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.

Robust,Breathable and Flexible Smart Textiles as Multifunctional Sensor and Heater for Personal Health Management

Smart textiles with high sensitivity and rapid response for various external stimuli have gained tremendous attentions in human healthcare monitoring,personal heat management,and wearable electronics.However,the current smart textiles only acquire desired signal passively,regularly lacking subsequent on-demand therapy actively.Herein,a robust,breathable,and flexible smart textiles as multi-function sensor and wearable heater for human health monitoring and gentle thermotherapy in real time is constructed.The composite fiber as strain sensor(CFY@PU)was fabricated via warping carbon fiber yarns(CFY)onto polyurethane fibers(PU),which endowed composite fiber with high conductivity,excellent sensitivity(GF=76.2),and fantastic dynamic durability(7500 cycles)in strain sensing.In addition,CFY@PU can detect various degrees of human movements such as elbow bending,swallowing and pulse,which can provide effective information for disease diagnosis.More surprisingly,weaving CFY@PU into a fabric can assemble highly sensitive pressure sensor for remote communication and information encryption.Warping CFY onto Kevlar would obtain temperature-sensitive composite fiber(CFY@Kevlar)as temperature sensor and wearable heater for on-demand thermotherapy,which provided unique opportunities in designing smart textiles with ultrahigh sensitivity,rapid response,and great dynamic durability.

Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm

Least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.

Foldable-circuit-enabled miniaturized multifunctional sensor for smart digital dust

Smart dust,which refers to miniaturized,multifunctional sensor motes,would open up data acquisition opportunities for Internet of Things(IoT)and Environmental protection applications.However,critical obstacles remain challenging in the integration of high-density sensors,further miniaturization of device platforms,and reduction of cost.Here,we demonstrate the concept of smart digital dust to address these problems,the results of which combine the benefit of(i)maturity of complementary metal-oxide semiconductor(CMOS)processing approaches and(ii)unique form factors of emerging flex-ible electronics.As a prototype for smart digital dust,we present a millimeter-scale multifunctional optoelectronic sensor platform con-sisting of high-performance optoelectronic sensor cores and commer-cially available integrated-circuit components.The smart material-assisted optoelectronic sensing mechanism enables real-time,high-sensitivity hydrogen,temperature,and relative humidity(RH)sens-ing based on a single chip with ultralow power consumption.Such a microsystem presented here introduces a viable solution to the multi-functional sensing need of IoT and could serve as a building block for the rapidly evolving future framework of smart dust.

An All‑In‑One Multifunctional Touch Sensor with Carbon‑Based Gradient Resistance Elements

Human–machine interactions using deep-learning methods are important in the research of virtual reality,augmented reality,and metaverse.Such research remains challenging as current interactive sensing interfaces for single-point or multipoint touch input are trapped by massive crossover electrodes,signal crosstalk,propagation delay,and demanding configuration requirements.Here,an all-inone multipoint touch sensor(AIOM touch sensor)with only two electrodes is reported.The AIOM touch sensor is efficiently constructed by gradient resistance elements,which can highly adapt to diverse application-dependent configurations.Combined with deep learning method,the AIOM touch sensor can be utilized to recognize,learn,and memorize human–machine interactions.A biometric verification system is built based on the AIOM touch sensor,which achieves a high identification accuracy of over 98%and offers a promising hybrid cyber security against password leaking.Diversiform human–machine interactions,including freely playing piano music and programmatically controlling a drone,demonstrate the high stability,rapid response time,and excellent spatiotemporally dynamic resolution of the AIOM touch sensor,which will promote significant development of interactive sensing interfaces between fingertips and virtual objects.

Transparent,Ultra-Stretching,Tough,Adhesive Carboxyethyl Chitin/Polyacrylamide Hydrogel Toward High-Performance Soft Electronics

To date,hydrogels have gained increasing attentions as a flexible conductive material in fabricating soft electronics.However,it remains a big challenge to integrate multiple functions into one gel that can be used widely under various conditions.Herein,a kind of multifunc-tional hydrogel with a combination of desirable characteristics,including remarkable transparency,high conductivity,ultra-stretchability,tough-ness,good fatigue resistance,and strong adhesive ability is presented,which was facilely fabricated through multiple noncovalent crosslinking strategy.The resultant versatile sensors are able to detect both weak and large deformations,which owns a low detection limit of 0.1%strain,high stretchability up to 1586%,ultrahigh sensitivity with a gauge factor up to 18.54,as well as wide pressure sensing range(0-600 kPa).Meanwhile,the fabrication of conductive hydrogel-based sensors is demonstrated for various soft electronic devices,including a flexible human-machine interactive system,the soft tactile switch,an integrated electronic skin for unprecedented nonplanar visualized pressure sensing,and the stretchable triboelectric nanogenerators with excellent biomechanical energy harvesting ability.This work opens up a simple route for multifunctional hydrogel and promises the practical application of soft and self-powered wearable electronics in various complex scenes.

A machine learning-assisted multifunctional tactile sensor for smart prosthetics

The absence of tactile perception limits the dexterity of a prosthetic hand and its acceptance by amputees.Recreating the sensing properties of the skin using a flexible tactile sensor could have profound implications for prosthetics,whereas existing tactile sensors often have limited functionality with cross-interference.In this study,we propose a machine-learning-assisted multifunctional tactile sensor for smart prosthetics,providing a human-like tactile sensing approach for amputations.This flexible sensor is based on a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)-melamine sponge,which enables the detection of force and temperature with low cross-coupling owing to two separate sensing mechanisms:the open-circuit voltage of the sensor as a force-insensitive intrinsic variable to measure the absolute temperature and the resistance as a temperature-insensitive extrinsic variable to measure force.Furthermore,by analyzing the unsteady heat conduction and characterizing it using real-time thermal imaging,we demonstrated that the process of open-circuit voltage variation resulting from the unsteady heat conduction is closely correlated with the heatconducting capabilities of materials,which can be utilized to discriminate between substances.Assisted by the decision tree algorithm,the device is endowed with thermal conductivity sensing ability,which allows it to identify 10 types of substances with an accuracy of 94.7%.Furthermore,an individual wearing an advanced myoelectric prosthesis equipped with the above sensor can sense pressure,temperature,and recognize different materials.We demonstrated that our multifunctional tactile sensor provides a new strategy to help amputees feel force,temperature and identify the material of objects without the aid of vision.

One-step growth of large-area silicon nanowire fabrics for high-performance multifunctional wearable sensors

Silicon nanowire(SiNW)fabrics are of great interest for fabricating high-performance multifunctional wearable sensors.However,it remains a big challenge to fabricate high-quality SiNW fabrics in a simple and efficient manner.Here we report,for the first time,one-step growth of large-area SiNW fabrics for multifunctional wearable sensors,by using a massive metal-assisted chemical vapor deposition(CVD)method.With bulk Sn as a catalyst source,numerous millimeter-long SiNWs grow and naturally interweave with each other,forming SiNw fabrics over 80 cm2 in one experiment.In addition to intrinsic electronic properties of Si materials,the SiNw fabrics also feature high flxibility,good tailorability and light weight,rendering them ideal for fabricating multifunctional wearable sensors.The prototype sensors based on the SiNW fabrics could efectively detect various stimuli including temperature,light,strain and pressure,with outstanding performance among reported multifunctional sensors.We further demonstrate the integration of the prototype sensors onto the body of a robot,enabling its perception to various environmental stimuli.The ability to prepare high-quality SiNW fabrics in a simple and eficient manner will stimulate the development of wearable devices for applications in portable electronics,Internet of Things,health care and robotics.

A waterproof and breathable Cotton/rGO/CNT composite for constructing a layer-by-layer structured multifunctional flexible sensor

Developing a cotton fabric sensing layer with good waterproofness and breathability via a low-cost and eco-friendly method is increasingly important for the construction of comfortable and wearable electronic devices.Herein,a waterproof and breathable cotton fabric composite decorated by reduced graphene oxide(rGO)and carbon nanotube(CNT),Cotton/rGO/CNT,is reported by a facile solution infiltration method,and we adopt such Cotton/rGO/CNT composite to develop a layer-by-layer structured multifunctional flexible sensor,enabling the high-sensitivity detection of pressure and temperature stimulus.Particularly,the multifunctional flexible sensor exhibits a high response toward tiny pressure,demonstrating salient superiority in the continuous and reliable monitoring of human physiological information.Concerning temperature sensing,a good linear response for the temperatures ranging from 28 to 40℃ is achieved by the multifunctional flexible sensor and gives rise to be successfully applied to the non-contact real-time monitoring of human respiration signal.Finally,an array consisting of multifunctional flexible sensors further demonstrates its feasibility in perceiving and mapping the pressure and temperature information of contact objects.This work provides a feasible strategy for designing cotton-based sensing layers that can effectively resist liquid water penetration and allow water vapor transmission,and offers reasonable insight for constructing comfort and multifunctional wearable electronics.

Highly Durable and Fast Response Fabric Strain Sensor for Movement Monitoring Under Extreme Conditions

The exploration of smart electronic textiles is a common goal to improve people’s quality of life.However,current smart e-textiles still face challenges such as being prone to failure under humid or cold conditions,lack of washing durability and chemical fragility.Herein,a multifunctional strain sensor with a negative resistance change was developed based on the excellent elasticity of knitted fabrics.A reduced graphene oxide(rGO)conductive fabric was first obtained by electrostatic self-assembly of chitosan(CS).Then a strain sensor was prepared using a dip-coating process to adsorb nanoscale silica dioxide and poly(dimethylsiloxane)(PDMS).A broad working range of 60%,a fast response time(22 ms)and stable cycling durability over 4000 cycles were simultaneously achieved using the prepared sensor.Furthermore,the sensor showed excel-lent superhydrophobicity,photothermal effects and UV protection,as graphene,silica and PDMS acted in synergy.This multifunctional sensor could be mounted on human joints to perform tasks,including activity monitoring,medical rehabili-tation evaluation and gesture recognition,due to its superior electromechanical capabilities.Based on its multiple superior properties,this sensor could be used as winter sportswear for athletes to track their actions without being impacted by water and as a warmer to ensure the wearer's comfort.

1D-2D nanohybrid-based textile strain sensor to boost multiscale deformative motion sensing performance

The development of strain sensors with both superior sensitivity(gauge factor(GF)>100)and broad strain-sensing range(>50%strain)is still a grand challenge.Materials,which demonstrate significant structural deformation under microscale motion,are required to offer high sensitivity.Structural connection of materials upon large-scale motion is demanded to widen strainsensing range.However,it is hard to achieve both features simultaneously.Herein,we design a crepe roll structure-inspired textile yarn-based strain sensor with one-dimensional(1D)-two-dimensional(2D)nanohybrid strain-sensing sheath,which possesses superior stretchability.This ultrastretchable strain sensor exhibits a wide and stable strain-sensing range from microscale to large-scale(0.01%–125%),and superior sensitivity(GF of 139.6 and 198.8 at 0.01%and 125%,respectively)simultaneously.The strain sensor is structurally constructed by a superelastic 1D-structured core elastomer polyurethane yarn(PUY),a novel high conductive crepe roll-structured(CRS)1D-2D nanohybrid multilayer sheath which assembled by 1D nanomaterials silver nanowires(AgNWs)working as bridges to connect adjacent layers and 2D nanomaterials graphene nanoplates(GNPs)offering brittle lamellar structure,and a thin polydopamine(PDA)wrapping layer providing protection in exterior environment.During the stretching/deformation process,microcracks originate and propagate in the GNPs lamellar structure enable resistance to change significantly,while AgNWs bridge adjacent GNPs to accommodate applied stress partially and boost strain.The 1D crepe roll structure-inspired strain sensor demonstrates multifunctionality in multiscale deformative motion detection,such as respiratory motions of Sprague–Dawleyw rat,flexible digital display,and proprioception of multi-joint finger bending and antagonistic flexion/extension motions of its flexible continuum body.