Smart Gas Sensors:Recent Developments and Future Prospective

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.

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.

An Artificial Intelligence‑Assisted Flexible and Wearable Mechanoluminescent Strain Sensor System

The complex wiring,bulky data collection devices,and difficulty in fast and on-site data interpretation significantly limit the practical application of flexible strain sensors as wearable devices.To tackle these challenges,this work develops an artificial intelligenceassisted,wireless,flexible,and wearable mechanoluminescent strain sensor system(AIFWMLS)by integration of deep learning neural network-based color data processing system(CDPS)with a sandwich-structured flexible mechanoluminescent sensor(SFLC)film.The SFLC film shows remarkable and robust mechanoluminescent performance with a simple structure for easy fabrication.The CDPS system can rapidly and accurately extract and interpret the color of the SFLC film to strain values with auto-correction of errors caused by the varying color temperature,which significantly improves the accuracy of the predicted strain.A smart glove mechanoluminescent sensor system demonstrates the great potential of the AIFWMLS system in human gesture recognition.Moreover,the versatile SFLC film can also serve as a encryption device.The integration of deep learning neural network-based artificial intelligence and SFLC film provides a promising strategy to break the“color to strain value”bottleneck that hinders the practical application of flexible colorimetric strain sensors,which could promote the development of wearable and flexible strain sensors from laboratory research to consumer markets.

Bioinspired Ultrasensitive Flexible Strain Sensors for Real‑Time Wireless Detection of Liquid Leakage

Liquid leakage of pipeline networks not only results in considerableresource wastage but also leads to environmental pollution and ecological imbalance.In response to this global issue, a bioinspired superhydrophobic thermoplastic polyurethane/carbon nanotubes/graphene nanosheets flexible strain sensor (TCGS) hasbeen developed using a combination of micro-extrusion compression molding andsurface modification for real-time wireless detection of liquid leakage. The TCGSutilizes the synergistic effects of Archimedean spiral crack arrays and micropores,which are inspired by the remarkable sensory capabilities of scorpions. This designachieves a sensitivity of 218.13 at a strain of 2%, which is an increase of 4300%. Additionally, it demonstrates exceptional durability bywithstanding over 5000 usage cycles. The robust superhydrophobicity of the TCGS significantly enhances sensitivity and stability indetecting small-scale liquid leakage, enabling precise monitoring of liquid leakage across a wide range of sizes, velocities, and compositionswhile issuing prompt alerts. This provides critical early warnings for both industrial pipelines and potential liquid leakage scenariosin everyday life. The development and utilization of bioinspired ultrasensitive flexible strain sensors offer an innovative and effectivesolution for the early wireless detection of liquid leakage.

Flexible Strain Sensors with Ultra‑High Sensitivity and Wide Range Enabled by Crack‑Modulated Electrical Pathways

This study presents a breakthrough in flexible strain sensor technology with the development of an ultrahigh sensitivity and wide-range sensor,addressing the critical challenge of reconciling sensitivity with measurement range.Inspired by the structure of bamboo slips,we introduce a novel approach that utilises liquid metal to modulate the electrical pathways within a cracked platinum fabric electrode.The resulting sensor demonstrates a gauge factor greater than 108 and a strain measurement capability exceeding 100%.The integration of patterned liquid metal enables customisable tuning of the sensor’s response,while the porous fabric structure ensures superior comfort and air permeability for the wearer.Our design not only optimises the sensor’s performance but also enhances the electrical stability that is essential for practical applications.Through systematic investigation,we reveal the intrinsic mechanisms governing the sensor’s response,offering valuable insights for the design of wearable strain sensors.The sensor’s exceptional performance across a spectrum of applications,from micro-strain to large-strain detection,highlights its potential for a wide range of real-world uses,demonstrating a significant advancement in the field of flexible electronics.

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.

A smart finger patch with coupled magnetoelastic and resistive bending sensors

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.

Recent progress on artificial intelligence-enhanced multimodal sensors integrated devices and systems

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.

Advancements in implantable temperature sensors:Materials,mechanisms,and biological applications

Implantable temperature sensors are revolutionizing physiological monitoring and playing a crucial role in diagnostics,therapeutics,and life sciences research.This review classifies the materials used in these sensors into three categories:metal-based,inorganic semiconductor,and organic semiconductor materials.Metal-based materials are widely used in medical and industrial applications due to their linearity,stability,and reliability.Inorganic semiconductors provide rapid response times and high miniaturization potential,making them promising for biomedical and environmental monitoring.Organic semiconductors offer high sensitivity and ease of processing,enabling the development of flexible and stretchable sensors.This review analyzes recent studies for each material type,covering design principles,performance characteristics,and applications,highlighting key advantages and challenges regarding miniaturization,sensitivity,response time,and biocompatibility.Furthermore,critical performance parameters of implantable temperature sensors based on different material types are summarized,providing valuable references for future sensor design and optimization.The future development of implantable temperature sensors is discussed,focusing on improving biocompatibility,long-term stability,and multifunctional integration.These advancements are expected to expand the application potential of implantable sensors in telemedicine and dynamic physiological monitoring.

Recent progress in flexible sensors based on 2D materials

With the rapid development of the internet of things(IoT)and wearable electronics,the role of flexible sensors is becoming increasingly irreplaceable,due to their ability to process and convert information acquisition.Two-dimensional(2D)materials have been widely welcomed by researchers as sensitive layers,which broadens the range and application of flexible sensors due to the advantages of their large specific surface area,tunable energy bands,controllable thickness at the atomic level,stable mechanical properties,and excellent optoelectronic properties.This review focuses on five different types of 2D materials for monitoring pressure,humidity,sound,gas,and so on,to realize the recognition and conversion of human body and environmental signals.Meanwhile,the main problems and possible solutions of flexible sensors based on 2D materials as sensitive layers are summarized.

Design strategies and insights of flexible infrared optoelectronic sensors

Infrared optoelectronic sensing is the core of many critical applications such as night vision,health and medication,military,space exploration,etc.Further including mechanical flexibility as a new dimension enables novel features of adaptability and conformability,promising for developing next-generation optoelectronic sensory applications toward reduced size,weight,price,power consumption,and enhanced performance(SWaP^(3)).However,in this emerging research frontier,challenges persist in simultaneously achieving high infrared response and good mechanical deformability in devices and integrated systems.Therefore,we perform a comprehensive review of the design strategies and insights of flexible infrared optoelectronic sensors,including the fundamentals of infrared photodetectors,selection of materials and device architectures,fabrication techniques and design strategies,and the discussion of architectural and functional integration towards applications in wearable optoelectronics and advanced image sensing.Finally,this article offers insights into future directions to practically realize the ultra-high performance and smart sensors enabled by infrared-sensitive materials,covering challenges in materials development and device micro-/nanofabrication.Benchmarks for scaling these techniques across fabrication,performance,and integration are presented,alongside perspectives on potential applications in medication and health,biomimetic vision,and neuromorphic sensory systems,etc.

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.

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.

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.

Recent progress on nanomaterial-based electrochemical dissolved oxygen sensors

Dissolved oxygen(DO)usually refers to the amount of oxygen dissolved in water.In the environment,medicine,and fermentation industries,the DO level needs to be accurate and capable of online monitoring to guide the precise control of water quality,clinical treatment,and microbial metabolism.Compared with other analytical methods,the electrochemical strategy is superior in its fast response,low cost,high sensitivity,and portable device.However,an electrochemical DO sensor faces a trade-off between sensitivity and long-term stability,which strongly limits its practical applications.To solve this problem,various advanced nanomaterials have been proposed to promote detection performance owing to their excellent electrocatalysis,conductivity,and chemical stability.Therefore,in this review,we focus on the recent progress of advanced nanomaterial-based electrochemical DO sensors.Through the comparison of the working principles on the main analysis techniques toward DO,the advantages of the electrochemical method are discussed.Emphasis is placed on recently developed nanomaterials that exhibit special characteristics,including nanostructures and preparation routes,to benefit DO determination.Specifically,we also introduce some interesting research on the configuration design of the electrode and device,which is rarely introduced.Then,the different requirements of the electrochemical DO sensors in different application fields are included to provide brief guidance on the selection of appropriate nanomaterials.Finally,the main challenges are evaluated to propose future development prospects and detection strategies for nanomaterial-based electrochemical sensors.

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.

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.

Characteristic Study of Self-Powered Sensors Based on Native Protein Composite Film

Flexible electronic sensors composed of flexible film and conductive materials play an increasingly important role in wearable and internet information transmission.It has received more and more attention and made some progress over the decades.However,it is still a great challenge to prepare biocompatible and highly transparent conductive films.Egg white is a pure natural protein-rich material.Hydroxypropylmethyl cellulose has a good compatibility and high transparency,which is an ideal material for flexible sensors.Here,we overcome the problem of poor mechanical flexibility and electrical conductivity of protein,and develop a high transparency and good flexibility hydroxypropylmethyl cellulose/egg white protein composite membrane-based triboelectric nanogenerator('X'-TENG).The experimental results show that the flexible pressure sensor based on'X'-TENG has a high sensitivity,fast response speed,and low detection limit.It can even be used as a touch/pressure sensing artificial electronic skin.It can also be made into an intelligent waffle keyboard for recording and tracking users of the keyboard.Our strategy may provide a new way to easily build flexible electronic sensors and move toward practical applications.

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.