Recent Advances in TiO2 -Based Nanostructured Surfaces with Controllable Wettability and Adhesion.

Bioinspired surfaces with special wettability and adhesion have attracted great interest in both fundamental research and industry applications. Various kinds of special wetting surfaces have been constructed by adjusting the topographical structure and chemical composition. Here, recent progress of the artificial superhydrophobic surfaces with high contrast in solid/liquid adhesion has been reviewed, with a focus on the bioinspired construction and applications of one-dimensional (1D) TiO2-based surfaces. In addition, the significant applications related to artificial super-wetting/antiwetting TiO2-based structure surfaces with controllable adhesion are summarized, e.g., self-cleaning, friction reduction, anti-fogging/icing, microfluidic manipulation, fog/water collection, oil/water separation, anti-bioadhesion, and micro-templates for patterning. Finally, the current challenges and future prospects of this renascent and rapidly developing field, especially with regard to 1D TiO2-based surfaces with special wettability and adhesion, are proposed and discussed.

Scalable Fabrication of Multiplexed Plasmonic Nanoparticle Structures Based on AFM Lithography.

A controllable and scalable strategy is developed to fabricate multiplexed plasmonic nanoparticle structures by mechanical scratching with AFM lithography, which exhibit multiplex plasmonic properties and surface-enhanced Raman scattering responses. It offers an intuitive way to explore the plasmonic effects on the performance of an organic light-emitting diode device integrating with multiplexed plasmonic nanostructures.

Multiscale Heterogeneities-Based Piezoresistive Interfaces with Ultralow Detection Limitation and Adaptively Switchable Pressure Detectability.

Mechanical compliance and electrical enhancement are crucial for pressure sensors to promote performances when perceiving external stimuli. Here we propose a bioinspired multiscale heterogeneity-based interface to adaptively regulate its structure layout and switch to desirable piezoresistive behaviors with ultralow detection limitation. In such a multiscale heterogeneities system, the micro-/nanoscale spiny Ag-MnO2 heterostructure contributes to an ultralow detection limitation of 0.008 Pa and can perceive minor pressure increments under preloads with high resolution (0.0083%). The macroscale heterogeneous orientation of the cellular backbone enables anisotropic deformation, allowing the sensor to switch to rational sensitivity and working range (e.g., 580 kPa-1 for 0-20 kPa/54 kPa-1 for 60-140 kPa) as required. The sensor's stepwise activation progresses from the micro-/nanoscale heterostructure to the macroscale heterogeneous orientation, which can adaptively match diverse sensing tasks in complex applications scenarios. This multiscale heterogeneous and switchable design holds immense potential in the development of intelligent electromechanical devices, including wearable sensors, soft robotics, and smart actuators.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration.

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

A flexible optoacoustic blood 'stethoscope' for noninvasive multiparametric cardiovascular monitoring.

Quantitative and multiparametric blood analysis is of great clinical importance in cardiovascular disease diagnosis. Although there are various methods to extract blood information, they often require invasive procedures, lack continuity, involve bulky instruments, or have complicated testing procedures. Flexible sensors can realize on-skin assessment of several vital signals, but generally exhibit limited function to monitor blood characteristics. Here, we report a flexible optoacoustic blood 'stethoscope' for noninvasive, multiparametric, and continuous cardiovascular monitoring, without requiring complicated procedures. The optoacoustic blood 'stethoscope' features the light delivery elements to illuminate blood and the piezoelectric acoustic elements to capture light-induced acoustic waves. We show that the optoacoustic blood 'stethoscope' can adhere to the skin for continuous and non-invasive in-situ monitoring of multiple cardiovascular biomarkers, including hypoxia, intravascular exogenous agent concentration decay, and hemodynamics, which can be further visualized with a tailored 3D algorithm. Demonstrations on both in-vivo animal trials and human subjects highlight the optoacoustic blood 'stethoscope''s potential for cardiovascular disease diagnosis and prediction.

Strain-Enabled Phase Transition of Periodic Metasurfaces.

Phase transitions are universal in solid-state matters, as well as in periodic electromagnetic metasurfaces-the photonic analogues of crystals. Although such transitions dictate the properties of active metasurfaces, universal ways to describe the structure transition of periodic metasurfaces have not yet been established. Here, the authors report the strain-enabled phase transition (or lattice deformation) of stretchable metasurfaces with the crystallographic description. They analytically and experimentally demonstrate the phase transition of plasmonic lattices between two arbitrary 2D Bravais lattices under certain strain configurations. The strain-induced symmetry lowering of the structures gives rise to optical anisotropy upon polarization, namely, linearly and circularly polarized dichroism. They further demonstrate the potential of phase transition in information decoding with applied strain. Interpreting the phase transition of metasurfaces from a standpoint of symmetry would accelerate the discovery of emergent properties, and provide a generalizable approach to designing active metasurfaces.

A Mechanically Interlocking Strategy Based on Conductive Microbridges for Stretchable Electronics.

Stretchable electronics incorporating critical sensing, data transmission, display and powering functionalities, is crucial to emerging wearable healthcare applications. To date, methods to achieve stretchability of individual functional devices have been extensively investigated. However, integration strategies of these stretchable devices to achieve all-stretchable systems are still under exploration, in which the reliable stretchable interconnection is a key element. Here, solderless stretchable interconnections based on mechanically interlocking microbridges are developed to realize the assembly of individual stretchable devices onto soft patternable circuits toward multifunctional all-stretchable platforms. This stretchable interconnection can effectively bridge interlayer conductivity with tight adhesion through both conductive microbridges and selectively distributed adhesive polymer. Consequently, enhanced stretchability up to a strain of 35% (R/R0  ≤ 5) is shown, compared with conventional solder-assisted connections which lose electrical conduction at a strain of less than 5% (R/R0  ≈ 30). As a proof of concept, a self-powered all-stretchable data-acquisition platform is fabricated by surface mounting a stretchable strain sensor and a supercapacitor onto a soft circuit through solderless interconnections. This solderless interconnecting strategy for surface-mountable devices can be utilized as a valuable technology for the integration of stretchable devices to achieve all-soft multifunctional systems.

Shape morphing of plastic films.

Three-dimensional (3D) architectures have qualitatively expanded the functions of materials and flexible electronics. However, current fabrication techniques for devices constrain their substrates to 2D geometries and current post-shape transformation strategies are limited to heterogenous or responsive materials and are not amenable to free-standing inert plastic films such as polyethylene terephthalate (PET) and polyimide (PI), which are vital substrates for flexible electronics. Here, we realize the shape morphing of homogeneous plastic films for various free-standing 3D frameworks from their 2D precursors by introducing a general strategy based on programming the plastic strain in films under peeling. By modulating the peeling parameters, previously inaccessible free-standing 3D geometries ranging from millimeter to micrometer were predicted theoretically and obtained experimentally. This strategy is applicable to most materials capable of plastic deformation, including polymers, metals, and composite materials, and can even enable 4D transformation with responsive plastic films. Enhanced performance of 3D circuits and piezoelectric systems demonstrates the enormous potential of peeling-induced shape morphing for 3D devices.

Haptically Quantifying Young's Modulus of Soft Materials Using a Self-Locked Stretchable Strain Sensor.

Simple and rapid Young's modulus measurements of soft materials adaptable to various scenarios are of general significance, and they require miniaturized measurement platforms with easy operation. Despite the advances made in portable and wearable approaches, acquiring and analyzing multiple or complicated signals necessitate tethered bulky components and careful preparation. Here, a new methodology based on a self-locked stretchable strain sensor to haptically quantify Young's modulus of soft materials (kPa-MPa) rapidly is reported. The method demonstrates a fingertip measurement platform, which endows a prosthetic finger with human-comparable haptic behaviors and skills on elasticity sensing without activity constraints. A universal strategy is offered toward ultraconvenient and high-efficient Young's modulus measurements with wide adaptability to various fields for unprecedented applications.

Mechanically Durable Memristor Arrays Based on a Discrete Structure Design.

Memristors constitute a promising functional component for information storage and in-memory computing in flexible and stretchable electronics including wearable devices, prosthetics, and soft robotics. Despite tremendous efforts made to adapt conventional rigid memristors to flexible and stretchable scenarios, stretchable and mechanical-damage-endurable memristors, which are critical for maintaining reliable functions under unexpected mechanical attack, have never been achieved. Here, the development of stretchable memristors with mechanical damage endurance based on a discrete structure design is reported. The memristors possess large stretchability (40%) and excellent deformability (half-fold), and retain stable performances under dynamic stretching and releasing. It is shown that the memristors maintain reliable functions and preserve information after extreme mechanical damage, including puncture (up to 100 times) and serious tearing situations (fully diagonally cut). The structural strategy offers new opportunities for next-generation stretchable memristors with mechanical damage endurance, which is vital to achieve reliable functions for flexible and stretchable electronics even in extreme and highly dynamic environments.

Freestanding and Scalable Force-Softness Bimodal Sensor Arrays for Haptic Body-Feature Identification.

Tactile technologies that can identify human body features are valuable in clinical diagnosis and human-machine interactions. Previously, cutting-edge tactile platforms have been able to identify structured non-living objects; however, identification of human body features remains challenging mainly because of the irregular contour and heterogeneous spatial distribution of softness. Here, freestanding and scalable tactile platforms of force-softness bimodal sensor arrays are developed, enabling tactile gloves to identify body features using machine-learning methods. The bimodal sensors are engineered by adding a protrusion on a piezoresistive pressure sensor, endowing the resistance signals with combined information of pressure and the softness of samples. The simple design enables 112 bimodal sensors to be integrated into a thin, conformal, and stretchable tactile glove, allowing the tactile information to be digitalized while hand skills are performed on the human body. The tactile glove shows high accuracy (98%) in identifying four body features of a real person, and four organ models (healthy and pathological) inside an abdominal simulator, demonstrating identification of body features of the bimodal tactile platforms and showing their potential use in future healthcare and robotics.

Artificial Sense Technology: Emulating and Extending Biological Senses.

Biological senses are critical for the survival of organisms. A great deal of attention has focused on elucidating the underlying physiological mechanisms of the senses, inspiring various sensing techniques. Despite progress in this area, gaps remain between the biological senses and conventional sensing techniques. In this Perspective, we propose the concept of artificial sense technology, which mimics the biological senses but differs in terms of objective sensing and intelligent feedback capabilities. We first summarize recent progress in the use of nanotechnologies to emulate the biological senses and then outline the advantages of artificial sense technology, which extend the capabilities of its biological counterparts. We envision artificial sense technology as a powerful perceptual interface that will play key roles in sensation substitution, digital healthcare, animal interactions, plant electronics, smart robots, and other areas that enrich the connections of the physical and virtual worlds.

A Stretchable and Transparent Electrode Based on PEGylated Silk Fibroin for In Vivo Dual-Modal Neural-Vascular Activity Probing.

Transparent electrodes that form seamless contact and enable optical interrogation at the electrode-brain interface are potentially of high significance for neuroscience studies. Silk hydrogels can offer an ideal platform for transparent neural interfaces owing to their superior biocompatibility. However, conventional silk hydrogels are too weak and have difficulties integrating with highly conductive and stretchable electronics. Here, a transparent and stretchable hydrogel electrode based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and PEGylated silk protein is reported. PEGylated silk protein with poly(ethylene glycol) diglycidyl ether (PEGDE) improves the Young's modulus to 1.51-10.73 MPa and the stretchability to ≈400% from conventional silk hydrogels (<10 kPa). The PEGylated silk also helps form a robust interface with PEDOT:PSS thin film, making the hydrogel electrode synergistically incorporate superior stretchability (≈260%), stable electrical performance (≈4 months), and a low sheet resistance (≈160 ± 56 Ω sq-1 ). Finally, the electrode facilitates efficient electrical recording, and stimulation with unobstructed optical interrogation and rat-brain imaging are demonstrated. The highly transparent and stretchable hydrogel electrode offers a practical tool for neuroscience and paves the way for a harmonized tissue-electrode interface.

Pangolin-Inspired Stretchable, Microwave-Invisible Metascale.

Microwave-invisible devices are emerging as a valuable technology in various applications, including soft robotics, shape-morphing structures, and textural camouflages, especially in electronic countermeasures. Unfortunately, conventional microwave-absorbing metastructures and bulk absorbers are stretching confined, limiting their application in deformable or special-shaped targets. To overcome such limitations, a conceptually novel soft-rigid-connection strategy, inspired by the pangolin, is proposed. Pangolin-inspired metascale (PIMS), which is a kind of stretchable metamaterial consisting of an electromagnetic dissipative scale (EMD-scale) and elastomer, is rationally designed. Such a device exhibits robust microwave-absorbing capacity under the interference of 50% stretching. Besides, profiting from the covering effect and size-confined effect of EMD-scale, the out-of-plane indentation failure force of PIMS is at least 5 times larger than conventional device. As a proof of concept, the proposed device is conformally pasted on nondevelopable surfaces. For a spherical dome surface, the maximum radar cross-section (RCS) reduction of PIMS is 6.3 dB larger than that of a conventional device, while for a saddle surface, the bandwidth of 10 dB RCS reduction exhibits an increase of 83%. In short, this work provides a conceptually novel platform to develop stretchable, nondevelopable surface conformable functional devices.

Portable Food-Freshness Prediction Platform Based on Colorimetric Barcode Combinatorics and Deep Convolutional Neural Networks.

Artificial scent screening systems (known as electronic noses, E-noses) have been researched extensively. A portable, automatic, and accurate, real-time E-nose requires both robust cross-reactive sensing and fingerprint pattern recognition. Few E-noses have been commercialized because they suffer from either sensing or pattern-recognition issues. Here, cross-reactive colorimetric barcode combinatorics and deep convolutional neural networks (DCNNs) are combined to form a system for monitoring meat freshness that concurrently provides scent fingerprint and fingerprint recognition. The barcodes-comprising 20 different types of porous nanocomposites of chitosan, dye, and cellulose acetate-form scent fingerprints that are identifiable by DCNN. A fully supervised DCNN trained using 3475 labeled barcode images predicts meat freshness with an overall accuracy of 98.5%. Incorporating DCNN into a smartphone application forms a simple platform for rapid barcode scanning and identification of food freshness in real time. The system is fast, accurate, and non-destructive, enabling consumers and all stakeholders in the food supply chain to monitor food freshness.

Mechanical Tolerance of Cascade Bioreactions via Adaptive Curvature Engineering for Epidermal Bioelectronics.

Epidermal bioelectronics that can monitor human health status non-invasively and in real time are core to wearable healthcare equipment. Achieving mechanically tolerant surface bioreactions that convert biochemical information to detectable signals is crucial for obtaining high sensing fidelity. In this work, by combining simulations and experiments, a typical epidermal biosensor system is investigated based on a redox enzyme cascade reaction (RECR) comprising glucose oxidase/lactate oxidase enzymes and Prussian blue nanoparticles. Simulations reveal that strain-induced change in surface reactant flux is the key to the performance drop in traditional flat bioelectrodes. In contrast, wavy bioelectrodes capable of curvature adaptation maintain the reactant flux under strain, which preserves sensing fidelity. This rationale is experimentally proven by bioelectrodes with flat/wavy geometry under both static strain and dynamic stretching. When exposed to 50% strain, the signal fluctuations for wavy bioelectrodes are only 7.0% (4.9%) in detecting glucose (lactate), which are significantly lower than the 40.3% (51.8%) in flat bioelectrodes. Based on this wavy bioelectrode, a stable human epidermal metabolite biosensor insensitive to human gestures is further demonstrated. This mechanically tolerant biosensor based on adaptive curvature engineering provides a reliable bio/chemical-information monitoring platform for soft healthcare bioelectronics.

Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures.

Coupling myoelectric and mechanical signals during voluntary muscle contraction is paramount in human-machine interactions. Spatiotemporal differences in the two signals intrinsically arise from the muscular excitation-contraction process; however, current methods fail to deliver local electromechanical coupling of the process. Here we present the locally coupled electromechanical interface based on a quadra-layered ionotronic hybrid (named as CoupOn) that mimics the transmembrane cytoadhesion architecture. CoupOn simultaneously monitors mechanical strains with a gauge factor of ~34 and surface electromyogram with a signal-to-noise ratio of 32.2 dB. The resolved excitation-contraction signatures of forearm flexor muscles can recognize flexions of different fingers, hand grips of varying strength, and nervous and metabolic muscle fatigue. The orthogonal correlation of hand grip strength with speed is further exploited to manipulate robotic hands for recapitulating corresponding gesture dynamics. It can be envisioned that such locally coupled electromechanical interfaces would endow cyber-human interactions with unprecedented robustness and dexterity.

Smectic Layer Origami via Preprogrammed Photoalignment.

Hierarchical architecture is of vital importance in soft materials. Focal conic domains (FCDs) of smectic liquid crystals, characterized by an ordered lamellar structure, attract intensive attention. Simultaneously tailoring the geometry and clustering characteristics of FCDs remains a challenge. Here, the 3D smectic layer origami via a 2D preprogrammed photoalignment film is accomplished. Full control of hierarchical superstructures is demonstrated, including the domain size, shape, and orientation, and the lattice symmetry of fragmented toric FCDs. The unique symmetry breaking of resultant superstructures combined with the optical anisotropy of the liquid crystals induces an intriguing polarization-dependent diffraction. This work broadens the scientific understanding of self-assembled soft materials and may inspire new opportunities for advanced functional materials and devices.

Fast patterning of oriented organic microstripes for field-effect ammonia gas sensors.

A series of organic field-effect transistors (OFETs) with patterned ultra-thin films for NH3 detection are achieved via fast dip-coating. The morphology and packing structure of the ultra-thin films are greatly dependent on the surface energy of the substrates, geometry features of the patterned electrodes and evaporation atmosphere during the dip-coating process, which in turn results in a significant difference in the NH3 sensing properties. Based on the newly proposed mechanism, low-trap dielectric-semiconductor interfaces, a stripe-like morphology and an ultrathin film (as low as 2 nm) enable the OFET-based sensors to exhibit unprecedented sensitivity (∼160) with a short response/recovery time. The efficient (2 mm s(-1)), reliable, and scalable patterning strategy opens a new route for solution-processed OFET-based gas sensors.