Dual Mode Strain–Temperature Sensor with High Stimuli Discriminability and Resolution for Smart Wearables

Strain and temperature are important physiological parameters for health monitoring, providing access to the respiration state, movement of joints, and inflammation processes. The challenge for smart wearables is to unambiguously discriminate strain and temperature using a single sensor element assuring a high degree of sensor integration. Here, a dual-mode sensor with two electrodes and tubular mechanically heterogeneous structure enabling simultaneous sensing of strain and temperature without cross-talk is reported. The sensor structure consists of a thermocouple coiled around an elastic strain-to-magnetic induction conversion unit, revealing a giant magnetoelastic effect, and accommodating a magnetic amorphous wire. The thermocouple provides access to temperature and its coil structure allows to measure impedance changes caused by the applied strain. The dual-mode sensor also exhibits interference-free temperature sensing performance with high coefficient of 54.49 µV °C⁻¹, low strain and temperature detection limits of 0.05% and 0.1 °C, respectively. The use of these sensors in smart textiles to monitor continuously breathing, body movement, body temperature, and ambient temperature is demonstrated. The developed multifunctional wearable sensor is needed for applications in early disease prevention, health monitoring, and interactive electronics as well as for smart prosthetics and intelligent soft robotics.     

Black Phosphorus@Laser-Engraved Graphene Heterostructure-Based Temperature–Strain Hybridized Sensor for Electronic-Skin Applications

Smart electronic skin (e-skin) requires the easy incorporation of multifunctional sensors capable of mimicking skin-like perception in response to external stimuli. However, efficient and reliable measurement of multiple parameters in a single functional device is limited by the sensor layout and choice of functional materials. The outstanding electrical properties of black phosphorus and laser-engraved graphene (BP@LEG) demonstrates a new paradigm for a highly sensitive dual-modal temperature and strain sensor platform to modulate e-skin sensing functionality. Moreover, the unique hybridized sensor design enables efficient and accurate determination of each parameter without interfering with each other. The cationic polymer passivated BP@LEG composite material on polystyrene-block-poly(ethylene-ran-butylene)-block-polystyrene (SEBS) substrate outperforms as a positive temperature coefficient material, exhibiting a high thermal index of 8106 K (25–50  ° C) with high strain sensitivity (i.e., gauge factor, GF) of up to 2765 ( > 19.2%), ultralow strain resolution of 0.023%, and longer durability ( > 18 400 cycles), satisfying the e-skin requirements. Looking forward, this technique provides unique opportunities for broader applications, such as e-skin, robotic appendages, and health monitoring technologies.     

Optically Powered Pressure Sensor with Optical Fiber Link

An optically powered sensor for measuring pressure which is linked by optical fiber is developed in new scheme.Its pulse positio modulation(PPM)optical signal and op-tical supply power for electronics in probe are transmitted via a single optical fiber.The opti-cal power is carried by a 1300nm laser diode(LD)and the sensing data are carried by a 850nm LED.The remote ptobe uses all CMOS chips and particular modulations(PPM and PWM).Its electrical consumption including signal manipulation and LED driven current from optically converted is less than 100μW.The laser diode supplies 5mW optical power into fhe fiber.A Photodetector converts suffichently this power into electrical power to drive the whole probe operation.The optically powered distance gets up to 500m.The novel sen-sor combines optical fiber and electronies technology into a system.Because of using the prin-ciple of ratio measurement between measured and reference signals.as well as light feedback,the system is available with high reliab,outstanding accuracy and repeatability.     

Fusing Stretchable Sensing Technology with Machine Learning for Human–Machine Interfaces

Sensors and algorithms are two fundamental elements to construct intelligent systems. The recent progress in machine learning (ML) has produced great advancements in intelligent systems, owing to the powerful data analysis capability of ML algorithms. However, the performance of most systems is still hindered by sensing techniques that typically rely on rigid and bulky sensor devices, which cannot conform to irregularly curved and dynamic surfaces for high-quality data acquisition. Skin-like stretchable sensing technology with unique characteristics, such as high conformability, low modulus, and light weight, has been recently developed to solve this issue. Here, the recent progress in the fusion of emerging stretchable electronics and ML technology, for bioelectrical signal recognition, tactile perception, and multimodal integration is summarized, and the challenges and future developments are further discussed. These efforts aim to accelerate various perception and reasoning tasks for advanced intelligent applications, such as human–machine interfaces, healthcare, and robotics.     

Stretchable and Shape-Adaptable Triboelectric Nanogenerator Based on Biocompatible Liquid Electrolyte for Biomechanical Energy Harvesting and Wearable Human–Machine Interaction

The significant demand of sustainable power sources has been triggered by the development of wearable electronics (e.g., electronic skin, human health monitors, and intelligent robotics). However, tensile strain limitation and low conformability of existing power sources cannot match their development. Herein, a stretchable and shape-adaptable liquid-based single-electrode triboelectric nanogenerator (LS-TENG) based on potassium iodide and glycerol (KI-Gly) liquid electrolyte as work electrode is developed for harvesting human motion energy to power wearable electronics. The LS-TENG demonstrates high output performances (open-circuit voltage of 300 V, short-circuit current density of 17.5 mA m^–2, and maximum output power of 2.0 W m^–2) and maintains the stable output performances without deterioration under 250% tension stretching and after 10 000 cycles of repeated contact-separation motion. Moreover, the LS-TENG can harvest biomechanical energy, including arm shaking, human walking, and hand tapping, to power commercial electronics without extra power sources. The LS-TENG attached on different joints of body enables to work as self-powered human motion monitor. Furthermore, a flexible touch panel based on the LS-TENG combined with a microcontroller is explored for human–machine interactions. Consequently, the stretchable and shape-adaptable LS-TENG based on KI-Gly electrolyte would act as an exciting platform for biomechanical energy harvesting and wearable human–machine interaction.     

Advanced Primary–Backup Platform with Container-Based Automatic Deployment for Fault-Tolerant Systems

Within mission-critical systems, the primary–backup scheme is a desirable approach for improving reliability and fault tolerance. It can be used to ensure a high mission success rate despite unexpected errors. However, it must cope with the need to maintain consistency between a primary and a backup whenever the primary encounters unexpected errors. We overcome this issue by introducing a platform that uses container-based light virtualization and an automatic build system to isolate an application so that it may then be deployed on different devices without manual intervention. We believe an advanced deployment procedure can retain the consistency of the primary–backup systems with low implementation complexity. Integrated with a cloud application, it can also manage mission-critical systems effectively, communicate with the redundant systems, and detect unexpected errors by using sophisticated fault-detection technologies. We demonstrate that the platform can improve the reliability of mission-critical systems through realistic experiment using a model electronic vehicle and can reduce hardware dependencies.     

Stretchable and Ultrasensitive Intelligent Sensors for Wireless Human–Machine Manipulation

Metallic two-dimensional conductive nanomaterials are extensively explored in stretchable strain sensors, which have promising applications ranging from health monitoring to human–machine manipulation. However, there are limited materials available in this category, and their sensing abilities need to be strengthened. Herein, a controllable deoxidation–nitridation strategy via the pyrolysis of an amine nitrogen source to synthesize oxygen-doped vanadium nitride (VNO) nanosheets with high conductivity is reported. Its metallic characteristics and low dimensionality, together with layer-to-layer slippage make VNO particularly suitable for stretchable strain sensors with remarkable performance, including extraordinary sensitivity (a maximum gauge factor of 2667), wide detection range (0–100%), high durability (over 6000 cycles), and rapid response (44 ms). Furthermore, the strain sensors can capture various physiological signals; in particular, a state-of-the-art wireless vehicle control system designed for differently abled people is fabricated based on the sensors. Moreover, by engineering the thickness of the VNO layer, it can behave as an elastic conductor, demonstrating its feasibility for stretchable wiring.     

Flexible Antiswelling Photothermal-Therapy MXene Hydrogel-Based Epidermal Sensor for Intelligent Human–Machine Interfacing

Conductive hydrogel-based epidermal sensors are regarded with broad prospects in bridging the gap between human and machine for personalized healthcare. However, it is still challenging to simultaneously achieve high sensitivity, wide sensing range, and reliable cycling stability in hydrogel-based epidermal sensors for ultrasensitive human–machine interfacing, along with brilliant antiswelling capability, and near-infrared (NIR) light-triggered dissociation and drug release for further smart on-demand photothermal therapy. Herein, the facile preparation of a flexible multifunctional epidermal sensor from the elaborately fabricated, highly stretchable, and antiswelling MXene hydrogel is presented. It exhibits high sensitivity, wide sensing range (up to 350% strain), and reliable reproducibility for enabling ultrasensitive human-machine interfacing. It displays excellent antiswelling capability for the hydrogel to avoid expanding the wound due to excessive swelling for further reliable wound therapy. Furthermore, it possesses good biocompatibility and robust photothermal performance for the smart photothermal therapy after healthcare monitoring. Meanwhile, the sensor can be triggered to be softened and partly dissociated under the prolonged NIR light irradiation with the transformation of the temperature-sensitive low-melting-point Agar into a sol state and the partial dissociation in the hydrogel to release the loaded drug on demand for synergistically sterilizing bacteria and efficiently promoting wound healing.     

Flexible MXene-Based Hydrogel Enables Wearable Human–Computer Interaction for Intelligent Underwater Communication and Sensing Rescue

Conductive hydrogels have recently attracted extensive attention in the field of smart wearable electronics. Despite the current versatility of conductive hydrogels, the balance between mechanical properties (tensile properties, strength, and toughness) and electrical properties (electrical conductivity, sensitivity, and stability) still faces great challenges. Herein, a simplified method for constructing hydrophobic association hydrogels with excellent mechanical and electrical properties is proposed. The prepared conductive hydrogels exhibit high tensile properties (≈1224%), high linearity in the whole-strain–range (R² = 0.999), and a wide strain sensing range (2700%). The conductive hydrogel can realize more than 1000 cycles of sensing under 500% tensile strain. As an application demonstration, an underwater communication device is assembled in combination with polydimethylsiloxane/Triton X-100 film coating, which successfully transmits underwater signals and provides warning of potential hazards. This study provides a new research method for developing underwater equipment with excellent mechanical properties and sensing properties.     

A Customized Many-Core Hardware Acceleration Platform for Short Read Mapping Problems Using Distributed Memory Interface with 3D–Stacked Architecture

Rapidly developing Next Generation Sequencing technologies produce huge amounts of short reads that consisting randomly fragmented DNA base pair strings. Assembling of those short reads poses a challenge on the mapping of reads to a reference genome in terms of both sensitivity and execution time. In this paper, we propose a customized many-core hardware acceleration platform for short read mapping problems based on hash-index method. The processing core is highly customized to suite both 2-hit string matching and banded Smith-Waterman sequence alignment operations, while distributed memory interface with 3D–stacked architecture provides high bandwidth and low access latency for highly customized dataset partitioning and memory access scheduling. Conformal with original BFAST program, our design provides an amazingly 45,012 times speedup over software approach for single-end short reads and 21,102 times for paired-end short reads, while also beats similar single FPGA solution for 1466 times in case of single end reads. Optimized seed generation gives much better sensitivity while the performance boost is still impressive.     

A Flexible and Regenerative Aptameric Graphene–Nafion Biosensor for Cytokine Storm Biomarker Monitoring in Undiluted Biofluids toward Wearable Applications

Wearable sensors that can conveniently detect cytokine levels in human biofluids are essential for assisting hospitals to maximize the benefits of anti-inflammatory therapies and avoid cytokine storms. Measurement of cytokine levels in biofluids still remains challenging for existing sensors due to high interference from the background. Here, this challenge is overcome through developing a flexible and regenerative aptameric field-effect transistor biosensor, consisting of a graphene–Nafion composite film, for detecting cytokine storm biomarkers in undiluted human biofluids. The composite film enables the minimization of nonspecific adsorption and empowers the renewability to the biosensor. With these capabilities, the device is capable of consistently and sensitively monitoring cytokines (e.g., IFN-γ, an inflammatory and cancer biomarker) in undiluted human sweat with a detection range from 0.015 to 250 nm and limit of detection down to 740 fm . The biosensor is also shown to incur no visible mechanical damage and maintain a consistent sensing response throughout the regenerative (up to 80 cycles) and crumpling (up to 100 cycles) tests. Experimental results demonstrate that the biosensor is expected to offer opportunities for developing wearable biosensing systems for distinguishing acute infectious disease patients and monitoring of patients’ health conditions in daily life.     

Expectation–maximization algorithm with total variation regularization for vector-valued image segmentation

We integrate the total variation (TV) minimization into the expectation–maximization (EM) algorithm to perform the task of image segmentation for general vector-valued images. We first propose a unified variational method to bring together the EM and the TV regularization and to take advantages from both approaches. The idea is based on operator interchange and constraint optimization. In the second part of the paper we propose a simple two-phase approach by splitting the above functional into two steps. In the first phase, a typical EM method can classify pixels into different classes based on the similarity in their measurements. However, since no local geometric information of the image has yet been incorporated into the process, such classification in practice gives unsatisfactory segmentation results. In the second phase, the TV-step obtains the segmentation of the image by applying a TV regularization directly to the clustering result from EM.     

MIMO solution for performance improvements of OFDM–CDMA system with pilot tone

In this paper, MIMO OFDM–CDMA downlink scheme is proposed as a solution for improving performance of the OFDM–CDMA downlink system with pilot tone and threshold detection combining (optimum TDC). The new presented system with MIMO included uses space–time block coding applied to two, three and four transmit antennas and it has an arbitrary number of receive antennas. Bit error rate performance in the case of Ricean frequency selective fading is evaluated for the original system as well as for the one with MIMO included. For that reason an adequate simulation model is developed. The results show that the proposed system significantly outperforms the OFDM–CDMA downlink system with pilot tone and optimum TDC.     

Sensor Performance of Nanostructured TiO2–Cr2O3 Thin Films Derived by a Particulate Sol–Gel Route with Various Cr:Ti Molar Ratios

Nanocrystalline and nanostructured TiO₂–Cr₂O₃ thin films and powders were prepared by a facile and straightforward aqueous particulate sol–gel route at low temperature of 400°C. The prepared sols showed a narrow particle size distribution with hydrodynamic diameter in the range of 17.7 nm to 19.0 nm. Moreover, the sols were stable over 4 months, with constant zeta potential measured during this period. The effect of the Cr:Ti molar ratio on the crystallization behavior of the products was studied. X-ray diffraction (XRD) analysis revealed that the powders crystallized at low temperature of 400°C, containing anatase-TiO₂, rutile-TiO₂, and Cr₂O₃ phases, depending on the annealing temperature and Cr:Ti molar ratio. Furthermore, it was found that Cr₂O₃ retarded the anatase to rutile transformation up to 800°C. The activation energy of crystallite growth was calculated to be in the range of 1.3 kJ/mol to 2.9 kJ/mol. Transmission electron microscopy (TEM) imaging showed that one of the smallest crystallite sizes was obtained for TiO₂–Cr₂O₃ binary mixed oxide, being 5 nm at 500°C. Field-emission scanning electron microscopy (FESEM) analysis revealed that the deposited thin films had nanostructured morphology with average grain size in the range of 20 nm to 40 nm at 500°C. Thin films produced under optimized conditions showed excellent microstructural properties for gas sensing applications. They exhibited a remarkable response towards low concentrations of NO₂ gas at low operating temperature of 200°C, resulting in increased thermal stability of sensing films as well as a decrease in their power consumption. Furthermore, calibration curves revealed that TiO₂–Cr₂O₃ sensors followed the power law \({S = A[\mathrm{gas}]^{B}}\) (where S is the sensor response, the coefficients A and B are constants, and [gas] is the gas concentration) for two types of gas, exhibiting excellent capability for detection of low gas concentrations.     

Trajectory prediction control for digital control DC–DC converters with fast transient response

A novel trajectory prediction control algorithm for digital control DC–DC converters has been presented in this paper. The proposed trajectory prediction control algorithm can provide an accurate prediction of the duty ratio of the next several switching cycles, so as to overcome the inherent time delay of the digital control loop, and to improve the transient response of digital control DC–DC converters, including load response, line response and reference tracking response. A digital control buck DC–DC converter was implemented to verify the effectiveness of the proposed prediction control algorithm. The recovery time is about 8 μs and 4 μs respectively, when the load current changes from a full load to a 17% load and the input voltage changing between 5 V to 6 V. The fastest reference tracking speed is about 26.7 μs/V.     

Nanosilver-Promoted Trimetallic Ni–Co–Mn Perovskite Fluorides for Advanced Aqueous Supercabatteries with Pseudocapacitive Multielectrons Phase Conversion Mechanisms

Aqueous supercapacitors (ASCs) and batteries (ABs) have drawn great attention as promising energy storage devices. However, the key issues of limited energy density of ASCs and inferior power density/poor cycling life of ABs discourage their further application. Herein, a new concept of advanced aqueous supercabatteries (ASCBs) realized by nanosilver-promoted trimetallic Ni–Co–Mn perovskite fluorides (K_1.0Ni_0.4Co_0.2Mn_0.4F_3.2 (KNCMF-10^#)/Ag(37%), denoted as 10^#/Ag(37%)) electrode materials is proposed, integrating with the respective superior specific power/cycling behavior and energy density of ASCs and ABs. A pseudocapacitance-dominated multielectrons phase conversion mechanism of the 10^#/Ag(37%) electrode materials can be deduced by ex situ characterizations and electrochemical techniques. The constructed ASCBs by matching 10^#/Ag(37%) cathode with activated carbon (AC)/Bi(17%) anode achieve great energy density without sacrifice of power density and cycling life in wide temperatures, benefiting from the synergistic energy storage superiority of ASCs and ABs containing capacitive, pseudocapacitive, and Faradaic response in electrochemical processes. Overall, this work highlights the new idea of nano-Ag-promoted trimetallic Ni–Co–Mn perovskite fluorides with a pseudocapacitive multielectrons phase conversion mechanism as a new pop star for advanced ASCBs, showing a great significance in the context of designing advanced electrode materials and in-depth understanding of their complicated charge storage mechanisms for aqueous electrochemical energy storage systems.     

A 0.3–3.5 GHz active-feedback low-noise amplifier with linearization design for wideband receivers

LNAs for wideband receivers usually require a high linearity to protect the desired signals from out-band interference. Active feedback LNAs always suffer from the nonlinear feedback of source follower, and present a poor linearity. In order to solve this problem, a complementary source follower (CSF) is proposed, which utilizes the different characteristic of NMOS and PMOS to linearize the source follower, leading to an improvement of LNA’s IIP₃ and IIP₂ by about 10 dBm and 21 dBm respectively. In addition, a post-distortion technique is also used on the common source stage, which further enhances the IIP₃ by about 2 dBm and IIP₂ by 11 dBm. After using the two techniques, the noise figure (NF) does not deteriorate; instead it achieves a 0.3 dB improvement. A prototype is designed in TSMC 0.18 μm CMOS process, and a 14.8 mW power is dissipated from a 1.6 V supply. In typical process corner, across 0.3 to 3.5 GHz, this LNA achieves a 14.6 dB gain, a 2.9 dB minimum NF, and an IIP₂ larger than +22 dBm and IIP₃ larger than +1.2 dBm.