailorability. For a single device with ~ 6 cm in length and ~ 3 mm in diameter, the open-circuit voltage of ~ 59.7 V, transferred charge of ~ 23.7 nC, short-circuit current of ~ 2.67 μA and average power of ~ 2.13 μW can be obtained at 2.5 Hz. By knitting several FST–TENGs to be a fabric or a bracelet, it enables to harvest human motion energy and then to drive a wearable electronic device. Finally, it can also be woven on dorsum of glove to monitor the movements of gesture, which can recognize every single finger, different bending angle, and numbers of bent finger by analyzing voltage signals.

Energy collection ways using solar energy, wave, wind, or mechanical energy have attracted widespread attention for small self-powered electronic devices with low power consumption, such as sensors, wearable devices, electronic skin, and implantable devices. Among them, triboelectric nanogenerator (TENG) operated by coupling effect of triboelectrification and electrostatic induction has gradually gained prominence due to its advantages such as low cost, lightweight, high degree of freedom in material selection, large power, and high applicability. The device with a single energy exchange mechanism is limited by its conversion efficiency and work environment and cannot achieve the maximum conversion of energy. Thus, this article reviews the research status of different types of hybrid generators based on TENG in recent years. Hybrid energy generators will improve the output performance though the integration of different energy exchange methods, which have an excellent application prospect. From the perspective of energy complementation, it can be divided into harvesting mechanical energy by various principles, combining with harvesters of other clean energy, and converting mechanical energy or various energy sources into hydrogen energy. For integrating multitype energy harvesters, mechanism of single device and structural design of integrated units for different application scenarios are summarized. The expanding energy harvesting efficiency of the hybrid TENG makes the scheme of self-charging unit to power intelligent mobile electronic feasible and has practical significance for the development of self-powered sensor network.

Summary: Sensors are a key component of the Internet of Things (IoTs) to collect information of environments or objects. Considering the tremendous number and complex working conditions of sensors, multifunction and self-powered feathers are two basic requirements. Nanogenerators are a kind of devices based on the triboelectric, piezoelectric, or pyroelectric effects to harvest ambient energy and then converting to electricity. The hybridized nanogenerators that combined multiple effects in one device have great potential in multifunctional self-powered sensors because of the unique superiority such as generating electrical signals directly, responding to diverse stimuli, etc. This review aims at introducing the latest advancements of hybridized nanogenerators for multifunctional self-powered sensing. Firstly, the principles and sensor prototypes based on TENG are summarized. To avoid signal interference and energy insufficiently, the multifunctional self-powered sensors based on hybridized nanogenerators are reviewed. At last, the challenges and future development of multifunctional self-powered sensors have prospected.

Abstract Progress has been developed in harvesting low-frequency and irregular blue energy using a triboelectric–electromagnetic hybrid generator in recent years. However, the design of the high-efficiency, mechanically durable hybrid structure is still challenging. In this study, we report a fully packaged triboelectric–electromagnetic hybrid generator (TEHG), in which magnets were utilized as the trigger to drive contact–separation-mode triboelectric nanogenerators (CS-TENGs) and coupled with copper coils to operate rotary freestanding-mode electromagnetic generators (RF-EMGs). The magnet pairs that produce attraction were used to transfer the external mechanical energy to the CS-TENGs, and packaging of the CS-TENG part was achieved to protect it from the ambient environment. Under a rotatory speed of 100 rpm, the CS-TENGs enabled the TEHG to deliver an output voltage, current, and average power of 315.8 V, 44.6 μA, and ~ 90.7 μW, and the output of the RF-EMGs was 0.59 V, 1.78 mA, and 79.6 μW, respectively. The cylinder-like structure made the TEHG more easily driven by water flow and demonstrated to work as a practical power source to charge commercial capacitors. It can charge a 33 μF capacitor from 0 to 2.1 V in 84 s, and the stored energy in the capacitor can drive an electronic thermometer and form a self-powered water-temperature sensing system.

The components in traditional human–machine interaction (HMI) systems are relatively independent, distributed and low-integrated, and the wearing experience is poor when the system adopts wearable electronics for intelligent control. The continuous and stable operation of every part always poses challenges for energy supply. In this work, a triboelectric technology-based all-in-one self-powered HMI system for wireless remote telemetry and the control of intelligent cars is proposed. The dual-network crosslinking hydrogel was synthesized and wrapped with functional layers to fabricate a stretchable fibrous triboelectric nanogenerator (SF-TENG) and a supercapacitor (SF-SC), respectively. A self-charging power unit containing woven SF-TENGs, SF-SCs, and a power management circuit was exploited to harvest mechanical energy from the human body and provided power for the whole system. A smart glove designed with five SF-TENGs on the dorsum of five fingers acts as a gesture sensor to generate signal permutations. The signals were processed by the microcontroller and then wirelessly transmitted to the intelligent car for remote telemetry and control. This work is of paramount potential for the application of various terminal devices in self-powered HMI systems with high integration for wearable electronics.

Abstract Looking toward world technology trends over the next few decades, self-powered sensing networks are a key field of technological and economic driver for global industries. Since 2006, Zhong Lin Wang’s group has proposed a novel concept of nanogenerators (NGs), including piezoelectric nanogenerator and triboelectric nanogenerator, which could convert a mechanical trigger into an electric output. Considering motion ubiquitously exists in the surrounding environment and for any most common materials used every day, NGs could be inherently served as an energy source for our daily increasing requirements or as one of self-powered environmental sensors. In this regard, by coupling the piezoelectric or triboelectric properties with semiconducting gas sensing characterization, a new research field of self-powered gas sensing has been proposed. Recent works have shown promising concept to realize NG-based self-powered gas sensors that are capable of detecting gas environment without the need of external power sources to activate the gas sensors or to actively generate a readout signal. Compared with conventional sensors, these self-powered gas sensors keep the approximate performance. Meanwhile, these sensors drastically reduce power consumption and additionally reduce the required space for integration, which are significantly suitable for the wearable devices. This paper gives a brief summary about the establishment and latest progress in the fundamental principle, updated progress and potential applications of NG-based self-powered gas sensing system. The development trend in this field is envisaged, and the basic configurations are also introduced.

As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%.

The pretreatment of flue-gas desulfurization (FGD) wastewater directly affects the subsequent treatment effect of water. Liquid ferrate(VI) was used for the first time in the pretreatment of FGD wastewater. Influential factors including ferrate(VI) dosage and dosing method were investigated by batch tests. The results show that when the dosage of Na2FeO4 is 1.0 g/L, the removal rate of Mg2+, Ca2+, SO42-, NH4+ and chemical oxygen demand were 99.80%, 83.09%, 7.24%, 28.72% and 26.46%, respectively. The strong oxidizing property of the liquid ferrate, the alkali therein, and the co-precipitation of the product promote the removal of these substances. Morphologic and element analysis confirmed that the composition of precipitates were Fe16O16(SO4)2(OH)12·nH2O, FeO(OH), CaSO4 and Mg(OH)2. This paper provides a demonstration and theoretical guidance for the application of ferrate(VI) in FGD wastewater pretreatment. [ABSTRACT FROM AUTHOR]

Extensive measurements and circuit modeling are used for describing high-frequency electrical conduction in carbon nanofibers by a frequency-independent capacitance in parallel with a frequency-independent resistance. The resistance is determined and the capacitance [C.sub.F] is obtained as a free parameter.

Flue gas desulfurization (FGD) wastewater is a terminal wastewater in power plant which seriously restricts the realization of zero-liquid discharge. Bipolar membrane electrodialysis (BMED) is a sustainable and eco-friendly technology widely applied in wastewater treatment. In this study, response surface methodology is employed to optimize the three key independent operating parameters: feed concentration, current density and initial acid and base concentration in order to increase desalination rate and by-product yield. The optimum condition was obtained as feed concentration 0.675 mol/L, current density 25 mA/cm² and initial acid and base concentration 0 mol/L. In this optimum condition, the mean value of alkali conversion rate could be higher than 89.99%. The process cost for the regeneration of 1 kg NaOH from the FGD wastewater was $0.84. Increasing current density is an effective method to enhance by-product yield and shorten operation time, but it can cause a higher energy consumption, which means that the performance of the BMED system should be improved by optimizing operational conditions. Therefore, BMED is a new technology to realize the resource utilization and reuse of FGD wastewater. [ABSTRACT FROM AUTHOR]

A study of germanium antimonide (GeSb) phase-change nanowire as a potential candidate for programmable random access memory (PRAM) application is presented. The newly designed NW-based PRAM is expected to reduce the cell size, programming current, and intercell thermal interference, thus enabling unimpeded scalability beyond conventional thin-film PRAMs.

Several studies are conducted to explain the tunneling taking place in the carbon nanofiber (CNF)-metal system and gold electrodes. The significance of current stressing in the reduction of the total resistance of the system is also demonstrated.

Raman spectra are measured for different size germanium nanowires with different excitation laser powers and wavelengths. The phonon confinement effect is identified for small size nanowires by eliminating the local heating effect.

As a result of severe environmental pressure and stringent government regulations, refined energy management for vehicles has become inevitable. To improve vehicle fuel economy, this paper presents a bus-based energy management system for the electrical system of internal combustion engine vehicles. Both the model of an intelligent alternator and the model of a lead-acid battery are discussed. According to these models, the energy management for a vehicular electrical system is formulated as a global optimal control problem which aims to minimize fuel consumption. Pontryagin’s minimum principle is applied to solve the optimal control problem to realize a real-time control strategy for electrical energy management in vehicles. The control strategy can change the output of the intelligent alternator and the battery with the changes of electrical load and driving conditions in real-time. Experimental results demonstrate that, compared to the traditional open-loop control strategy, the proposed control strategy for vehicle energy management can effectively reduce fuel consumption and the fuel consumption per 100 km is decreased by approximately 1.7%. [ABSTRACT FROM AUTHOR]