Force and impulse multi-sensor based on flexible gate dielectric field effect transistor

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.

Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots.Compared to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static stimuli.Here,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic stimuli.Specifically,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential differences.The controllable and reversible polarization process of the conjugated polymers is fully in situ characterized.Then,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference outputs.Compared with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior bio-friendliness.As demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning algorithms.This tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

Fabrication Techniques and Sensing Mechanisms of Textile‑Based Strain Sensors:From Spatial 1D and 2D Perspectives

The intelligent textile sensors based on fiber(1D)and fabric(2D)are the ideal candidates for wearable devices.Their flexible weaving and unique structure endow them with flexibility,lightweight,good air permeability,and feasible integration with garments.In view of the spring-up of novel textile-based strain sensors,the novel materials and fabrication approaches were elaborated from spatial perspectives,i.e.,1D fibers/yarn and 2D fabric.The intrinsic sensing mechanism is the primary fac-tor affecting sensor sensitivity,and the variation trend of the sensing signal is closely related to it.Although existing studies have involved various sensing mechanisms,there is still lacking systematic classification and discussion.Hence,the sensing mechanisms of textile-based sensors were elaborated from spatial perspectives.Considering that strain sensors were mostly based on resistance variation,the sensing mechanisms of resistive textile-based strain sensors were mainly focused,mainly including fiber deformation,tunneling effect,crack propagation,fabric deformation,electrical contact and bridge connec-tion.Meanwhile,the corresponding resistance prediction models,usually used as important data fitting methodology,were also comprehensively discussed,which can reproduce the resistance trend and provide guidance for the sensor performance.Finally,the multifunctionality of textile-based strain sensors was summarized,namely multi-mode signal detection,visual interaction,energy collection,thermal management and medical treatment were discussed.It was expected to provide research insights into the multifunctional integration of textile sensors.

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Distributed fiber optic sensors for tunnel monitoring:A state-of-the-art review

Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

Low‑Cost,Scalable Fabrication of All‑Fabric Piezoresistive Sensors via Binder‑Free,In‑Situ Welding of Carbon Nanotubes on Bicomponent Nonwovens

Wearable piezoresistive sensors have shown enormous application prospects in flexible electronics and human-machine interfaces.However,current piezoresistive sensors suffer from common deficiencies including high fabrication cost,poor comfort and low attachment fastness of conductive substances on substrates,thereby impeding their large-scale production and practical use.Herein,a three-dimensional all-fabric piezoresistive sensor is reported based on coating multi-wall carbon nanotubes(MWCNTs)on bicomponent nonwovens composed of core-sheath fibers.The combination of core-sheath fibers with a heat-induced welding strategy greatly improves the adhesion fastness and stability of MWCNT network.The multi-layered all-fabric structure provides as-prepared sensors with high sensitivity(9.43%kPa^(-1)in 0-10 kPa and 0.076%kPa^(-1)in 20-120 kPa),wide pressure-sensing range(0-120 kPa),fast response/relaxation time(100 and 60 ms),good reproducibility and air permeability.Application of the sensor is demonstrated through the detection of human activities(such as pulse,cough and joint movements)and the wireless monitoring of forefinger bending.Moreover,our sensor is fabricated out of cost-effective materials,using scalable approach without using glue or binders.The method established in this work may provide an efficient strategy for the design and production of high-performance all-fabric piezoresistive sensors.

A Universal,Highly Sensitive and Seamlessly Integratable Textile Resistive Strain Sensor

Textile strain sensors capable of monitoring human physiological signals and activities have great potential in health moni-toring and sports.However,fabricating sensors with a wide sensing range,high sensitivity,robustness,and the capability for seamless integration into apparel remains challenging.In this work,a textile resistive strain sensor(TRSS)fabricated by selectively inlaying a conductive yarn,that is covered with water-repellent and antioxidative acrylic/copper complex fibers,into a highly elastic substrate via an industrialized knitting process is proposed.The conductive yarn is folded and compactly stacked to sense strains by changing contact resistance through contact separation of adjacent yarn sections in stretching.Owing to this folded structure,the TRSS has a wide sensing range(0–70%),high sensitivity(maximum gauge factor GF_(max)=1560),low detection limit(<0.5%),long-term fatigue resistance over 4000 cycles,and it can be seamlessly integrated into and become a part of various smart apparel products.An elbow sleeve,a knee sleeve and a sock are demon-strated to effectively monitor and distinguish various human bending motions.The fabrication strategy paves a viable way for customizing high-performance strain sensors for developing novel wearable electronics and smart clothing to detect multimode human motions.

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.

Electrochemical biosensors for point-of-care testing

Point-of-care testing(POCT)is the practice of diagnosing and monitoring diseases where the patient is located,as opposed to traditional treatment conducted solely in a medical laboratory or other clinical setting.POCT has been less common in the recent past due to a lack of portable medical devices capable of facilitating effective medical testing.However,recent growth has occurred in this field due to advances in diagnostic technologies,device miniaturization,and progress in wearable electronics.Among these developments,electrochemical sensors have attracted interest in the POCT field due to their high sensitivity,compact size,and affordability.They are used in various applications,from disease diagnosis to health status monitoring.In this paper we explore recent advancements in electrochemical sensors,the methods of fabricating them,and the various types of sensing mechanisms that can be used.Furthermore,we delve into methods for immobilizing specific biorecognition elements,including enzymes,antibodies,and aptamers,onto electrode surfaces and how these sensors are used in real-world POCT settings.

Non‑Enzyme,Temperature Calibrating,and Bioactive Fiber‑based Flexible Sensors for Dopamine and Lactic Acid Detection

Flexible electrochemical biosensors enable the in-situ monitoring and quantification of human biochemical constituents in molecular scale,spearheading and thriving the field toward precision medicine.However,specific biorecognition elements for multiplexed biomarkers detection,temperature stability and versatility need to be improved for higher adaption.Here,we propose a bioactive sensor patch comprising a non-enzyme Co_(3)O_(4)/carbon fiber-based biorecognition element and a temperature calibration unit.The optimized serpentine configuration renders the sensor intimate and seamless attachment with skin,operating robustly even subjected to 40%tensile strain.The fiber-based sensor could selectively monitor dopa-mine and lactic acid contents based on cyclic voltammetry and amperometry,respectively.The bioanalytical results at room temperature indicate that the electrochemical biosensor has a wide detection range(0.001–1.100 mM for dopamine and 2–35 mM for lactic acid),excellent selectivity and reproducibility(maximum error 3.2%for dopamine and 5.6%for lactic acid).In addition,temperature calibration contour maps of these two biomarkers are established in an ambient temperature range from 25 to 45℃.The continuously collected data could be aggregated and wirelessly transmitted to portable devices using an electrochemical signal transducer and an acquisition module,promising personalized and preventative health care in various scenarios.

Ultra-broadband microwave absorber and high-performance pressure sensor based on aramid nanofiber,polypyrrole and nickel porous aerogel

Electronic devices have become ubiquitous in our daily lives,leading to a surge in the use of microwave absorbers and wearable sensor devices across various sectors.A prime example of this trend is the aramid nanofibers/polypyrrole/nickel(APN)aerogels,which serve dual roles as both microwave absorbers and pressure sensors.In this work,we focused on the preparation of aramid nanofibers/polypyrrole(AP15)aerogels,where the mass ratio of aramid nanofibers to pyrrole was 1:5.We employed the oxidative polymerization method for the preparation process.Following this,nickel was thermally evaporated onto the surface of the AP15 aerogels,resulting in the creation of an ultralight(9.35 mg·cm^(-3)).This aerogel exhibited a porous structure.The introduction of nickel into the aerogel aimed to enhance magnetic loss and adjust impedance matching,thereby improving electromagnetic wave absorption performance.The minimum reflection loss value achieved was-48.7 dB,and the maximum effective absorption bandwidth spanned 8.42 GHz with a thickness of 2.9 mm.These impressive metrics can be attributed to the three-dimensional network porous structure of the aerogel and perfect impedance matching.Moreover,the use of aramid nanofibers and a three-dimensional hole structure endowed the APN aerogels with good insulation,flame-retardant properties,and compression resilience.Even under a compression strain of 50%,the aerogel maintained its resilience over 500 cycles.The incorporation of polypyrrole and nickel particles further enhanced the conductivity of the aerogel.Consequently,the final APN aerogel sensor demonstrated high sensitivity(10.78 kPa-1)and thermal stability.In conclusion,the APN aerogels hold significant promise as ultra-broadband microwave absorbers and pressure sensors.

UAV-assisted data collection for wireless sensor networks with dynamic working modes

Wireless Sensor Network(WSN)is a cornerstone of Internet of Things(IoT)and has rich application scenarios.In this work,we consider a heterogeneous WSN whose sensor nodes have a diversity in their Residual Energy(RE).In this work,to protect the sensor nodes with low RE,we investigate dynamic working modes for sensor nodes which are determined by their RE and an introduced energy threshold.Besides,we employ an Unmanned Aerial Vehicle(UAV)to collect the stored data from the heterogeneous WSN.We aim to jointly optimize the cluster head selection,energy threshold and sensor nodes’working mode to minimize the weighted sum of energy con-sumption from the WSN and UAV,subject to the data collection rate constraint.To this end,we propose an efficient search method to search for an optimal energy threshold,and develop a penalty-based successive convex approximation algorithm to select the cluster heads.Then we present a low-complexity iterative approach to solve the joint optimization problem and discuss the implementation procedure.Numerical results justify that our proposed approach is able to reduce the energy consumption of the sensor nodes with low RE significantly and also saves energy for the whole WSN.

Synergy of ZnO Nanowire Arrays and Electrospun Membrane Gradient Wrinkles in Piezoresistive Materials for Wide‑Sensing Range and High‑Sensitivity Flexible Pressure Sensor

Flexible pressure sensors have come under the spotlight because of their widespread adoption in human motion detection and human‒machine interactions.However,manufacturing pressure sensors with broad sensing ranges and large sensitivities continues to be a daunting task.Herein,a pressure sensor based on a gradient wrinkled electrospun polyurethane membrane with MXene-embedded ZnO nanowire arrays(ZAGW)was proposed.Under tiny pressure,dramatic increases in the contact area caused by interlocks of MXene-embedded ZnO nanowire arrays contributed to realizing a high sensitivity(236.5 kPa^(−1)).Additionally,the wide-sensing range(0–260 kPa)came from the fact that a wrinkled membrane with a gradient contact height ensured a continuous contact area change by gradually activating contact wrinkles.Meanwhile,the contact states of the gradient wrinkled membrane at varying pressures were investigated to expound the sensing mechanism of the ZAGW sensor.These exceptional performances enabled the ZAGW sensor to have vast application potential in human motion monitoring and tactile sensing.Furthermore,the ZAGW sensor can be integrated into the sensor array to monitor the pressure distribution.Considering the outstanding performance,the combination of ZnO nanowire arrays and electrospun membrane gradient wrinkles provides an innovative avenue for future sensing research.

Comparison of displacement damage effects on the dark signal in CMOS image sensors induced by CSNS back-n and XAPR neutrons

This study investigates the effects of displacement damage on the dark signal of a pinned photodiode CMOS image sensor(CIS)following irradiation with back-streaming white neutrons from white neutron sources at the China spallation neutron source(CSNS)and Xi'an pulsed reactor(XAPR).The mean dark signal,dark signal non-uniformity(DSNU),dark signal distribution,and hot pixels of the CIS were compared between the CSNS back-n and XAPR neutron irradiations.The nonionizing energy loss and energy distribution of primary knock-on atoms in silicon,induced by neutrons,were calculated using the open-source package Geant4.An analysis combining experimental and simulation results showed a noticeable proportionality between the increase in the mean dark signal and the displacement damage dose(DDD).Additionally,neutron energies influence DSNU,dark signal distribution,and hot pixels.High neutron energies at the same DDD level may lead to pronounced dark signal non-uniformity and elevated hot pixel values.

Progress of Proximity Sensors for Potential Applications in Electronic Skins

Recently,electronic skins and fl exible wearable devices have been developed for widespread applications in medical monitoring,artifi cial intelligence,human–machine interaction,and artifi cial prosthetics.Flexible proximity sensors can accurately perceive external objects without contact,introducing a new way to achieve an ultrasensitive perception of objects.This article reviews the progress of fl exible capacitive proximity sensors,fl exible triboelectric proximity sensors,and fl exible gate-enhanced proximity sensors,focusing on their applications in the electronic skin fi eld.Herein,their working mechanism,materials,preparation methods,and research progress are discussed in detail.Finally,we summarize the future challenges in developing fl exible proximity sensors.

Flexible piezoresistive pressure sensor based on a graphene-carbon nanotube-polydimethylsiloxane composite

Flexible sensors are used widely in wearable devices, specifically flexible piezoresistive sensors, which are common and easy to manipulate.However, fabricating such sensors is expensive and complex, so proposed here is a simple fabrication approach involving a sensor containing microstructures replicated from a sandpaper template onto which polydimethylsiloxane containing a mixture of graphene and carbon nanotubes is spin coated. The surface morphologies of three versions of the sensor made using different grades of sandpaper are observed, and the corresponding pressure sensitivities and linearity and hysteresis characteristics are assessed and analyzed. The results show that the sensor made using 80-mesh sandpaper has the best sensing performance. Its sensitivity is 0.341 kPa-1in the loading range of 0–1.6 kPa, it responds to small external loading of 100 Pa with a resistance change of 10%, its loading and unloading response times are 0.126 and 0.2 s, respectively,and its hysteresis characteristic is ~7%, indicating that the sensor has high sensitivity, fast response, and good stability. Thus, the presented piezoresistive sensor is promising for practical applications in flexible wearable electronics.

Overcoming the Limits of Cross-Sensitivity:Pattern Recognition Methods for Chemiresistive Gas Sensor Array

As information acquisition terminals for artificial olfaction,chemiresistive gas sensors are often troubled by their cross-sensitivity,and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area.Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors.It is crucial to choose an appropriate pattern recognition method for enhancing data analysis,reducing errors and improving system reliability,obtaining better classification or gas concentration prediction results.In this review,we analyze the sensing mechanism of crosssensitivity for chemiresistive gas sensors.We further examine the types,working principles,characteristics,and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays.Additionally,we report,summarize,and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification.At the same time,this work showcases the recent advancements in utilizing these methods for gas identification,particularly within three crucial domains:ensuring food safety,monitoring the environment,and aiding in medical diagnosis.In conclusion,this study anticipates future research prospects by considering the existing landscape and challenges.It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

Solution-processing approach of nanomaterials toward an artificial sensory system

Artificial sensory systems have emerged as pivotal technologies to bridge the gap between the virtual and real-world,replicating human senses to interact intelligently with external stimuli.To practically apply artificial sensory systems in the real-world,it is essential to mass-produce nanomaterials with ensured sensitivity and selectivity,purify them for desired functions,and integrate them into large-area sensory devices through assembly techniques.A comprehensive understanding of each process parameter from material processing to device assembly is crucial for achieving a high-performing artificial sensory system.This review provides a technological framework for fabricating high-performance artificial sensory systems,covering material processing to device integrations.We introduce recent approaches for dispersing and purifying various nanomaterials including 0D,1D,and 2D nanomaterials.We then highlight advanced coating and printing techniques of the solution-processed nanomaterials based on representative three methods including(i)evaporation-based assembly,(ii)assisted assembly,and(iii)direct patterning.We explore the application and performances of these solution-processed materials and printing methods in fabricating sensory devices mimicking five human senses including vision,olfaction,gustation,hearing,and tactile perception.Finally,we suggest an outlook for possible future research directions to solve the remaining challenges of the artificial sensory systems such as ambient stability,device consistency,and integration with AI-based software.