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.

Double enzyme mimetic activities of multifunctional Ag nanoparticle-decorated Co_(3)V_(2)O_(8)hollow hexagonal prismatic pencils for application in colorimetric sensors and disinfection

Since the catalytic activity of most nanozymes is still far lower than the corresponding natural enzymes,there is urgent need to discover novel highly efficient enzyme-like materials.In this work,Co_(3)V_(2)O_(8)with hollow hexagonal prismatic pencil structures were prepared as novel artificial enzyme mimics.They were then decorated by photo-depositing Ag nanoparticles(Ag NPs)on the surface to further improve its catalytic activities.The Ag NPs decorated Co_(3)V_(2)O_(8)(ACVPs)showed both excellent oxidase-and peroxidase-like catalytic activities.They can oxidize the colorless 3,3’,5,5’-tetramethylbenzidine rapidly to induce a blue change.The enhanced enzyme mimetic activities can be attributed to the surface plasma resonance(SPR)effect of Ag NPs as well as the synergistic catalytic effect between Ag NPs and Co_(3)V_(2)O_(8),accelerating electron transfer and promoting the catalytic process.ACVPs were applied in constructing a colorimetric sensor,validating the occurrence of the Fenton reaction,and disinfection,presenting favorable catalytic performance.The enzyme-like catalytic mechanism was studied,indicating the chief role of⋅O_(2)-radicals in the catalytic process.This work not only discovers a novel functional material with double enzyme mimetic activity but also provides a new insight into exploiting artificial enzyme mimics with highly efficient catalytic ability.

Nanocellulose-Assisted Construction of Multifunctional MXene-Based Aerogels with Engineering Biomimetic Texture for Pressure Sensor and Compressible Electrode

Multifunctional architecture with intriguing structural design is highly desired for realizing the promising performances in wearable sensors and flexible energy storage devices.Cellulose nanofiber(CNF)is employed for assisting in building conductive,hyperelastic,and ultralight Ti_(3)C_(2)T_(x)MXene hybrid aerogels with oriented tracheid-like texture.The biomimetic hybrid aerogels are constructed by a facile bidirectional freezing strategy with CNF,carbon nanotube(CNT),and MXene based on synergistic electrostatic interaction and hydrogen bonding.Entangled CNF and CNT“mortars”bonded with MXene“bricks”of the tracheid structure produce good interfacial binding,and superior mechanical strength(up to 80%compressibility and extraordinary fatigue resistance of 1000 cycles at 50%strain).Benefiting from the biomimetic texture,CNF/CNT/MXene aerogel shows ultralow density of 7.48 mg cm^(-3)and excellent electrical conductivity(~2400 S m^(-1)).Used as pressure sensors,such aerogels exhibit appealing sensitivity performance with the linear sensitivity up to 817.3 kPa^(-1),which affords their application in monitoring body surface information and detecting human motion.Furthermore,the aerogels can also act as electrode materials of compressive solid-state supercapacitors that reveal satisfactory electrochemical performance(849.2 mF cm^(-2)at 0.8 mA cm^(-2))and superior long cycle compression performance(88%after 10,000 cycles at a compressive strain of 30%).

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.

2D multifunctional devices:from material preparation to device fabrication and neuromorphic applications

Neuromorphic computing systems,which mimic the operation of neurons and synapses in the human brain,are seen as an appealing next-generation computing method due to their strong and efficient computing abilities.Two-dimensional (2D) materials with dangling bond-free surfaces and atomic-level thicknesses have emerged as promising candidates for neuromorphic computing hardware.As a result,2D neuromorphic devices may provide an ideal platform for developing multifunctional neuromorphic applications.Here,we review the recent neuromorphic devices based on 2D material and their multifunctional applications.The synthesis and next micro–nano fabrication methods of 2D materials and their heterostructures are first introduced.The recent advances of neuromorphic 2D devices are discussed in detail using different operating principles.More importantly,we present a review of emerging multifunctional neuromorphic applications,including neuromorphic visual,auditory,tactile,and nociceptive systems based on 2D devices.In the end,we discuss the problems and methods for 2D neuromorphic device developments in the future.This paper will give insights into designing 2D neuromorphic devices and applying them to the future neuromorphic systems.

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.

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.

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.

Highly Aligned Graphene Aerogels for Multifunctional Composites

Stemming from the unique in-plane honeycomb lattice structure and the sp^(2)hybridized carbon atoms bonded by exceptionally strong carbon–carbon bonds,graphene exhibits remarkable anisotropic electrical,mechanical,and thermal properties.To maximize the utilization of graphene’s in-plane properties,pre-constructed and aligned structures,such as oriented aerogels,films,and fibers,have been designed.The unique combination of aligned structure,high surface area,excellent electrical conductivity,mechanical stability,thermal conductivity,and porous nature of highly aligned graphene aerogels allows for tailored and enhanced performance in specific directions,enabling advancements in diverse fields.This review provides a comprehensive overview of recent advances in highly aligned graphene aerogels and their composites.It highlights the fabrication methods of aligned graphene aerogels and the optimization of alignment which can be estimated both qualitatively and quantitatively.The oriented scaffolds endow graphene aerogels and their composites with anisotropic properties,showing enhanced electrical,mechanical,and thermal properties along the alignment at the sacrifice of the perpendicular direction.This review showcases remarkable properties and applications of aligned graphene aerogels and their composites,such as their suitability for electronics,environmental applications,thermal management,and energy storage.Challenges and potential opportunities are proposed to offer new insights into prospects of this material.

Enhancing multifunctional photocatalysis with acetate-assisted cesium doping and unlocking the potential of Z-scheme solar water splitting

Graphitic carbon nitride(g-C_(3)N_(4))has been extensively doped with alkali metals to enlarge photocatalytic output,in which cesium(Cs)doping is predicted to be the most efficient.Nevertheless,the sluggish diffusion and doping kinetics of precursors with high melting points,along with imprecise regulation,have raised the debate on whether Cs doping could make sense.For this matter,we attempt to confirm the positive effects of Cs doping on multifunctional photocatalysis by first using cesium acetate with the character of easy manipulation.The optimized Csdoped g-C_(3)N_(4)(CCN)shows a 41.6-fold increase in visible-light-driven hydrogen evolution reaction(HER)compared to pure g-C_(3)N_(4) and impressive degradation capability,especially with 77%refractory tetracycline and almost 100%rhodamine B degradedwithin an hour.The penetration ofCs+is demonstrated to be a mode of interlayer doping,and Cs–N bonds(especially with sp^(2) pyridine N in C═N–C),along with robust chemical interaction and electron exchange,are fabricated.This atomic configuration triggers the broadened spectral response,the improved charge migration,and the activated photocatalytic capacity.Furthermore,we evaluate the CCN/cadmium sulfide hybrid as a Z-scheme configuration,promoting the visible HER yield to 9.02 mmol g^(−1) h^(−1),which is the highest ever reported among all CCN systems.This work adds to the rapidly expanding field of manipulation strategies and supports further development of mediating served for photocatalysis.

Converting an O-vacancy-rich oxide into a multifunctional separator modifier for long-lifespan lithium metal batteries

The lithium metal anode is hailed as the desired "holy grail" for the forthcoming generation of highenergy-density batteries,given its astounding theoretical capacity and low potential.Nonetheless,the formation and growth of dendrites seriously compromise battery life and safety.Herein,an yttriastabilized bismuth oxide(YSB) layer is fabricated on the polypropylene(PP) separator,where YSB reacts with Li anode in-situ in the cell to form a multi-component composite interlayer consisting of Li_(3)Bi,Li_(2)O,and Y_(2)O_(3).The interlayer can function not only as a redistributor to regulate Li^(+) distribution but also as an anion adsorber to increase the Li^(+) transference number from 0.37 to 0.79 for suppressing dendrite nucleation and growth.Consequently,compared with the cell with a baseline separator,those with modified separators exhibit prolonged lifespan in both Li/Li symmetrical cells and Li/Cu half-cells.Notably,the full cells coupled with ultrahigh-loading LiFePO_(4) display an excellent cycling performance of 1700 cycles with a high capacity retention of ~80% at 1 C,exhibiting great potential for practical applications.This work provides a feasible and effective new strategy for separator modification towards building a much-anticipated dendrite-free Li anode and realizing long-lifespan lithium metal batteries.

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.

Multifunctional phase change film with high recyclability, adjustable thermal responsiveness, and intrinsic self-healing ability for thermal energy storage

Phase change materials(PCMs) present promising potential for guaranteeing safety in thermal management systems.However,most reported PCMs have a single application in energy storage for thermal management systems,which does not meet the growing demand for multi-functional materials.In this paper,the flexible material and hydrogen-bonding function are innovatively combined to design and prepare a novel multi-functional flexible phase change film(PPL).The 0.2PPL-2 film exhibits solid-solid phase change behavior with energy storage density of 131.8 J/g at the transition temperature of42.1℃,thermal cycling stability(500 cycles),wide-temperature range flexibility(0-60℃) and selfhealing property.Notably,the PPL film can be recycled up to 98.5% by intrinsic remodeling.Moreover,the PPL film can be tailored to the desired colors and configurations and can be cleverly assembled on several thermal management systems at ambient temperature through its flexibility combined with shape-memory properties.More interestingly,the transmittance of PPL will be altered when the ambient temperature changes(60℃),conveying a clear thermal signal.Finally,the thermal energy storage performance of the PPL film is successfully tested by human thermotherapy and electronic device temperature control experiments.The proposed functional integration strategy provides innovative ideas to design PCMs for multifunctionality,and makes significant contributions in green chemistry,highefficiency thermal management,and energy sustainability.

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.

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

Ecosystem service multifunctionality of mixed conifer-broad-leaved forests under climate change and forest management based on matrix growth modelling

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality.However,the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear,especially for natural mixed forests.In this study,our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data.We evaluated the effects of seven management scenarios(combinations of various cutting methods and intensities)on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China,under four climate scenarios(SSP1-2.6,SSP2-4.5,SSP5-8.5,and constant climate).Provisioning,regulating,cultural,and supporting services were described by timber production,carbon storage,carbon sequestration,tree species diversity,deadwood volume,and the number of large living trees.Our findings indicated that timber production was significantly influenced by management scenarios,while tree species diversity,deadwood volume,and large living trees were impacted by both climate and management separately.Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management.These findings emphasized the profound impact of forest management on ecosystem services,outweighing that of climate scenarios alone.We found no single management scenario maximized all six ecosystem service indicators.The upper story thinning by 5%intensity with 5-year interval(UST5)management strategy emerged with the highest multifunctionality,surpassing the lowest values by more than 20%across all climate scenarios.In conclusion,our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context.Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.

Tailored multifunctional hydrazine derivatives for efficient printable hole-conductive-free mesoscopic perovskite solar cells via enhancing defect passivation

The low-cost and easy large-scale fabrication advantages of printable mesoscopic perovskite solar cells(p-MPSCs)are overshadowed by their limited photovoltaic conversion efficiency(PCE).Here,we introduce the hydrazide derivative of 4-Hydroxybenzoylhydrazine(4-HBH)to improve the PCE of p-MPSCs by inducing enhanced defect passivation.Both carbonyl and hydrazine groups in hydrazide groups present strong interaction with perovskite.The hydroxyl group,as an electron donor group,increases the electron cloud density of the hydrazide group in 4-HBH under the conjugation of the benzene ring,and thus enhances its interaction with perovskite.Additionally,the hydroxy group itself interacts with perovskite and passivates defects synergistically.The hydrazine agents can also reduce I2and suppress the loss of iodine in perovskite films,which inhibits the formation of iodine-related defects.Consequently,p-MPSCs with 4-HBH achieve a high PCE of 19.21%,and present well improved stability.

Advances of Electrochemical and Electrochemiluminescent Sensors Based on Covalent Organic Frameworks

Covalent organic frameworks(COFs),a rapidly developing category of crystalline conjugated organic polymers,possess highly ordered structures,large specific surface areas,stable chemical properties,and tunable pore microenvironments.Since the first report of boroxine/boronate ester-linked COFs in 2005,COFs have rapidly gained popularity,showing important application prospects in various fields,such as sensing,catalysis,separation,and energy storage.Among them,COFs-based electrochemical(EC)sensors with upgraded analytical performance are arousing extensive interest.In this review,therefore,we summarize the basic properties and the general synthesis methods of COFs used in the field of electroanalytical chemistry,with special emphasis on their usages in the fabrication of chemical sensors,ions sensors,immunosensors,and aptasensors.Notably,the emerged COFs in the electrochemiluminescence(ECL)realm are thoroughly covered along with their preliminary applications.Additionally,final conclusions on state-of-the-art COFs are provided in terms of EC and ECL sensors,as well as challenges and prospects for extending and improving the research and applications of COFs in electroanalytical chemistry.