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Compression garments are elastic clothing with an engineered compression gradient that can be worn on limbs, upper, lower, or full body to use for therapy and sports. This article presents an overview and review on the compression garments and concentrates on the design of compression garments with an appropriate pressure for specific applications. It covers the types of compression garments, fibers and yarns, knitted fabric construction, garment design, an evaluation system, and pressure measurement and modeling. The material properties, fabric properties, pressure modeling, and the garment design system presents the prediction, design, and fabrication of the compression garments. Lastly, the research status and directions are discussed.

The development of continuous conducting polymer fibres is essential for applications ranging from advanced fibrous devices to frontier fabric electronics. The use of continuous conducting polymer fibres requires a small diameter to maximize their electroactive surface, microstructural orientation, and mechanical strength. However, regularly used wet spinning techniques have rarely achieved this goal due primarily to the insufficient slenderization of rapidly solidified conducting polymer molecules in poor solvents. Here we report a good solvent exchange strategy to wet spin the ultrafine polyaniline fibres. The slow diffusion between good solvents distinctly decreases the viscosity of protofibers, which undergo an impressive drawing ratio. The continuously collected polyaniline fibres have a previously unattained diameter below 5 µm, high energy and charge storage capacities, and favorable mechanical performance. We demonstrated an ultrathin all-solid organic electrochemical transistor based on ultrafine polyaniline fibres, which operated as a tactile sensor detecting pressure and friction forces at different levels. Strong, electroactive and ultrafine conducting polymer fibres are prepared at the large scale by a modified wet spinning strategy. The obtained ultrafine polyaniline fibres are qualified to build tactile organic electrochemical transistors.

Moisture-electric generators (MEGs) has emerged as promising green technology to achieve carbon neutrality in next-generation energy suppliers, especially combined with ecofriendly materials. Hitherto, challenges remain for MEGs as direct power source in practical applications due to low and intermittent electric output. Here we design a green MEG with high direct-current electricity by introducing polyvinyl alcohol-sodium alginate-based supramolecular hydrogel as active material. A single unit can generate an improved power density of ca. 0.11 mW cm −2 , a milliamp-scale short-circuit current density of ca. 1.31 mA cm −2 and an open-circuit voltage of ca. 1.30 V. Such excellent electricity is mainly attributed to enhanced moisture absorption and remained water gradient to initiate ample ions transport within hydrogel by theoretical calculation and experiments. Notably, an enlarged current of ca. 65 mA is achieved by a parallel-integrated MEG bank. The scalable MEGs can directly power many commercial electronics in real-life scenarios, such as charging smart watch, illuminating a household bulb, driving a digital clock for one month. This work provides new insight into constructing green, high-performance and scalable energy source for Internet-of-Things and wearable applications. The emerging moisture-electric harvester suffers from insufficient power output. Here, the authors report a green, efficient, and scalable moisture-electric generator by introducing polyvinyl alcohol-sodium alginate hydrogel as active material.

Electrochemical actuators directly converting electrical energy to mechanical energy are critically important for artificial intelligence. However, their energy transduction efficiency is always lower than 1.0% because electrode materials lack active units in microstructure, and their assembly systems can hardly express the intrinsic properties. Here, we report a molecular-scale active graphdiyne-based electrochemical actuator with a high electro-mechanical transduction efficiency of up to 6.03%, exceeding that of the best-known piezoelectric ceramic, shape memory alloy and electroactive polymer reported before, and its energy density (11.5 kJ m −3 ) is comparable to that of mammalian skeletal muscle (~8 kJ m −3 ). Meanwhile, the actuator remains responsive at frequencies from 0.1 to 30 Hz with excellent cycling stability over 100,000 cycles. Furthermore, we verify the alkene–alkyne complex transition effect responsible for the high performance through in situ sum frequency generation spectroscopy. This discovery sheds light on our understanding of actuation mechanisms and will accelerate development of smart actuators. Transduction efficiency in electrochemical actuators hardly exceeds 1% because the current electrode materials do not allow to efficiently exploit microstructural changes to achieve large actuation effects. Here the authors demonstrate transduction efficiencies up to 6% in actuators by using graphdiyne as electrode material.

Solar‐driven overall water splitting based on metal sulfide semiconductor photocatalysts remains as a challenge owing to the strong charge recombination and deficient catalytic active sites. Additionally, significant inhibition of back reactions, especially the oxidation of sulfide ions during the photocatalytic water oxidation catalysis, is an arduous task that requires an efficient photogenerated hole transfer dynamics. Here, a ternary dumbbell‐shaped catalyst based on RuO2/CdS/MoS2 with spatially separated catalytic sites is developed to achieve simultaneous production of hydrogen and oxygen under simulated solar‐light without any sacrificial agents. Particularly, MoS2 nanosheets anchored on the two ends of CdS nanowires are identified as a reduction cocatalyst to accelerate hydrogen evolution, while RuO2 nanoparticles as an oxidation cocatalyst are deposited onto the sidewalls of CdS nanowires to facilitate oxygen evolution kinetics. The density functional theory simulations and ultrafast spectroscopic results reveal that photogenerated electrons and holes directionally migrate to MoS2 and RuO2 catalytic sites, respectively, thus achieving efficient charge carrier separation. The design of ternary dumbbell structure guarantees metal sulfides against photocorrosion and thus extends their range in solar water splitting. The ternary dumbbell‐like RuO2/CdS/MoS2 photocatalyst with selective attachment of reduction and oxidation cocatalysts enables water splitting into H2 and O2. The critical aspect is the spatially separated distribution of MoS2 and RuO2 dual cocatalysts, which not only achieves photogenerated electron–hole pairs separation, but also protects CdS from photocorrosion by holes.

Apart from the rapid development in macroscale green energies, such as wind energy and hydro energy, micro/nanoscale self-powered energy systems are increasingly attractive in wearable energy systems. To utilize the energy harvester more conveniently and effectively, an energy harvester, viz., single-electrode textile-based triboelectric nanogenerator (ST-TENG), is reported in this study. The ST-TENG is a polydimethylsiloxane (PDMS)/Ag-coated chinlon fabric (PACF) composite film with the surface microstructures induced by sandpapers. The PACF composite is self-powered based on the triboelectrification and electrostatic induction. The merits of ST-TENG include: (1) all the basic materials are flexible and scalable; (2) the resultant PACF is a free-standing composite film, which can be easily peeled off from the sandpaper substrate; (3) an extremely low-cost method was first introduced to fabricate the surface microstructures in flexible triboelectric nanogenerator though sandpapers; and (4) the as-fabricated PACF composite film can directly harvest energy though squeezing, warping and folding. Experimental results demonstrate that the ST-TENG can generate an average maximum output voltage of 46.52 V and a high-power density of 613 mW m−2 at the external resistance of 20 MΩ. Additionally, the ST-TENG can also be utilized to detect the variation of contact area, frequency and force.

In the fields of humanoid robots, soft robotics, and wearable electronics, the development of artificial skins entails pressure sensors that are low in modulus, high in sensitivity, and minimal in hysteresis. However, few sensors in the literature can meet all the three requirements, especially in the low pressure range (<10 kPa). This article presents a design for such pressure sensors. The bioinspired liquid-filled cell-type structural design endows the sensor with appropriate softness (Young’s modulus < 230 kPa) and high sensitivity (highest at 0.7 kPa−1) to compression forces below 0.65 N (6.8 kPa). The low-end detection limit is ~0.0012 N (13 Pa), only triple the mass of a bee. Minimal resistance hysteresis of the pressure sensor is 7.7%. The low hysteresis is attributed to the study on the carbon/silicone nanocomposite, which reveals the effect of heat treatment on its mechanical and electromechanical hysteresis. Pressure measurement range and sensitivity of the sensor can be tuned by changing the structure and strain gauge parameters. This concept of sensor design, when combined with microfluidics technology, is expected to enable soft, stretchable, and highly precise touch-sensitive artificial skins.

Catalysts for oxygen reduction reaction (ORR) are at the heart of key green-energy fuel cell technology. N-doped graphene is a potential metal-free electrode with much better electrocatalytic activity, long-term stability and tolerance to crossover effect than expensive platinum-based electrocatalysts. Here, we report a feasible direct-synthesis method in preparing N-graphene with manageable N contents in a large scale. The resultant N-graphene used as electrocatalysts exhibits similar catalytic activity but superior stability compared to commercial Pt/C for ORR in an alkaline solution. It was found that their electrocatalytic activities were demonstrated to depend largely on N-doping content. When nitrogen content reaches a high value at about 24–25%, ORR reaction exhibits a favorable formation of water via a four-electron pathway. Furthermore, the effect of pyrolysis temperature and precursor on the activity of N-graphene is systematically analyzed and may shed some light on the principle of choosing appropriate way for preparing N-graphene.

Physiological signal monitoring and driver behavior analysis have gained increasing attention in both fundamental research and applied research. This study involved the analysis of driving behavior using multimodal physiological data collected from 35 participants. The data included 59-channel EEG, single-channel ECG, 4-channel EMG, single-channel GSR, and eye movement data obtained via a six-degree-of-freedom driving simulator. We categorized driving behavior into five groups: smooth driving, acceleration, deceleration, lane changing, and turning. Through extensive experiments, we confirmed that both physiological and vehicle data met the requirements. Subsequently, we developed classification models, including linear discriminant analysis (LDA), MMPNet, and EEGNet, to demonstrate the correlation between physiological data and driving behaviors. Notably, we propose a multimodal physiological dataset for analyzing driving behavior(MPDB). The MPDB dataset’s scale, accuracy, and multimodality provide unprecedented opportunities for researchers in the autonomous driving field and beyond. With this dataset, we will contribute to the field of traffic psychology and behavior.

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode.