In-Sensor Tactile Fusion and Logic for Accurate Intention Recognition.

Touch control intention recognition is an important direction for the future development of human-machine interactions (HMIs). However, the implementation of parallel-sensing functional modules generally requires a combination of different logical blocks and control circuits, which results in regional redundancy, redundant data, and low efficiency. Here, a location-and-pressure intelligent tactile sensor (LPI tactile sensor) unprecedentedly combined with sensing, computing, and logic is proposed, enabling efficient and ultrahigh-resolution action-intention interaction. The LPI tactile sensor eliminates the need for data transfer among the functional units through the core integration design of the layered structure. It actuates in-sensor perception through feature transmission, fusion, and differentiation, thereby revolutionizing the traditional von Neumann architecture. While greatly simplifying the data dimensionality, the LPI tactile sensor achieves outstanding resolution sensing in both location (<400 µm) and pressure (75 Pa). Synchronous feature fusion and decoding support the high-fidelity recognition of action and combinatorial logic intentions. Benefiting from location and pressure synergy, the LPI tactile sensor demonstrates robust privacy as an encrypted password device and interaction intelligence through pressure enhancement. It can recognize continuous touch actions in real time, map real intentions to target events, and promote accurate and efficient intention-driven HMIs.

A New Method to Evaluate Pressure Distribution Using a 3D-Printed C2-C3 Cervical Spine Model with an Embedded Sensor Array.

Cervical degenerative disc diseases such as myelopathy and radiculopathy often require conventional treatments like artificial cervical disc replacement or anterior cervical discectomy and fusion (ACDF). When designing a medical device, like the stand-alone cage, there are many design inputs to consider. However, the precise biomechanics of the force between the vertebrae and implanted devices under certain conditions require further investigation. In this study, a new method was developed to evaluate the pressure between the vertebrae and implanted devices by embedding a sensor array into a 3D-printed C2-C3 cervical spine. The 3D-printed cervical spine model was subjected to a range of axial loads while under flexion, extension, bending and compression conditions. Cables were used for the application of a preload and a robotic arm was used to recreate the natural spine motions (flexion, extension, and bending). To verify and predict the total pressure between the vertebrae and the implanted devices, a 3D finite element (FE) numerical mathematical model was developed. A preload was represented by applying 22 N of force on each of the anterior tubercles for the C2 vertebra. The results of this study suggest that the sensor is useful in identifying static pressure. The pressure with the robot arm was verified from the FE results under all conditions. This study indicates that the sensor array has promising potential to reduce the trial and error with implants for various surgical procedures, including multi-level artificial cervical disk replacement and ACDF, which may help clinicians to reduce pain, suffering, and costly follow-up procedures.

Conformal Human-Machine Integration Using Highly Bending-Insensitive, Unpixelated, and Waterproof Epidermal Electronics Toward Metaverse.

Efficient and flexible interactions require precisely converting human intentions into computer-recognizable signals, which is critical to the breakthrough development of metaverse. Interactive electronics face common dilemmas, which realize high-precision and stable touch detection but are rigid, bulky, and thick or achieve high flexibility to wear but lose precision. Here, we construct highly bending-insensitive, unpixelated, and waterproof epidermal interfaces (BUW epidermal interfaces) and demonstrate their interactive applications of conformal human-machine integration. The BUW epidermal interface based on the addressable electrical contact structure exhibits high-precision and stable touch detection, high flexibility, rapid response time, excellent stability, and versatile "cut-and-paste" character. Regardless of whether being flat or bent, the BUW epidermal interface can be conformally attached to the human skin for real-time, comfortable, and unrestrained interactions. This research provides promising insight into the functional composite and structural design strategies for developing epidermal electronics, which offers a new technology route and may further broaden human-machine interactions toward metaverse.

Investigation on external quantum efficiency droops and inactivation efficiencies of AlGaN-based ultraviolet-c LEDs at 265-285 nm.

The temperature-dependent external quantum efficiency (EQE) droops of 265 nm, 275 nm, 280 nm, and 285 nm AlGaN-based ultraviolet-c light-emitting diodes (UVC-LEDs) differed in Al contents have been comprehensively investigated. The modifiedABCmodel (R = An+Bn2+Cn3) with the current-leakage related term,f(n)= Dn4, has been employed to analyze the recombination mechanisms in these UVC-LED samples. Experimental results reveal that, at relatively low electrical-current levels, the contribution of Shockley-Read-Hall (SRH) recombination exceeds those of the Auger recombination and carrier leakage. At relatively high electrical-current levels, the Auger recombination and carrier leakage jointly dominate the EQE droop phenomenon. Moreover, the inactivation efficiencies of 222 nm excimer lamp, 254 nm portable Mercury lamp, 265 nm, 280 nm, and 285 nm UVC-LED arrays in the inactivation ofEscherichia colihave been experimentally investigated, which could provide a technical reference for fighting against the new COVID-19.

Extracellular-matrix-mimicked 3D nanofiber and hydrogel interpenetrated wound dressing with a dynamic autoimmune-derived healing regulation ability based on wound exudate.

Dynamic regulation of wound physiological signals is the basis of wound healing. Conventional biomaterials delivering growth factors to drive wound healing leads to the passive repair of soft tissues because of the mismatch of wound healing stages. Meanwhile, the bioactivity of wound exudate is often restricted by oxidation and bacterial contamination. Herein, an extracellular matrix mimicked nanofiber/hydrogel interpenetrated network (NFHIN) was constructed with a 3D nanofibrous framework for cell immigration, and interfiled aerogel containing cross-linked hyaluronic acid and hyperbranched polyamidoamine to balance the wound microenvironment. The aerogel can collect wound exudate and transform into a polycationic hydrogel with contact-killing effects even against intracellular pathogens (bactericidal rate > 99.9% in 30 min) and real-time scavenging property of reactive oxygen species. After co-culturing with the NFHIN, the bioactivity of fibroblast in theex vivoblister fluid was improved by 389.69%. The NFHIN showed sustainable exudate management with moisture-vapor transferring rate (6000 g m-2×24 h), equilibrium liquid content (75.3%), Young's modulus (115.1 ± 7 kPa), and anti-tearing behavior similar to human skin. The NFHIN can collect and activate wound exudate, turning it from a clinical problem to an autoimmune-derived wound regulation system, showing potential for wound care in critical skin diseases.

Quantitative and Real-Time Evaluation of Human Respiration Signals with a Shape-Conformal Wireless Sensing System.

Respiration signals reflect many underlying health conditions, including cardiopulmonary functions, autonomic disorders and respiratory distress, therefore continuous measurement of respiration is needed in various cases. Unfortunately, there is still a lack of effective portable electronic devices that meet the demands for medical and daily respiration monitoring. This work showcases a soft, wireless, and non-invasive device for quantitative and real-time evaluation of human respiration. This device simultaneously captures respiration and temperature signatures using customized capacitive and resistive sensors, encapsulated by a breathable layer, and does not limit the user's daily life. Further a machine learning-based respiration classification algorithm with a set of carefully studied features as inputs is proposed and it is deployed into mobile clients. The body status of users, such as being quiet, active and coughing, can be accurately recognized by the algorithm and displayed on clients. Moreover, multiple devices can be linked to a server network to monitor a group of users and provide each user with the statistical duration of physiological activities, coughing alerts, and body health advice. With these devices, individual and group respiratory health status can be quantitatively collected, analyzed, and stored for daily physiological signal detections as well as medical assistance.

An All-In-One Multifunctional Touch Sensor with Carbon-Based Gradient Resistance Elements.

HIGHLIGHTS: Carbon-based gradient resistance element structure is proposed for the construction of multifunctional touch sensor, which will promote wide detection and recognition range of multiple mechanical stimulations. Multifunctional touch sensor with gradient resistance element and two electrodes is demonstrated to eliminate signals crosstalk and prevent interference during position sensing for human-machine interactions. Biological sensing interface based on a deep-learning-assisted all-in-one multipoint touch sensor enables users to efficiently interact with virtual world. Human-machine interactions using deep-learning methods are important in the research of virtual reality, augmented reality, and metaverse. Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes, signal crosstalk, propagation delay, and demanding configuration requirements. Here, an all-in-one multipoint touch sensor (AIOM touch sensor) with only two electrodes is reported. The AIOM touch sensor is efficiently constructed by gradient resistance elements, which can highly adapt to diverse application-dependent configurations. Combined with deep learning method, the AIOM touch sensor can be utilized to recognize, learn, and memorize human-machine interactions. A biometric verification system is built based on the AIOM touch sensor, which achieves a high identification accuracy of over 98% and offers a promising hybrid cyber security against password leaking. Diversiform human-machine interactions, including freely playing piano music and programmatically controlling a drone, demonstrate the high stability, rapid response time, and excellent spatiotemporally dynamic resolution of the AIOM touch sensor, which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.

A bioinspired analogous nerve towards artificial intelligence.

A bionic artificial device commonly integrates various distributed functional units to mimic the functions of biological sensory neural system, bringing intricate interconnections, complicated structure, and interference in signal transmission. Here we show an all-in-one bionic artificial nerve based on a separate electrical double-layers structure that integrates the functions of perception, recognition, and transmission. The bionic artificial nerve features flexibility, rapid response (<21 ms), high robustness, excellent durability (>10,000 tests), personalized cutability, and no energy consumption when no mechanical stimulation is being applied. The response signals are highly regionally differentiated for the mechanical stimulations, which enables the bionic artificial nerve to mimic the spatiotemporally dynamic logic of a biological neural network. Multifunctional touch interactions demonstrate the enormous potential of the bionic artificial nerve for human-machine hybrid perceptual enhancement. By incorporating the spatiotemporal resolution function and algorithmic analysis, we hope that bionic artificial nerves will promote further development of sophisticated neuroprosthetics and intelligent robotics.

Development of a Handheld Volumetric Photoacoustic Imaging System With a Central-Holed 2D Matrix Aperture.

OBJECTIVE: Photoacoustics has been evolving rapidly in the recent several decades. With the aim of clinical translation, a photoacoustic imaging platform with a portable system size, a miniaturized imaging probe, and convenient handheld capability is of great demand. METHODS: In this work, by adopting an ultrathin central-holed matrix array and a compact coaxial photoacoustic design, a water-free handheld photoacoustic imager is developed (weight: 44 g). Optical Monte Carlo simulation and acoustic k-wave simulation are performed to confirm a relatively homogenous photoacoustic sensitivity distribution within a wide field of view (larger than 10 × 10 × 10 mm3). RESULTS: Imaging resolution characterized by imaging two hairs is estimated to be about 0.80 mm in the lateral direction and 0.73 mm in the axial direction. To demonstrate the handheld capability in real time, handheld imaging guided needle biopsy in the rat's abdomen is performed at a rate of about 10 Hz (CNR ∼ 14.3 dB). Furthermore, handheld imaging is also demonstrated on visualizing vasculature (mainly cephalic vein) in the human arm (CNR > 4.1 dB). CONCLUSION: Results demonstrate that the volumetric photoacoustic imaging system using a central-holed 2D matrix array is an attractive choice for achieving convenient handheld operation in real time. SIGNIFICANCE: Such a compact handheld design may promote the clinical translation of photoacoustic technique.

3D Viscoplastic Finite Element Modeling of Dislocation Generation in a Large Size Si Ingot of the Directional Solidification Stage.

Growing very large size silicon ingots with low dislocation density is a critical issue for the photovoltaic industry to reduce the production cost of the high-efficiency solar cell for affordable green energy. The thermal stresses, which are produced as the result of the non-uniform temperature field, would generate dislocation in the ingot. This is a complicated thermal viscoplasticity process during the cooling process of crystal growth. A nonlinear three-dimensional transient formulation derived from the Hassen-Sumino model (HAS) was applied to predict the number of dislocation densities, which couples the macroscopic viscoplastic deformation with the microscopic dislocation dynamics. A typical cooling process during the growth of very large size (G5 size: 0.84 m × 0.84 m × 0.3 m) Si ingot is used as an example to validate the developed HAS model and the results are compared with those obtained from qualitatively critical resolved shear stress model (CRSS). The result demonstrates that this finite element model not only predicts a similar pattern of dislocation generation with the CRSS model but also anticipate the dislocation density quantity generated in the Si ingot. A modified cooling process is also employed to study the effect of the cooling process on the generation of the dislocation. It clearly shows that dislocation density is drastically decreased by modifying the cooling process. The results obtained from this model can provide valuable information for engineers to design a better cooling process for reducing the dislocation density produced in the Si ingot under the crystal growth process.

Controllably Enhancing Stretchability of Highly Sensitive Fiber-Based Strain Sensors for Intelligent Monitoring.

Functional strain sensing is essential to develop health monitoring and Internet of Things. The performance of either narrow sensing range or low sensitivity restricts strain sensors in a wider range of future applications. Attaining both high sensitivity and wide sensing range of a strain sensor remains challenging. Herein, a cluster-type microstructures strategy is proposed for engineering high stretchability of highly sensitive strain sensor. The resistance change of the strain sensor is determined by the deformation of the cluster-type microstructures from close arrangement to orderly interval state during being stretched. Because of the unique geometric structure and conductive connection type of the sensing material, the strain sensor achieves a considerable performance that features both high sensitivity (gauge factor up to 2700) and high stretchability (sensing range of 160% strain). Fast response time and long-term stability are other characteristics of the strain sensor. Monitoring of multiple limb joints and controlling of audible and visual devices are demonstrated as the proof-of-concept abilities of the strain sensor. This study not only puts forward a novel design thought of strain sensor but also offers considerable insights into its potential value toward burgeoning fields including but not limited to real-time health monitoring and intelligent controls.

Efficient Yttrium(III) Chloride-Treated TiO2 Electron Transfer Layers for Performance-Improved and Hysteresis-Less Perovskite Solar Cells.

Hybrid organic-inorganic metal halide perovskite solar cells have attracted widespread attention, owing to their high performance, and have undergone rapid development. In perovskite solar cells, the charge transfer layer plays an important role for separating and transferring photogenerated carriers. In this work, an efficient YCl3 -treated TiO2 electron transfer layer (ETL) is used to fabricate perovskite solar cells with enhanced photovoltaic performance and less hysteresis. The YCl3 -treated TiO2 layers bring about an upward shift of the conduction band minimum (ECBM ), which results in a better energy level alignment for photogenerated electron transfer and extraction from the perovskite into the TiO2 layer. After optimization, perovskite solar cells based on the YCl3 -treated TiO2 layers achieve a maximum power conversion efficiency of about 19.99 % (19.29 % at forward scan) and a steady-state power output of about 19.6 %. Steady-state and time-resolved photoluminescence measurements and impedance spectroscopy are carried out to investigate the charge transfer and recombination dynamics between the perovskite and the TiO2 electron transfer layer interface. The improved perovskite/TiO2 ETL interface with YCl3 treatment is found to separate and extract photogenerated charge rapidly and suppress recombination effectively, which leads to the improved performance.

Enhanced Efficiency and Stability of Perovskite Solar Cells via Anti-Solvent Treatment in Two-Step Deposition Method.

The low-cost inorganic-organic lead halide perovskite materials become particularly promising for solar cells with high photovoltaic conversion efficiency. The uniform and pinhole-free perovskite films play an important role for high-performance solar cells. We demonstrate an antisolvent treatment by controlling the PbI2 morphology to enhance the perovskite conversion and photophysical properties, including high absorption, crystallinity, and rapid carrier transfer. The fabricated perovskite solar cells show tremendous PCE improvement to about 16.1% from 12% with less hysteresis, and retain over 90% initial PCE after 30 days in ambient and dark atmosphere. In prospect, this antisolvent treatment will be a feasible route to prepare high-quality perovskite films including favorite photophysical properties.

Flexible, Cuttable, and Self-Waterproof Bending Strain Sensors Using Microcracked Gold Nanofilms@Paper Substrate.

Rapid advances in functional sensing electronics place tremendous demands on innovation toward creative uses of versatile advanced materials and effective designs of device structures. Here, we first report a feasible and effective fabrication strategy to integrate commercial abrasive papers with microcracked gold (Au) nanofilms to construct cuttable and self-waterproof crack-based resistive bending strain sensors. Via introducing surface microstructures, the sensitivities of the bending strain sensors are greatly enhanced by 27 times than that of the sensors without surface microstructures, putting forward an alternative suggestion for other flexible electronics to improve their performances. Besides, the bending strain sensors also endow rapid response and relaxation time of 20 ms and ultrahigh stability of >18 000 strain loading-unloading cycles in conjunction with flexibility and robustness. In addition, the concepts of cuttability and self-waterproofness (attain and even surpass IPX-7) of the bending strain sensors have been demonstrated. Because of the distinctive sensing properties, flexibility, cuttability, and self-waterproofness, the bending strain sensors are attractive and promising for wearable electronic devices and smart health monitoring system.

Recyclable and Green Triboelectric Nanogenerator.

A recyclable and green triboelectronic nanogenerator (TENG) is developed based on triboelectrification and designed cascade reactions. Once triggered by water, the TENG can fully dissolve and degrade into environmentally benign end products. With features of rapid dissolution, reproductivity, and green electronic, the TENG has potential of serving as clearable energy harvester and nanosensor for health monitoring and motion sensing.

Flexible and printable paper-based strain sensors for wearable and large-area green electronics.

Paper-based (PB) green electronics is an emerging and potentially game-changing technology due to ease of recycling/disposal, the economics of manufacture and the applicability to flexible electronics. Herein, new-type printable PB strain sensors (PPBSSs) from graphite glue (graphite powder and methylcellulose) have been fabricated. The graphite glue is exposed to thermal annealing to produce surface micro/nano cracks, which are very sensitive to compressive or tensile strain. The devices exhibit a gauge factor of 804.9, response time of 19.6 ms and strain resolution of 0.038%, all performance indicators attaining and even surpassing most of the recently reported strain sensors. Due to the distinctive sensing properties, flexibility and robustness, the PPBSSs are suitable for monitoring of diverse conditions such as structural strain, vibrational motion, human muscular movements and visual control.

Integrated active sensor system for real time vibration monitoring.

We report a self-powered, lightweight and cost-effective active sensor system for vibration monitoring with multiplexed operation based on contact electrification between sensor and detected objects. The as-fabricated sensor matrix is capable of monitoring and mapping the vibration state of large amounts of units. The monitoring contents include: on-off state, vibration frequency and vibration amplitude of each unit. The active sensor system delivers a detection range of 0-60 Hz, high accuracy (relative error below 0.42%), long-term stability (10000 cycles). On the time dimension, the sensor can provide the vibration process memory by recording the outputs of the sensor system in an extend period of time. Besides, the developed sensor system can realize detection under contact mode and non-contact mode. Its high performance is not sensitive to the shape or the conductivity of the detected object. With these features, the active sensor system has great potential in automatic control, remote operation, surveillance and security systems.

Enhanced performance of ZnO piezotronic pressure sensor through electron-tunneling modulation of MgO nanolayer.

Piezoelectric materials can be applied into electromechanical conversion and attract extensive attention with potential applications in various sensors. Here, we present two types of piezotronic pressure sensors based on ZnO nanoarrays. By introducing an insulating MgO (i-MgO) nanolayer, the "on/off" current ratio of the sensor is significantly improved up to 10(5). Furthermore, the sensor shows a high sensitivity of 7.1 × 10(4) gf(-1), a fast response time of 128 ms. The excellent properties are attributed to the combination of piezoelectric effect of ZnO nanoarrays and electron-tunneling modulation of MgO nanolayer, and the reversible potential barrier height controlled by piezoelectric potential. We further investigate the service behavior of the sensor, which can detect force varying from 3.2 to 27.2 gf. Our research provides a promising approach to boost the performance of nanodevices.