Single fibre enables acoustic fabrics via nanometre-scale vibrations

Will the fibers of the future be considered fibers?

This work explores the pivotal breakthroughs and historical developments in fibers over the past century, while also identifying future research directions and emerging trends that promise to shape the future of this field.

Thermally drawn multi-material fibers: from fundamental research to industrial applications

Thermally drawn fiber devices, with their complex micro- to nanoscale architectures, hold great promises not only for scientific research but also for scalable industrial applications in soft smart systems.

A Nanoparticle-Based Artificial Ear for Personalized Classification of Emotions in the Human Voice Using Deep Learning

Artificial intelligence and human-computer interaction advances demand bioinspired sensing modalities capable of comprehending human affective states and speech. However, endowing skin-like interfaces with such intricate perception abilities remains challenging. Here, we have developed a flexible piezoresistive artificial ear (AE) sensor based on gold nanoparticles, which can convert sound signals into electrical signals through changes in resistance. By testing the sensor's performance at both frequency and sound pressure level (SPL), the AE has a frequency response range of 20 Hz to 12 kHz and can sense sound signals from up to 5 m away at a frequency of 1 kHz and an SPL of 126 dB. Furthermore, through deep learning, the device achieves up to 96.9% and 95.0% accuracy in classification and recognition applications for seven emotional and eight urban environmental noises, respectively. Hence, on one hand, our device can monitor the patient's emotional state by their speech, such as sudden yelling and screaming, which can help healthcare workers understand patients' condition in time. On the other hand, the device could also be used for real-time monitoring of noise levels in aircraft, ships, factories, and other high-decibel equipment and environments.

Integrated Piezoelectric/Pyroelectric Sensing from Organic-Inorganic Perovskite Nanocomposites

Flexible ferroelectric materials are in high demand in emerging energy harvesting and self-powered sensing electronics. However, current flexible ferroelectric polymers, such as poly(vinylidene fluoride) (PVDF) and P(VDF-co-trifluoroethylene) [P(VDF-TrFE)], cannot fulfill the requirement of emerging applications because of their low piezoelectric/pyroelectric performance. In this work, using organic-inorganic hybrid perovskite [(4-aminotetrahydropyran)2PbBr2Cl2] ferroelectric nanorods as reinforcement and P(VDF-TrFE) as the matrix, we prepared flexible core-sheath piezoelectric nanofibers and pyroelectric nanocomposite films. The core-sheath nanofibers possess a record-high piezoelectric coefficient of 78.1 pC·N-1, and the output voltage reaches to 192 V, with the maximum power density of 1.04 W·m-2. On the other hand, the nanocomposite film exhibits a high pyroelectric coefficient of 58.2 μC·m-2·K-1 at 333 K, which yields a voltage of 6.1 V under 6.6 K temperature fluctuation. An integrated flexible sensing device was prepared by combining piezoelectric nanofibers and pyroelectric films, which can wirelessly detect vibration and temperature fluctuation simultaneously. The integrated device is suitable for pipelines, power equipment, and other scenarios, where vibration and temperature need to be monitored at the same time.

Multi-Objective Bayesian Optimization for Laminate-Inspired Mechanically Reinforced Piezoelectric Self-Powered Sensing Yarns

Piezoelectric fiber yarns produced by electrospinning offer a versatile platform for intelligent devices, demonstrating mechanical durability and the ability to convert mechanical strain into electric signals. While conventional methods involve twisting a single poly(vinylidene fluoride-co-trifluoroethylene)(P(VDF-TrFE)) fiber mat to create yarns, by limiting control over the mechanical properties, an approach inspired by composite laminate design principles is proposed for strengthening. By stacking multiple electrospun mats in various sequences and twisting them into yarns, the mechanical properties of P(VDF-TrFE) yarn structures are efficiently optimized. By leveraging a multi-objective Bayesian optimization-based machine learning algorithm without imposing specific stacking restrictions, an optimal stacking sequence is determined that simultaneously enhances the ultimate tensile strength (UTS) and failure strain by considering the orientation angles of each aligned fiber mat as discrete design variables. The conditions on the Pareto front that achieve a balanced improvement in both the UTS and failure strain are identified. Additionally, applying corona poling induces extra dipole polarization in the yarn state, successfully fabricating mechanically robust and high-performance piezoelectric P(VDF-TrFE) yarns. Ultimately, the mechanically strengthened piezoelectric yarns demonstrate superior capabilities in self-powered sensing applications, particularly in challenging environments and sports scenarios, substantiating their potential for real-time signal detection.

Fibres-threads of intelligence-enable a new generation of wearable systems

Fabrics represent a unique platform for seamlessly integrating electronics into everyday experiences. The advancements in functionalizing fabrics at both the single fibre level and within constructed fabrics have fundamentally altered their utility. The revolution in materials, structures, and functionality at the fibre level enables intimate and imperceptible integration, rapidly transforming fibres and fabrics into next-generation wearable devices and systems. In this review, we explore recent scientific and technological breakthroughs in smart fibre-enabled fabrics. We examine common challenges and bottlenecks in fibre materials, physics, chemistry, fabrication strategies, and applications that shape the future of wearable electronics. We propose a closed-loop smart fibre-enabled fabric ecosystem encompassing proactive sensing, interactive communication, data storage and processing, real-time feedback, and energy storage and harvesting, intended to tackle significant challenges in wearable technology. Finally, we envision computing fabrics as sophisticated wearable platforms with system-level attributes for data management, machine learning, artificial intelligence, and closed-loop intelligent networks.

Fabrication, sustainability, and key performance indicators of bioelectronics via fiber building blocks

Bioelectronics provide efficient information exchange between living systems and man-made devices, acting as a vital bridge in merging the domains of biology and technology. Using functional fibers as building blocks, bioelectronics could be hierarchically assembled with vast design possibilities across different scales, enhancing their application-specific biointegration, ergonomics, and sustainability. In this work, the authors review recent developments in bioelectronic fiber elements by reflecting on their fabrication approaches and key performance indicators, including the life cycle sustainability, environmental electromechanical performance, and functional adaptabilities. By delving into the challenges associated with physical deployment and exploring innovative design strategies for adaptability, we propose avenues for future development of bioelectronics via fiber building blocks, boosting the potential of "Fiber of Things" for market-ready bioelectronic products with minimized environmental impact.

Advances in Portable and Wearable Acoustic Sensing Devices for Human Health Monitoring

The practice of auscultation, interpreting body sounds to assess organ health, has greatly benefited from technological advancements in sensing and electronics. The advent of portable and wearable acoustic sensing devices marks a significant milestone in telemedicine, home health, and clinical diagnostics. This review summarises the contemporary advancements in acoustic sensing devices, categorized based on varied sensing principles, including capacitive, piezoelectric, and triboelectric mechanisms. Some representative acoustic sensing devices are introduced from the perspective of portability and wearability. Additionally, the characteristics of sound signals from different human organs and practical applications of acoustic sensing devices are exemplified. Challenges and prospective trends in portable and wearable acoustic sensors are also discussed, providing insights into future research directions.

Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

In-Sensor Tactile Fusion and Logic for Accurate Intention Recognition

Touch control intention recognition is an important direction for the future development of human-machine interactions (HMIs). However, the implementation of parallel-sensing functional modules generally requires a combination of different logical blocks and control circuits, which results in regional redundancy, redundant data, and low efficiency. Here, a location-and-pressure intelligent tactile sensor (LPI tactile sensor) unprecedentedly combined with sensing, computing, and logic is proposed, enabling efficient and ultrahigh-resolution action-intention interaction. The LPI tactile sensor eliminates the need for data transfer among the functional units through the core integration design of the layered structure. It actuates in-sensor perception through feature transmission, fusion, and differentiation, thereby revolutionizing the traditional von Neumann architecture. While greatly simplifying the data dimensionality, the LPI tactile sensor achieves outstanding resolution sensing in both location (<400 µm) and pressure (75 Pa). Synchronous feature fusion and decoding support the high-fidelity recognition of action and combinatorial logic intentions. Benefiting from location and pressure synergy, the LPI tactile sensor demonstrates robust privacy as an encrypted password device and interaction intelligence through pressure enhancement. It can recognize continuous touch actions in real time, map real intentions to target events, and promote accurate and efficient intention-driven HMIs.

Piezoelectric Biomaterials Inspired by Nature for Applications in Biomedicine and Nanotechnology

Bioelectricity provides electrostimulation to regulate cell/tissue behaviors and functions. In the human body, bioelectricity can be generated in electromechanically responsive tissues and organs, as well as biomolecular building blocks that exhibit piezoelectricity, with a phenomenon known as the piezoelectric effect. Inspired by natural bio-piezoelectric phenomenon, efforts have been devoted to exploiting high-performance synthetic piezoelectric biomaterials, including molecular materials, polymeric materials, ceramic materials, and composite materials. Notably, piezoelectric biomaterials polarize under mechanical strain and generate electrical potentials, which can be used to fabricate electronic devices. Herein, a review article is proposed to summarize the design and research progress of piezoelectric biomaterials and devices toward bionanotechnology. First, the functions of bioelectricity in regulating human electrophysiological activity from cellular to tissue level are introduced. Next, recent advances as well as structure-property relationship of various natural and synthetic piezoelectric biomaterials are provided in detail. In the following part, the applications of piezoelectric biomaterials in tissue engineering, drug delivery, biosensing, energy harvesting, and catalysis are systematically classified and discussed. Finally, the challenges and future prospects of piezoelectric biomaterials are presented. It is believed that this review will provide inspiration for the design and development of innovative piezoelectric biomaterials in the fields of biomedicine and nanotechnology.

Frequency-Selective, Multi-Channel, Self-Powered Artificial Basilar Membrane Sensor with a Spiral Shape and 24 Critical Bands Inspired by the Human Cochlea

A spiral-artificial basilar membrane (S-ABM) sensor is reported that mimics the basilar membrane (BM) of the human cochlea and can detect sound by separating it into 24 sensing channels based on the frequency band. For this, an analytical function is proposed to design the width of the BM so that the frequency bands are linearly located along the length of the BM. To fabricate the S-ABM sensor, a spiral-shaped polyimide film is used as a vibrating membrane, with maximum displacement at locations corresponding to specific frequency bands of sound, and attach piezoelectric sensor modules made of poly(vinylidene fluoride-trifluoroethylene) film on top of the polyimide film to measure the vibration amplitude at each channel location. As the result, the S-ABM sensor implements a characteristic frequency band of 96-12,821 Hz and 24-independent critical bands. Using real-time signals from discriminate channels, it is demonstrated that the sensor can rapidly identify the operational noises from equipment processes as well as vehicle sounds from environmental noises on the road. The sensor can be used in a variety of applications, including speech recognition, dangerous situation recognition, hearing aids, and cochlear implants, and more.

Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode.

Self-Poled Piezoelectric Nanocomposite Fiber Sensors for Wireless Monitoring of Physiological Signals

Self-powered sensors have the potential to enable real-time health monitoring without contributing to the ever-growing demand for energy. Piezoelectric nanogenerators (PENGs) respond to mechanical deformations to produce electrical signals, imparting a sensing capability without external power sources. Textiles conform to the human body and serve as an interactive biomechanical energy harvesting and sensing medium without compromising comfort. However, the textile-based PENG fabrication process is complex and lacks scalability, making these devices impractical for mass production. Here, we demonstrate the fabrication of a long-length PENG fiber compatible with industrial-scale manufacturing. The thermal drawing process enables the one-step fabrication of self-poled MoS2-poly(vinylidene fluoride) (PVDF) nanocomposite fiber devices integrated with electrodes. Heat and stress during thermal drawing and MoS2 nanoparticle addition facilitate interfacial polarization and dielectric modulation to enhance the output performance. The fibers show a 57 and 70% increase in the output voltage and current compared to the pristine PVDF fiber, respectively, at a considerably low MoS2 loading of 3 wt %. The low Young's modulus of the outer cladding ensures an effective stress transfer to the piezocomposite domain and allows minute motion detection. The flexible fibers demonstrate wireless, self-powered physiological sensing and biomotion analysis capability. The study aims to guide the large-scale production of highly sensitive integrated fibers to enable textile-based and plug-and-play wearable sensors.

Single Layer Silk and Cotton Woven Fabrics for Acoustic Emission and Active Sound Suppression

Whether intentionally generating acoustic waves or attempting to mitigate unwanted noise, sound control is an area of challenge and opportunity. This study investigates traditional fabrics as emitters and suppressors of sound. When attached to a single strand of a piezoelectric fiber actuator, a silk fabric emits up to 70 dB of sound. Despite the complex fabric structure, vibrometer measurements reveal behavior reminiscent of a classical thin plate. Fabric pore size relative to the viscous boundary layer thickness is found-through comparative fabric analysis-to influence acoustic-emission efficiency. Sound suppression is demonstrated using two distinct mechanisms. In the first, direct acoustic interference is shown to reduce sound by up to 37 dB. The second relies on pacifying the fabric vibrations by the piezoelectric fiber, reducing the amplitude of vibration waves by 95% and attenuating the transmitted sound by up to 75%. Interestingly, this vibration-mediated suppression in principle reduces sound in an unlimited volume. It also allows the acoustic reflectivity of the fabric to be dynamically controlled, increasing by up to 68%. The sound emission and suppression efficiency of a 130 µm silk fabric presents opportunities for sound control in a variety of applications ranging from apparel to transportation to architecture.

Acoustically Enhanced Triboelectric Stethoscope for Ultrasensitive Cardiac Sounds Sensing and Disease Diagnosis

Electronic stethoscope used to detect cardiac sounds that contain essential clinical information is a primary tool for diagnosis of various cardiac disorders. However, the linear electromechanical constitutive relation makes conventional piezoelectric sensors rather ineffective to detect low-intensity, low-frequency heart acoustic signal without the assistance of complex filtering and amplification circuits. Herein, it is found that triboelectric sensor features superior advantages over piezoelectric one for microquantity sensing originated from the fast saturated constitutive characteristic. As a result, the triboelectric sensor shows ultrahigh sensitivity (1215 mV Pa-1) than the piezoelectric counterpart (21 mV Pa-1) in the sound pressure range of 50-80 dB under the same testing condition. By designing a trumpet-shaped auscultatory cavity with a power function cross-section to achieve acoustic energy converging and impedance matching, triboelectric stethoscope delivers 36 dB signal-to-noise ratio for human test (2.3 times of that for piezoelectric one). Further combining with machine learning, five cardiac states can be diagnosed at 97% accuracy. In general, the triboelectric sensor is distinctly unique in basic mechanism, provides a novel design concept for sensing micromechanical quantities, and presents significant potential for application in cardiac sounds sensing and disease diagnosis.

Electrostatic Smart Textiles for Braille-To-Speech Translation

A wearable Braille-to-speech translation system is of great importance for providing auditory feedback in assisting blind people and people with speech impairment. However, previous reported Braille-to-speech translation systems still need to be improved in terms of comfortability or integration. Here, a Braille-to-speech translation system that uses dual-functional electrostatic transducers which are made of fabric-based materials and can be integrated into textiles is reported. Based on electrostatic induction, the electrostatic transducer can either serve as a tactile sensor or a loudspeaker with the same design. The proposed electrostatic transducers have excellent output performances, mechanical robustness, and working stability. By combining the devices with machine learning algorithms, it is possible to translate the Braille alphabet and 40 commonly used words (extensible) into speech with an accuracy of 99.09% and 97.08%, respectively. This work demonstrates a new approach for further developments of advanced assistive technology toward improving the lives of disabled people.

Imperceptible augmentation of living systems with organic bioelectronic fibres

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.

Stretchable electronic strips for electronic textiles enabled by 3D helical structure

The development of stretchable electronic devices is a critical area of research for wearable electronics, particularly electronic textiles (e-textiles), where electronic devices embedded in clothing need to stretch and bend with the body. While stretchable electronics technologies exist, none have been widely adopted. This work presents a novel and potentially transformative approach to stretchable electronics using a ubiquitous structure: the helix. A strip of flexible circuitry ('e-strip') is twisted to form a helical ribbon, transforming it from flexible to stretchable. A stretchable core-in this case rubber cord-supports the structure, preventing damage from buckling. Existing helical electronics have only extended to stretchable interconnects between circuit modules, and individual components such as printed helical transistors. Fully stretchable circuits have, until now, only been produced in planar form: flat circuits, either using curved geometry to enable them to stretch, or using inherently stretchable elastomer substrates. Helical e-strips can bend along multiple axes, and repeatedly stretch between 30 and 50%, depending on core material and diameter. LED and temperature sensing helical e-strips are demonstrated, along with design rules for helical e-strip fabrication. Widely available materials and standard fabrication processes were prioritized to maximize scalability and accessibility.

Intelligent Biomaterialomics: Molecular Design, Manufacturing, and Biomedical Applications

Materialomics integrates experiment, theory, and computation in a high-throughput manner, and has changed the paradigm for the research and development of new functional materials. Recently, with the rapid development of high-throughput characterization and machine-learning technologies, the establishment of biomaterialomics that tackles complex physiological behaviors has become accessible. Breakthroughs in the clinical translation of nanoparticle-based therapeutics and vaccines have been observed. Herein, recent advances in biomaterials, including polymers, lipid-like materials, and peptides/proteins, discovered through high-throughput screening or machine learning-assisted methods, are summarized. The molecular design of structure-diversified libraries; high-throughput characterization, screening, and preparation; and, their applications in drug delivery and clinical translation are discussed in detail. Furthermore, the prospects and main challenges in future biomaterialomics and high-throughput screening development are highlighted.

Soft mechanical sensors for wearable and implantable applications

Wearable and implantable sensing of biomechanical signals such as pressure, strain, shear, and vibration can enable a multitude of human-integrated applications, including on-skin monitoring of vital signs, motion tracking, monitoring of internal organ condition, restoration of lost/impaired mechanoreception, among many others. The mechanical conformability of such sensors to the human skin and tissue is critical to enhancing their biocompatibility and sensing accuracy. As such, in the recent decade, significant efforts have been made in the development of soft mechanical sensors. To satisfy the requirements of different wearable and implantable applications, such sensors have been imparted with various additional properties to make them better suited for the varied contexts of human-integrated applications. In this review, focusing on the four major types of soft mechanical sensors for pressure, strain, shear, and vibration, we discussed the recent material and device design innovations for achieving several important properties, including flexibility and stretchability, bioresorbability and biodegradability, self-healing properties, breathability, transparency, wireless communication capabilities, and high-density integration. We then went on to discuss the current research state of the use of such novel soft mechanical sensors in wearable and implantable applications, based on which future research needs were further discussed. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices Implantable Materials and Surgical Technologies > Nanomaterials and Implants.

Fibration of powdery materials

Non-destructive processing of powders into macroscopic materials with a wealth of structural and functional possibilities has immeasurable scientific significance and application value, yet remains a challenge using conventional processing techniques. Here we developed a universal fibration method, using two-dimensional cellulose as a mediator, to process diverse powdered materials into micro-/nanofibres, which provides structural support to the particles and preserves their own specialties and architectures. It is found that the self-shrinking force drives the two-dimensional cellulose and supported particles to pucker and roll into fibres, a gentle process that prevents agglomeration and structural damage of the powder particles. We demonstrate over 120 fibre samples involving various powder guests, including elements, compounds, organics and hybrids in different morphologies, densities and particle sizes. Customized fibres with an adjustable diameter and guest content can be easily constructed into high-performance macromaterials with various geometries, creating a library of building blocks for different fields of applications. Our fibration strategy provides a universal, powerful and non-destructive pathway bridging primary particles and macroapplications.

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.

Single Channel Based Interference-Free and Self-Powered Human-Machine Interactive Interface Using Eigenfrequency-Dominant Mechanism

The recent development of wearable devices is revolutionizing the way of human-machine interaction (HMI). Nowadays, an interactive interface that carries more embedded information is desired to fulfill the increasing demand in era of Internet of Things. However, present approach normally relies on sensor arrays for memory expansion, which inevitably brings the concern of wiring complexity, signal differentiation, power consumption, and miniaturization. Herein, a one-channel based self-powered HMI interface, which uses the eigenfrequency of magnetized micropillar (MMP) as identification mechanism, is reported. When manually vibrated, the inherent recovery of the MMP causes a damped oscillation that generates current signals because of Faraday's Law of induction. The time-to-frequency conversion explores the MMP-related eigenfrequency, which provides a specific solution to allocate diverse commands in an interference-free behavior even with one electric channel. A cylindrical cantilever model is built to regulate the MMP eigenfrequencies via precisely designing the dimensional parameters and material properties. It is shown that using one device and two electrodes, high-capacity HMI interface can be realized when the magnetic micropillars (MMPs) with different eigenfrequencies have been integrated. This study provides the reference value to design the future HMI system especially for situations that require a more intuitive and intelligent communication experience with high-memory demand.

A three-dimensional liquid diode for soft, integrated permeable electronics

Wearable electronics with great breathability enable a comfortable wearing experience and facilitate continuous biosignal monitoring over extended periods1-3. However, current research on permeable electronics is predominantly at the stage of electrode and substrate development, which is far behind practical applications with comprehensive integration with diverse electronic components (for example, circuitry, electronics, encapsulation)4-8. Achieving permeability and multifunctionality in a singular, integrated wearable electronic system remains a formidable challenge. Here we present a general strategy for integrated moisture-permeable wearable electronics based on three-dimensional liquid diode (3D LD) configurations. By constructing spatially heterogeneous wettability, the 3D LD unidirectionally self-pumps the sweat from the skin to the outlet at a maximum flow rate of 11.6 ml cm-2 min-1, 4,000 times greater than the physiological sweat rate during exercise, presenting exceptional skin-friendliness, user comfort and stable signal-reading behaviour even under sweating conditions. A detachable design incorporating a replaceable vapour/sweat-discharging substrate enables the reuse of soft circuitry/electronics, increasing its sustainability and cost-effectiveness. We demonstrated this fundamental technology in both advanced skin-integrated electronics and textile-integrated electronics, highlighting its potential for scalable, user-friendly wearable devices.

Programming mechanics in knitted materials, stitch by stitch

Knitting turns yarn, a 1D material, into a 2D fabric that is flexible, durable, and can be patterned to adopt a wide range of 3D geometries. Like other mechanical metamaterials, the elasticity of knitted fabrics is an emergent property of the local stitch topology and pattern that cannot solely be attributed to the yarn itself. Thus, knitting can be viewed as an additive manufacturing technique that allows for stitch-by-stitch programming of elastic properties and has applications in many fields ranging from soft robotics and wearable electronics to engineered tissue and architected materials. However, predicting these mechanical properties based on the stitch type remains elusive. Here we untangle the relationship between changes in stitch topology and emergent elasticity in several types of knitted fabrics. We combine experiment and simulation to construct a constitutive model for the nonlinear bulk response of these fabrics. This model serves as a basis for composite fabrics with bespoke mechanical properties, which crucially do not depend on the constituent yarn.

Speaking without vocal folds using a machine-learning-assisted wearable sensing-actuation system

Voice disorders resulting from various pathological vocal fold conditions or postoperative recovery of laryngeal cancer surgeries, are common causes of dysphonia. Here, we present a self-powered wearable sensing-actuation system based on soft magnetoelasticity that enables assisted speaking without relying on the vocal folds. It holds a lightweighted mass of approximately 7.2 g, skin-alike modulus of 7.83 × 105 Pa, stability against skin perspiration, and a maximum stretchability of 164%. The wearable sensing component can effectively capture extrinsic laryngeal muscle movement and convert them into high-fidelity and analyzable electrical signals, which can be translated into speech signals with the assistance of machine learning algorithms with an accuracy of 94.68%. Then, with the wearable actuation component, the speech could be expressed as voice signals while circumventing vocal fold vibration. We expect this approach could facilitate the restoration of normal voice function and significantly enhance the quality of life for patients with dysfunctional vocal folds.

Insights into Materials, Physics, and Applications in Flexible and Wearable Acoustic Sensing Technology

Sound plays a crucial role in the perception of the world. It allows to communicate, learn, and detect potential dangers, diagnose diseases, and much more. However, traditional acoustic sensors are limited in their form factors, being rigid and cumbersome, which restricts their potential applications. Recently, acoustic sensors have made significant advancements, transitioning from rudimentary forms to wearable devices and smart everyday clothing that can conform to soft, curved, and deformable surfaces or surroundings. In this review, the latest scientific and technological breakthroughs with insightful analysis in materials, physics, design principles, fabrication strategies, functions, and applications of flexible and wearable acoustic sensing technology are comprehensively explored. The new generation of acoustic sensors that can recognize voice, interact with machines, control robots, enable marine positioning and localization, monitor structural health, diagnose human vital signs in deep tissues, and perform organ imaging is highlighted. These innovations offer unique solutions to significant challenges in fields such as healthcare, biomedicine, wearables, robotics, and metaverse. Finally, the existing challenges and future opportunities in the field are addressed, providing strategies to advance acoustic sensing technologies for intriguing real-world applications and inspire new research directions.

Sandwich-Like Flexible Breathable Strain Sensor with Tunable Thermal Regulation Capability for Human Motion Monitoring

High-performance flexible strain sensors with synergistic and outstanding thermal regulation function are poised to make a significant impact on next-generation multifunctional sensors. However, it has long been intractable to optimize the sensing performance and high thermal conductivity simultaneously. Herein, a novel flexible sandwich-like strain sensor with advanced thermal regulation capability was prepared by assembling electrospun thermoplastic polyurethane (TPU) fibrous membrane, MXene layer, and TPU/boron nitride nanosheet (BNNS) composite films. The as-prepared sensor demonstrates a wide strain working range (∼100% strain), an ultrahigh gauge factor (2080.9), and a satisfactory reliability. Meanwhile, benefiting from the uniform dispersion and promising orientation of BNNSs in TPU composites, the sensor possesses a high thermal conductivity of 1.5 W·m-1·K-1, guaranteeing wearer comfort. Additionally, the unique structure endows the sensor with high stretchability, breathability, biocompatibility, and tunable electromagnetic interference shielding performances. Furthermore, an integrated wireless motion monitoring device based on this sensor is rationally designed. It exhibits a fast response time, a wide recognition range, and the ability to maintain skin temperature during prolonged physical activity. These encouraging findings provide a new and feasible approach to designing high-performance and versatile flexible strain sensors with broad applications in advanced wearable technology.

High-Performance All-Textile Triboelectric Nanogenerator toward Intelligent Sports Sensing and Biomechanical Energy Harvesting

Merging textiles with advanced energy harvesting technology via triboelectric effects brings novel insights into self-powered wearable textile electronics. However, fabrication of a comfortable textile-based triboelectric nanogenerator (TENG) with high outputs remains challenging. Herein, we propose a highly flexible, tailorable, single-electrode all-textile TENG (t-TENG) with both wear comfort and high outputs. A dielectric modulated porous composite coating containing poly(vinylidene fluoride)-hexafluoropropylene copolymer and barium titanate nanoparticles is constructed on conductive fabric to counterpart with highly positive glass fiber fabric through knotted yarn bonding, maintaining the superiority of textiles and strong triboelectricity. Through the synergistic optimization of charge storage via dielectric modulation and charge dissipation offset by electrical poling, remarkable outputs (261 V, 1.5 μA, and 12.7 nC) are obtained from a miniaturized, lightweight t-TENG (2 × 2 cm2, 130 mg) with an instantaneous power density of 654.48 mW·m-2, as well as excellent electrical robustness and device durability over 20,000 cycles. The t-TENG also exhibits a high sensitivity of 3.438 V·kPa-1 in the force region (1-10 N), demonstrating great potential in TENG-based intelligent sports sensing applications for monitoring and correcting the basketball shooting hand and foot arch posture. Furthermore, over 110 light-emitting diode arrays can be lightened up by gently tapping this miniaturized t-TENG. It also offers a wearable power source scheme through integrating the single-electrode device into clothing and utilizing the skin as the grounded electrode, revealing its ease of integration and biomechanical energy harvesting capability. This work provides an attractive paradigm for next-generation textile electronics with well-balanced device performance and wear comfort.

Stretchable Fibers with Highly Conductive Surfaces and Robust Electromechanical Performances for Electronic Textiles

One-dimensional conductive fibers that can simultaneously accommodate multiple deformations are crucial materials to enable next-generation electronic textile technologies for applications in the fields of healthcare, energy harvesting, human-machine interactions, etc. Stretchable conductive fibers (SCFs) with high conductivity on their external structure are important for their direct integration with other electronic components. However, the dilemma to achieve high conductivity and concurrently large stretchability is still quite challenging to resolve among conductive fibers with a conductive surface. Here, a three-layer coaxial conductive fiber, which can provide robust electrical performance under various deformations, is reported. A dual conducting structure with a semisolid metallic layer and a stretchable composite layer was designed in the fibers, providing exceptional conductivity and mechanical stability under mechanical strains. The conductive fiber achieved an initial conductivity of 2291.83 S cm-1 on the entire fiber and could be stretched up to 600% strains. With the excellent electromechanical properties of the SCF, we were able to demonstrate different electronic textile applications including physiological monitoring, neuromuscular electrical stimulation, and energy harvesting.

Iontronic Dynamic Sensor with Broad Bandwidth and Flat Frequency Response Using Controlled Preloading Strategy

Rapid advancements in human-machine interaction and voice biometrics impose desirability on soft mechanical sensors for sensing complex dynamic signals. However, existing soft mechanical sensors mainly concern quasi-static signals such as pressure and pulsation for health monitoring, limiting their applications in emerging wearable electronics. Here, we propose a hydrogel-based soft mechanical sensor that enables recording a wide range of dynamic signals relevant to humans by combining a preloading design strategy and iontronic sensing mechanism. The proposed sensor offers a two-orders-of-magnitude larger working bandwidth (up to 1000 Hz) than most of the reported soft mechanical sensors and meanwhile provides a high sensitivity (-23 dB) that surpasses the common commercial microphone. The amplitude-frequency characteristic of the proposed sensor can be precisely tuned to meet the desired requirement by adjusting the preloads and the parameters of the microstructured hydrogel. The sensor is capable of recording instrumental sounds with high fidelity from simple pure tones to melodic songs. Demonstration of a skin-mountable sensor used for human-voice-based remote control of a toy car shows great potential for applications in the voice user interface of human-machine interactions.

Ultrasensitive Soft Sensor from Anisotropic Conductive Biphasic Liquid Metal-Polymer Gels

Subtle vibrations, such as sound and ambient noises, are common mechanical waves that can transmit energy and signals for modern technologies such as robotics and health management devices. However, soft electronics cannot accurately distinguish ultrasmall vibrations owing to their extremely small pressure, complex vibration waveforms, and high noise susceptibility. This study successfully recognizes signals from subtle vibrations using a highly flexible anisotropic conductive gel (ACG) based on biphasic liquid metals. The relationships between the anisotropic structure, subtle vibrations, and electrical performance are investigated using rheological-electrical experiments. The refined anisotropic design successfully realized low-cost flexible electronics with ultrahigh sensitivity (Gauge Factor: 12787), extremely low detection limit (strain: 0.01%), and excellent frequency recognition accuracy (>99%), significantly surpassing those of current flexible sensors. The ultrasensitive flexible electronics in this study are beneficial for diverse advanced technologies such as acoustic engineering, wearable electronics, and intelligent robotics.

Well-defined in-textile photolithography towards permeable textile electronics

Textile-based wearable electronics have attracted intensive research interest due to their excellent flexibility and breathability inherent in the unique three-dimensional porous structures. However, one of the challenges lies in achieving highly conductive patterns with high precision and robustness without sacrificing the wearing comfort. Herein, we developed a universal and robust in-textile photolithography strategy for precise and uniform metal patterning on porous textile architectures. The as-fabricated metal patterns realized a high precision of sub-100 µm with desirable mechanical stability, washability, and permeability. Moreover, such controllable coating permeated inside the textile scaffold contributes to the significant performance enhancement of miniaturized devices and electronics integration through both sides of the textiles. As a proof-of-concept, a fully integrated in-textiles system for multiplexed sweat sensing was demonstrated. The proposed method opens up new possibilities for constructing multifunctional textile-based flexible electronics with reliable performance and wearing comfort.

Encoded sewing soft textile robots

Incorporating soft actuation with soft yet durable textiles could effectively endow the latter with active and flexible shape morphing and motion like mollusks and plants. However, creating highly programmable and customizable soft robots based on textiles faces a longstanding design and manufacturing challenge. Here, we report a methodology of encoded sewing constraints for efficiently constructing three-dimensional (3D) soft textile robots through a simple 2D sewing process. By encoding heterogeneous stretching properties into three spatial seams of the sewed 3D textile shells, nonlinear inflation of the inner bladder can be guided to follow the predefined spatial shape and actuation sequence, for example, tendril-like shape morphing, tentacle-like sequential manipulation, and bioinspired locomotion only controlled by single pressure source. Such flexible, efficient, scalable, and low-cost design and formation methodology will accelerate the development and iteration of soft robots and also open up more opportunities for safe human-robot interactions, tailored wearable devices, and health care.

Continuous Melt Spinning of Adaptable Covalently Cross-Linked Self-Healing Ionogel Fibers for Multi-Functional Ionotronics

Stretchable conductive fibers play key roles in electronic textiles, which have substantial improvements in terms of flexibility, breathability, and comfort. Compared to most existing electron-conductive fibers, ion-conductive fibers are usually soft, stretchable, and transparent, leading to increasing attention. However, the integration of desirable functions including high transparency, stretchability, conductivity, solvent resistance, self-healing ability, processability, and recyclability remains a challenge to be addressed. Herein, a new molecular strategy based on dynamic covalent cross-linking networks is developed to enable continuous melt spinning of the ionogel fiber with the aforementioned properties. As a proof of concept, adaptable covalently cross-linked ionogel fibers based on dimethylglyoximeurethane (DOU) groups (DOU-IG fiber) are prepared. The resultant DOU-IG fiber exhibited high transparency (>93%), tensile strength (0.76 MPa), stretchability (784%), and solvent resistance. Owing to the dynamic of DOU groups, the DOU-IG fiber shows high healing performance using near-infrared light. Taking advantage of DOU-IG fibers, multifunctional ionotronics with the integration of several desirable functionalities including sensor, triboelectric nanogenerator, and electroluminescent display are fabricated and used for motion monitoring, energy harvesting, and human-machine interaction. It is believed that these DOU-IG fibers are promising for fabricating the next generation of electronic textiles and other wearable electronics.

Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.

Axially Encoded Mechano-Metafiber Electronics by Local Strain Engineering

Multimaterial integration, such as soft elastic and stiff components, exhibits rich deformation and functional behaviors to meet complex needs. Integrating multimaterials in the level of individual fiber is poised to maximize the functional design capacity of smart wearable electronic textiles, but remains unfulfilled. Here, this work continuously integrates stiff and soft elastic components into single fiber to fabricate encoded mechano-metafiber by programmable microfluidic sequence spinning (MSS). The sequences with programmable modulus feature the controllable localization of strain along metafiber length. The mechano-metafibers feature two essential nonlinear deformation modes, which are local strain amplification and retardation. This work extends the sequence-encoded metafiber into fiber networks to exhibit greatly enhanced strain amplification and retardation capability in cascades. Local strain engineering enables the design of highly sensitive strain sensors, stretchable fiber devices to protect brittle components and the fabrication of high-voltage supercapacitors as well as axial electroluminescent arrays. The approach allows the scalably design of multimaterial metafibers with programmable localized mechanical properties for woven metamaterials, smart textiles, and wearable electronics.

Sustainable electronic textiles towards scalable commercialization

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.

High-Hole-Mobility Fiber Organic Electrochemical Transistors for Next-Generation Adaptive Neuromorphic Bio-Hybrid Technologies

The latest developments in fiber design and materials science are paving the way for fibers to evolve from parts in passive components to functional parts in active fabrics. Designing conformable, organic electrochemical transistor (OECT) structures using poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) fibers has excellent potential for low-cost wearable bioelectronics, bio-hybrid devices, and adaptive neuromorphic technologies. However, to achieve high-performance, stable devices from PEDOT:PSS fibers, approaches are required to form electrodes on fibers with small diameters and poor wettability, that leads to irregular coatings. Additionally, PEDOT:PSS-fiber fabrication needs to move away from small batch processing to roll-to-roll or continuous processing. Here, it is shown that synergistic effects from a superior electrode/organic interface, and exceptional fiber alignment from continuous processing, enable PEDOT:PSS fiber-OECTs with stable contacts, high µC* product (1570.5 F cm-1 V-1 s-1 ), and high hole mobility over 45 cm2 V-1 s-1 . Fiber-electrochemical neuromorphic organic devices (fiber-ENODes) are developed to demonstrate that the high mobility fibers are promising building blocks for future bio-hybrid technologies. The fiber-ENODes demonstrate synaptic weight update in response to dopamine, as well as a form factor closely matching the neuronal axon terminal.

Redesigning Natural Materials for Energy, Water, Environment, and Devices

The United Nations Framework Convention on Climate Change (UNFCCC) acknowledges that global cooperation is paramount to mitigate climate change and further warming. The global community is committed to renewable energy and natural materials to tackle this challenge for all humankind. The widespread use of natural materials is embraced as one such action to reach net-zero carbon emissions. Given the hierarchical framework and earth abundance, cellulose-based materials extend their negative carbon benefits to our daily products and accelerate our pace toward carbon neutrality. Here, we present an overview of recent developments of cellulose-based materials in upsurging applications in radiative cooling, thermal insulation, nanofluidics, and wearable devices. We also highlight various modifications and functionalized processes that transform massive amounts of cellulose into green products. The prosperous development of functionalized cellulose materials aligns with a circular economy. Expedited interdisciplinary fundamental investigations are expected to make fibrillated cellulose penetrate more into carbon downdraw at speed and scale.

Progress in wearable acoustical sensors for diagnostic applications

With extensive and widespread uses of miniaturized and intelligent wearable devices, continuously monitoring subtle spatial and temporal changes in human physiological states becomes crucial for daily healthcare and professional medical diagnosis. Wearable acoustical sensors and related monitoring systems can be comfortably applied onto human body with a distinctive function of non-invasive detection. This paper reviews recent advances in wearable acoustical sensors for medical applications. Structural designs and characteristics of the structural components of wearable electronics, including piezoelectric and capacitive micromachined ultrasonic transducer (i.e., pMUT and cMUT), surface acoustic wave sensors (SAW) and triboelectric nanogenerators (TENGs) are discussed, along with their fabrication techniques and manufacturing processes. Diagnostic applications of these wearable sensors for detection of biomarkers or bioreceptors and diagnostic imaging have further been discussed. Finally, main challenges and future research directions in these fields are highlighted.

Health Monitoring via Heart, Breath, and Korotkoff Sounds by Wearable Piezoelectret Patches

Real-time monitoring of vital sounds from cardiovascular and respiratory systems via wearable devices together with modern data analysis schemes have the potential to reveal a variety of health conditions. Here, a flexible piezoelectret sensing system is developed to examine audio physiological signals in an unobtrusive manner, including heart, Korotkoff, and breath sounds. A customized electromagnetic shielding structure is designed for precision and high-fidelity measurements and several unique physiological sound patterns related to clinical applications are collected and analyzed. At the left chest location for the heart sounds, the S1 and S2 segments related to cardiac systole and diastole conditions, respectively, are successfully extracted and analyzed with good consistency from those of a commercial medical device. At the upper arm location, recorded Korotkoff sounds are used to characterize the systolic and diastolic blood pressure without a doctor or prior calibration. An Omron blood pressure monitor is used to validate these results. The breath sound detections from the lung/ trachea region are achieved a signal-to-noise ration comparable to those of a medical recorder, BIOPAC, with pattern classification capabilities for the diagnosis of viable respiratory diseases. Finally, a 6×6 sensor array is used to record heart sounds at different locations of the chest area simultaneously, including the Aortic, Pulmonic, Erb's point, Tricuspid, and Mitral regions in the form of mixed data resulting from the physiological activities of four heart valves. These signals are then separated by the independent component analysis algorithm and individual heart sound components from specific heart valves can reveal their instantaneous behaviors for the accurate diagnosis of heart diseases. The combination of these demonstrations illustrate a new class of wearable healthcare detection system for potentially advanced diagnostic schemes.

Mechanically-Guided 3D Assembly for Architected Flexible Electronics

Architected flexible electronic devices with rationally designed 3D geometries have found essential applications in biology, medicine, therapeutics, sensing/imaging, energy, robotics, and daily healthcare. Mechanically-guided 3D assembly methods, exploiting mechanics principles of materials and structures to transform planar electronic devices fabricated using mature semiconductor techniques into 3D architected ones, are promising routes to such architected flexible electronic devices. Here, we comprehensively review mechanically-guided 3D assembly methods for architected flexible electronics. Mainstream methods of mechanically-guided 3D assembly are classified and discussed on the basis of their fundamental deformation modes (i.e., rolling, folding, curving, and buckling). Diverse 3D interconnects and device forms are then summarized, which correspond to the two key components of an architected flexible electronic device. Afterward, structure-induced functionalities are highlighted to provide guidelines for function-driven structural designs of flexible electronics, followed by a collective summary of their resulting applications. Finally, conclusions and outlooks are given, covering routes to achieve extreme deformations and dimensions, inverse design methods, and encapsulation strategies of architected 3D flexible electronics, as well as perspectives on future applications.

Fibrous wearable and implantable bioelectronics

Fibrous wearable and implantable devices have emerged as a promising technology, offering a range of new solutions for minimally invasive monitoring of human health. Compared to traditional biomedical devices, fibers offer a possibility for a modular design compatible with large-scale manufacturing and a plethora of advantages including mechanical compliance, breathability, and biocompatibility. The new generation of fibrous biomedical devices can revolutionize easy-to-use and accessible health monitoring systems by serving as building blocks for most common wearables such as fabrics and clothes. Despite significant progress in the fabrication, materials, and application of fibrous biomedical devices, there is still a notable absence of a comprehensive and systematic review on the subject. This review paper provides an overview of recent advancements in the development of fibrous wearable and implantable electronics. We categorized these advancements into three main areas: manufacturing processes, platforms, and applications, outlining their respective merits and limitations. The paper concludes by discussing the outlook and challenges that lie ahead for fiber bioelectronics, providing a holistic view of its current stage of development.

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array

Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide applications for early diagnosis. Here, we developed an intelligent blood pressure and cardiac function monitoring system based on a conformal and flexible strain sensor array and deep learning neural networks. The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.

Emerging Trends in Soft Electronics: Integrating Machine Intelligence with Soft Acoustic/Vibration Sensors

In the last decade, soft acoustic/vibration sensors have gained tremendous research interest due to their unique ability to detect broadband acoustic/vibration stimuli, potentializing futuristic applications including voice biometrics, voice-controlled human-machine-interfaces, electronic skin, and skin-mountable healthcare devices. Importantly, to benefit most from these sensors, it is inevitable to use machine learning (ML) to process their output signals; with ML, a more accurate and efficient interpretation of original data is possible. This paper is dedicated to offering an overview of recent advances empowering the development of soft acoustic/vibration sensors and their signal processing using ML. First, the key performance parameters of the sensors are discussed. Second, popular transduction mechanisms for the sensors are addressed, followed by an in-depth overview of each type, covering materials used, structural designs, and sensing performances. Third, potential applications of the sensors are elaborated and fourth, a thorough discussion on ML is conducted, exploring different types of ML, specific ML algorithms suitable for processing acoustic/vibration signals, and current trends in ML-assisted applications. Finally, the challenges and potential opportunities in soft acoustic/vibration sensor and ML research are revealed to offer new insights into future prospects in these fields.

Excellent-Moisture-Resistance Fluorinated Polyimide Composite Film and Self-Powered Acoustic Sensing

As a clean, sustainable energy source, sound can carry a wealth of information and play a huge role in the Internet of Things era. In recent years, triboelectric acoustic sensors have received increasing attention due to the advantages of self-power supply and high sensitivity. However, the triboelectric charge is susceptible to ambient humidity, which reduces the reliability of the sensor and limits the application scenarios significantly. In this paper, a highly moisture-resistant fluorinated polyimide composited with an amorphous fluoropolymer film was prepared. The charge injection performance, triboelectric performance, and moisture resistance of the composite film were investigated. In addition, we developed a self-powered, highly sensitive, and moisture-resistant porous-structure acoustic sensor based on contact electrification. The detection characteristics of the acoustic sensor are also obtained.

Active self-assembly of piezoelectric biomolecular films via synergistic nanoconfinement and in-situ poling

Piezoelectric biomaterials have attracted great attention owing to the recent recognition of the impact of piezoelectricity on biological systems and their potential applications in implantable sensors, actuators, and energy harvesters. However, their practical use is hindered by the weak piezoelectric effect caused by the random polarization of biomaterials and the challenges of large-scale alignment of domains. Here, we present an active self-assembly strategy to tailor piezoelectric biomaterial thin films. The nanoconfinement-induced homogeneous nucleation overcomes the interfacial dependency and allows the electric field applied in-situ to align crystal grains across the entire film. The β-glycine films exhibit an enhanced piezoelectric strain coefficient of 11.2 pm V^-1 and an exceptional piezoelectric voltage coefficient of 252 × 10^-3 Vm N^-1. Of particular significance is that the nanoconfinement effect greatly improves the thermostability before melting (192 °C). This finding offers a generally applicable strategy for constructing high-performance large-sized piezoelectric bio-organic materials for biological and medical microdevices.