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The properties of self-healing polymers are traditionally identified through destructive testing. This means that the mechanics are explored in hindsight with either theoretical derivations and/or simulations. Here, a self-healing property evolution using energy functional dynamical (SPEED) model is proposed to predict and understand the mechanics of self-healing of polymers using images of cuts dynamically healing over time. Using machine learning, an energy functional minimization (EFM) model extracted an effective underlying dynamical system from a time series of two-dimensional cut images on a self-healing polymer of constant thickness. This model can be used to capture the physics behind the self-healing dynamics in terms of potential and interface energies. When combined with a static property prediction model, the SPEED model can predict the macroscopic evolution of material properties after training only on a small set of experimental measurements. Such temporal evolutions are usually inaccessible from pure experiments or computational modeling due to the need for destructive testing. As an example, we validate this approach on toughness measurements of an intrinsic self-healing conductive polymer by capturing over 100 000 image frames of cuts to build the machine learning (ML) model. The results show that the SPEED model can be applied to predict the temporal evolution of macroscopic properties using few measurements as training data.

This article presents a versatile soft robotic gripper system whereby its fingers can be reconfigured into different poses such as scoop, pinch, and claw. This allows the gripper to efficiently and safely handle food samples of different shapes, sizes and stiffness such as uncooked tofu and broccoli floret. The 3D-printed fingers were tested to last up to 25 000 cycles without significant changes in the curvature profile and force output profile. A benchmark experiment was conducted to evaluate the performance of the gripper and state-of-the-art gripping solutions. Capability of versatile soft gripper was optimized by integrating vision and tactile sensing facilities. An object recognition system was developed to identify food samples such as potato, broccoli, and sausage. Position and orientation of food samples were identified and pick-and-place pathway was optimized to achieve the best gripping performance. Flexible tactile sensors were integrated into soft fingers and closed-loop force feedback control system was developed. This allowed the gripper to automatically explore and select the most stable grip pose for different food samples. Integration of vision and force feedback system ensure that objects detected by the system would be firmly gripped. The reconfigurable soft robotic gripper system has been demonstrated to perform high-speed pick-and-place tasks (∼3 s per item) with object recognition system, making it a potential solution to food and grocery supply chain needs.

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative efforts, scientific breakthroughs can be made sooner and capitalized for the betterment of humanity. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) Submitted/Accepted version Y.L., Z.L., M.Z., and X.C. acknowledge the National Research Foundation, Singapore (NRF) under NRF’s Medium Sized Centre: Singapore Hybrid-Integrated Next-Generation μElectronics (SHINE) Centre funding programme, and AME programming funding scheme of Cyber Physiochemical Interface (CPI) project (no. A18A1b0045). Y.L. acknowledges National Natural Science Foundation of China (62201243). C.J. acknowledges funding support from the National Key R&D Program of China (no. 2019YFA0706100), the National Natural Science Foundation of China (82151305), Lingang Laboratory (LG-QS-202202-09). T.Q.T. and N.E.L. acknowledge support by the Basic Science Research Program (no. 2020R1A2C3013480) through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. A.F. acknowledges the AFOSR (grant FA9550-22-1-0423). Y.L. and Y.Z. would like to acknowledge the NSF (award no. 2134664) and NIH (award no. R01HD108473) for financial support. X.F. acknowledges the support from the National Natural Science Foundation of China (grant no. U20A6001). L.Y. would like to thank the A*STAR Central Research Fund (CRF) and the AME Programmatic A18A1b0045 (Cyber Physiochemical Interfaces) for funding support. C.F.G. acknowledges the National Natural Science Foundation of China (no. T2225017). T.Q.T. acknowledges the Brain Pool Program (No. 2020H1D3A2A02111068) through the National Research Foundation (NRF) funded by the Ministry of Science. Z.L. acknowledges the support from RIE2020 AME Programmatic Grant funded by A*STAR-SERC, Singapore (Grant No. A18A1b0045). X.G. acknowledges funding support through the Shanghai Science and Technology Commission (grant no. 19JC1412400), the National Science Fund for Excellent Young Scholars (grant no. 61922057). C.D. acknowledges National Science Foundation CAREER: Conformable Piezoelectrics for Soft Tissue Imaging (grant no. 2044688) and MIT Media Lab Consortium funding. D.K. and O.G.S. acknowledge Leibniz Association and the German Research Foundation DFG (Gottfried Wilhelm Leibniz Program SCHM 1298/22-1, KA5051/1-1 and KA 5051/3-1), as well as the Leibniz association (Leibniz Transfer Program T62/2019). C.W. acknowledges the National Key Research and Development Program of China (grant no. 2021YFA1202600), National Natural Science Foundation of China (grant no. 62174082). A.V.-Y.T., E.Z., Y.Z., X.Z., and J.P. acknowledge the National Research Foundation, Singapore (NRF) under NRF’s Medium Sized Centre: Singapore Hybrid-Integrated Next-Generation μElectronics (SHINE) Centre funding programme, and AME programming funding scheme of Cyber Physiochemical Interface (CPI) project (no. A18A1b0045). R.Z. acknowledges National Natural Science Foundation of China (grant no. 51735007) and Beijing Natural Science Foundation (grant no. 3191001). N.M. acknowledges the support by JST PRESTO Grant Number JPMJPR20B7 and JST Adaptable and Seamless Technology transfer Program through Target-driven R&D (ASTEP) grant number JPMJTM22BK. C.P. acknowledges the Korean government (Ministry of Science and ICT, MSIT) (2022R1A4A3032923). M.W. acknowledges the National Key R&D Program of China under Grant (2021YFB3601200). X.Z. acknowledges National Natural Science Foundation of China (no. 62074029). S.X. acknowledges the 3M nontenured faculty award. T.-W.L. and D.-G.S. acknowledge the Pioneer Research Center Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (grant no. NRF-2022M3C1A3081211). C.T.L. would like to acknowledge support from the Institute for Health Innovation and Technology (iHealthtech), the MechanoBioEngineering Laboratory at the Department of Biomedical Engineering and the Institute for Functional Intelligent Materials (I-FIM) at the National University of Singapore (NUS). C.T.L. also acknowledges support from the National Research Foundation and A*STAR, under its RIE2020 Industry Alignment Fund − Industry Collaboration Projects (IAF-ICP) (grant no. I2001E0059) − SIA-NUS Digital Aviation Corp Lab and the NUS ARTIC Research (grant no. HFM-RP1). X.Y. acknowledges funding support by City University of Hong Kong (grant no. 9667221). T.X. and X.Z. acknowledge National Natural Science Foundation of China (22234006). B.C.K.T. acknowledges Cyber-Physiochemical Interfaces CPI, A*STAR A18A1b0045. H.G. acknowledges a research start-up grant (002479-00001) from Nanyang Technological University and the Agency for Science, Technology and Research (A*STAR) in Singapore. W.G. acknowledges National Science Foundation grant 2145802. D.J.L. acknowledges support from the US National Science Foundation grant number CBET-2223566. G.Y. acknowledges support from The Welch Foundation award F-1861, and Camille Dreyfus Teacher-Scholar Award. M.D.D. acknowledges funding support from NSF (grant no. EEC1160483). J.-H.A acknowledges the National Research Foundation of Korea (NRF-2015R1A3A2066337). J.C. acknowledges the Henry Samueli School of Engineering & Applied Science and the Department of Bioengineering at the University of California, Los Angeles for startup support and a Brain & Behavior Research Foundation Young Investigator Grant. K.T. acknowledges JST AIP Accelerated Program (no. JPMJCR21U1) and JSPS KAKENHI (grant no. JP22H00594). P.S.W. acknowledges the National Science Foundation (CMMI1636136) for support. A.M.A., M.C.H., and P.S.W. thank the National Institute on Drug Abuse (DA045550) for support. S.M. and X.C. appreciated the support from the Smart Grippers for Soft Robotics (SGSR) Programme under the National Research Foundation, Prime Minister’s Office, Singapore under its Campus of Research Excellence and Technological Enterprise (CREATE) programme.

Electronic skins are essential for real-time health monitoring and tactile perception in robots. Although the use of soft elastomers and microstructures have improved the sensitivity and pressure-sensing range of tactile sensors, the intrinsic viscoelasticity of soft polymeric materials remains a long-standing challenge resulting in cyclic hysteresis. This causes sensor data variations between contact events that negatively impact the accuracy and reliability. Here, we introduce the Tactile Resistive Annularly Cracked E-Skin (TRACE) sensor to address the inherent trade-off between sensitivity and hysteresis in tactile sensors when using soft materials. We discovered that piezoresistive sensors made using an array of three-dimensional (3D) metallic annular cracks on polymeric microstructures possess high sensitivities (> 10(7) Ω ⋅ kPa(−1)), low hysteresis (2.99 ± 1.37%) over a wide pressure range (0–20 kPa), and fast response (400 Hz). We demonstrate that TRACE sensors can accurately detect and measure the pulse wave velocity (PWV) when skin mounted. Moreover, we show that these tactile sensors when arrayed enabled fast reliable one-touch surface texture classification with neuromorphic encoding and deep learning algorithms.

Skin-like sensors that transduce tactile pressures and vibrations with minimal environment variation on performance are crucial in robotic sensing and prosthetic skins. However, sensor performance ...

Poly(dimethylsiloxane) (PDMS) as one of the electron-drawing materials has been widely used in triboelectric nanogenerators (TENG), which is expected to generate electron through friction and required to endure dynamic loads. However, the nature of the siloxane bond and the low interchain interaction between the methyl side groups result in low fracture energy in PDMS elastomers. Here, a strategy that combined the advantages of the dynamic of hierarchical hydrogen bonding and phase-separation-like structure was adopted to improve the toughness of PDMS elastomers. By varying both stronger and weaker hydrogen bonding within the PDMS network, a series of super tough (up to 24,000 J/m2), notch-insensitive, transparent, and autonomous self-healable elastomers were achieved. In addition, a hydrophilic polymeric material (PDMAS-U10) was synthesized as the conductive layer. A transparent TENG was fabricated by sandwiching the PDMAS-U10 between two pieces of the PDMS elastomer. Despite its hydrophilic nature, PDMAS-U10 exhibit strong adhesion interaction with hydrophobic PDMS elastomers. As such, a tough (16,500 J/m2), self-healable (efficiency ∼97%), and transparent triboelectric nanogenerator was constructed. A self-powered system employing the TENG is also demonstrated in this work.

Mechanical properties of hydrogels are crucial to emerging devices and machines for wearables, robotics and energy harvesters. Various polymer network architectures and interactions have been explored for achieving specific mechanical characteristics, however, extreme mechanical property tuning of single-composition hydrogel material and deployment in integrated devices remain challenging. Here, we introduce a macromolecule conformational shaping strategy that enables mechanical programming of polymorphic hydrogel fiber based devices. Conformation of the single-composition polyelectrolyte macromolecule is controlled to evolve from coiling to extending states via a pH-dependent antisolvent phase separation process. The resulting structured hydrogel microfibers reveal extreme mechanical integrity, including modulus spanning four orders of magnitude, brittleness to ultrastretchability, and plasticity to anelasticity and elasticity. Our approach yields hydrogel microfibers of varied macromolecule conformations that can be built-in layered formats, enabling the translation of extraordinary, realistic hydrogel electronic applications, i.e., large strain (1000%) and ultrafast responsive (~30 ms) fiber sensors in a robotic bird, large deformations (6000%) and antifreezing helical electronic conductors, and large strain (700%) capable Janus springs energy harvesters in wearables.

Wireless networks of sensors, displays and smart devices that can be placed on a person’s body could have applications in health monitoring, medical interventions and human–machine interfaces. Such wireless body networks are, however, typically energy-inefficient and vulnerable to eavesdropping because they rely on radio-wave communications. Here, we report energy-efficient and secure wireless body sensor networks that are interconnected through radio surface plasmons propagating on metamaterial textiles. The approach uses clothing made from conductive fabrics that can support surface-plasmon-like modes at radio communication frequencies. Our body sensor networks enhance transmission efficiencies by three orders of magnitude compared to conventional radiative networks without the metamaterial textile, and confine wireless communication to within 10 cm of the body. We also show that the approach can offer wireless power transfer that is robust to motion and textile-based wireless touch sensing. Energy-efficient and secure wireless body sensor networks can be created by using conductive fabrics that support surface-plasmon-like modes at radio communication frequencies.

This work presents an area- and energy-efficient decoder for tactile e-skin sensing encoding to scale up receptor density to the human scale. A fully-digital signal-adaptive receptor interface and event decoder architecture are introduced, leveraging temporal/spatial tactile signal sparsity to dynamically reduce activity and time resolution at negligible accuracy degradation. A novel reference-less self-calibrating senseamp is introduced to cancel offset by exploiting the statistical balance of spread-spectrum tactile pulses and noise. The 40nm testchip shows 1.6-fJ/convstep energy (0.0075mm2 area) per receptor with 50X (5X) improvement over prior art, and 80-receptor e-skin aggregation on a single pad.

Power sources with good mechanical compliance are essential for various flexible and stretchable electronics. However, most of the current energy storage devices comprise of hazardous materials that may cause environmental pollution when improperly disposed. We show the first example of a stretchable, yet fully degradable battery made from nontoxic and environmentally friendly materials such as fruit‐based gel electrolytes and cellulose paper electrodes. The battery exhibits an areal capacity of 2.9 μAh cm−2 at 40 μA cm−2, corresponding to a maximum energy density around 4.0 μW h cm−2 at 56 μW cm−2 power density. The biomaterials constituted battery shows good mechanical tolerance to twisting, bending, and stretching while powering various electronic devices when combined with kirigami. Importantly, the entire battery disintegrates readily in phosphate buffered saline/cellulase solution. We integrate the “green” battery with various sensors in wearable healthcare devices for pulsation sensing and low‐noise surface electromyography applications.

Description, A wireless sensor based on bioresponsive DNA hydrogel provides smartphone-based detection of wound infection., The confluence of wireless technology and biosensors offers the possibility to detect and manage medical conditions outside of clinical settings. Wound infections represent a major clinical challenge in which timely detection is critical for effective interventions, but this is currently hindered by the lack of a monitoring technology that can interface with wounds, detect pathogenic bacteria, and wirelessly transmit data. Here, we report a flexible, wireless, and battery-free sensor that provides smartphone-based detection of wound infection using a bacteria-responsive DNA hydrogel. The engineered DNA hydrogels respond selectively to deoxyribonucleases associated with pathogenic bacteria through tunable dielectric changes, which can be wirelessly detected using near-field communication. In a mouse acute wound model, we demonstrate that the wireless sensor can detect physiologically relevant amounts of Staphylococcus aureus even before visible manifestation of infection. These results demonstrate strategies for continuous infection monitoring, which may facilitate improved management of surgical or chronic wounds.

Monitoring surgical wounds post-operatively is necessary to prevent infection, dehiscence and other complications. However, the monitoring of deep surgical sites is typically limited to indirect observations or to costly radiological investigations that often fail to detect complications before they become severe. Bioelectronic sensors could provide accurate and continuous monitoring from within the body, but the form factors of existing devices are not amenable to integration with sensitive wound tissues and to wireless data transmission. Here we show that multifilament surgical sutures functionalized with a conductive polymer and incorporating pledgets with capacitive sensors operated via radiofrequency identification can be used to monitor physicochemical states of deep surgical sites. We show in live pigs that the sutures can monitor wound integrity, gastric leakage and tissue micromotions, and in rodents that the healing outcomes are equivalent to those of medical-grade sutures. Battery-free wirelessly operated bioelectronic sutures may facilitate post-surgical monitoring in a wide range of interventions. Multifilament surgical sutures functionalized with a conductive polymer and incorporating pledgets with capacitive sensors operated via radiofrequency identification can be used to monitor physicochemical states of deep surgical sites.

Human skin is a self-healing mechanosensory system that detects various mechanical contact forces efficiently through three-dimensional innervations. Here, we propose a biomimetic artificially innervated foam by embedding three-dimensional electrodes within a new low-modulus self-healing foam material. The foam material is synthesized from a one-step self-foaming process. By tuning the concentration of conductive metal particles in the foam at near-percolation, we demonstrate that it can operate as a piezo-impedance sensor in both piezoresistive and piezocapacitive sensing modes without the need for an encapsulation layer. The sensor is sensitive to an object’s contact force directions as well as to human proximity. Moreover, the foam material self-heals autonomously with immediate function restoration despite mechanical damage. It further recovers from mechanical bifurcations with gentle heating (70 °C). We anticipate that this material will be useful as damage robust human-machine interfaces., Designing mechanosensory system that detects mechanical contact forces like human skin remains a challenge. Here, the authors present artificially innervated self-healing foams by embedding 3D electrodes for piezo-impedance sensors that can operate in both piezoresistive and piezocapacitive sensing modes to address various proximity and mechanical interactions efficiently.

Electronic skins are critical for many applications in human-machine-environment interactions. Tactile sensitivity over large areas can be especially applied to prosthetics. Moreover, the potential for wearables, interactive surfaces, and human robotics have propelled research in this area. In this Element, we provide an account and directional atlas of the progress in materials and devices for electronic skins, in the context of sensing principles and skin-like features. Additionally, we give an overview of essential electronic circuits and systems used in large-area tactile sensor arrays. Finally, we present the challenges and provide perspectives on future developments.

Robots are increasingly assisting humans in performing various tasks. Like special agents with elite skills, they can venture to distant locations and adverse environments, such as the deep sea and outer space. Micro/nanobots can also act as intrabody agents for healthcare applications. Self-healing materials that can autonomously perform repair functions are useful to address the unpredictability of the environment and the increasing drive toward the autonomous operation. Having self-healable robotic materials can potentially reduce costs, electronic wastes, and improve a robot endowed with such materials longevity. This review aims to serve as a roadmap driven by past advances and inspire future cross-disciplinary research in robotic materials and electronics. By first charting the history of self-healing materials, new avenues are provided to classify the various self-healing materials proposed over several decades. The materials and strategies for self-healing in robotics and stretchable electronics are also reviewed and discussed. It is believed that this article encourages further innovation in this exciting and emerging branch in robotics interfacing with material science and electronics.

Gelatinous underwater invertebrates such as jellyfish have organs that are transparent, stretchable, touch-sensitive and self-healing, which allow the creatures to navigate, camouflage themselves and, indeed, survive in aquatic environments. Artificial skins that emulate such functionality could be used to develop applications such as aquatic soft robots and water-resistant human–machine interfaces. Here we report a bio-inspired skin-like material that is transparent, electrically conductive and can autonomously self-heal in both dry and wet conditions. The material, which is composed of a fluorocarbon elastomer and a fluorine-rich ionic liquid, has an ionic conductivity that can be tuned to as high as 10−3 S cm−1 and can withstand strains as high as 2,000%. Owing to ion–dipole interactions, it offers fast and repeatable electro-mechanical self-healing in wet, acidic and alkali environments. To illustrate the potential applications of the approach, we used our electronic skins to create touch, pressure and strain sensors. We also show that the material can be printed into soft and pliable ionic circuit boards. A transparent electronic skin, composed of an elastomer and an ionic liquid, can autonomously self-heal in both dry and wet conditions due to ion–dipole interactions.

The present review will introduce the basic concepts of silk-based electronics/optoelectronics including the latest technological advances on the use of silk fibroin in combination with other functional components, with an emphasis on improving the performance of next-generation silk-based materials. It also highlights the patterning of silk fibroin to produce micro/nano-scale features, as well as the functionalization of silk fibroin to impart antimicrobial (i.e. antibacterial) properties. Silk-based bioelectronics have great potential for advanced or futuristic bio-applications including e-skins, e-bandages, biosensors, wearable displays, implantable devices, artificial muscles, etc. Notably, silk-based organic field-effect transistors have highly promising applications in e-skins and biosensors; silk-based electrodes/antennas are used for in vivo bioanalysis or sensing purpose (e.g., measurement of neurotransmitter such as dopamine) in addition to their use as food sensors; silk-based diodes can be applied as light sources for wound healing or tissue engineering, e.g., in cutaneous wound closure or induction of photothrombosis of corneal neovascularization; silk-based actuators have promising applications as artificial muscles; whereas silk-based memristors have exciting applications as logic or synaptic network for realizing e-skins or bionic brains.

Stretchable electronics have advanced rapidly and many applications require high repeatability and robustness under various mechanical deformations. It has been described here that how a highly stretchable and reliable conductor composite made from helical copper wires and a soft elastomer, named eHelix, can provide mechanically robust and strain-insensitive electronic conductivity for wearable devices. The reversibility of the mechanical behavior of the metal-elastomer system has been studied using finite element modeling methods. Optimal design parameters of such helical metal-elastomer structures are found. The scaling of multiple copper wires into such helical shapes to form a Multi-eHelix system is further shown. With the same elastomer volume, Multi-eHelix has more conductive paths and a higher current density than the single-eHelix. Integrations of these eHelix stretchable conductors with fabrics showed wearable displays that can survive machine-washes and hundreds of mechanical loading cycles. The integration of the eHelix developed by us with a wearable optical heart rate sensor enabled a wearable health monitoring system that can display measured heart rates on clothing. Furthermore, Multi-eHelix conductors are used to connect flexible printed circuit boards and piezoresistive sensors on a tactile sensing glove for the emerging sensorized prosthetics.

Hydrogel microneedle patch enables the extraction of skin interstitial fluid (ISF) through in situ swelling in a minimally invasive manner without assistance of mechano-chemical peripherals. However, existing hydrogel microneedles require tens of minutes with multistep process to collect sufficient volume (1 mL) for effective analysis. This study introduces an osmolyte-powered hydrogel microneedle patch that can extract ISF three times faster than the existing platforms and provide in situ analysis of extracted biomarkers. The microneedle patch is composed of osmolytes (i.e., maltose) and hydrogel (i.e., methacrylated hyaluronic acid). During the extraction process, the osmolytes dissolve in the matrix and provide the osmotic pressure that increases the diffusion of ISF from skin to the hydrogel matrix. A patch with 100 microneedles can extract 7.90 µL of ISF from pig skin ex vivo and 3.82 µL of ISF from mouse skin in vivo within 3 min, whereas the control (i.e., hydrogel microneedle without osmolytes) requires >10 min to achieve similar results. The extracted ISF allows the quantification of biomarkers such as glucose and/or drugs such as insulin in vivo. Through the integration with the electronic glucose sensors, the whole system permits the direct and rapid analysis of the extracted glucose.

Stretchable optoelectronic materials are essential for applications in wearable electronics, human-machine interfaces and soft robots. However, intrinsically stretchable optoelectronic devices such as light-emitting capacitors usually require high driving alternating voltages and excitation frequencies to achieve sufficient luminance in ambient lighting conditions. Here, we present a healable, low-field illuminating optoelectronic stretchable (HELIOS) device by introducing a transparent, high permittivity polymeric dielectric material. The HELIOS device turns on at an alternating voltage of 23 V and a frequency below 1 kHz, safe operating conditions for human-machine interactions. We achieved a brightness of 1,460 cd m

Pressure and touch sensitivity is crucial for intuitive human-machine interfaces. Here, we investigate the use of different microstructured elastomers for use as dielectric material in capacitive pressure sensors. We use finite element modeling to simulate how different microstructures can reduce the effective mechanical modulus. We found that pyramidal structures are optimal shapes that reduce the effective mechanical modulus of the elastomer by an order of magnitude. We also investigate the dependence of spacing of the pyramidal microstructures and how it impacts mechanical sensitivity. We further demonstrate the use of these elastomeric microstructures as the dielectric material on a variety of flexible and stretchable substrates to capture touch information in order to enable large area human-computer interfaces for next generation input devices, as well as continuous health-monitoring sensors.

Tuning the threshold voltage of a transistor is crucial for realizing robust digital circuits. For silicon transistors, the threshold voltage can be accurately controlled by doping. However, it remains challenging to tune the threshold voltage of single-wall nanotube (SWNT) thin-film transistors. Here, we report a facile method to controllably n-dope SWNTs using 1H-benzoimidazole derivatives processed via either solution coating or vacuum deposition. The threshold voltages of our polythiophene-sorted SWNT thin-film transistors can be tuned accurately and continuously over a wide range. Photoelectron spectroscopy measurements confirmed that the SWNT Fermi level shifted to the conduction band edge with increasing doping concentration. Using this doping approach, we proceeded to fabricate SWNT complementary inverters by inkjet printing of the dopants. We observed an unprecedented noise margin of 28 V at V(DD) = 80 V (70% of 1/2V(DD)) and a gain of 85. Additionally, robust SWNT complementary metal-oxide-semiconductor inverter (noise margin 72% of 1/2VDD) and logic gates with rail-to-rail output voltage swing and subnanowatt power consumption were fabricated onto a highly flexible substrate.

Stretchable conductors are critical building blocks for enabling new forms of wearable and curvilinear electronics. In this paper, we introduce a new method using the interfacial design to enable stretchable conductors with ultra-high conductivity and robustness to strain using three-dimensional helical copper micro-interconnects embedded in an elastic rubber substrate (eHelix-Cu). We studied the interfacial mechanics of the metal-elastomer to achieve highly reversible conductivities with strains. The stretchable eHelix-Cu interconnect has an ultra-high conductivity (∼105 S cm−1) that remains almost invariant when stretched to 170%, which is significantly higher than in other approaches using nanomaterials. The stretchable conductors can withstand strains of 100% for thousands of cycles, demonstrating remarkable durability for exciting potential wearable electronic applications.

Solution coating of organic semiconductors offers great potential for achieving low-cost manufacturing of large-area and flexible electronics. However, the rapid coating speed needed for industrial-scale production poses challenges to the control of thin-film morphology. Here, we report an approach—termed fluid-enhanced crystal engineering (FLUENCE)—that allows for a high degree of morphological control of solution-printed thin films. We designed a micropillar-patterned printing blade to induce recirculation in the ink for enhancing crystal growth, and engineered the curvature of the ink meniscus to control crystal nucleation. Using FLUENCE, we demonstrate the fast coating and patterning of millimetre-wide, centimetre-long, highly aligned single-crystalline organic semiconductor thin films. In particular, we fabricated thin films of 6,13-bis(triisopropylsilylethynyl) pentacene having non-equilibrium single-crystalline domains and an unprecedented average and maximum mobilities of 8.1±1.2 cm2 V−1 s−1 and 11 cm2 V−1 s−1. FLUENCE of organic semiconductors with non-equilibrium single-crystalline domains may find use in the fabrication of high-performance, large-area printed electronics. Solution printing of organic semiconductors could in principle be scaled to industrial needs, yet attaining aligned single-crystals directly with this method has been challenging. By using a micropillar-patterned printing blade designed to enhance the control of crystal nucleation and growth, thin films of macroscopic, highly aligned single crystals of organic semiconductors can now be fabricated.

Optical pressure sensors are highly responsive and are unaffected by surrounding parameters such as electronic noise, humidity, temperature, etc. A new type of optical pressure sensor is described that demonstrates the stretchability and transparency of a polydimethylsiloxane waveguide, while also serving as a substrate. The pressure sensors are both robust and easy to fabricate over a large area.

Constructing a complementary inverter is technically more complex because both pand n-channel transistors are required to be patterned onto a common substrate. Here, we report a simple solution processing method to fabricate complementary inverters based on n-channel C 60 single crystals and p-channel 6,13-bis(triisopropyl-silylethynyl) pentacene (TIPS-pentacene) single crystals. We achieved a signal gain as high as 155. Hence, this work provides a platform to study high-performance complementary circuits based on organic single-crystals. Organic FETs have been widely used for electronic applications such as displays [ 5 , 6 ] and sensors. [ 7–9 ] Organic single-crystals show the best FET performance with the highest charge mobility among organic materials. The p-channel organic single-crystal FETs have exhibited hole mobility as high as 40 cm 2 V − 1 s − 1 , [ 10–14 ]

Despite the ubiquity of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as a transparent conducting electrode in flexible organic electronic devices, its potential as a stretchable conductor has not been fully explored. This paper describes the electronic and morphological characteristics of PEDOT:PSS on stretchable poly(dimethylsiloxane) (PDMS) substrates. The evolution of resistance with strain depends dramatically on the methods used to coat the hydrophobic surface of PDMS with PEDOT:PSS, which is cast from an aqueous suspension. Treatment of the PDMS with an oxygen plasma produces a brittle skin that causes the PEDOT:PSS film to fracture and an increase in resistivity by four orders of magnitude at only 10% strain. In contrast, a mild treatment of the PDMS surface with ultraviolet/ozone (UV/O3) and the addition of 1% Zonyl fluorosurfactant to the PEDOT:PSS solution produces a mechanically resilient film whose resistance increases by a factor of only two at 50% strain and retains si...

Skin is the body's largest organ and is responsible for the transduction of a vast amount of information. This conformable material simultaneously collects signals from external stimuli that translate into information such as pressure, pain, and temperature. The development of an electronic material, inspired by the complexity of this organ is a tremendous, unrealized engineering challenge. However, the advent of carbon-based electronics may offer a potential solution to this long-standing problem. In this Account, we describe the use of an organic field-effect transistor (OFET) architecture to transduce mechanical and chemical stimuli into electrical signals. In developing this mimic of human skin, we thought of the sensory elements of the OFET as analogous to the various layers and constituents of skin. In this fashion, each layer of the OFET can be optimized to carry out a specific recognition function. The separation of multimodal sensing among the components of the OFET may be considered a "divide and conquer" approach, where the electronic skin (e-skin) can take advantage of the optimized chemistry and materials properties of each layer. This design of a novel microstructured gate dielectric has led to unprecedented sensitivity for tactile pressure events. Typically, pressure-sensitive components within electronic configurations have suffered from a lack of sensitivity or long mechanical relaxation times often associated with elastomeric materials. Within our method, these components are directly compatible with OFETs and have achieved the highest reported sensitivity to date. Moreover, the tactile sensors operate on a time scale comparable with human skin, making them ideal candidates for integration as synthetic skin devices. The methodology is compatible with large-scale fabrication and employs simple, commercially available elastomers. The design of materials within the semiconductor layer has led to the incorporation of selectivity and sensitivity within gas-sensing devices and has enabled stable sensor operation within aqueous media. Furthermore, careful tuning of the chemical composition of the dielectric layer has provided a means to operate the sensor in real time within an aqueous environment and without the need for encapsulation layers. The integration of such devices as electronic mimics of skin will require the incorporation of biocompatible or biodegradable components. Toward this goal, OFETs may be fabricated with99% biodegradable components by weight, and the devices are robust and stable, even in aqueous environments. Collectively, progress to date suggests that OFETs may be integrated within a single substrate to function as an electronic mimic of human skin, which could enable a large range of sensing-related applications from novel prosthetics to robotic surgery.

The development of an electronic skin is critical to the realization of artificial intelligence that comes into direct contact with humans, and to biomedical applications such as prosthetic skin. To mimic the tactile sensing properties of natural skin, large arrays of pixel pressure sensors on a flexible and stretchable substrate are required. We demonstrate flexible, capacitive pressure sensors with unprecedented sensitivity and very short response times that can be inexpensively fabricated over large areas by microstructuring of thin films of the biocompatible elastomer polydimethylsiloxane. The pressure sensitivity of the microstructured films far surpassed that exhibited by unstructured elastomeric films of similar thickness, and is tunable by using different microstructures. The microstructured films were integrated into organic field-effect transistors as the dielectric layer, forming a new type of active sensor device with similarly excellent sensitivity and response times.

Flexible/stretchable electronic devices and systems are attracting great attention because they can have important applications in many areas, such as artificial intelligent (AI) robotics, brain-machine interfaces, medical devices, structural and environmental monitoring, and healthcare. In addition to the electronic performance, the electronic devices and systems should be mechanically flexible or even stretchable. Traditional electronic materials including metals and semiconductors usually have poor mechanical flexibility and very limited elasticity. Three main strategies are adopted for the development of flexible/stretchable electronic materials. One is to use organic or polymeric materials. These materials are flexible, and their elasticity can be improved through chemical modification or composition formation with plasticizers or elastomers. Another strategy is to exploit nanometer-scale materials. Many inorganic materials in nanometer sizes can have high flexibility. They can be stretchable through the composition formation with elastomers. Ionogels can be considered as the third type of materials because they can be stretchable and ionically conductive. This article provides the recent progress of soft functional materials development including intrinsically conductive polymers for flexible/stretchable electrodes, and thermoelectric conversion and polymer composites for large area, flexible stretchable electrodes, and tactile sensors.

Sensing the force digitally Our skin provides us with a flexible waterproof barrier, but it also contains a sensor array that feels the world around us. This array provides feedback and helps us to avoid a hot object or increase the strength of our grip on an object that may be slipping away. Tee et al. describe an approach to simulate the mechanoreceptors of human skin, using pressure-sensitive foils and printed ring oscillators (see the Perspective by Anikeeva and Koppes). The sensor successfully converted pressure into a digital response in a pressure range comparable to that found in a human grip. Science , this issue p. 313 ; see also p. 274