Wenyu Wang

While silk is attractive for on-body sensing due to its biocompatibility and skin affinity, its smooth fiber surface and limited capillary absorption make it poorly suited to existing fabrication methods based on liquid infiltration and mechanical anchoring. Inspired by Gambiered Canton Gauze (Xiangyunsha), a traditional craft with a centuries-long history of silk surface modification, we present SilkSense, a fabric-level workflow for functionalizing commercially available silk. By analyzing the craft’s core processing stages and identifying the underlying interfacial mechanisms, we organize the responsible material components into a two-stage workflow: Dioscorea cirrhosa polyphenol pretreatment followed by Fe-HA/FA and PEDOT: PSS composite coating. The resulting fabric supports mask-based patterning (up to 1.5 mm resolution) and freehand painting and exhibits wash durability (approximately 15.6% resistance drift after 20 high-intensity cycles) under our test conditions. SilkSense fabric enables three on-body input modalities, including pressing, bending, and pinching, whose sensing characteristics can be translated into wearable interface designs across different body locations, validated through a drone control demonstration in which subtle single-hand finger movements drive three-channel real-time closed-loop interaction. Together, these results show how craft-derived interfacial principles can support patternable, maintainable, and multimodal silk-based interaction surfaces.

Wearable silent speech systems hold significant potential for restoring communication in patients with speech impairments. However, seamless, coherent speech remains elusive, and clinical efficacy is still unproven. Here, we present an AI-driven intelligent throat (IT) system that integrates throat muscle vibrations and carotid pulse signal sensors with large language model (LLM) processing to enable fluent, emotionally expressive communication. The system utilizes ultrasensitive textile strain sensors to capture high-quality signals from the neck area and supports token-level processing for real-time, continuous speech decoding, enabling seamless, delay-free communication. In tests with five stroke patients with dysarthria, IT’s LLM agents intelligently corrected token errors and enriched sentence-level emotional and logical coherence, achieving low error rates (4.2% word error rate, 2.9% sentence error rate) and a 55% increase in user satisfaction. This work establishes a portable, intuitive communication platform for patients with dysarthria with the potential to be applied broadly across different neurological conditions and in multi-language support systems.

Skin motions encode rich information about our gestures, bodily status, and environmental interactions. However, large-area detection, sensing resolution, and imperceptibility have been a trilemma for current technologies to truthfully record...

The ability to integrate materials with heterogeneous properties into a soft magnetic machine is important to expand its applications to various emerging fields. However, the lack of an efficient fabrication method limits the design‐ability of multi‐material soft magnetic machines with complex shapes. Here, a 3D printing strategy is reported to fabricate versatile multi‐material soft magnetic machines with heterogeneous mechanical and magnetic properties. Using a supporting matrix, different elastomeric inks can be co‐printed into 3D architectures with well‐merged interfaces, in a one‐step process. Multi‐material grippers, leapers, and rollers are shown that can perform motion and deformation patterns that are challenging for 2D or single‐material structures. This facile approach expands the material and structural design space of soft magnetic machines for future soft robotic and biomedical applications.

Harnessing intrinsic triboelectric signals from human skin holds promise for enhancing tactile perception. However, collecting these signals without disrupting normal skin functions and convoluting motion artifacts remains challenging. Additionally, person‐to‐person signal variance complicates data processing. In this study, it is demonstrated that triboelectric signals generated from touch can be imperceptibly collected and processed using a machine learning model to achieve tactile augmentation. When one hand contacts and rubs against a target object, charge transfer occurs between the skin and the object's surface. By placing a substrate‐less microfiber electrode on the finger of the other hand, a body‐coupled triboelectric circuit is formed to collect these signals, which contain material‐specific features such as amplitude and peak ratio. A machine learning technique is developed to process the triboelectric signals, enabling the classification of six different materials with a prediction accuracy of ≈95%. The material differentiation model is further validated across different users, achieving an overall accuracy of ≈88 %, illustrating the potential of utilizing the body‐coupled triboelectric circuit for tactile augmentation.

Developing methods to non-destructively deposit conductive materials onto existing objects can enhance their functionalities on-demand. However, designing and creating such structures to accommodate diverse shapes and surface textures of pre-fabricated objects remains challenging. We report an on-demand printing strategy for creating substrate-less, conducting microfiber patterns that can be adaptively deposited onto a wide range of objects, including daily-use stationery, tools, smartwatches, and unconventional materials like porous graphene aerogels. Solution-drawn microfibers are directly deposited onto the object in a semi-wet state upon synthesis, enabling seamless fiber-object integration in a single step. The design and format of the microfiber patterns can be tuned on-demand to adapt to the shapes and surface textures of target objects, ensuring compatibility with user-specific applications. These air-permissive, highly transparent layers minimally obstruct the original appearance and functions of the objects while equipping them with additional sensing, energy conversion, and electronic connectivity capabilities. Graphical abstract

The functional and sensory augmentation of living structures, such as human skin and plant epidermis, with electronics can be used to create platforms for health management and environmental monitoring. Ideally, such bioelectronic interfaces should not obstruct the inherent sensations and physiological changes of their hosts. The full life cycle of the interfaces should also be designed to minimize their environmental footprint. Here we report imperceptible augmentation of living systems through in situ tethering of organic bioelectronic fibres. Using an orbital spinning technique, substrate-free and open fibre networks—which are based on poly (3,4-ethylenedioxythiophene):polystyrene sulfonate—can be tethered to biological surfaces, including fingertips, chick embryos and plants. We use customizable fibre networks to create on-skin electrodes that can record electrocardiogram and electromyography signals, skin-gated organic electrochemical transistors and augmented touch and plant interfaces. We also show that the fibres can be used to couple prefabricated microelectronics and electronic textiles, and that the fibres can be repaired, upgraded and recycled.

Textiles represent a fundamental material format that is extensively integrated into our everyday lives. The quest for more versatile and body-compatible wearable electronics has led to the rise of electronic textiles (e-textiles). By enhancing textiles with electronic functionalities, e-textiles define a new frontier of wearable platforms for human augmentation. To realize the transformational impact of wearable e-textiles, materials innovations can pave the way for effective user adoption and the creation of a sustainable circular economy. We propose a repair, recycle, replacement and reduction circular e-textile paradigm. We envisage a systematic design framework embodying material selection and biofabrication concepts that can unify environmental friendliness, market viability, supply-chain resilience and user experience quality. This framework establishes a set of actionable principles for the industrialization and commercialization of future sustainable e-textile products.

Embryonic tissues undergoing shape change draw mechanical input from extraembryonic substrates. In avian eggs, the early blastoderm disk is under the tension of the vitelline membrane (VM). Here we report that the chicken VM characteristically downregulates tension and stiffness to facilitate stage-specific embryo morphogenesis. Experimental relaxation of the VM early in development impairs blastoderm expansion, while maintaining VM tension in later stages resists the convergence of the posterior body causing stalled elongation, failure of neural tube closure, and axis rupture. Biochemical and structural analysis shows that VM weakening is associated with the reduction of outer-layer glycoprotein fibers, which is caused by an increasing albumen pH due to CO₂ release from the egg. Our results identify a previously unrecognized potential cause of body axis defects through mis-regulation of extraembryonic tissue tension.