Direct 3D Printing of Highly Anisotropic, Flexible, Constriction-Resistive Sensors for Multidirectional Proprioception in Soft Robots

Superflexible Carbon Nanofibers for Multidimensional Complex Deformation Sensing in Soft Robots

Soft robots can make complex motions or deformations due to their infinite freedom, which poses great challenges for monitoring their motion and position. While previous investigations of flexible sensing either focused on stretchable or compression deformations in one or two directions, the complex multidimensional deformations that occur on the surfaces of soft robots have been frequently overlooked. In this work, inspired by spider silk, superflexible carbon nanofibers with a bundled structure were biomimetically designed and fabricated using electrospinning technology and carbonization treatment. The fabricated fibers can be microscopically folded at 180° and can sustain multidimensional shrinkage deformation without microstructural damage during 200,000 times of repeated folding. In addition, the fibers process ultrasmall bending resistance that is two orders of magnitude lower than that of A4 paper and commercial conductive fibers, demonstrating excellent flexibility that is ideal for fabricating sensors in soft robots. Combining the study of origami techniques and mechanical simulations, the bending resistance of the fibers was found to have a step change in response to different deformation angles and radii. As a demonstration, a sensor based on this flexible carbon nanofiber successfully monitors the irregular shrinkage deformation of soft parts, showing great potential in applications of grasping, recognition, and perception. This work sheds light on the design of ultraflexible conductive carbon materials and provides an avenue for the extreme shape-morphing monitoring of soft robots.

Characterization of the Anisotropic Electrical Properties of Additively Manufactured Structures Made from Electrically Conductive Composites by Material Extrusion

Additive manufacturing (AM) of components using material extrusion (MEX) offers the potential for the integration of functions through the use of multi-material design, such as sensors, actuators, energy storage, and electrical connections. However, there is a significant gap in the availability of electrical composite properties, which is essential for informed design of electrical functional structures in the product development process. This study addresses this gap by systematically evaluating the resistivity (DC, direct current) of 14 commercially available filaments as unprocessed filament feedstock, extruded fibers, and fabricated MEX-structures. The analysis of the MEX-structures considers the influence of anisotropic electrical properties induced by the selective material deposition inherent to MEX. The results demonstrate that composites containing fillers with a high aspect ratio, such as carbon nanotubes (CNT) and graphene, significantly enhance conductivity and improve the reproducibility of MEX structures. Notably, the extrusion of filaments into MEX structures generally leads to an increase in resistivity; however, composites with CNT or graphene exhibit less reduction in conductivity and lower variability compared to those containing only carbon black (CB) or graphite. These findings underscore the importance of filler selection and composition in optimizing the electrical performance of MEX structures.

High-Performance Stretchable Strain Sensors Based on Auxetic Fabrics for Human Motion Detection

Wearable strain sensors play a pivotal role in real-time human motion detection and health monitoring. Traditional fabric-based strain sensors, typically with a positive Poisson's ratio, face challenges in maintaining sensitivity and comfort during human motion due to conflicting resistance changes in different strain directions. In this work, high-performance stretchable strain sensors are developed based on graphene-modified auxetic fabrics (GMAF) for human motion detection in smart wearable devices. The proposed GMAF sensors, with a negative Poisson's ratio achieved through commercially available warp-knitting technology, exhibit an 8-fold improvement in sensitivity compared to conventional plain fabric sensors. The unique auxetic fabric structure enhances sensitivity by synchronizing resistance changes in both wale and course directions. The GMAF sensors demonstrate excellent washability, showing only slight degradation in auxeticity and an acceptable increase in resistance after 10 standard wash cycles. The GMAF sensors maintain stability under different strain levels and various motion frequencies, emphasizing their dynamic performance. The sensors exhibit superior conformability to joint movements, which effectively monitor a full range of motions, including joint bending, sports activities, and subtle actions like coughing and swallowing. The research underscores a promising approach to achieve industrial-scale production of wearable sensors with improved performance and comfort through fabric structure design.

3D Printing-Induced Hierarchically Aligned Nanocomposites With Exceptional Multidirectional Strain Sensing Performance

High-performance sensors capable of detecting multidirectional strains are indispensable to understand the complex motions involved in flexible electronics. Conventional isotropic strain sensors can only measure uniaxial deformations or single stimuli, hindering their practical application fields. The answer to such challenge resides in the construction of engineered anisotropic sensing structures. Herein, a hierarchically aligned carbon nanofiber (CNF)/polydimethylsiloxane nanocomposite strain sensor is developed by one-step 3D printing. The precisely controlled printing path and shear flow bring about highly aligned nanocomposite filaments at macroscale and orientated CNF network within each filament at microscale. The periodically orientated nanocomposite filaments along with the inner aligned CNF network successfully control the strain distribution and the appearance of microcracks, giving rise to anisotropic structural response to external deformations. The synergetic effect of the multiscale structural design leads to distinguishable gauge factors of 164 and 0.5 for applied loadings along and transverse to the alignment direction, leading to an exceptional selectivity of 3.77. The real-world applications of the hierarchically aligned sensors in multiaxial movement detector and posture-correction device are further demonstrated. The above findings propose new ideas for manufacturing nanocomposites with engineered anisotropic structure and properties, verifying promising applications in emerging wearable electronics and soft robotics.

Additively Manufactured Flexible Liquid Metal-Coated Self-Powered Magnetoelectric Sensors with High Design Freedom

Although additive manufacturing enables controllable structural design and customized performance for magnetoelectric sensors, their design and fabrication still require careful matching of the size and modulus between the magnetic and conductive components. Achieving magnetoelectric integration remains challenging, and the rigid coils limit the flexibility of the sensors. To overcome these obstacles, this study proposes a composite process combining selective laser sintering (SLS) and 3D transfer printing for fabricating flexible liquid metal-coated magnetoelectric sensors. The liquid metal forms a conformal conductive network on the SLS-printed magnetic lattice structure. Deformation of the structure alters the magnetic flux passing through it, thereby generating voltage. A reverse model segmentation and summation method is established to calculate the theoretical magnetic flux. The impact of the volume fraction, unit size, and height of the sensors on the voltage is studied, and optimization of these factors yields a maximum voltage of 45.6 µV. The sensor has excellent sensing performance with a sensitivity of 10.9 kPa-1 and a minimum detection pressure of 0.1 kPa. The voltage can be generated through various external forces. This work presents a significant advancement in fabricating liquid metal-based magnetoelectric sensors by improving their structural flexibility, magnetoelectric integration, and design freedom.

High-Performance Multidirectional Flexible Strain Sensor for Human Motion and Health Monitoring

Multidirectional strain sensors are pivotal for wearable electronic devices and human-computer interaction. In this investigation, we translocate carbon/graphene (CB/Gr) conductive nanocomposites onto an Ecoflex flexible substrate via a facile technique encompassing reverse molding and spraying, culminating in the fabrication of a 45° strain rosette-shaped multidirectional flexible strain sensor. The sensor distinguishes itself with extraordinary performance characteristics, including high sensitivity (boasting a gauge factor of 35), an extensive strain range from 0 to 100%, exceptional linearity, a rapid response time of merely 200 ms, remarkable stability, and outstanding durability, effortlessly withstanding over 5000 stretch-release cycles. The sensor exhibits its exceptional capability to discern intricate movements, particularly in detecting human hand and neck motions. The sensor's remarkable comprehensive performance and strain direction recognition ability underscore its significant potential for diverse applications, notably in human-computer interaction, human motion monitoring, and health monitoring.

Hand-held all-in-one (HAO) self-test kit for rapid and on-site detection of SARS-CoV-2 with colorimetric LAMP

Throughout the COVID-19 pandemic, individuals potentially infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were forcibly recalled to local or central hospitals, where the diagnostic results were obtained a couple of days after the liquid biopsies were subjected to conventional polymerase chain reaction (PCR). This slow output of such a complex and time-consuming laboratory procedure hindered its widespread application. To overcome the limitations associated with such a centralized diagnostic system, we developed a hand-held and all-in-one type test kit in which the analytical results can be obtained in only 30 min. The test kit consists of three major steps for on-site SARS-CoV-2 RNA detection: 1) virus lysis by heat, 2) RNA enrichment by membrane, and 3) real-time detection by colorimetric loop-mediated isothermal amplification (c-LAMP). The proposed device operates in a sample-to-answer format, is fully automated, and reduces dependence on traditional laboratory settings, facilitating large-scale population screening.

Anisotropic V-Groove/Wrinkle Hierarchical Arrays for Multidirectional Strain Sensors with High Sensitivity and Exceptional Selectivity

Flexible strain sensors have been continuously optimized and widely used in various fields such as health monitoring, motion detection, and human-machine interfaces. There is a higher demand for sensors that can sensitively identify both the strain amplitude and direction in real-time to adapt to complex human movements. This study proposes a flexible strain sensor construction strategy based on V-groove/wrinkle hierarchical structures via a facile and scalable prestretching approach. A gold film is sputtered on a V-groove structure soft substrate under a vertical biaxial prestrain. When the strain is released, a variety of wondrous V-groove/wrinkle hierarchical structures are formed. The microstructure and the properties of the resulting sensor can be controlled by adjusting the prestrain, which has obvious anisotropic response characteristics and exhibits high sensitivity (maximum gauge factor up to 20,727.46) and a wide sensing range (up to 51%). In addition, the resulting multidirectional sensor based on double-sided microstructures has an exceptional directional selectivity of 67.39, at an advanced level among all stretchable multidirectional strain sensors reported so far. The sensor can detect human motion signals and distinguish motion patterns, proving its great potential in the field of human motion detection and laying a foundation for high-performance wearable devices.

Materials and Structural Designs toward Motion Artifact-Free Bioelectronics

Bioelectronics encompassing electronic components and circuits for accessing human information play a vital role in real-time and continuous monitoring of biophysiological signals of electrophysiology, mechanical physiology, and electrochemical physiology. However, mechanical noise, particularly motion artifacts, poses a significant challenge in accurately detecting and analyzing target signals. While software-based "postprocessing" methods and signal filtering techniques have been widely employed, challenges such as signal distortion, major requirement of accurate models for classification, power consumption, and data delay inevitably persist. This review presents an overview of noise reduction strategies in bioelectronics, focusing on reducing motion artifacts and improving the signal-to-noise ratio through hardware-based approaches such as "preprocessing". One of the main stress-avoiding strategies is reducing elastic mechanical energies applied to bioelectronics to prevent stress-induced motion artifacts. Various approaches including strain-compliance, strain-resistance, and stress-damping techniques using unique materials and structures have been explored. Future research should optimize materials and structure designs, establish stable processes and measurement methods, and develop techniques for selectively separating and processing overlapping noises. Ultimately, these advancements will contribute to the development of more reliable and effective bioelectronics for healthcare monitoring and diagnostics.

A liquid metal/polypyrrole electrospun TPU composite conductive network for highly sensitive strain sensing in human motion monitoring

Developing soft wearable sensors with high sensitivity, low cost, and a wide monitoring range is crucial for monitoring human health. Despite advances in strain sensor technology, achieving high sensitivity and a wide operating range in a single device remains a major challenge in its design and preparation. Herein, a liquid metal (LM) is innovatively ultrasonically anchored to the gaps and surfaces of thermoplastic polyurethane (TPU) electrospun fibers, and then a conductive pathway is constructed through polypyrrole (PPy) self-polymerization to prepare a composite film. The strain sensor developed by ultrasonic anchoring and original polymerization technology shows a high strain coefficient (GF = 4.36 at 12.5% strain) and a low detection limit (less than 1% strain). Importantly, this sensor can monitor joint motion and subtle skin deformations in real time. In addition, the integration of strain sensors and N95 masks enables real-time monitoring of human respiration.

Carbon-Based Piezoresistive Polymer Nanocomposites by Extrusion Additive Manufacturing: Process, Material Design, and Current Progress

Advancement in additive manufacturing (AM) allows the production of nanocomposites with complex and custom geometries not typically allowable with conventional manufacturing techniques. The benefits of AM have led to recent interest in producing multifunctional materials capable of being printed with current AM technologies. In this article, piezoresistive composites realized by AM and the matrices and fillers utilized to make such devices are introduced and discussed. Carbon-based nanoparticles (Carbon Nanotubes, Graphene/Graphite, and Carbon Black) are often the filler choice of most researchers and are heavily discussed throughout this review in combination with extrusion AM methods. Piezoresistive applications such as physiological and wearable sensors, structural health monitoring, and soft robotics are presented with an emphasis on material and AM selection to meet the demands of such applications.

Age of Flexible Electronics: Emerging Trends in Soft Multifunctional Sensors

With the commercialization of first-generation flexible mobiles and displays in the late 2010s, humanity has stepped into the age of flexible electronics. Inevitably, soft multifunctional sensors, as essential components of next-generation flexible electronics, have attracted tremendous research interest like never before. This review is dedicated to offering an overview of the latest emerging trends in soft multifunctional sensors and their accordant future research and development (R&D) directions for the coming decade. First, key characteristics and the predominant target stimuli for soft multifunctional sensors are highlighted. Second, important selection criteria for soft multifunctional sensors are introduced. Next, emerging materials/structures and trends for soft multifunctional sensors are identified. Specifically, the future R&D directions of these sensors are envisaged based on their emerging trends, namely i) decoupling of multiple stimuli, ii) data processing, iii) skin conformability, and iv) energy sources. Finally, the challenges and potential opportunities for these sensors in future are discussed, offering new insights into prospects in the fast-emerging technology.

Three-Dimensional Printing of Hydrogels for Flexible Sensors: A Review

The remarkable flexibility and heightened sensitivity of flexible sensors have drawn significant attention, setting them apart from traditional sensor technology. Within this domain, hydrogels-3D crosslinked networks of hydrophilic polymers-emerge as a leading material for the new generation of flexible sensors, thanks to their unique material properties. These include structural versatility, which imparts traits like adhesiveness and self-healing capabilities. Traditional templating-based methods fall short of tailor-made applications in crafting flexible sensors. In contrast, 3D printing technology stands out with its superior fabrication precision, cost-effectiveness, and satisfactory production efficiency, making it a more suitable approach than templating-based strategies. This review spotlights the latest hydrogel-based flexible sensors developed through 3D printing. It begins by categorizing hydrogels and outlining various 3D-printing techniques. It then focuses on a range of flexible sensors-including those for strain, pressure, pH, temperature, and biosensors-detailing their fabrication methods and applications. Furthermore, it explores the sensing mechanisms and concludes with an analysis of existing challenges and prospects for future research breakthroughs in this field.

Assembled one-dimensional nanowires for flexible electronic devices via printing and coating: Techniques, applications, and perspectives

The rapid progress in flexible electronic devices has necessitated continual research into nanomaterials, structural design, and fabrication processes. One-dimensional nanowires, characterized by their distinct structures and exceptional properties, are considered essential components for various flexible electronic devices. Considerable attention has been directed toward the assembly of nanowires, which presents significant advantages. Printing and coating techniques can be used to assemble nanowires in a relatively simple, efficient, and cost-competitive manner and exhibit potential for scale-up production in the foreseeable future. This review aims to provide an overview of nanowire assembly using printing and coating techniques, such as bar coating, spray coating, dip coating, blade coating, 3D printing, and so forth. The application of assembled nanowires in flexible electronic devices is subsequently discussed. Finally, further discussion is presented on the potential and challenges of flexible electronic devices based on assembled nanowires via printing and coating.

Process Parameters and Geometry Effects on Piezoresistivity in Additively Manufactured Polymer Sensors

The current work experimentally determined how the initial resistance and gauge factor in additively manufactured piezoresistive sensors are affected by the material, design, and process parameters. This was achieved through the tensile testing of sensors manufactured with different infill angles, layer heights, and sensor thicknesses using two conductive polymer composites. Linear regression models were then used to analyze which of the input parameters had significant effects on the sensor properties and which interaction effects existed. The findings demonstrated that the initial resistance in both materials was strongly dependent on the sensor geometry, decreasing as the cross-sectional area was increased. The resistance was also significantly influenced by the layer height and the infill angle, with the best variants achieving a resistance that was, on average, 22.3% to 66.5% lower than less-favorable combinations, depending on the material. The gauge factor was most significantly affected by the infill angle and, depending on the material, by the layer height. Of particular interest was the finding that increasing in the infill angle resulted in an increase in the sensitivity that outweighed the associated increase in the initial resistance, thereby improving the gauge factor by 30.7% to 114.6%, depending on the material.

3D-printing-assisted flexible pressure sensor with a concentric circle pattern and high sensitivity for health monitoring

In this study, a flexible pressure sensor is fabricated using polydimethylsiloxane (PDMS) with a concentric circle pattern (CCP) obtained through a fused deposition modeling (FDM)-type three-dimensional (3D) printer and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as the active layer. Through layer-by-layer additive manufacturing, the CCP surface is generated from a thin cone model with a rough surface by the FDM-type 3D printer. A novel compression method is employed to convert the cone shape into a planar microstructure above the glass transition temperature of a polylactic acid (PLA) filament. To endow the CCP surface with conductivity, PDMS is used to replicate the compressed PLA, and PEDOT:PSS is coated by drop-casting. The size of the CCP is controlled by changing the printing layer height (PLH), which is one of the 3D printing parameters. The sensitivity increases as the PLH increases, and the pressure sensor with a 0.16 mm PLH exhibits outstanding sensitivity (160 kPa^-1), corresponding to a linear pressure range of 0-0.577 kPa with a good linearity of R ² = 0.978, compared to other PLHs. This pressure sensor exhibits stable and repeatable operation under various pressures and durability under 6.56 kPa for 4000 cycles. Finally, monitoring of various health signals such as those for the wrist pulse, swallowing, and pronunciation of words is demonstrated as an application. These results support the simple fabrication of a highly sensitive, flexible pressure sensor for human health monitoring.

Preparation of Thermoplastic Polyurethane/Multi-Walled Carbon Nanotubes Composite Foam with High Resilience Performance via Fused Filament Fabrication and CO2 Foaming Technique

Wearable flexible sensors with high sensitivity and wide detection range are applied in motion detection, medical diagnostic result and other fields, but poor resilience and hysteresis remain a challenge. In this study, a high-resilience foam sensor was prepared through a combination of additive manufacturing and green physical foaming method. The conductive filaments were prepared by using MWCNTs-modified TPU by the physical method of melt blending. Samples were prefabricated using the FFF printer and then saturated with CO2 in an autoclave before being removed and heated to foam. The composite foam effectively reduced residual strain, demonstrating the high resilience of the 3D-printed composite materials with a foam porous structure. The residual strain of the sample before foaming was >6% after a single cycle, and then gradually increased. The residual strain of the foamed samples is less than 5%. In addition, composite foam has high sensitivity and can monitor subtle pressure changes (0~40 kPa). The sensing performance of the composite foam was evaluated, and the current signal remained stable under different loading rates and small compression strains (2~5%). By using this highly resilient conductive composite material, a hierarchical shoe insole was designed that successfully detected human walking and running movements.

Ultra-sensitive, Multi-directional Flexible Strain Sensors Based on an MXene Film with Periodic Wrinkles

The fast-growing motion capturing/monitoring technique has raised a great demand for flexible strain sensors. For capturing complex motions (e.g., facial motion), both the strain amplitude and direction should be accurately detected. Although some reported sensors based on anisotropic conductive networks are proved to show accurate localization of strain directions, it is still a great challenge to achieve both high sensitivity and a high sensing range in these designs. Here, a self-assembled Ti₃C₂T_x MXene film with parallel and periodic wrinkles is fabricated on a stretchable poly(dimethylsiloxane) substrate for constructing multi-directional strain sensors. During stretching, relative slip and crack will occur between the stacked MXene nanosheets, which contribute to high structural sensitivity in the MXene film. Meanwhile, the wrinkled structure contributes to high stretchability. As a result, the sensor based on the film with one-dimensional periodic wrinkles shows a large sensing range (>50%) and a gauge factor of 45. Furthermore, the sensor can accurately detect both the strain amplitude and direction by using the MXene film with two-dimensional wrinkles. It shows distinguishable electrical responses when detecting different-amplitude human/robot motions such as joint bending and walking. Additionally, the directions in complex human motions (e.g., facial motion) can also be well-tracked. This work provides an effective strategy to detect multi-directional motions.

Recent Progress of Tactile and Force Sensors for Human-Machine Interaction

Human-Machine Interface (HMI) plays a key role in the interaction between people and machines, which allows people to easily and intuitively control the machine and immersively experience the virtual world of the meta-universe by virtual reality/augmented reality (VR/AR) technology. Currently, wearable skin-integrated tactile and force sensors are widely used in immersive human-machine interactions due to their ultra-thin, ultra-soft, conformal characteristics. In this paper, the recent progress of tactile and force sensors used in HMI are reviewed, including piezoresistive, capacitive, piezoelectric, triboelectric, and other sensors. Then, this paper discusses how to improve the performance of tactile and force sensors for HMI. Next, this paper summarizes the HMI for dexterous robotic manipulation and VR/AR applications. Finally, this paper summarizes and proposes the future development trend of HMI.

Porous AgNWs/Poly(vinylidene fluoride) Composite-Based Flexible Piezoresistive Sensor with High Sensitivity and Wide Pressure Ranges

Flexible piezoresistive sensors are highly desirable for tactile sensing and wearable electronics. However, the reported flexible piezoresistive sensors have the inherent trade-off effect between high sensitivity and wide pressure ranges. Herein, we report a flexible piezoresistive sensor with a three-dimensional (3D) porous microstructured sensing layer composed of silver nanowires (AgNWs) and a poly(vinylidene fluoride) (PVDF) matrix, exhibiting high sensitivity and wide pressure ranges. Benefiting from the conductive networks of AgNWs and the 3D porous structure of PVDF, the porous AgNWs/PVDF composite (PAPC)-based flexible piezoresistive sensor exhibits high sensitivities of 0.014 and 0.009 kPa^-1 in the wide pressure ranges of 0-30 and 30-100 kPa, respectively. In addition, the fabricated sensor also shows a fast response time of 64 ms, a low detection limit of 25 Pa, and long-term durability over 10,000 continuous cycles. The PAPC-based flexible piezoresistive sensor can accurately monitor various human physiological activities (ranging from subtle deformations to vigorous body movements) by quantitatively measuring the tactile sensation on human skin. This work indicates that the proposed sensor can be potentially applicable to mobile healthcare monitoring devices as well as next-generation wearable electronics.

Printable Carbon Nanotube-Liquid Elastomer-Based Multifunctional Adhesive Sensors for Monitoring Physiological Parameters

Developing a printed elastomeric wearable sensor with good conformity and proper adhesion to skin, coupled with the capability of monitoring various physiological parameters, is very crucial for the development of point-of-care sensing devices with high precision and sensitivity. While there have been previous reports on the fabrication of elastomeric multifunctional sensors, research on the printable elastomeric multifunctional adhesive sensor is not very well explored. Herein, we report the development of a stencil printable multifunctional adhesive sensor fabricated in a solvent-free condition, which demonstrated the capability of having good contact with skin and its ability to function as a temperature and strain sensor. Functionalized liquid isoprene rubber was selected as the matrix while carboxylated multiwalled carbon nanotubes (c-CNTs) were used as the nanofiller. The selection of the above model compounds facilitated the printability and also helped the same composition to demonstrate stretchability and adhesiveness. A realistic three-dimensional microstructure (representative volume element model) was generated through a computational framework for the current c-CNT-liquid elastomer. Further computational simulations were performed to test and validate the correlation between electrical responses to that of experimental studies. Various physiological parameters like motion sensing, pulse, respiratory rate, and phonetics detection were detected by leveraging the electrically resistive nature of the sensor. This development route can be extended toward developing different innovative adhesives for point-of-care sensing applications.

An ultrasensitive and stretchable strain sensor based on a microcrack structure for motion monitoring

Flexible strain sensors are promising candidates for intelligent wearable devices. Among previous studies, although crack-based sensors have attracted a lot of attention due to their ultrahigh sensitivity, large strain usually causes fractures in the conductive paths. Because of the unstable crack structure, the tradeoff between sensitivity and workable strain range is still a challenge. As carbon nanotubes (CNTs) and silver nanowires (AgNWs) can form a strong interface with the thermoplastic substrate and strengthen the conductive network by capillary force during water evaporation, CNTs and AgNWs were deposited on electrospun TPU fiber mats via vacuum-assisted filtration in this work. The prestretching treatment constructed a microcrack structure that endowed the sensor with the combined characteristics of a wide working range (0~171% strain), ultrahigh sensitivity (a gauge factor of 691 within 0~102% strain, ~2 × 10⁴ within 102~135% strain, and >11 × 10⁴ within 135~171% strain), a fast response time (~65 ms), small hysteresis, and superior durability (>2000 cycles). Subsequently, the sensing mechanism of the sensor was studied. Distributed microcrack propagation based on the "island-bridge" structure was explained in detail, and its influence on the strain-sensing behavior of the sensor was analyzed. Finally, the sensor was assembled to monitor various vibration signals and human motions, demonstrating its potential applications in the fields of electronic skin and human health monitoring.

Multifunctional Electronic Skins Enable Robots to Safely and Dexterously Interact with Human

Human-robot collaboration is playing more and more important roles in current deployments of robotic systems in our lives. Haptic perception and intelligent control are essential to ensure safety and efficiency of human-robot interaction. However, existing robotic sensory and control systems are deficient in terms of performance issues, complexity, and cost. Here, the authors report a multifunctional electronic skin (e-skin) incorporating multiple perceptions with intelligent robotic control, by which robots can safely and dexterously interact with humans. The e-skin with a simple and cost-effective sensory structure has multimodal perceptions of proximity, temperature, contact force, and contact position with broad measuring range, high sensitivity, and fast response. The e-skin is applied onto robots to accomplish obstacle avoidance, safe and dexterous human-robot interaction, smart teaching, and playing Tai-Chi, which demonstrate a broad range of applications for intelligent robots equipped with e-skins.

Wearable Pressure Sensors Based on MXene/Tissue Papers for Wireless Human Health Monitoring

Though the widely available, low-cost, and disposable papers have been explored in flexible paper-based pressure sensors, it is still difficult for them to simultaneously achieve ultrahigh sensitivity, low limit and broad range of detection, and high-pressure resolution. Herein, we demonstrate a novel flexible paper-based pressure sensing platform that features the MXene-coated tissue paper (MTP) sandwiched between a polyimide encapsulation layer and a printing paper with interdigital electrodes. After replacing the polyimide with weighing paper in the MTP pressure sensor, the silver interdigital electrodes can be recycled through incineration. The resulting pressure sensor with polyimide or paper encapsulation exhibits a high sensitivity of 509.5 or 344.0 kPa^-1, a low limit (∼1 Pa) and a broad range (100 kPa) of detection, and outstanding stability over 10 000 loading/unloading cycles. With ultrahigh sensitivity over a wide pressure range, the flexible pressure sensor can monitor various physiological signals and human movements. Configuring the pressure sensors into an array layout results in a smart artificial electronic skin to recognize the spatial pressure distribution. The flexible pressure sensor can also be integrated with signal processing and wireless communication modules on a face mask as a remote respiration monitoring system to wirelessly detect various respiration conditions and respiratory abnormalities for early self-identification of opioid overdose, pulmonary fibrosis, and other cardiopulmonary diseases.

Reviews on Machine Learning Approaches for Process Optimization in Noncontact Direct Ink Writing

Recently, machine learning has gained considerable attention in noncontact direct ink writing because of its novel process modeling and optimization techniques. Unlike conventional fabrication approaches, noncontact direct ink writing is an emerging 3D printing technology for directly fabricating low-cost and customized device applications. Despite possessing many advantages, the achieved electrical performance of produced microelectronics is still limited by the printing quality of the noncontact ink writing process. Therefore, there has been increasing interest in the machine learning for process optimization in the noncontact direct ink writing. Compared with traditional approaches, despite machine learning-based strategies having great potential for efficient process optimization, they are still limited to optimize a specific aspect of the printing process in the noncontact direct ink writing. Therefore, a systematic process optimization approach that integrates the advantages of state-of-the-art machine learning techniques is in demand to fully optimize the overall printing quality. In this paper, we systematically discuss the printing principles, key influencing factors, and main limitations of the noncontact direct ink writing technologies based on inkjet printing (IJP) and aerosol jet printing (AJP). The requirements for process optimization of the noncontact direct ink writing are classified into four main aspects. Then, traditional methods and the state-of-the-art machine learning-based strategies adopted in IJP and AJP for process optimization are reviewed and compared with pros and cons. Finally, to further develop a systematic machine learning approach for the process optimization, we highlight the major limitations, challenges, and future directions of the current machine learning applications.

Anisotropic conductive networks for multidimensional sensing

In the past decade, flexible physical sensors have attracted great attention due to their wide applications in many emerging areas including health-monitoring, human-machine interfaces, smart robots, and entertainment. However, conventional sensors are typically designed to respond to a specific stimulus or a deformation along only one single axis, while directional tracking and accurate monitoring of complex multi-axis stimuli is more critical in practical applications. Multidimensional sensors with distinguishable signals for simultaneous detection of complex postures and movements in multiple directions are highly demanded for the development of wearable electronics. Recently, many efforts have been devoted to the design and fabrication of multidimensional sensors that are capable of distinguishing stimuli from different directions accurately. Benefiting from their unique decoupling mechanisms, anisotropic architectures have been proved to be promising structures for multidimensional sensing. This review summarizes the present state and advances of the design and preparation strategies for fabricating multidimensional sensors based on anisotropic conducting networks. The fabrication strategies of different anisotropic structures, the working mechanism of various types of multidimensional sensing and their corresponding unique applications are presented and discussed. The potential challenges faced by multidimensional sensors are revealed to provide an insightful outlook for the future development.

Conductive Polymer Nanocomposites for Stretchable Electronics: Material Selection, Design, and Applications

Stretchable electronics that can elongate elastically as well as flex are crucial to a wide range of emerging technologies, such as wearable medical devices, electronic skin, and soft robotics. Critical to stretchable electronics is their ability to withstand large mechanical strain without failure while retaining their electrical conduction properties, a feat significantly beyond traditional metals and silicon-based semiconductors. Herein, we present a review of the recent advances in stretchable conductive polymer nanocomposites with exceptional stretchability and electrical properties, which have the potential to transform a wide range of applications, including wearable sensors for biophysical signals, stretchable conductors and electrodes, and deformable energy-harvesting and -storage devices. Critical to achieving these stretching properties are the judicious selection and hybridization of nanomaterials, novel microstructure designs, and facile fabrication processes, which are the focus of this Review. To highlight the potentials of conductive nanocomposites, a summary of some recent important applications is presented, including COVID-19 remote monitoring, connected health, electronic skin for augmented intelligence, and soft robotics. Finally, perspectives on future challenges and new research opportunities are also presented and discussed.

Highly Sensitive and Stretchable c-MWCNTs/PPy Embedded Multidirectional Strain Sensor Based on Double Elastic Fabric for Human Motion Detection

Owing to the multi-dimensional complexity of human motions, traditional uniaxial strain sensors lack the accuracy in monitoring dynamic body motions working in different directions, thus multidirectional strain sensors with excellent electromechanical performance are urgently in need. Towards this goal, in this work, a stretchable biaxial strain sensor based on double elastic fabric (DEF) was developed by incorporating carboxylic multi-walled carbon nanotubes(c-MWCNTs) and polypyrrole (PPy) into fabric through simple, scalable soaking and adsorption-oxidizing methods. The fabricated DEF/c-MWCNTs/PPy strain sensor exhibited outstanding anisotropic strain sensing performance, including relatively high sensitivity with the maximum gauge factor (GF) of 5.2, good stretchability of over 80%, fast response time < 100 ms, favorable electromechanical stability, and durability for over 800 stretching-releasing cycles. Moreover, applications of DEF/c-MWCNTs/PPy strain sensor for wearable devices were also reported, which were used for detecting human subtle motions and dynamic large-scale motions. The unconventional applications of DEF/c-MWCNTs/PPy strain sensor were also demonstrated by monitoring complex multi-degrees-of-freedom synovial joint motions of human body, such as neck and shoulder movements, suggesting that such materials showed a great potential to be applied in wearable electronics and personal healthcare monitoring.

Artificial Intelligence of Things (AIoT) Enabled Virtual Shop Applications Using Self-Powered Sensor Enhanced Soft Robotic Manipulator

Rapid advancements of artificial intelligence of things (AIoT) technology pave the way for developing a digital-twin-based remote interactive system for advanced robotic-enabled industrial automation and virtual shopping. The embedded multifunctional perception system is urged for better interaction and user experience. To realize such a system, a smart soft robotic manipulator is presented that consists of a triboelectric nanogenerator tactile (T-TENG) and length (L-TENG) sensor, as well as a poly(vinylidene fluoride) (PVDF) pyroelectric temperature sensor. With the aid of machine learning (ML) for data processing, the fusion of the T-TENG and L-TENG sensors can realize the automatic recognition of the grasped objects with the accuracy of 97.143% for 28 different shapes of objects, while the temperature distribution can also be obtained through the pyroelectric sensor. By leveraging the IoT and artificial intelligence (AI) analytics, a digital-twin-based virtual shop is successfully implemented to provide the users with real-time feedback about the details of the product. In general, by offering a more immersive experience in human-machine interactions, the proposed remote interactive system shows the great potential of being the advanced human-machine interface for the applications of the unmanned working space.

Reconfigurable Magnetic Origami Actuators with On-Board Sensing for Guided Assembly

Origami utilizes orchestrated transformation of soft 2D structures into complex 3D architectures, mimicking shapes and functions found in nature. In contrast to origami in nature, synthetic origami lacks the ability to monitor the environment and correspondingly adjust its behavior. Here, magnetic origami actuators with capabilities to sense their orientation and displacement as well as detect their own magnetization state and readiness for supervised folding are designed, fabricated, and demonstrated. These origami actuators integrate photothermal heating and magnetic actuation by using composite thin films (≈60 µm thick) of shape-memory polymers with embedded magnetic NdFeB microparticles. Mechanically compliant magnetic field sensors, known as magnetosensitive electronic skins, are laminated on the surface of the soft actuators. These ultrathin actuators accomplish sequential folding and recovery, with hinge locations programmed on the fly. Endowing mechanically active smart materials with cognition is an important step toward realizing intelligent, stimuli-responsive structures.

Modelling of Anisotropic Electrical Conduction in Layered Structures 3D-Printed with Fused Deposition Modelling

3D-printing conductive structures have recently been receiving increased attention, especially in the field of 3D-printed sensors. However, the printing processes introduce anisotropic electrical properties due to the infill and bonding conditions. Insights into the electrical conduction that results from the anisotropic electrical properties are currently limited. Therefore, this research focuses on analytically modeling the electrical conduction. The electrical properties are described as an electrical network with bulk and contact properties in and between neighbouring printed track elements or traxels. The model studies both meandering and open-ended traxels through the application of the corresponding boundary conditions. The model equations are solved as an eigenvalue problem, yielding the voltage, current density, and power dissipation density for every position in every traxel. A simplified analytical example and Finite Element Method simulations verify the model, which depict good correspondence. The main errors found are due to the limitations of the model with regards to 2D-conduction in traxels and neglecting the resistance of meandering ends. Three dimensionless numbers are introduced for the verification and analysis: the anisotropy ratio, the aspect ratio, and the number of traxels. Conductive behavior between completely isotropic and completely anisotropic can be modeled, depending on the dimensionless properties. Furthermore, this model can be used to explain the properties of certain 3D-printed sensor structures, like constriction-resistive strain sensors.

Materials, Electrical Performance, Mechanisms, Applications, and Manufacturing Approaches for Flexible Strain Sensors

With the recent great progress made in flexible and wearable electronic materials, the upcoming next generation of skin-mountable and implantable smart devices holds extensive potential applications for the lifestyle modifying, including personalized health monitoring, human-machine interfaces, soft robots, and implantable biomedical devices. As a core member within the wearable electronics family, flexible strain sensors play an essential role in the structure design and functional optimization. To further enhance the stretchability, flexibility, sensitivity, and electricity performances of the flexible strain sensors, enormous efforts have been done covering the materials design, manufacturing approaches and various applications. Thus, this review summarizes the latest advances in flexible strain sensors over recent years from the material, application, and manufacturing strategies. Firstly, the critical parameters measuring the performances of flexible strain sensors and materials development contains different flexible substrates, new nano- and hybrid- materials are introduced. Then, the developed working mechanisms, theoretical analysis, and computational simulation are presented. Next, based on different material design, diverse applications including human motion detection and health monitoring, soft robotics and human-machine interface, implantable devices, and biomedical applications are highlighted. Finally, synthesis consideration of the massive production industry of flexible strain sensors in the future; different fabrication approaches that are fully expected are classified and discussed.

Synergy of Porous Structure and Microstructure in Piezoresistive Material for High-Performance and Flexible Pressure Sensors

A porous and microstructure piezoresistive material composed of polydimethylsiloxane (PDMS) and multiwalled carbon nanotubes (MWCNTs) was designed and prepared for a flexible and highly sensitive pressure sensor over a wide detection range. The microstructure was patterned on the surface of the partially cured PDMS/MWCNTs/NaCl mixture by imprinting a nonwoven fabric. After curing and dissolving the NaCl powders, the porous and surface microstructure PDMS/MWCNT film was obtained. Two PDMS/MWCNT films were stacked together and sandwiched between two copper foil electrodes, in which the two microstructure surfaces were in contact with the electrodes. Due to the synergistic effects of the combination of the porous structure and surface microstructure, the flexible sensor had highly sensitive response over a wide pressure range from 1 Pa to 100 kPa. Under the small pressure, the high sensitivity was achieved by the change in contact areas between the electrodes and the surface microstructures; at high pressure up to 100 kPa, the sensor retained its high sensitivity because of the porous structure of the piezoresistive PDMS/MWCNT material. Additionally, the sensor had fast response speed and good durability. The piezoresistive pressure sensors based on the porous and microstructure PDMS/MWCNTs were demonstrated in detection of sound, monitoring of human activities, and array mapping of the spatial pressure distribution.

Effects of 3D Printing-Line Directions for Stretchable Sensor Performances

Health monitoring sensors that are attached to clothing are a new trend of the times, especially stretchable sensors for human motion measurements or biological markers. However, price, durability, and performance always are major problems to be addressed and three-dimensional (3D) printing combined with conductive flexible materials (thermoplastic polyurethane) can be an optimal solution. Herein, we evaluate the effects of 3D printing-line directions (45°, 90°, 180°) on the sensor performances. Using fused filament fabrication (FDM) technology, the sensors are created with different print styles for specific purposes. We also discuss some main issues of the stretch sensors from Carbon Nanotube/Thermoplastic Polyurethane (CNT/TPU) and FDM. Our sensor achieves outstanding stability (10,000 cycles) and reliability, which are verified through repeated measurements. Its capability is demonstrated in a real application when detecting finger motion by a sensor-integrated into gloves. This paper is expected to bring contribution to the development of flexible conductive materials-based on 3D printing.

Novel Resistive Sensor Design Utilizing the Geometric Freedom of Additive Manufacturing

Direct additive manufacturing (AM) of sensors has in recent years become possible, but still remains a largely unexplored area. This work proposes a novel resistive sensor design that utilizes the geometric freedom offered by AM, especially by material extrusion, to enable a customizable and amplified response to force and deformation. This is achieved by using a multi-material design made of an elastomer and an electrically conductive polymer that enables a physical shortening of the conductive path under compressive load through a specific definition of shape. A number of different variants of this novel sensor design are tested, measuring their mechanical and electrical behavior under compression. The results of these tests confirm a strong resistive response to mechanical loading. Furthermore, the results provide insight into the influencing factors of the design, i.e., the gap size between the conductive pathing and the stiffness of the sense element support structure are found to be primary influencing factors governing sensor behavior.

Shape Memory Polyurethane Microcapsules with Active Deformation

From smart self-tightening sutures and expandable stents to morphing airplane wings, shape memory structures are increasingly present in our daily life. The lack of methods for synthesizing intricate structures from them on the micron and submicron level, however, is stopping the field from developing. In particular, the methods for the synthesis of shape memory polymers (SMPs) and structures at this scale and the effect of new geometries remain unexplored. Here, we describe the synthesis of shape memory polyurethane (PU) capsules accomplished by interfacial polymerization of emulsified droplets. The emulsified droplets contain the monomers for the hard segments, while the continuous aqueous phase contains the soft segments. A trifunctional chemical cross-linker for shape memory PU synthesis was utilized to eliminate creep and improve the recovery ratios of the final capsules. We observe an anomalous dependence of the recovery ratio with the amount of programmed strain compared to previous SMPs. We develop quantitative characterization methods and theory to show that when dealing with thin-shell objects, alternative parameters to quantify recovery ratios are needed. We show that while achieving 94-99% area recovery ratios, the linear capsule recovery ratios can be as low as 70%. This quantification method allows us to convert from observed linear aspect ratios in capsules to find out unrecovered area strain and stress. The hollow structure of the capsules grants high internal volume for some applications (e.g., drug delivery), which benefit from much higher loading of active ingredients than polymeric particles. The methods we developed for capsule synthesis and programming could be easily scaled up for larger volume applications.

Wearable Temperature Sensors with Enhanced Sensitivity by Engineering Microcrack Morphology in PEDOT:PSS-PDMS Sensors

Wearable temperature sensors with high sensitivity, linearity, and flexibility are required to meet the increasing demands for unobtrusive monitoring of temperature changes indicative of the onset of infections and diseases. Herein, we present a new method for engineering highly sensitive and flexible temperature sensors made by sandwiching a poly(3,4-ethylenedioxythiophene):polystyrene (PEDOT:PSS) sensing film between two poly(dimethylsiloxane) (PDMS) substrates. Pre-stretching the sensor to a certain strain can create stable microcracks in the sensing layer that bestow high senstivity and linearity. The average length and density of the microcracks, which dictate the sensor's temperature sensitivity, can be engineered by controlling three key processing parameters, incuding (a) pre-stretching strain, (b) sulfuric acid treatment time, and (c) surface roughness of the substrate. For a given acid treatment time and surface roughness condition, the density and average length of the microcracks increase pre-stretching strain. A smooth PDMS substrate tends to yield long and straight cracks in the PEDOT:PSS film, compared to shorter microcracks with higher density on rough surfaces. Crack density can be further increased via sulfuric acid treatment with an optimum duration of approximately 3 h. Prolonged treatment would result in weak adhesion between the PEDOT:PSS film and the PDMS substrate, which in turn reduces the microcrack density but increases the crack length. By optimizing the three design parameters we have designed a high performance PEDOT:PSS-PDMS sensor that provides a combined high temperature sensitivity of 0.042 °C^-1 with an excellent linearity of 0.998 (from 30 to 55 °C), better than the highest temperature sensitivity of PEDOT:PSS based sensors reported in the literature. With a good optical transparency, high temperature sensitivity, excellent linearity, and high flexibility, this microcrack-based sensor is a very promising wearable temperature-sensing solution.