Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart...Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.展开更多
In the modern technological landscape,magnetic field sensors play a crucial role and are indispensable across a range of high-tech applications[1].In conjunction with magnets,magnetic field sensors can accurately dete...In the modern technological landscape,magnetic field sensors play a crucial role and are indispensable across a range of high-tech applications[1].In conjunction with magnets,magnetic field sensors can accurately detect any form of relative movement of objects without physical contact.For instance,in the precise control of robotic arms or machine tools,a permanent magnet is used as a reference.The magnetic sensor detects the relative movement of magnet by sensing changes in the magnetic field strength.These changes are converted into electrical signals,which are fed back to the control system,enabling accurate positioning and control of the device.This advanced detection technology not only greatly enhances measurement precision but also significantly extends the lifespan of equipment.Among various types of magnetic field sensors,magnetoresistive(MR)sensors stand out for their exceptional performance[1].The high sensitivity allows them to detect minimal changes of magnetic fields in high-precision measurements.Today,MR sensors are widely used across numerous fields,including automobile industries,information processing and storage,navigation systems,biomedical applications,etc[1,2].With their outstanding performance and wide-ranging applications,MR sensors are at the forefront of sensor technology.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
Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive ...Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.展开更多
The Design and manufacturing of a noble piezoresistive pressure sensor(PS) for subtle pressures(<1 kPa) were presented. Meanwhile, in the studies conducted in the field of pressure sensors, the measurement of subtl...The Design and manufacturing of a noble piezoresistive pressure sensor(PS) for subtle pressures(<1 kPa) were presented. Meanwhile, in the studies conducted in the field of pressure sensors, the measurement of subtle pressures has received less attention. The limitations in the inherent gauge factor in silicon, have led to the development of polymer and composite resistive sensitive elements. However,in the development of resistance sensing elements, the structure of composite elements with reinforcement core has not been used. The proposed PS had a composite sandwich structure consisting of a nanocomposite graphene layer covered by layers of PDMS at the bottom and on the top coupled with a polyimide(PI) core. Various tests were performed to analyze the PS. The primary design target was improved sensitivity, with a finite-element method(FEM) utilized to simulate the stress profile over piezoresistive elements and membrane deflection at various pressures. The PS manufacturing process is based on Laser-engraved graphene(LEG) technology and PDMS casting. Experimental data indicated that the manufactured PS exhibits a sensitivity of 67.28 mV/kPa for a pressure range of 30-300 Pa in ambient temperature.展开更多
In the era of Metaverse and virtual reality(VR)/augmented reality(AR),capturing finger motion and force interactions is crucial for immersive human-machine interfaces.This study introduces a flexible electronic skin f...In the era of Metaverse and virtual reality(VR)/augmented reality(AR),capturing finger motion and force interactions is crucial for immersive human-machine interfaces.This study introduces a flexible electronic skin for the index finger,addressing coupled perception of both state and process in dynamic tactile sensing.The device integrates resistive and giant magnetoelastic sensors,enabling detection of surface pressure and finger joint bending.This e-skin identifies three phases of finger action:bending state,dynamic normal force and tangential force(sweeping).The system comprises resistive carbon nanotubes(CNT)/polydimethylsiloxane(PDMS)films for bending sensing and magnetoelastic sensors(NdFeB particles,EcoFlex,and flexible coils)for pressure detection.The inward bending resistive sensor,based on self-assembled microstructures,exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0°to 120°.The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude,as well as sensitivity to surface roughness during sliding and material hardness.The system’s capability is demonstrated through tactile-based bread type and condition recognition,achieving 92%accuracy.This intelligent patch shows broad potential in enhancing interactions across various fields,from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.展开更多
A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in thi...A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in this paper.High-order acoustic modes(HOAMs)are used to achieve individual or simultaneous measurement of the two parameters.Transverse acoustic waves(TAWs)involved in the FSBS process can efficiently sense the mechanical or environmental changes outside the fiber cladding,which will be reflected in a linear shift of the acoustic resonance frequency.By analyzing the frequencies of specific scattering peaks,the temperature and acoustic impedance outside the fiber cladding can be obtained simultaneously.The highest measured temperature and acoustic impedance sensitivities are 184.93 k Hz/℃and444.56 k Hz/MRayl,and the measurement accuracies are 0.09℃and 0.009 MRayl,respectively,which are both at desirable levels.We believe this work can provide potential application solutions for sensing fields involving temperature or acoustic impedance measurements.展开更多
A compact and highly sensitive gas pressure and temperature sensor based on Fabry-Pérot interferometer(FPI)and fiber Bragg grating(FBG)is proposed and demonstrated experimentally in this paper.The theoretical mod...A compact and highly sensitive gas pressure and temperature sensor based on Fabry-Pérot interferometer(FPI)and fiber Bragg grating(FBG)is proposed and demonstrated experimentally in this paper.The theoretical model for pressure and temperature sensing is established.Building on this foundation,a novel micro silicon cavity sensor structure sensitive to pressure is devised downstream of an FBG.The concept of separate measurement and the mechanisms enhancing pressure sensitivity are meticulously analyzed,and the corresponding samples are fabricated.The experimental results indicate that the pressure sensitivity of the sensor is-747.849 nm/MPa in 0—100 k Pa and its linearity is 99.7%and it maintains good stability in 150 min.The sensor offers the advantages of compact size,robust construction,easy fabrication,and high sensitivity,making it potentially valuable for micro-pressure application.展开更多
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
Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,a...Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,and improve the reliability and safety of the system.Artificial intelligence(AI),referring to the simulation of human intelligence in machines that are programmed to think and learn like humans,represents a pivotal frontier in modern scientific research.With the continuous development and promotion of AI technology in Sensor 4.0 age,multimodal sensor fusion is becoming more and more intelligent and automated,and is expected to go further in the future.With this context,this review article takes a comprehensive look at the recent progress on AI-enhanced multimodal sensors and their integrated devices and systems.Based on the concept and principle of sensor technologies and AI algorithms,the theoretical underpinnings,technological breakthroughs,and pragmatic applications of AI-enhanced multimodal sensors in various fields such as robotics,healthcare,and environmental monitoring are highlighted.Through a comparative study of the dual/tri-modal sensors with and without using AI technologies(especially machine learning and deep learning),AI-enhanced multimodal sensors highlight the potential of AI to improve sensor performance,data processing,and decision-making capabilities.Furthermore,the review analyzes the challenges and opportunities afforded by AI-enhanced multimodal sensors,and offers a prospective outlook on the forthcoming advancements.展开更多
Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense in...Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.展开更多
Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to tre...Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to treat respiratory disorders such as asthma,bronchitis,and emphysema,has a narrow therapeutic window with a safe plasma concentration ranging from 55.5-111.0μmol·L^(-1)in adults.Accurate monitoring of TP levels is essential because too low or too high can cause se-rious side effects.In this regard,non-enzymatic electrochemical sensors offer a practical solution with rapidity,portability,and high sensitivity.This article aims to provide a comprehensive review of the recent developments of non-enzymatic electrochemical sensors for TP detection,highlighting the basic principles,electro-oxidation mechanisms,catalytic effects,and the role of modifying materials on electrode performance.Carbon-based electrodes such as glassy carbon electrodes(GCEs),carbon paste electrodes(CPEs),and carbon screen-printed electrodes(SPCEs)have become the primary choices for non-enzymatic sensors due to their chemical stability,low cost,and flexibility in modification.This article identifies the sig-nificant contribution of various modifying materials,including nanomaterials such as carbon nanotubes(CNTs),graphene,metal oxides,and multi-element nanocomposites.These modifications enhance sensors’electron transfer,sensitivity,and selectivity in detecting TP at low concentrations in complex media such as blood plasma and pharmaceutical samples.The electro-oxidation mechanism of TP is also discussed in depth,emphasizing the hydroxyl and carbonyl reaction pathways strongly influenced by pH and electrode materials.These mechanisms guide the selection of the appropriate electrode ma-terial for a particular application.The main contribution of this article is to identify superior modifying materials that can improve the performance of non-enzymatic electrochemical sensors.In a recent study,the combination of multi-element nanocomposites based on titanium dioxide(TiO_(2)),CNTs,and gold nanoparticles(AuNPs)resulted in the lowest detection limit of 3×10^(-5)μmol·L^(-1),reflecting the great potential of these materials for developing high-performance electrochemical sensors.The main conclusion of this article is the importance of a multidisciplinary approach in electrode material design to support the sensitivity and selectivity of TP detection.In addition,there is still a research gap in understanding TP’s more detailed oxidation mechanism,especially under pH variations and complex environments.Therefore,further research on electrode modification and analysis of the TP oxidation mechanism are urgently needed to improve the accuracy and sta-bility of the sensor while expanding its applications in pharmaceutical monitoring and medical diagnostics.By integrating various innovative materials and technical approaches,this review is expected to be an essential reference for developing efficient and affordable non-enzymatic electrochemical sensors.展开更多
Position sensitive device(PSD)sensor is a vital optical element that is mainly used in tracking systems for visible light communication(VLC).Recently,a new reconfigurable PSD architecture emerged.The proposed architec...Position sensitive device(PSD)sensor is a vital optical element that is mainly used in tracking systems for visible light communication(VLC).Recently,a new reconfigurable PSD architecture emerged.The proposed architecture makes the PSD perform more functions by modifying its architecture.As the PSD is mainly formed of an array of photodiodes.The primary concept involves employing transistors to alternate between the operating modes of the photodiodes(photoconductive and photovoltaic).Additionally,alternating among output pins can be done based on the required function.This paper presents the mathematical modeling and simulation of a reconfigurable-multifunctional optical sensor which can perform energy harvesting and data acquisition,as well as positioning,which is not available in the traditional PSDs.Simulation using the MATLAB software tool was achieved to demonstrate the modeling.The simulation results confirmed the validity of the mathematical modeling and proved that the modified sensor architecture,as depicted by the equations,accurately describes its behavior.The proposed sensor is expected to extend the battery's lifecycle,reduce its physical size,and increase the integration and functionality of the system.The presented sensor might be used in free space optical(FSO)communication like cube satellites or even in underwater wireless optical communication(UWOC).展开更多
High-sensitivity sensors represent a critical frontier in modern sensing technology,driving innovations across fields such as biomedical monitoring,precision instrumentation,environmental detection,and indus-trial aut...High-sensitivity sensors represent a critical frontier in modern sensing technology,driving innovations across fields such as biomedical monitoring,precision instrumentation,environmental detection,and indus-trial automation.As demands for accuracy,miniaturization,and reliability continue to grow,developing novel sensor architectures and functional materials has become essential to achieving enhanced performance under extreme or complex conditions.展开更多
Pacinian Corpuscle(PC)is the largest tactile vibration receptor in mammalian skin,with a layered structure that enables signal amplification and high-pass filtering functions.Modern robots feature vibro-tactile sensor...Pacinian Corpuscle(PC)is the largest tactile vibration receptor in mammalian skin,with a layered structure that enables signal amplification and high-pass filtering functions.Modern robots feature vibro-tactile sensors with excellent mechanical properties and fine resolution,but these sensors are prone to low-frequency noise interference when detecting high-frequency vibrations.In this study,a bionic PC with a longitudinally decreasing dynamic fractal structure is proposed.By creating a lumped parameter model of the PC’s layered structure,the bionic PC made of gelatin-chitosan based hydrogel can achieve high-pass filtering and specific frequency band signal amplification without requiring back-end circuits.The experimental results demonstrate that the bionic PC retains the structural characteristics of a natural PC,and the influence of structural factors,such as the number of layers in its shell,on filtration characteristics is explored.Additionally,a vibration source positioning experiment was conducted to simulate the earthquake sensing abilities of elephants.This natural structural design simplifies the filter circuit,is low-cost,cost-effective,stable in performance,and reduces redundancy in the robot’s signal circuit.Integrating this technology with robots can enhance their environmental perception,thereby improving the safety of interactions.展开更多
Over recent decades,carbon-based chemical sensor technologies have advanced significantly.Nevertheless,significant opportunities persist for enhancing analyte recognition capabilities,particularly in complex environme...Over recent decades,carbon-based chemical sensor technologies have advanced significantly.Nevertheless,significant opportunities persist for enhancing analyte recognition capabilities,particularly in complex environments.Conventional monovariable sensors exhibit inherent limitations,such as susceptibility to interference from coexisting analytes,which results in response overlap.Although sensor arrays,through modification of multiple sensing materials,offer a potential solution for analyte recognition,their practical applications are constrained by intricate material modification processes.In this context,multivariable chemical sensors have emerged as a promising alternative,enabling the generation of multiple outputs to construct a comprehensive sensing space for analyte recognition,while utilizing a single sensing material.Among various carbon-based materials,carbon nanotubes(CNTs)and graphene have emerged as ideal candidates for constructing high-performance chemical sensors,owing to their well-established batch fabrication processes,superior electrical properties,and outstanding sensing capabilities.This review examines the progress of carbon-based multivariable chemical sensors,focusing on CNTs/graphene as sensing materials and field-effect transistors as transducers for analyte recognition.The discussion encompasses fundamental aspects of these sensors,including sensing materials,sensor architectures,performance metrics,pattern recognition algorithms,and multivariable sensing mechanism.Furthermore,the review highlights innovative multivariable extraction schemes and their practical applications when integrated with advanced pattern recognition algorithms.展开更多
Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the lim...Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.展开更多
With the rise of artificial intelligence(AI),neuromorphic sensory systems that emulate the five basic human sensations including tactility,audition,olfaction,gustation,and vision have attracted significant attention.I...With the rise of artificial intelligence(AI),neuromorphic sensory systems that emulate the five basic human sensations including tactility,audition,olfaction,gustation,and vision have attracted significant attention.In particular,research on integrating sensors with artificial synapses is being carried out extensively.These studies offer valuable opportunities for making another breakthrough in AI technology,including autonomous systems,real-time monitoring systems,and human-machine interactions.In this review,we introduce promising reports of neuromorphic sensory systems.Specifically,the core sensing material,device architecture,fabrication process,and applications of the proposed systems are presented in detail.Finally,the unsolved challenges and the prospects of neuromorphic sensory systems are discussed.展开更多
Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages...Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages,which hampers effective communication for non-standard language people.Here,we prepare an ultralight Ti_(3)C_(2)T_(x)MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 k Pa,rapid response/recovery time,and low hysteresis(13.69%).The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference,allowing for accurate recognition of six dialects(96.2%accuracy)and seven different words(96.6%accuracy)with the assistance of convolutional neural networks.This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.展开更多
This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer mult...This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.展开更多
基金supported by the National Natural Science Foundation of China(No.22376159)the Fundamental Research Funds for the Central Universities.
文摘Gas sensor is an indispensable part of modern society withwide applications in environmental monitoring,healthcare,food industry,public safety,etc.With the development of sensor technology,wireless communication,smart monitoring terminal,cloud storage/computing technology,and artificial intelligence,smart gas sensors represent the future of gassensing due to their merits of real-time multifunctional monitoring,earlywarning function,and intelligent and automated feature.Various electronicand optoelectronic gas sensors have been developed for high-performancesmart gas analysis.With the development of smart terminals and the maturityof integrated technology,flexible and wearable gas sensors play an increasingrole in gas analysis.This review highlights recent advances of smart gassensors in diverse applications.The structural components and fundamentalprinciples of electronic and optoelectronic gas sensors are described,andflexible and wearable gas sensor devices are highlighted.Moreover,sensorarray with artificial intelligence algorithms and smart gas sensors in“Internet of Things”paradigm are introduced.Finally,the challengesand perspectives of smart gas sensors are discussed regarding the future need of gas sensors for smart city and healthy living.
文摘In the modern technological landscape,magnetic field sensors play a crucial role and are indispensable across a range of high-tech applications[1].In conjunction with magnets,magnetic field sensors can accurately detect any form of relative movement of objects without physical contact.For instance,in the precise control of robotic arms or machine tools,a permanent magnet is used as a reference.The magnetic sensor detects the relative movement of magnet by sensing changes in the magnetic field strength.These changes are converted into electrical signals,which are fed back to the control system,enabling accurate positioning and control of the device.This advanced detection technology not only greatly enhances measurement precision but also significantly extends the lifespan of equipment.Among various types of magnetic field sensors,magnetoresistive(MR)sensors stand out for their exceptional performance[1].The high sensitivity allows them to detect minimal changes of magnetic fields in high-precision measurements.Today,MR sensors are widely used across numerous fields,including automobile industries,information processing and storage,navigation systems,biomedical applications,etc[1,2].With their outstanding performance and wide-ranging applications,MR sensors are at the forefront of sensor technology.
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.
基金financially supported by the National Natural Science Foundation of China(Nos.52272160,U2330112,and 52002254)Sichuan Science and Technology Foundation(Nos.2020YJ0262,2021YFH0127,2022YFH0083,2022YFSY0045,and 2023YFSY0002)+1 种基金the Chunhui Plan of Ministry of Education,Fundamental Research Funds for the Central Universities,China(No.YJ201893)the Foundation of Key Laboratory of Lidar and Device,Sichuan Province,China(No.LLD2023-006)。
文摘Nowadays,force sensors play an important role in industrial production,electronic information,medical health,and many other fields.Two-dimensional material-based filed effect transistor(2D-FET)sensors are competitive with nano-level size,lower power consumption,and accurate response.However,few of them has the capability of impulse detection which is a path function,expressing the cumulative effect of the force on the particle over a period of time.Herein we fabricated the flexible polymethyl methacrylate(PMMA)gate dielectric MoS_(2)-FET for force and impulse sensor application.We systematically investigated the responses of the sensor to constant force and varying forces,and achieved the conversion factors of the drain current signals(I_(ds))to the detected impulse(I).The applied force was detected and recorded by I_(ds)with a low power consumption of~30 nW.The sensitivity of the device can reach~8000%and the 4×1 sensor array is able to detect and locate the normal force applied on it.Moreover,there was almost no performance loss for the device as left in the air for two months.
文摘The Design and manufacturing of a noble piezoresistive pressure sensor(PS) for subtle pressures(<1 kPa) were presented. Meanwhile, in the studies conducted in the field of pressure sensors, the measurement of subtle pressures has received less attention. The limitations in the inherent gauge factor in silicon, have led to the development of polymer and composite resistive sensitive elements. However,in the development of resistance sensing elements, the structure of composite elements with reinforcement core has not been used. The proposed PS had a composite sandwich structure consisting of a nanocomposite graphene layer covered by layers of PDMS at the bottom and on the top coupled with a polyimide(PI) core. Various tests were performed to analyze the PS. The primary design target was improved sensitivity, with a finite-element method(FEM) utilized to simulate the stress profile over piezoresistive elements and membrane deflection at various pressures. The PS manufacturing process is based on Laser-engraved graphene(LEG) technology and PDMS casting. Experimental data indicated that the manufactured PS exhibits a sensitivity of 67.28 mV/kPa for a pressure range of 30-300 Pa in ambient temperature.
基金supported by the National Natural Science Foundation of China(Grant No.12204271)Shenzhen Science and Technology Program(Grant No.JCYJ20220530141014032)Guangdong Basic and Applied Basic Research Foundation program(Grant No.2022A1515011526),China.
文摘In the era of Metaverse and virtual reality(VR)/augmented reality(AR),capturing finger motion and force interactions is crucial for immersive human-machine interfaces.This study introduces a flexible electronic skin for the index finger,addressing coupled perception of both state and process in dynamic tactile sensing.The device integrates resistive and giant magnetoelastic sensors,enabling detection of surface pressure and finger joint bending.This e-skin identifies three phases of finger action:bending state,dynamic normal force and tangential force(sweeping).The system comprises resistive carbon nanotubes(CNT)/polydimethylsiloxane(PDMS)films for bending sensing and magnetoelastic sensors(NdFeB particles,EcoFlex,and flexible coils)for pressure detection.The inward bending resistive sensor,based on self-assembled microstructures,exhibits directional specificity with a response time under 120 ms and bending sensitivity from 0°to 120°.The magnetoelastic sensors demonstrate specific responses to frequency and deformation magnitude,as well as sensitivity to surface roughness during sliding and material hardness.The system’s capability is demonstrated through tactile-based bread type and condition recognition,achieving 92%accuracy.This intelligent patch shows broad potential in enhancing interactions across various fields,from VR/AR interfaces and medical diagnostics to smart manufacturing and industrial automation.
文摘A temperature and acoustic impedance simultaneous sensor based on forward stimulated Brillouin scattering(FSBS)in highly nonlinear fiber(HNLF)with high sensitivity and high accuracy is proposed and demonstrated in this paper.High-order acoustic modes(HOAMs)are used to achieve individual or simultaneous measurement of the two parameters.Transverse acoustic waves(TAWs)involved in the FSBS process can efficiently sense the mechanical or environmental changes outside the fiber cladding,which will be reflected in a linear shift of the acoustic resonance frequency.By analyzing the frequencies of specific scattering peaks,the temperature and acoustic impedance outside the fiber cladding can be obtained simultaneously.The highest measured temperature and acoustic impedance sensitivities are 184.93 k Hz/℃and444.56 k Hz/MRayl,and the measurement accuracies are 0.09℃and 0.009 MRayl,respectively,which are both at desirable levels.We believe this work can provide potential application solutions for sensing fields involving temperature or acoustic impedance measurements.
基金supported in part by the National Natural Science Foundation of China(Nos.61735014 and 61927812)the Shaanxi Provincial Education Department(No.18JS093)+2 种基金the Natural Science Basic Research Program of Shaanxi Province(No.2024JC-YBMS-530)the Operation Fund of Logging Key Laboratory of Group Company(No.2021DQ0107-11)the Graduate Student Innovation Fund of Xi’an Shiyou University(No.YCS23213193)。
文摘A compact and highly sensitive gas pressure and temperature sensor based on Fabry-Pérot interferometer(FPI)and fiber Bragg grating(FBG)is proposed and demonstrated experimentally in this paper.The theoretical model for pressure and temperature sensing is established.Building on this foundation,a novel micro silicon cavity sensor structure sensitive to pressure is devised downstream of an FBG.The concept of separate measurement and the mechanisms enhancing pressure sensitivity are meticulously analyzed,and the corresponding samples are fabricated.The experimental results indicate that the pressure sensitivity of the sensor is-747.849 nm/MPa in 0—100 k Pa and its linearity is 99.7%and it maintains good stability in 150 min.The sensor offers the advantages of compact size,robust construction,easy fabrication,and high sensitivity,making it potentially valuable for micro-pressure application.
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supported by the National Natural Science Foundation of China(No.62404111)Natural Science Foundation of Jiangsu Province(No.BK20240635)+2 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.24KJB510025)Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(No.NY223157 and NY223156)Opening Project of Advanced Inte-grated Circuit Package and Testing Research Center of Jiangsu Province(No.NTIKFJJ202303).
文摘Multimodal sensor fusion can make full use of the advantages of various sensors,make up for the shortcomings of a single sensor,achieve information verification or information security through information redundancy,and improve the reliability and safety of the system.Artificial intelligence(AI),referring to the simulation of human intelligence in machines that are programmed to think and learn like humans,represents a pivotal frontier in modern scientific research.With the continuous development and promotion of AI technology in Sensor 4.0 age,multimodal sensor fusion is becoming more and more intelligent and automated,and is expected to go further in the future.With this context,this review article takes a comprehensive look at the recent progress on AI-enhanced multimodal sensors and their integrated devices and systems.Based on the concept and principle of sensor technologies and AI algorithms,the theoretical underpinnings,technological breakthroughs,and pragmatic applications of AI-enhanced multimodal sensors in various fields such as robotics,healthcare,and environmental monitoring are highlighted.Through a comparative study of the dual/tri-modal sensors with and without using AI technologies(especially machine learning and deep learning),AI-enhanced multimodal sensors highlight the potential of AI to improve sensor performance,data processing,and decision-making capabilities.Furthermore,the review analyzes the challenges and opportunities afforded by AI-enhanced multimodal sensors,and offers a prospective outlook on the forthcoming advancements.
基金supported by the National Research Foundation(NRF)grant funded by the Korean government(MSIT)(RS-2023-00211580,RS-2023-00237308).
文摘Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.
基金the funding from Lembaga Penelitian dan Pengabdian Masyarakat(LPPM)Universitas Indonesia,by Riset Kolaborasi Indonesia(RKI)-World Class University(WCU)Program with grant number NKB-1067/UN2-RST/HKP.05.00/2023 and NKB-781/UN2.RST/HKP.05.00/2024.
文摘Detection of target analytes at low concentrations is significant in various fields,including pharmaceuticals,healthcare,and environmental protection.Theophylline(TP),a natural alkaloid used as a bronchodilator to treat respiratory disorders such as asthma,bronchitis,and emphysema,has a narrow therapeutic window with a safe plasma concentration ranging from 55.5-111.0μmol·L^(-1)in adults.Accurate monitoring of TP levels is essential because too low or too high can cause se-rious side effects.In this regard,non-enzymatic electrochemical sensors offer a practical solution with rapidity,portability,and high sensitivity.This article aims to provide a comprehensive review of the recent developments of non-enzymatic electrochemical sensors for TP detection,highlighting the basic principles,electro-oxidation mechanisms,catalytic effects,and the role of modifying materials on electrode performance.Carbon-based electrodes such as glassy carbon electrodes(GCEs),carbon paste electrodes(CPEs),and carbon screen-printed electrodes(SPCEs)have become the primary choices for non-enzymatic sensors due to their chemical stability,low cost,and flexibility in modification.This article identifies the sig-nificant contribution of various modifying materials,including nanomaterials such as carbon nanotubes(CNTs),graphene,metal oxides,and multi-element nanocomposites.These modifications enhance sensors’electron transfer,sensitivity,and selectivity in detecting TP at low concentrations in complex media such as blood plasma and pharmaceutical samples.The electro-oxidation mechanism of TP is also discussed in depth,emphasizing the hydroxyl and carbonyl reaction pathways strongly influenced by pH and electrode materials.These mechanisms guide the selection of the appropriate electrode ma-terial for a particular application.The main contribution of this article is to identify superior modifying materials that can improve the performance of non-enzymatic electrochemical sensors.In a recent study,the combination of multi-element nanocomposites based on titanium dioxide(TiO_(2)),CNTs,and gold nanoparticles(AuNPs)resulted in the lowest detection limit of 3×10^(-5)μmol·L^(-1),reflecting the great potential of these materials for developing high-performance electrochemical sensors.The main conclusion of this article is the importance of a multidisciplinary approach in electrode material design to support the sensitivity and selectivity of TP detection.In addition,there is still a research gap in understanding TP’s more detailed oxidation mechanism,especially under pH variations and complex environments.Therefore,further research on electrode modification and analysis of the TP oxidation mechanism are urgently needed to improve the accuracy and sta-bility of the sensor while expanding its applications in pharmaceutical monitoring and medical diagnostics.By integrating various innovative materials and technical approaches,this review is expected to be an essential reference for developing efficient and affordable non-enzymatic electrochemical sensors.
文摘Position sensitive device(PSD)sensor is a vital optical element that is mainly used in tracking systems for visible light communication(VLC).Recently,a new reconfigurable PSD architecture emerged.The proposed architecture makes the PSD perform more functions by modifying its architecture.As the PSD is mainly formed of an array of photodiodes.The primary concept involves employing transistors to alternate between the operating modes of the photodiodes(photoconductive and photovoltaic).Additionally,alternating among output pins can be done based on the required function.This paper presents the mathematical modeling and simulation of a reconfigurable-multifunctional optical sensor which can perform energy harvesting and data acquisition,as well as positioning,which is not available in the traditional PSDs.Simulation using the MATLAB software tool was achieved to demonstrate the modeling.The simulation results confirmed the validity of the mathematical modeling and proved that the modified sensor architecture,as depicted by the equations,accurately describes its behavior.The proposed sensor is expected to extend the battery's lifecycle,reduce its physical size,and increase the integration and functionality of the system.The presented sensor might be used in free space optical(FSO)communication like cube satellites or even in underwater wireless optical communication(UWOC).
文摘High-sensitivity sensors represent a critical frontier in modern sensing technology,driving innovations across fields such as biomedical monitoring,precision instrumentation,environmental detection,and indus-trial automation.As demands for accuracy,miniaturization,and reliability continue to grow,developing novel sensor architectures and functional materials has become essential to achieving enhanced performance under extreme or complex conditions.
基金funded by the National Natural Science Foundation of China(No.52475190 and 52275191)China Postdoctoral Science Foundation Funded Project(No.2024M751165)the Tribology Science Fund of State Key Laboratory of Tribology in Advanced Equipment(No.SKLTKF24B17).
文摘Pacinian Corpuscle(PC)is the largest tactile vibration receptor in mammalian skin,with a layered structure that enables signal amplification and high-pass filtering functions.Modern robots feature vibro-tactile sensors with excellent mechanical properties and fine resolution,but these sensors are prone to low-frequency noise interference when detecting high-frequency vibrations.In this study,a bionic PC with a longitudinally decreasing dynamic fractal structure is proposed.By creating a lumped parameter model of the PC’s layered structure,the bionic PC made of gelatin-chitosan based hydrogel can achieve high-pass filtering and specific frequency band signal amplification without requiring back-end circuits.The experimental results demonstrate that the bionic PC retains the structural characteristics of a natural PC,and the influence of structural factors,such as the number of layers in its shell,on filtration characteristics is explored.Additionally,a vibration source positioning experiment was conducted to simulate the earthquake sensing abilities of elephants.This natural structural design simplifies the filter circuit,is low-cost,cost-effective,stable in performance,and reduces redundancy in the robot’s signal circuit.Integrating this technology with robots can enhance their environmental perception,thereby improving the safety of interactions.
基金supported by National Natural Science Foundation of China(92263109,52305607 and 61904188)the Shanghai Rising-Star Program(22QA1410400)+1 种基金the Natural Science Foundation of Shanghai(23ZR1472200)the Medical Innovation Research Program of Shanghai Science and Technology Innovation Action Plan(Grant No.24DX2800100)。
文摘Over recent decades,carbon-based chemical sensor technologies have advanced significantly.Nevertheless,significant opportunities persist for enhancing analyte recognition capabilities,particularly in complex environments.Conventional monovariable sensors exhibit inherent limitations,such as susceptibility to interference from coexisting analytes,which results in response overlap.Although sensor arrays,through modification of multiple sensing materials,offer a potential solution for analyte recognition,their practical applications are constrained by intricate material modification processes.In this context,multivariable chemical sensors have emerged as a promising alternative,enabling the generation of multiple outputs to construct a comprehensive sensing space for analyte recognition,while utilizing a single sensing material.Among various carbon-based materials,carbon nanotubes(CNTs)and graphene have emerged as ideal candidates for constructing high-performance chemical sensors,owing to their well-established batch fabrication processes,superior electrical properties,and outstanding sensing capabilities.This review examines the progress of carbon-based multivariable chemical sensors,focusing on CNTs/graphene as sensing materials and field-effect transistors as transducers for analyte recognition.The discussion encompasses fundamental aspects of these sensors,including sensing materials,sensor architectures,performance metrics,pattern recognition algorithms,and multivariable sensing mechanism.Furthermore,the review highlights innovative multivariable extraction schemes and their practical applications when integrated with advanced pattern recognition algorithms.
文摘Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.
基金supported by the National Research Foundation of Korea(NRF)Grant funded by the Korea Government(Ministry of Science and ICT)(No.NRF-2022R1A2C2010774)by the GRRC program of Gyeonggi Province(GRRC Sungkyunkwan 2023-B04)by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0020967,Advanced Training Program for Smart Sensor Engineers).
文摘With the rise of artificial intelligence(AI),neuromorphic sensory systems that emulate the five basic human sensations including tactility,audition,olfaction,gustation,and vision have attracted significant attention.In particular,research on integrating sensors with artificial synapses is being carried out extensively.These studies offer valuable opportunities for making another breakthrough in AI technology,including autonomous systems,real-time monitoring systems,and human-machine interactions.In this review,we introduce promising reports of neuromorphic sensory systems.Specifically,the core sensing material,device architecture,fabrication process,and applications of the proposed systems are presented in detail.Finally,the unsolved challenges and the prospects of neuromorphic sensory systems are discussed.
基金supported by the National Nature Science Foundation of China(No.62122030,62333008,62371205,52103208)National Key Research and Development Program of China(No.2021YFB3201300)+1 种基金Application and Basic Research of Jilin Province(20130102010 JC)Fundamental Research Funds for the Central Universities,Jilin Provincial Science and Technology Development Program(20230101072JC)。
文摘Wearable pressure sensors capable of adhering comfortably to the skin hold great promise in sound detection.However,current intelligent speech assistants based on pressure sensors can only recognize standard languages,which hampers effective communication for non-standard language people.Here,we prepare an ultralight Ti_(3)C_(2)T_(x)MXene/chitosan/polyvinylidene difluoride composite aerogel with a detection range of 6.25 Pa-1200 k Pa,rapid response/recovery time,and low hysteresis(13.69%).The wearable aerogel pressure sensor can detect speech information through the throat muscle vibrations without any interference,allowing for accurate recognition of six dialects(96.2%accuracy)and seven different words(96.6%accuracy)with the assistance of convolutional neural networks.This work represents a significant step forward in silent speech recognition for human–machine interaction and physiological signal monitoring.
基金supported by the National Natural Science Foundation of China (Nos. 62276204, 62203343)。
文摘This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.
