Flexible Triboelectric Tactile Sensor Based on a Robust MXene/Leather Film for Human-Machine Interaction

Cellulose Nanofibril-Based Triboelectric Nanogenerators Enhanced by Isoreticular Metal-Organic Frameworks for Long-Term Motion Monitoring

Cellulose nanofibril (CNF) is a sort of novel nanomaterial directly extracted from plant resources, inheriting the advantages of cellulose as a cheap, green and renewable material for the development of new-generation eco-friendly electronics. In recent years, CNF-based triboelectric nanogenerator (TENG) has attracted increasing research interests, as the unique chemical, morphological, and electrical properties of CNF render the device with considerable flexibility, mechanical strength, and triboelectric output. In this study, we explore the use of isoreticular metal-organic frameworks (IRMOF) as functional filler to improve the performance of CNF based TENGs. Two types of IRMOFs that own the same network topology, namely IRMOF-1 and its aminated version IRMOF-3, are embedded with CNF to fabricated TENGs; their contribution to triboelectric output enhancement, including the roughness effect induced by large particles as well as the charge induction effect arisen from -NH2 groups, are discussed. The performance-enhanced CNF-based TENG with 0.6 wt.% of IRMOF-3 is utilized to harvest mechanical energy from human activities and charge commercial capacitors, from which the electrical energy is sufficient to light up light-emitting diodes (LEDs) and drive low-power electronic devices. In addition, a locomotor analysis system is established by assembling the above TENGs and capacitors into a 3 × 3 sensing array, which allowed signal extraction from each sensing unit to display a motion distribution map. These results demonstrate the great potential of CNF/IRMOF-based TENGs for development of self-powered sensing devices for long-term motion monitoring.

A Flexible Leather-Based Sensor via the Dual In Situ Growth of Conductive Materials for Human Motion Detection

Natural leather, with its mechanical strength, flexibility, and wearing comfort, is an ideal substrate material for wearable sensors. Currently, leather-based piezoresistive sensors still suffer from poor uniformity of conductive networks and weak interfacial interactions between conductive materials and leather, which limit their performance. Herein, it was innovatively proposed that polypyrrole (PPy) and silver nanoparticles (AgNPs) were sequentially grown in situ on the surface of collagen fibers (CFs). Then, the tanning process was carried out to produce a leather-based flexible wearable sensor (PPy/AgNPs-LBPS) with excellent conductivity, hydrothermal, and environmental stability. Specifically, the dual in situ growth and tanning process ensured the uniform penetration and distribution of conductive materials in leather substrates. Meanwhile, the hydrogen bonds between the conductive materials and CFs provided a firm combination to prevent the dropping of conductive materials. The synergistic effect of PPy and AgNPs enhanced the sensing performance of PPy/AgNPs-LBPS. It exhibited high sensitivity (0.65 kPa-1 and 3.76), a wide detection range (0-80 kPa and 0-100%), and fast response capability. These characteristics enabled PPy/AgNPs-LBPS to monitor subtle activities and large-scale movements of the human body in real time, as well as tactile perception. This thesis provides a new idea for the intelligent design of traditional leather materials, multidimensional perception in electronic skin, and advancements in artificial intelligence.

Iron-Supported Asymmetric Iontronic Pressure Sensors with High Sensitivity and Extended Linearity

Iontronic pressure sensors (IPSs) are emerging as promising candidates for integration into wearable electronics and healthcare monitoring systems due to their high sensitivity and low power consumption. However, achieving high sensitivity across a broad linear pressure range remains a significant challenge. This study presents a novel IPS device with an asymmetric sandwich structure, which includes a three-dimensional electrode made of nickel manganese oxide/carbon nanotubes (NMO/CNT) and an embedded iron needles ionic dielectric layer. The proposed device demonstrates exceptional linearity over 1700 kPa, with a sensitivity exceeding 7700 kPa-1. It exhibits rapid response and recovery times in the millisecond range and maintains a consistent capacitive response over 15,000 loading-unloading cycles. Moreover, the device enables noncontact sensing in response to magnetic field variations, broadening its potential applications. The innovative IPS design effectively balances high sensitivity and a wide linear pressure range, rendering it suitable for various applications such as nonverbal communication aids and healthcare monitoring systems.

Comprehensive Insights on MXene-Based TENGs: from Structures, Functions to Applications

The rapid advancement of triboelectric nanogenerators (TENGs) has introduced a transformative approach to energy harvesting and self-powered sensing in recent years. Nonetheless, the untapped potential of TENGs in practical scenarios necessitates multiple strategies like material selections and structure designs to enhance their output performance. Given the various superior properties, MXenes, a kind of novel 2D materials, have demonstrated great promise in enhancing TENG functionality. Here, this review comprehensively delineates the advantages of incorporating MXenes into TENGs, majoring in six pivotal aspects. First, an overview of TENGs is provided, stating their theoretical foundations, working modes, material considerations, and prevailing challenges. Additionally, the structural characteristics, fabrication methodologies, and family of MXenes, charting their developmental trajectory are highlighted. The selection of MXenes as various functional layers (negative and positive triboelectric layer, electrode layer) while designing TENGs is briefed. Furthermore, the distinctive advantages of MXene-based TENGs and their applications are emphasized. Last, the existing challenges are highlighted, and the future developing directions of MXene-based TENGs are forecasted.

Triboelectric nanogenerator for high-entropy energy, self-powered sensors, and popular education

Triboelectric nanogenerator (TENG) has become a promising option for high-entropy energy harvesting and self-powered sensors because of their ability to combine the effects of contact electrification and electrostatic induction to effectively convert mechanical energy into electric power or signals. Here, the theoretical origin of TENG, strategies for high-performance TENG, and its applications in high-entropy energy, self-powered sensors, and blue energy are comprehensively introduced on the basis of the fundamental science and principle of TENG. Besides, a series of work in popular science education for TENG that includes numerous scientific and technological products from our science education base, Maxwell Science+, is emphatically introduced. This topic provides an angle and notable insights into the development of TENG.

Recent Progress on Flexible Self-Powered Tactile Sensing Platforms for Health Monitoring and Robotics

Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self-powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e-skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self-powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self-powered tactile sensing systems are discussed.

A Signal Amplitude-Insensitive Triboelectric Touch Panel with a Significantly Reduced Signal Channel and Deep-Learning-Enhanced Robustness

The self-powered triboelectric touch panel has garnered considerable research attention due to its potential to reduce system energy consumption and its applications in human-machine interfaces, e-skin, and the Internet of Things. Current methods for achieving triboelectric-based touch positioning in an M × N detection pixel array typically require signal amplitude comparison across at least M + N signal channels, thereby limiting lightweight design possibilities. In contrast, our novel "resistor ladder" approach necessitates only 4 signal channels for touch positioning. This method leverages a lookup table correlating touch positions with amplitude ratios from different channels, rendering it insensitive to signal amplitude and significantly enhancing robustness. We fabricated a transparent touch panel using PET tribomaterial, where the surface roughness was enhanced through plasma treatment. The panel successfully demonstrated touch positioning for 128 taps within a 4 × 4 pixel detection array and sliding positioning using a predefined lookup table. To further enhance device robustness, a 2D convolutional neural network was implemented, which achieved an impressive touch positioning accuracy of 97.7% even under artificially introduced signal defects. This study represents an initial exploration of amplitude-insensitive touch and sliding positioning methods, significantly reducing the number of required signal channels and enhancing the robustness of triboelectric touch panels.

Highly Sensitive Flexible Capacitive Pressure Sensor Based on a Multicross-Linked Dual-Network Ionic Hydrogel for Blood Pressure Monitoring Applications

Flexible capacitive pressure sensors based on ionic hydrogels (IHs) have garnered significant attention in the field of wearable technology. However, the vulnerability of traditional single-network hydrogels to mechanical damage and the complexity associated with preparing double-network hydrogels present challenges in developing a highly sensitive, easily prepared, and durable IH-based flexible capacitive pressure sensor. This study introduces a novel multicross-linked dual-network IH achieved through the physical and chemical cross-linking of polymers polyvinyl alcohol (PVA) and chitosan (CS), ionic solution H3PO4, and cross-linking agent gum arabic. Flexible capacitive pressure sensors, characterized by high sensitivity and a broad pressure range, are fabricated by employing mesh as templates to design cut-corner cube microstructures with high uniformity and controllability on the IHs. The sensor exhibits high sensitivity across a wide pressure range (0-290 kPa) and with excellent features such as high resolution (∼1.3 Pa), fast response-recovery time (∼11 ms), and repeatable compression stability at 25 kPa (>2000 cycles). The IHs as a dielectric layer demonstrate long-term water retention properties, enabling exposure to air for up to 100 days. Additionally, the developed sensor shows the ability to accurately measure the pulse wave within the small pressure range. By combining the pulse wave acquired by the sensor with a trained neural network model, we achieve successful blood pressure (BP) prediction, meeting the standards set by the Association for the Advancement of Medical Instrumentation and the British Hypertension Society. Ultimately, the sensor proposed in this study holds promising prospects for broad applications in high-precision wearable medical electronic devices.

Structure-Foldable and Performance-Tailorable PI Paper-Based Triboelectric Nanogenerators Processed and Controlled by Laser-Induced Graphene

Laser-induced graphene (LIG) technology has provided a new manufacturing strategy for the rapid and scalable assembling of triboelectric nanogenerators (TENG). However, current LIG-based TENG commonly rely on polymer films, e.g., polyimide (PI) as both friction material and carbon precursor of electrodes, which limit the structural diversity and performance escalation due to its incapability of folding and creasing. Using specialized PI paper composed of randomly distributed PI fibers to substantially enhance its foldability, this work creates a new type of TENG, which are structurally foldable and stackable, and performance tailorable. First, by systematically investigating the laser power-regulated performance of single-unit TENG, the open-circuit voltage can be effectively improved. By further exploiting the folding process, multiple TENG units can be assembled together to form multi-layered structures to continuously expand the open-circuit voltage from 5.3 to 34.4 V cm-2, as the increase of friction units from 1 to 16. Last, by fully utilizing the unique structure and performance, representative energy-harvesting and smart-sensing applications are demonstrated, including a smart shoe to recognize running motions and power LEDs, a smart leaf to power a thermometer by wind, a matrix sensor to recognize writing trajectories, as well as a smart glove to recognize different objects.

Flexible wide-range multidimensional force sensors inspired by bones embedded in muscle

Flexible sensors have been widely studied for use in motion monitoring, human‒machine interactions (HMIs), personalized medicine, and soft intelligent robots. However, their practical application is limited by their low output performance, narrow measuring range, and unidirectional force detection. Here, to achieve flexibility and high performance simultaneously, we developed a flexible wide-range multidimensional force sensor (FWMFS) similar to bones embedded in muscle structures. The adjustable magnetic field endows the FWMFS with multidimensional perception for detecting forces in different directions. The multilayer stacked coils significantly improved the output from the μV to the mV level while ensuring FWMFS miniaturization. The optimized FWMFS exhibited a high voltage sensitivity of 0.227 mV/N (0.5-8.4 N) and 0.047 mV/N (8.4-60 N) in response to normal forces ranging from 0.5 N to 60 N and could detect lateral forces ranging from 0.2-1.1 N and voltage sensitivities of 1.039 mV/N (0.2-0.5 N) and 0.194 mV/N (0.5-1.1 N). In terms of normal force measurements, the FWMFS can monitor finger pressure and sliding trajectories in response to finger taps, as well as measure plantar pressure for assessing human movement. The plantar pressure signals of five human movements collected by the FWMFS were analyzed using the k-nearest neighbors classification algorithm, which achieved a recognition accuracy of 92%. Additionally, an artificial intelligence biometric authentication system is being developed that classifies and recognizes user passwords. Based on the lateral force measurement ability of the FWMFS, the direction of ball movement can be distinguished, and communication systems such as Morse Code can be expanded. This research has significant potential in intelligent sensing and personalized spatial recognition.

The Need for Smart Materials in an Expanding Smart World: MXene-Based Wearable Electronics and Their Advantageous Applications

As a result of the transformation of inflexible electronic structures into flexible and stretchy devices, wearable electronics now provide great advantages in a variety of fields, including mobile healthcare sensing and monitoring, human-machine interfaces, portable energy storage and harvesting, and more. Because of their enriched surface functionalities, large surface area, and high electrical conductivity, transition metal nitrides and carbides (also known as MXenes) have recently come to be extensively considered as a group of functioning two-dimensional nanomaterials as well as exceptional fundamental elements for forming flexible electronics devices. This Review discusses the most recent advancements that have been made in the field of MXene-enabled flexible electronics for wearable electronics. The emphasis is placed on extensively established nonstructural features in order to highlight some MXene-enabled electrical devices that were constructed on a nanometric scale. These attributes include devices configured in three dimensions: printed materials, bioinspired structures, and textile and planar substrates. In addition, sample applications in electromagnetic interference (EMI) shielding, energy, healthcare, and humanoid control of machinery illustrate the exceptional development of these nanodevices. The increasing potential of MXene nanoparticles as a new area in next-generation wearable electronic technologies is projected in this Review. The design challenges associated with these electronic devices are also discussed, and possible solutions are presented.

Triboelectric Contact Localization Electronics: A Systematic Review

The growing demand from the extended reality and wearable electronics market has led to an increased focus on the development of flexible human-machine interfaces (HMI). These interfaces require efficient user input acquisition modules that can realize touch operation, handwriting input, and motion sensing functions. In this paper, we present a systematic review of triboelectric-based contact localization electronics (TCLE) which play a crucial role in enabling the lightweight and long-endurance designs of flexible HMI. We begin by summarizing the mainstream working principles utilized in the design of TCLE, highlighting their respective strengths and weaknesses. Additionally, we discuss the implementation methods of TCLE in realizing advanced functions such as sliding motion detection, handwriting trajectory detection, and artificial intelligence-based user recognition. Furthermore, we review recent works on the applications of TCLE in HMI devices, which provide valuable insights for guiding the design of application scene-specified TCLE devices. Overall, this review aims to contribute to the advancement and understanding of TCLE, facilitating the development of next-generation HMI for various applications.

Highly Compressible 3D-Printed Soft Magnetoelastic Sensors for Human-Machine Interfaces

Incorporating perception into robots or objects holds great potential to revolutionize daily human life. To achieve this, critical factors include the design of an integrable three-dimensional (3D) soft sensor with self-powering capability, a wide working range, and tuneable functionalities. Here, we introduce a highly compressible 3D-printed soft magnetoelastic sensor with a wide strain sensing range. Inspired by the lattice metamaterial, which offers a highly porous structure with tuneable mechanical properties, we realized a remarkably compliant 3D self-powering sensor. Using magnetoelastic composite materials and 3D printing combined with sacrificial molding, a broad design space for constituent materials and structures is investigated, allowing for tuneable mechanical properties and sensor performances. These sensors are successfully integrated with two robotic systems as the robot operation and perception units, enabling robot control and recognition of diverse physical interactions with a user. Overall, we believe that this work represents a cornerstone for compliant 3D self-powered soft sensors, giving impetus to the development of advanced human-machine interfaces.

Emerging Functional Polymer Composites for Tactile Sensing

In recent years, extensive research has been conducted on the development of high-performance flexible tactile sensors, pursuing the next generation of highly intelligent electronics with diverse potential applications in self-powered wearable sensors, human-machine interactions, electronic skin, and soft robotics. Among the most promising materials that have emerged in this context are functional polymer composites (FPCs), which exhibit exceptional mechanical and electrical properties, enabling them to be excellent candidates for tactile sensors. Herein, this review provides a comprehensive overview of recent advances in FPCs-based tactile sensors, including the fundamental principle, the necessary property parameter, the unique device structure, and the fabrication process of different types of tactile sensors. Examples of FPCs are elaborated with a focus on miniaturization, self-healing, self-cleaning, integration, biodegradation, and neural control. Furthermore, the applications of FPC-based tactile sensors in tactile perception, human-machine interaction, and healthcare are further described. Finally, the existing limitations and technical challenges for FPCs-based tactile sensors are briefly discussed, offering potential avenues for the development of electronic products.