Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-in...Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.展开更多
Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challe...Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challenge owing to the intrinsic trade-off relationship.Herein,we utilized the in situ controllable reduction of graphene oxide(GO)within a poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene)(P(VDF-Tr FE-CFE))matrix to regulate the dielectric properties.The as-obtained composite exhibited a high relative dielectric constant of 1415coupled with a low loss tangent of 0.380 at 100 Hz.Experimental and theoretical studies indicate that the increased degree of electron conjugation and conductivity of the reduced GO(RGO)are responsible for the high-k.The constrained reduction degree of GO,combined with its homogeneous dispersion in the polymer matrix,effectively suppresses long-range charge carrier migration,thereby minimizing dielectric loss.This novel strategy could be successfully applied to both organic and aqueous systems.Furthermore,a high-performance flexible capacitive proximity sensor was exemplified by the optimization of both the dielectric layer and electrode pattern,exhibiting excellent sensitivity and stability.The fundamental mechanisms elucidated in this study provide crucial design principles for developing dielectric PMCs with tailored properties,thereby opening new avenues for advanced flexible electronic applications.展开更多
The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates...The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates an excellent gas-sensing response of 14.8 at 23℃,which is 3.03 times that of Ni O/rGO sensor(4.89)and 6.49 times that of NiO sensor(2.28),respectively.The developed SnO_(2)/NiO/rGO sensor exhibits faster response/recovery speed(12.7/32.8 s@5 ppm),with extra-low theoretical detection limit of 0.15 ppb at room temperature.More fascinatingly,our sensors indicate great sensitivity,outstanding repeatability and long-term stability for longer than 7 weeks.Additionally,it also suggests that 1℃and 1%relative humidity have the same effect on the SnO_(2)/NiO/rGO sensor signal as approximately 13 ppb and 7.0 ppb NO_(2)gas change,respectively.Such excellent properties are mainly attributed to the large surface-to-volume ratio,which provides active sites to NO_(2)gas spread,adsorption and diffusion on material surface in redox reaction.Moreover,the ternary heterojunctions formed by NiO,rGO and SnO_(2)may serve as highly conductive channels to accelerate carrier transfer and abundant oxygen vacancies to reduce the adsorption energy for O_(2)and NO_(2)gas,thus further improving performance of the sensors.展开更多
NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a nec...NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a necessary option for the detection of existing exhaust emission standards. At present, there is limited and scattered information on knowledge and test methods of NOx sensors, the research of NOx sensors has become a challenging research topic at home and abroad. Based on these requirements, the article systematically integrates the knowledge of principle and testing methods. First of all, through introducing functional description of NOx sensors and the basic principle of NOx sensors, the relevant scholars can have an overall understanding of the product and master the operation mode of products. Secondly, the current status of performance test bench and methods of NOx sensors were described, which can contribute to having a clear understanding of the development process. After that, a new structure of NOx sensors test bench was purposed, which contains six major units including standard gas source, gas mixing unit, analyzer measurement unit, sensor measurement unit, data processing and display unit, exhaust gas treatment unit. And the test bench was validated. The experimental results show that the test bench has the advantages of high-repeatability, high reliability and low cost. And it can realize automatic detection of multiple target values, which is worthy further promotion. Thereby, the article can contribute to the development of its technology indirectly.展开更多
The integration of dual-mesoporous structures,the construction of heterojunctions,and the incorporation of highly concentrated oxygen vacancies are pivotal for advancing metal oxide-based gas sensors.Nonetheless,achie...The integration of dual-mesoporous structures,the construction of heterojunctions,and the incorporation of highly concentrated oxygen vacancies are pivotal for advancing metal oxide-based gas sensors.Nonetheless,achieving an optimal design that simultaneously combines mesoporous structures,precise heterojunction modulation,and controlled oxygen vacancies through a one-step process remains challenging.This study proposes an innovative method for fabricating zinc stannate semiconductors featuring dual-mesoporous structures and tunable oxygen vacancies via a direct solution precursor plasma spray technique.As a proof of concept,the resulting zinc stannate-based coatings are applied to detect 2-undecanone,a key biomarker for rice aging.Remarkably,the zinc oxide/zinc stannate heterojunctions with a well-defined secondary pore structure exhibit exceptional gas-sensing performance for 2-undecanone at room temperature.Furthermore,practical experiments indicate that the developed sensor effectively identifies adulteration in various rice varieties.These results underscore the potential of this method for designing metal oxides with tailored properties for high-performance gas sensors.The enhanced adsorption capacity and dual-mesoporous features of this semiconductor make it a promising candidate for sensing applications in agricultural food safety inspections.展开更多
Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health mon...Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health monitoring. Gallium(Ga)-based liquid metal(LM) has become an ideal candidate for wearable healthcare sensors due to its excellent physical and chemical properties, such as high stretchability, high electrical conductivity, self-healing and thermal conductivity, and good biocompatibility. However,the high surface tension of LM makes it difficult to be processed. After LM is modified, the LM surface tension is reduced to be able to form LM composites by tightly bonding with the elastomer matrix, and the LM composites exhibit enhanced electromechanical, thermal, and magnetic properties, among others. Here, we review the fabrication methods of LM composites;we describe in detail the composite forms of LM composites and recent advances in tensile, thermal and electrical conductivity, high dielectric constant and biocompatibility. Sensor devices(e.g.,piezoelectric sensors, friction electric sensors, strain sensors, and magnetic sensors) of LM composites for wearable healthcare monitoring are summarized. Finally, challenges and opportunities of LM composites in the neighborhood of wearable healthcare sensors are also discussed.展开更多
Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial...Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.展开更多
Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming pr...Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.展开更多
Gestational diabetes mellitus(GDM)is increasingly recognized not only for its immediate obstetric complications but also for its long-term metabolic consequences in both mothers and their offspring.Traditionally,resea...Gestational diabetes mellitus(GDM)is increasingly recognized not only for its immediate obstetric complications but also for its long-term metabolic consequences in both mothers and their offspring.Traditionally,research has emphasized the roles of pancreaticβ-cell dysfunction and placental dysregulation in GDM.However,emerging evidence highlights the maternal liver as a central metabolic hub during pregnancy coordinating glucose,lipid,and hormonal adaptations essential for fetal development.This review synthesizes current findings on how GDM disrupts the maternal liver’s adaptive roles,transforming it from a metabolic coordinator into a source of maladaptive endocrine,inflammatory,and nutrient signals.It outlines key mechanistic pathways through which maternal hepatic dysfunction may increase offspring susceptibility to non-alcoholic fatty liver disease and type 2 diabetes mellitus.These include hepatokine dysregulation,altered lipid metabolism,impaired insulin signaling,inflammatory and oxidative stress pathways,and epigenetic and transcriptomic reprogramming.In addition,it explores novel axes such as the gut-liver-placenta interplay,bile acid signaling disruptions,endoplasmic reticulum stress responses,and extracellular vesiclemediated communication.By reframing the maternal liver’s role in GDM pathophysiology,this review identifies critical windows for early clinical intervention and highlights the potential for liver-focused strategies to prevent the intergenerational transmission of metabolic disease.展开更多
Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexib...Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we prese...Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.展开更多
Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-...Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-sensor predictive accuracy,ensuring interpretability and reliable performance across varying industrial operating conditions remains a challenge[1]–[4].This is precisely what Industry 5.0,proposed by the European Commission in 2021,advocates[5],[6].It integrates various cutting-edge technologies,such as human-machine interaction,digital twins,cybersecurity and artificial intelligence,to facilitate the development of better soft sensors.展开更多
Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.Th...Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.This study introduces a composite denoising approach to address this challenge.This method is based on the ameliorated ellipse fitting algorithm(AEFA)and adaptive successive variational mode decomposition(ASVMD).This algorithm employs AEFA to eliminate system noise tightly coupled with direct-current and alternating-current components in the interference signal,thereby obtaining a phase signal containing only environmental noise.The ASVMD technique adaptively extracts environmental noise components predominantly present in the phase signal.To achieve optimal decomposition results automatically,the permutation entropy criterion is employed to refine decomposition parameters.The correlation coefficient is utilized to differentiate effective components from noise components in the decomposition results.Experimental results indicate that the combined AEFA and ASVMD algorithm effectively suppresses both system and environmental noises.When applied to 50 Hz vibration signal processing,the proposed approach achieves a noise reduction of 17.81 dB and a phase resolution of 35.14μrad/√Hz.Given the excellent performance of the noise suppression,the proposed approach holds great application potential in high-performance interferometric sensing systems.展开更多
Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations...Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.展开更多
This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on th...This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.展开更多
Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ion...Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.展开更多
MXene is a promising conductive nanofiller for hydrogels due to its excellent electricity conductivity and water dispersibility.However,MXene is prone to oxidize in the presence of air and water,resulting in a signifi...MXene is a promising conductive nanofiller for hydrogels due to its excellent electricity conductivity and water dispersibility.However,MXene is prone to oxidize in the presence of air and water,resulting in a significant loss of conductivity.Polydopamine(PDA)has been coated on MXene to enhance its antioxidation stability via the physical barrier and chemical reducing ability of PDA,which unavoidably causes severe aggregation and a significant decrease in conductivity due to the crosslinking and insulation of PDA.Herein,we propose a facile strategy to construct a highly conductive,stable,and self-healing MXene-based polyvinyl alcohol(PVA)hydrogel by a controlled assembly of PDA and cellulose nanocrystal(CNC).PDA is first formed by oxidation self-polymerization in PVA solution without the presence of CNC and MXene,which can effectively reduce the content of aggregation-inducing groups and avoid the formation of an insulating PDA layer on the surface of MXene.The addition of CNCs results in the easy dispersion of a high content of MXene via hydrogen bonding and electrostatic interactions.The PVA-PDA hydrogel with MXene and CNC as conductive and reinforcing nanofillers(PP-CM)is cross-linked by dynamic borax covalent bonds and shows a conductivity of 7.14 S m^(-1).The introduction of PDA effectively protects MXene and results in only a 14%decrease in conductivity after 7 days,significantly improving antioxidant stability.This hydrogel also possesses rapid self-healing capabilities,achieving 90.5%self-healing efficiency within 10 min.This versatile approach opens new avenues for the preparation and application of MXene-based conductive hydrogels.展开更多
Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framew...Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.展开更多
Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,...Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.展开更多
文摘Diabetes mellitus represents a major global health issue,driving the need for noninvasive alternatives to traditional blood glucose monitoring methods.Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers,providing innovative solutions for diabetes diagnosis and monitoring.This review comprehensively discusses the current developments in noninvasive wearable biosensors,emphasizing simultaneous detection of biochemical biomarkers(such as glucose,cortisol,lactate,branched-chain amino acids,and cytokines)and physiological signals(including heart rate,blood pressure,and sweat rate)for accurate,personalized diabetes management.We explore innovations in multimodal sensor design,materials science,biorecognition elements,and integration techniques,highlighting the importance of advanced data analytics,artificial intelligence-driven predictive algorithms,and closed-loop therapeutic systems.Additionally,the review addresses ongoing challenges in biomarker validation,sensor stability,user compliance,data privacy,and regulatory considerations.A holistic,multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.
基金financially supported by the Innovation and Technology Commission of the Hong Kong SAR Government(No.MRP/020/21)Hong Kong Polytechnic University(No.847A)+1 种基金RI-Wear Seed Fund of Poly U(1-CD8J)Start-up Fund of Poly U(1-BD49)。
文摘Polymer matrix composites with high dielectric constants and low dielectric losses are in high demand for flexible electronics.However,simultaneously satisfying these requirements poses a significant scientific challenge owing to the intrinsic trade-off relationship.Herein,we utilized the in situ controllable reduction of graphene oxide(GO)within a poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene)(P(VDF-Tr FE-CFE))matrix to regulate the dielectric properties.The as-obtained composite exhibited a high relative dielectric constant of 1415coupled with a low loss tangent of 0.380 at 100 Hz.Experimental and theoretical studies indicate that the increased degree of electron conjugation and conductivity of the reduced GO(RGO)are responsible for the high-k.The constrained reduction degree of GO,combined with its homogeneous dispersion in the polymer matrix,effectively suppresses long-range charge carrier migration,thereby minimizing dielectric loss.This novel strategy could be successfully applied to both organic and aqueous systems.Furthermore,a high-performance flexible capacitive proximity sensor was exemplified by the optimization of both the dielectric layer and electrode pattern,exhibiting excellent sensitivity and stability.The fundamental mechanisms elucidated in this study provide crucial design principles for developing dielectric PMCs with tailored properties,thereby opening new avenues for advanced flexible electronic applications.
基金funded by the National Natural Science Foundation of China(No.62364002)Key Scientific Research Projects of Universities in Henan Province(No.24A510014)+5 种基金Xinjiang-Changji Vocational Education Alliance Special Project(No.2050305)National Laboratory of Solid State Microstructures,Nanjing University(No.M36001)Jiangsu Key Laboratory of Optoelectronic Information Functional Materials,Nanjing University(No.ndgd2024005)Henan Province Higher Education College Student Innovation Training Program Project(No.202410478019)the Doctoral Research Initiation Fund Project,Zhoukou Normal University(No.ZKNUC2022018)the Natural Science Foundation Project of Xinjiang Uygur Autonomous Region(No.2022D01C006)。
文摘The porous NiO nanoplates modified with rGO nanosheets and SnO_(2)nanoparticles are developed for accurate and rapid ppb-level NO_(2)detection.The developed SnO_(2)/NiO/rGO sensor towards 50 ppm NO_(2)gas demonstrates an excellent gas-sensing response of 14.8 at 23℃,which is 3.03 times that of Ni O/rGO sensor(4.89)and 6.49 times that of NiO sensor(2.28),respectively.The developed SnO_(2)/NiO/rGO sensor exhibits faster response/recovery speed(12.7/32.8 s@5 ppm),with extra-low theoretical detection limit of 0.15 ppb at room temperature.More fascinatingly,our sensors indicate great sensitivity,outstanding repeatability and long-term stability for longer than 7 weeks.Additionally,it also suggests that 1℃and 1%relative humidity have the same effect on the SnO_(2)/NiO/rGO sensor signal as approximately 13 ppb and 7.0 ppb NO_(2)gas change,respectively.Such excellent properties are mainly attributed to the large surface-to-volume ratio,which provides active sites to NO_(2)gas spread,adsorption and diffusion on material surface in redox reaction.Moreover,the ternary heterojunctions formed by NiO,rGO and SnO_(2)may serve as highly conductive channels to accelerate carrier transfer and abundant oxygen vacancies to reduce the adsorption energy for O_(2)and NO_(2)gas,thus further improving performance of the sensors.
文摘NOx sensors, as a core component of diesel engine exhaust treatment system, play an important role in exhaust emission control, which can accurately and quickly detect the NOx and O2 concentration. It has become a necessary option for the detection of existing exhaust emission standards. At present, there is limited and scattered information on knowledge and test methods of NOx sensors, the research of NOx sensors has become a challenging research topic at home and abroad. Based on these requirements, the article systematically integrates the knowledge of principle and testing methods. First of all, through introducing functional description of NOx sensors and the basic principle of NOx sensors, the relevant scholars can have an overall understanding of the product and master the operation mode of products. Secondly, the current status of performance test bench and methods of NOx sensors were described, which can contribute to having a clear understanding of the development process. After that, a new structure of NOx sensors test bench was purposed, which contains six major units including standard gas source, gas mixing unit, analyzer measurement unit, sensor measurement unit, data processing and display unit, exhaust gas treatment unit. And the test bench was validated. The experimental results show that the test bench has the advantages of high-repeatability, high reliability and low cost. And it can realize automatic detection of multiple target values, which is worthy further promotion. Thereby, the article can contribute to the development of its technology indirectly.
基金supported by the Outstanding Youth Foundation of Jiangsu Province of China(Grant No.BK20211548)the Yangzhou Science and Technology Plan Project(Grant No.YZ2023246)。
文摘The integration of dual-mesoporous structures,the construction of heterojunctions,and the incorporation of highly concentrated oxygen vacancies are pivotal for advancing metal oxide-based gas sensors.Nonetheless,achieving an optimal design that simultaneously combines mesoporous structures,precise heterojunction modulation,and controlled oxygen vacancies through a one-step process remains challenging.This study proposes an innovative method for fabricating zinc stannate semiconductors featuring dual-mesoporous structures and tunable oxygen vacancies via a direct solution precursor plasma spray technique.As a proof of concept,the resulting zinc stannate-based coatings are applied to detect 2-undecanone,a key biomarker for rice aging.Remarkably,the zinc oxide/zinc stannate heterojunctions with a well-defined secondary pore structure exhibit exceptional gas-sensing performance for 2-undecanone at room temperature.Furthermore,practical experiments indicate that the developed sensor effectively identifies adulteration in various rice varieties.These results underscore the potential of this method for designing metal oxides with tailored properties for high-performance gas sensors.The enhanced adsorption capacity and dual-mesoporous features of this semiconductor make it a promising candidate for sensing applications in agricultural food safety inspections.
基金financially supported by Mianyang Science and Technology Bureau(No.2023ZYDF081)the Research topic of Zhongnanshan Youth Science and Technology Innovation Award Fund of China Youth Entrepreneurship and Employment Foundation
文摘Wearable healthcare sensors can convert various physical signals, physiological signals, and electrophysiological activities of the human body into quantifiable resistive or capacitive changes for real-time health monitoring. Gallium(Ga)-based liquid metal(LM) has become an ideal candidate for wearable healthcare sensors due to its excellent physical and chemical properties, such as high stretchability, high electrical conductivity, self-healing and thermal conductivity, and good biocompatibility. However,the high surface tension of LM makes it difficult to be processed. After LM is modified, the LM surface tension is reduced to be able to form LM composites by tightly bonding with the elastomer matrix, and the LM composites exhibit enhanced electromechanical, thermal, and magnetic properties, among others. Here, we review the fabrication methods of LM composites;we describe in detail the composite forms of LM composites and recent advances in tensile, thermal and electrical conductivity, high dielectric constant and biocompatibility. Sensor devices(e.g.,piezoelectric sensors, friction electric sensors, strain sensors, and magnetic sensors) of LM composites for wearable healthcare monitoring are summarized. Finally, challenges and opportunities of LM composites in the neighborhood of wearable healthcare sensors are also discussed.
基金supported by the projects funded by the Education Department of Shaanxi Provincial Government(NO.23JP116)the Natural Science Fund of Shaanxi Province(NO.2024JC-YBMS-396)+3 种基金the National Natural Science Foundation of China(NO.52171191,52371198,U22A20137)the Constructing National Independent Innovation Demonstration Zones(XM2024XTGXQ05)Shenzhen Science and Technology Innovation Program(JCYJ20220818102215033,GJHZ20210705142542015,JCYJ20220530160811027)Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization(2023B1212060012).
文摘Surface-enhanced Raman spectroscopy(SERS)has evolved from a laboratory technique to a practical tool for ultra-sensitive detection,particularly in the biomedical field,where precise molecular identification is crucial.Despite significant advancements,a gap remains in the literature,as no comprehensive review systematically addresses the high-precision construction of SERS substrates for ultrasensitive biomedical detection.This review fills that gap by exploring recent progress in fabricating high-precision SERS substrates,emphasizing their role in enabling ultrasensitive bio-medical sensors.We carefully examine the key to these advancements is the precision engineering of substrates,including noble metals,semiconductors,carbon-based materials,and two-dimensional materials,which is essential for achieving the high sensitivity required for ultrasensitive detection.Applications in biomedical diagnostics and molecular analysis are highlighted.Finally,we address the challenges in SERS substrate preparation and outline future directions,focusing on improvement strategies,design concepts,and expanding applications for these advanced materials.
基金Supported by the Guangdong-Hong Kong-Macao Joint Laboratory on Micro-Nano Manufacturing Technology,China(No.2021LSYS004)Guangdong Provincial Key Laboratory of Sustainable Biomimetic Materials and Green Energy,China(No.2024B1212010003)。
文摘Monitoring biogenic amines,which are metabolic byproducts of shrimp spoilage,is crucial for assessing food quality.Currently,most detection methods for biogenic amines suffer from limitations such as time-consuming procedures,complex operations,and delayed results.Colorimetric analysis techniques have gained attention in recent years due to their advantages of short analysis time,simple operation,and suitability for on-site testing.This study successfully developed a series of colorimetric sensor platforms for biogenic amines by loading the natural active ingredient curcumin(CUR)and its derivative of Boron complex BFCUR onto filter paper and electrospun nanofibre films(ENFs),respectively.By analyzing the color response differences of these sensors upon contact with biogenic amines,the colorimetric sensors with superior detection performance were selected and further applied to the visual monitoring and indication of shrimp spoilage processes.
文摘Gestational diabetes mellitus(GDM)is increasingly recognized not only for its immediate obstetric complications but also for its long-term metabolic consequences in both mothers and their offspring.Traditionally,research has emphasized the roles of pancreaticβ-cell dysfunction and placental dysregulation in GDM.However,emerging evidence highlights the maternal liver as a central metabolic hub during pregnancy coordinating glucose,lipid,and hormonal adaptations essential for fetal development.This review synthesizes current findings on how GDM disrupts the maternal liver’s adaptive roles,transforming it from a metabolic coordinator into a source of maladaptive endocrine,inflammatory,and nutrient signals.It outlines key mechanistic pathways through which maternal hepatic dysfunction may increase offspring susceptibility to non-alcoholic fatty liver disease and type 2 diabetes mellitus.These include hepatokine dysregulation,altered lipid metabolism,impaired insulin signaling,inflammatory and oxidative stress pathways,and epigenetic and transcriptomic reprogramming.In addition,it explores novel axes such as the gut-liver-placenta interplay,bile acid signaling disruptions,endoplasmic reticulum stress responses,and extracellular vesiclemediated communication.By reframing the maternal liver’s role in GDM pathophysiology,this review identifies critical windows for early clinical intervention and highlights the potential for liver-focused strategies to prevent the intergenerational transmission of metabolic disease.
基金supported by the National Key Research and Development Program of China(2023YFB3809800)the National Natural Science Foundation of China(52172249,52525601)+2 种基金the Chinese Academy of Sciences Talents Program(E2290701)the Jiangsu Province Talents Program(JSSCRC2023545)the Special Fund Project of Carbon Peaking Carbon Neutrality Science and Technology Innovation of Jiangsu Province(BE2022011).
文摘Flexible fiber sensors,However,traditional methods face challenges in fabricating low-cost,large-scale fiber sensors.In recent years,the thermal drawing process has rapidly advanced,offering a novel approach to flexible fiber sensors.Through the preform-tofiber manufacturing technique,a variety of fiber sensors with complex functionalities spanning from the nanoscale to kilometer scale can be automated in a short time.Examples include temperature,acoustic,mechanical,chemical,biological,optoelectronic,and multifunctional sensors,which operate on diverse sensing principles such as resistance,capacitance,piezoelectricity,triboelectricity,photoelectricity,and thermoelectricity.This review outlines the principles of the thermal drawing process and provides a detailed overview of the latest advancements in various thermally drawn fiber sensors.Finally,the future developments of thermally drawn fiber sensors are discussed.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Tactile sensing of subcutaneous organ vibrations provides a promising route toward human-machine interfaces and wear-able diagnostics,particularly for voice rehabilitation and silent-speech communication.Here,we present a bioinspired piezoelectric vibration sensor that mimics the graded stiffness and stress-based transduction mechanism of otolithic cilia in the human vestibular system.The device consists of a trapezoidal cantilever array with tip inertial masses,fabricated through a hybrid stereolithography 3D printing and laser micromachining process for rapid prototyping without cleanroom facilities.Finite-element modeling and experimental measurements demonstrate a fundamental resonance near 1.2 kHz,a 5%flat-bandwidth of 350 Hz,and an in-band charge sensitivity of 3.17 pC/g.A wearable proof-of-concept test further verifies the sensor's ability to reproducibly distinguish phoneme-specific vibration patterns in both time and frequency domains.This work establishes a foundation for bioinspired tactile sensing front-ends in wearable voice interfaces and other intelligent diagnostic systems integrated with machine-learning algorithms.
文摘Dear Editor,This letter presents a new approach to developing interpretable and reliable soft sensors for Industry 5.0 applications.Although sophisticated machine learning methods have made remarkable strides in soft-sensor predictive accuracy,ensuring interpretability and reliable performance across varying industrial operating conditions remains a challenge[1]–[4].This is precisely what Industry 5.0,proposed by the European Commission in 2021,advocates[5],[6].It integrates various cutting-edge technologies,such as human-machine interaction,digital twins,cybersecurity and artificial intelligence,to facilitate the development of better soft sensors.
文摘Noise interference critically impairs the stability and data accuracy of sensing systems.However,current suppression strategies fail to concurrently mitigate intrinsic system noise and extrinsic environmental noise.This study introduces a composite denoising approach to address this challenge.This method is based on the ameliorated ellipse fitting algorithm(AEFA)and adaptive successive variational mode decomposition(ASVMD).This algorithm employs AEFA to eliminate system noise tightly coupled with direct-current and alternating-current components in the interference signal,thereby obtaining a phase signal containing only environmental noise.The ASVMD technique adaptively extracts environmental noise components predominantly present in the phase signal.To achieve optimal decomposition results automatically,the permutation entropy criterion is employed to refine decomposition parameters.The correlation coefficient is utilized to differentiate effective components from noise components in the decomposition results.Experimental results indicate that the combined AEFA and ASVMD algorithm effectively suppresses both system and environmental noises.When applied to 50 Hz vibration signal processing,the proposed approach achieves a noise reduction of 17.81 dB and a phase resolution of 35.14μrad/√Hz.Given the excellent performance of the noise suppression,the proposed approach holds great application potential in high-performance interferometric sensing systems.
基金supported by the National Natural Science Foundation of China(General Program)under Grant 52571385National Key R&D Program of China(Grant No.2024YFC2815000 and No.2024YFB3816000)+12 种基金Open Fund of State Key Laboratory of Deep-sea Manned Vehicles(Grant No.2025SKLDMV07)Shenzhen Science and Technology Program(WDZC20231128114452001,JCYJ20240813112107010 and JCYJ20240813111910014)the Tsinghua SIGS Scientific Research Startup Fund(QD2022021C)the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM 01 Z006)the Ocean Decade International Cooperation Center(ODCC)(GHZZ3702840002024020000026)Shenzhen Key Laboratory of Advanced Technology for Marine Ecology(ZDSYS20230626091459009)Shenzhen Science and Technology Program(No.KJZD20240903100905008)the National Natural Science Foundation of China(No.22305141)Pearl River Talent Program(No.2023QN10C114)General Program of Guangdong Province(No.2025A1515011700)the Guangdong Innovative and Entrepreneurial Research Team Program(2023ZT10C040)Scientific Research Foundation from Shenzhen Finance Bureau(No.GJHZ20240218113600002)Tsinghua University(JC2023001).
文摘Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.
文摘This survey presents a comprehensive examination of sensor fusion research spanning four decades,tracing the methodological evolution,application domains,and alignment with classical hierarchical models.Building on this long-term trajectory,the foundational approaches such as probabilistic inference,early neural networks,rulebasedmethods,and feature-level fusion established the principles of uncertainty handling andmulti-sensor integration in the 1990s.The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering,Bayesian–Dempster–Shafer hybrids,distributed consensus algorithms,and machine learning ensembles for more robust and domain-specific implementations.From 2011 to 2020,the widespread adoption of deep learning transformed the field driving some major breakthroughs in the autonomous vehicles domain.A key contribution of this work is the assessment of contemporary methods against the JDL model,revealing gaps at higher levels-especially in situation and impact assessment.Contemporary methods offer only limited implementation of higher-level fusion.The survey also reviews the benchmark multi-sensor datasets,noting their role in advancing the field while identifying major shortcomings like the lack of domain diversity and hierarchical coverage.By synthesizing developments across decades and paradigms,this survey provides both a historical narrative and a forward-looking perspective.It highlights unresolved challenges in transparency,scalability,robustness,and trustworthiness,while identifying emerging paradigms such as neuromorphic fusion and explainable AI as promising directions.This paves the way forward for advancing sensor fusion towards transparent and adaptive next-generation autonomous systems.
基金National Natural Science Foundation of China(NSFC,No.22131008)Natural Science Foundation of Tianjin(No.22JCYBJC00500)the Haihe Laboratory of Sustainable Chemical Transformations for financial support.
文摘Possessing excellent mechanical properties,a high-coverage slide-ring conductive gel is constructed by in situ polymerization ofα-cyclodextrin(α-CD)polyrotaxane(PR)and 1-vinyl-3-ethylimidazolium bromide([VEIM]Br)ionic liquid(IL),using 1-ethyl-3-methylimidazolium bromide([EMIM]Br)IL as solvent.Benefiting from the compatibility of ILs and alkene-PR,the cross-linked network slide-ring gel not only maintains excellent conductivity(1.52×10^(−2) S/m),but also has effectively improved mechanical properties(513%fracture strain,0.713 MPa fracture stress,211 kPa elastic modulus and 1366 kJ/m^(3) toughness)and adhesive properties(472.3±25.9 kPa).The supramolecular gel can be used as a strain sensor to efficiently monitor deformation signals in real-time at least 200 times.Especially,the slide-ring gel can self-power generated by triboelectric effect and electrostatic induction between the skin layer and the polydimethylsiloxane(PDMS)layer that encapsulates the gel,achieving reversible and durable motion sensing,which provides a convenient pathway for constructing supramolecular self-powered flexible electronic materials.
基金support from Youth Promotion of Guangdong Natural Science Foundation(2024A1515030005)Guangdong Province Ordinary Universities Characteristic Innovation Project(2024KTSCX096)+4 种基金Guangdong Province University Key Field Special Program(2023ZDZX3002)Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education)Naikai University,Guangdong Provincial Key Laboratory of Optical Information Materials and Technology(No.2023B1212060065)Programs of Science and Technology Department of Yunnan Province(202301AT070217)MOE International Laboratory for Optical Information Technologies,the 111 Project,Science and Technology Bureau of Huzhou(2022GG24)ScienceK Ltd.
文摘MXene is a promising conductive nanofiller for hydrogels due to its excellent electricity conductivity and water dispersibility.However,MXene is prone to oxidize in the presence of air and water,resulting in a significant loss of conductivity.Polydopamine(PDA)has been coated on MXene to enhance its antioxidation stability via the physical barrier and chemical reducing ability of PDA,which unavoidably causes severe aggregation and a significant decrease in conductivity due to the crosslinking and insulation of PDA.Herein,we propose a facile strategy to construct a highly conductive,stable,and self-healing MXene-based polyvinyl alcohol(PVA)hydrogel by a controlled assembly of PDA and cellulose nanocrystal(CNC).PDA is first formed by oxidation self-polymerization in PVA solution without the presence of CNC and MXene,which can effectively reduce the content of aggregation-inducing groups and avoid the formation of an insulating PDA layer on the surface of MXene.The addition of CNCs results in the easy dispersion of a high content of MXene via hydrogen bonding and electrostatic interactions.The PVA-PDA hydrogel with MXene and CNC as conductive and reinforcing nanofillers(PP-CM)is cross-linked by dynamic borax covalent bonds and shows a conductivity of 7.14 S m^(-1).The introduction of PDA effectively protects MXene and results in only a 14%decrease in conductivity after 7 days,significantly improving antioxidant stability.This hydrogel also possesses rapid self-healing capabilities,achieving 90.5%self-healing efficiency within 10 min.This versatile approach opens new avenues for the preparation and application of MXene-based conductive hydrogels.
基金supported by the National Natural Science Foundation of China(62088101,62522307,62273045,U2341213)Beijing Nova Program(20230484481)。
文摘Formation control of multiple spacecraft has attracted extensive research attention.However,achieving reliable performance under sensor failures remains a significant challenge.This paper develops an integrated framework that jointly designs distributed observers and local controllers to ensure robust formation control in the presence of external disturbances and sensor malfunctions.Treating the spacecraft formation as a single interconnected system,each spacecraft constructs a distributed observer that estimates the overall system state by incorporating both its own measurements and the predicted control information shared among the spacecraft.Based on the observer estimates,a local control law is synthesized to maintain the desired formation.Rigorous theoretical analysis and numerical simulations demonstrate that the proposed integrated approach effectively guarantees formation stability and resilience against sensor failures and disturbances.
基金supported by the Basic Science Research Program(2023R1A2C3004336,RS-202300243807)&Regional Leading Research Center(RS-202400405278)through the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)。
文摘Wearable sensors integrated with deep learning techniques have the potential to revolutionize seamless human-machine interfaces for real-time health monitoring,clinical diagnosis,and robotic applications.Nevertheless,it remains a critical challenge to simultaneously achieve desirable mechanical and electrical performance along with biocompatibility,adhesion,self-healing,and environmental robustness with excellent sensing metrics.Herein,we report a multifunctional,anti-freezing,selfadhesive,and self-healable organogel pressure sensor composed of cobalt nanoparticle encapsulated nitrogen-doped carbon nanotubes(CoN CNT)embedded in a polyvinyl alcohol-gelatin(PVA/GLE)matrix.Fabricated using a binary solvent system of water and ethylene glycol(EG),the CoN CNT/PVA/GLE organogel exhibits excellent flexibility,biocompatibility,and temperature tolerance with remarkable environmental stability.Electrochemical impedance spectroscopy confirms near-stable performance across a broad humidity range(40%-95%RH).Freeze-tolerant conductivity under sub-zero conditions(-20℃)is attributed to the synergistic role of CoN CNT and EG,preserving mobility and network integrity.The Co N CNT/PVA/GLE organogel sensor exhibits high sensitivity of 5.75 k Pa^(-1)in the detection range from 0 to 20 k Pa,ideal for subtle biomechanical motion detection.A smart human-machine interface for English letter recognition using deep learning achieved 98%accuracy.The organogel sensor utility was extended to detect human gestures like finger bending,wrist motion,and throat vibration during speech.
