Multifunctional Meta-Tribomaterial Nanogenerators for Energy Harvesting and Active Sensing

Advanced Ultrasound Energy Transfer Technologies using Metamaterial Structures

Wireless energy transfer (WET) based on ultrasound-driven generators with enormous beneficial functions, is technologically in progress by the valuation of ultrasonic metamaterials (UMMs) in science and engineering domains. Indeed, novel metamaterial structures can develop the efficiency of mechanical and physical features of ultrasound energy receivers (US-ETs), including ultrasound-driven piezoelectric and triboelectric nanogenerators (US-PENGs and US-TENGs) for advantageous applications. This review article first summarizes the fundamentals, classification, and design engineering of UMMs after introducing ultrasound energy for WET technology. In addition to addressing using UMMs, the topical progress of innovative UMMs in US-ETs is conceptually presented. Moreover, the advanced approaches of metamaterials are reported in the categorized applications of US-PENGs and US-TENGs. Finally, some current perspectives and encounters of UMMs in US-ETs are offered. With this objective in mind, this review explores the potential revolution of reliable integrated energy transfer systems through the transformation of metamaterials into ultrasound-driven active mediums for generators.

Tailoring Stress-Strain Curves of Flexible Snapping Mechanical Metamaterial for On-Demand Mechanical Responses via Data-Driven Inverse Design

By incorporating soft materials into the architecture, flexible mechanical metamaterials enable promising applications, e.g., energy modulation, and shape morphing, with a well-controllable mechanical response, but suffer from spatial and temporal programmability towards higher-level mechanical intelligence. One feasible solution is to introduce snapping structures and then tune their responses by accurately tailoring the stress-strain curves. However, owing to the strongly coupled nonlinearity of structural deformation and material constitutive model, it is difficult to deduce their stress-strain curves using conventional ways. Here, a machine learning pipeline is trained with the finite element analysis data that considers those strongly coupled nonlinearities to accurately tailor the stress-strain curves of snapping metamaterialfor on-demand mechanical response with an accuracy of 97.41%, conforming well to experiment. Utilizing the established approach, the energy absorption efficiency of the snapping-metamaterial-based device can be tuned within the accessible range to realize different rebound heights of a falling ball, and soft actuators can be spatially and temporally programmed to achieve synchronous and sequential actuation with a single energy input. Purely relying on structure designs, the accurately tailored metamaterials increase the devices' tunability/programmability. Such an approach can potentially extend to similar nonlinear scenarios towards predictable or intelligent mechanical responses.

Mechanical Characterization of Multifunctional Metal-Coated Polymer Lattice Structures

Metal-coated lattice structures hold significant promise for customizing mechanical properties in diverse industrial applications, including the mechanical arms of unmanned aerial vehicles. However, their intricate geometries pose computational challenges, resulting in time-intensive and costly numerical evaluations. This study introduces a parameterization-based multiscale method to analyze body-centered cubic lattice structures with metal coatings. We establish the validity and precision of our proposed method with a comparative analysis of numerical results at the Representative Volume Element (RVE) scale and experimental findings, specifically addressing both elastic tensile and bending stiffness. Furthermore, we showcase the method's accuracy in interpreting the bending stiffness of coated lattice structures using a homogenized material-based solid model, underscoring its effectiveness in predicting the elastic properties of such structures. In exploring the mechanical characterization of coated lattice structures, we unveil positive correlations between elastic tensile stiffness and both coating thickness and strut diameter. Additionally, the metal coating significantly enhances the structural elastic bending stiffness multiple times over. The diverse failure patterns observed in coated lattices under tensile and bending loads primarily stem from varied loading-induced stress states rather than external factors. This work not only mitigates computational challenges but also successfully bridges the gap between mesoscale RVE mechanical properties and those at the global structural scale.

Maximizing Triboelectric Nanogenerators by Physics-Informed AI Inverse Design

Triboelectric nanogenerators offer an environmentally friendly approach to harvesting energy from mechanical excitations. This capability has made them widely sought-after as an efficient, renewable, and sustainable energy source, with the potential to decrease reliance on traditional fossil fuels. However, developing triboelectric nanogenerators with specific output remains a challenge mainly due to the uncertainties associated with their complex designs for real-life applications. Artificial intelligence-enabled inverse design is a powerful tool to realize performance-oriented triboelectric nanogenerators. This is an emerging scientific direction that can address the concerns about the design and optimization of triboelectric nanogenerators leading to a next generation nanogenerator systems. This perspective paper aims at reviewing the principal analysis of triboelectricity, summarizing the current challenges of designing and optimizing triboelectric nanogenerators, and highlighting the physics-informed inverse design strategies to develop triboelectric nanogenerators. Strategic inverse design is particularly discussed in the contexts of expanding the four-mode analytical models by physics-informed artificial intelligence, discovering new conductive and dielectric materials, and optimizing contact interfaces. Various potential development levels of artificial intelligence-enhanced triboelectric nanogenerators are delineated. Finally, the potential of physics-informed artificial intelligence inverse design to propel triboelectric nanogenerators from prototypes to multifunctional intelligent systems for real-life applications is discussed.

Data-Driven Design for Metamaterials and Multiscale Systems: A Review

Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that are assembled into multiscale systems, they hold great promise for realizing next-generation devices with exceptional, often exotic, functionalities. However, the vast design space and intricate structure-property relationships pose significant challenges in their design. A compelling paradigm that could bring the full potential of metamaterials to fruition is emerging: data-driven design. This review provides a holistic overview of this rapidly evolving field, emphasizing the general methodology instead of specific domains and deployment contexts. Existing research is organized into data-driven modules, encompassing data acquisition, machine learning-based unit cell design, and data-driven multiscale optimization. The approaches are further categorized within each module based on shared principles, analyze and compare strengths and applicability, explore connections between different modules, and identify open research questions and opportunities.

Ultra-Stretchable Kirigami Piezo-Metamaterials for Sensing Coupled Large Deformations

Mechanical metamaterials are known for their prominent mechanical characteristics such as programmable deformation that are due to periodic microstructures. Recent research trends have shifted to utilizing mechanical metamaterials as structural substrates to integrate with functional materials for advanced functionalities beyond mechanical, such as active sensing. This study reports on the ultra-stretchable kirigami piezo-metamaterials (KPM) for sensing coupled large deformations caused by in- and out-of-plane displacements using the lead zirconate titanate (PZT) and barium titanate (BaTiO3 ) composite films. The KPM are fabricated by uniformly compounding and polarizing piezoelectric particles (i.e., PZT and BaTiO3 ) in silicon rubber and structured by cutting the piezoelectric rubbery films into ligaments. Characterizes the electrical properties of the KPM and investigates the bistable mechanical response under the coupled large deformations with the stretching ratio up to 200% strains. Finally, the PZT KPM sensors are integrated into wireless sensing systems for the detection of vehicle tire bulge, and the non-toxic BaTiO3 KPM are applied for human posture monitoring. The reported kirigami piezo-metamaterials open an exciting venue for the control and manipulation of mechanically functional metamaterials for active sensing under complex deformation scenarios in many applications.

Mechanical metamaterials and beyond

Mechanical metamaterials enable the creation of structural materials with unprecedented mechanical properties. However, thus far, research on mechanical metamaterials has focused on passive mechanical metamaterials and the tunability of their mechanical properties. Deep integration of multifunctionality, sensing, electrical actuation, information processing, and advancing data-driven designs are grand challenges in the mechanical metamaterials community that could lead to truly intelligent mechanical metamaterials. In this perspective, we provide an overview of mechanical metamaterials within and beyond their classical mechanical functionalities. We discuss various aspects of data-driven approaches for inverse design and optimization of multifunctional mechanical metamaterials. Our aim is to provide new roadmaps for design and discovery of next-generation active and responsive mechanical metamaterials that can interact with the surrounding environment and adapt to various conditions while inheriting all outstanding mechanical features of classical mechanical metamaterials. Next, we deliberate the emerging mechanical metamaterials with specific functionalities to design informative and scientific intelligent devices. We highlight open challenges ahead of mechanical metamaterial systems at the component and integration levels and their transition into the domain of application beyond their mechanical capabilities.

Noncontact liquid-solid nanogenerators as self-powered droplet sensors

Liquid-solid triboelectric nanogenerators (L-S TENGs) can generate corresponding electrical signal responses through the contact separation of droplets and dielectrics and have a wide range of applications in energy harvesting and self-powered sensing. However, the contact between the droplet and the electret will cause the contact L-S TENG's performance degradation or even failure. Here we report a noncontact triboelectric nanogenerator (NCLS-TENG) that can effectively sense droplet stimuli without contact with droplets and convert them into electrical energy or corresponding electrical signals. Since there is no contact between the droplet and the dielectric, it can continuously and stably generate a signal output. To verify the feasibility of NCLS-TENG, we demonstrate the modified murphy's dropper as a smart infusion monitoring system. The smart infusion monitoring system can effectively identify information such as the type, concentration, and frequency of droplets. NCLS-TENG show great potential in smart medical, smart wearable and other fields.

Multifunctional Nanogenerator-Integrated Metamaterial Concrete Systems for Smart Civil Infrastructure

Creating multifunctional concrete materials with advanced functionalities and mechanical tunability is a critical step toward reimagining the traditional civil infrastructure systems. Here, the concept of nanogenerator-integrated mechanical metamaterial concrete is presented to design lightweight and mechanically tunable concrete systems with energy harvesting and sensing functionalities. The proposed metamaterial concrete systems are created via integrating the mechanical metamaterial and nano-energy-harvesting paradigms. These advanced materials are composed of reinforcement auxetic polymer lattices with snap-through buckling behavior fully embedded inside a conductive cement matrix. We rationally design their composite structures to induce contact-electrification between the layers under mechanical excitations/triggering. The conductive cement enhanced with graphite powder serves as the electrode in the proposed systems, while providing the desired mechanical performance. Experimental studies are conducted to investigate the mechanical and electrical properties of the designed prototypes. The metamaterial concrete systems are tuned to achieve up to 15% compressibility under cycling loading. The power output of the nanogenerator-integrated metamaterial concrete prototypes reaches 330 µW. Furthermore, the self-powered sensing functionality of the nanogenerator concrete systems for distributed health monitoring of large-scale concrete structures is demonstrated. The metamaterial concrete paradigm can possibly enable the design of smart civil infrastructure systems with a broad range of advanced functionalities.

Electrostatic Induction Nanogenerator Boosted by One-Dimensional Metastructure: Application to Energy and Information Transmitting Smart Tag System

The recent application of the internet of things demands the ubiquitous utilization of data and electrical power. Even with the development of a wide variety of energy-harvesting technologies, few studies have reported a device transporting electrical energy and data simultaneously. This paper reports an electrostatic induction nanogenerator (ESING) consisting of a one-dimensional metastructure that can modulate the output voltage based on the resonance of ultrasound waves to transmit energy and data simultaneously. The ESING device is fabricated using electronegative poly(vinylidene fluoride) (PVDF) membrane using a phase inversion process. The output voltage from the ESING device exhibits periodic resonant peaks as the gap between the PVDF membrane and the Al electrode changes, showing an up to 35-fold difference between the maximum and minimum output voltages depending on the resonance state. The energy and electrical signal can be transmitted simultaneously in free space because the ESING converts energy from high-frequency ultrasound waves. This paper provides proof of concept for a data and energy-transferable smart tag device based on ESING devices exhibiting resonant and non-resonant states. A device consisting of four ESINGs for a 4-bit signal is implemented to demonstrate 16 signals.

Biomechanical Sensing Systems for Cardiac Activity Monitoring

Cardiovascular disease is consistently ranked high among the causes of death on a global scale. Monitoring of cardiovascular signs throughout the course of a long period of time and in real time is necessary in order to discover anomalies and begin early intervention at the appropriate time. To this purpose, a significant amount of interest among researchers has been directed toward the creation of flexible sensors that may be worn or implanted and are capable of constant, immediate observation of a variety of main physiological indicators. The real-time readings of the heart and arteries' pressure fluctuations can be reflected directly by mechanical sensors, which are one of the many types of sensors. Potential benefits of mechanical sensors include excellent accuracy and considerable versatility. Capacitive, piezoresistive, piezoelectric, and triboelectric principles are the foundations of the four types of mechanical sensors that are discussed in this article as recent developments for the purpose of monitoring the cardiovascular system. The biomechanical systems that are present in the cardiovascular system are then detailed, along with their monitoring, and this includes blood and endocardial pressure, pulse wave, and heart rhythm. In conclusion, we examine the usefulness of the use of continuous health monitoring for the treatment of vascular disease and highlight the difficulties associated with its translation into clinical practice.

Emerging Deep-Sea Smart Composites: Advent, Performance, and Future Trends

To solve the global shortage of land and offshore resources, the development of deep-sea resources has become a popular topic in recent decades. Deep-sea composites are widely used materials in abyssal resources extraction, and corresponding marine exploration vehicles and monitoring devices for deep-sea engineering. This article firstly reviews the existing research results and limitations of marine composites and equipment or devices used for resource extraction. By combining the research progress of smart composites, deep-sea smart composite materials with the three characteristics of self-diagnosis, self-healing, and self-powered are proposed and relevant studies are summarized. Finally, the review summarizes research challenges for the materials, and looks forward to the development of new composites and their practical application in conjunction with the progress of composites disciplines and AI techniques.

Design of a Self-Powered System by Wind-Driven Triboelectric Nanogenerator Based on 0.94(Bi0.5 Na0.5 )TiO3 -0.06Ba(Zr0.25 Ti0.75 )O3 /Polyvinylidene Fluoride (BNT-BZT/PVDF) Composites

The portable power bank as an energy storage device has received tremendous attention while the limited capacity and periodical charging are critical issues. Here, a self-charging power system (SCPS) consisting of a 0.94(Bi_0.5 Na_0.5 )TiO₃ -0.06Ba(Zr_0.25 Ti_0.75 )O₃ /polyvinylidenefluoride (BNT-BZT/PVDF) composite film-based triboelectric nanogenerator (TENG) is designed as a wind energy harvester and an all-solid-state lithium-ion battery (ASSLIB) as the energy storage device. The optimized TENG can provide an output voltage of ≈400 V, a current of ≈45 µA, and a maximum power of ≈10.65 mW, respectively. The ASSLIB assembled by LiNiCoMnO₂ as the cathode, NiCo₂ S₄ as the anode, and Li₇ La₃ Zr₂ O₁₂ as the solid electrolyte can maintain a discharge capacity of 51.3 µAh after 200 cycles with a Coulombic efficiency of 98.5%. Particularly, an ASSLIB can be easily charged up to 3.8 V in 58 min using the wind-driven TENG, which can continuously drive 12 parallel-connected white light-emitting diodes (LEDs) or a pH meter. This work demonstrates the development of low-cost, high-performance and high-safety SCPSs and their large-scale practical application in self-powered microelectronic devices.

Highly Thermally Conductive Bimorph Structures for Low-Grade Heat Energy Harvester and Energy-Efficient Actuators

Low-power electronics are urgently needed for various emerging technologies, e.g., actuators as signal transducers and executors. Collecting energy from ubiquitous low-grade heat sources (T < 100 °C) as an uninterrupted power supply for low-power electronics is highly desirable. However, the majority of energy-harvesting systems are not capable of collecting low-grade heat energy in an efficient and constant manner. Limited by materials and driving mode, fabrications of low-power and energy-efficient actuators are still challenging. Here, highly thermally conductive bimorph structures based on graphene/poly(dimethylsiloxane) (PDMS) structures have been fabricated as low-grade heat energy harvesters and energy-efficient actuators. Regular temperature fluctuations on bimorph structures can be controlled by nonequilibrium heat transfer, leading to stable and self-sustained thermomechanical cycles. By coupling ferroelectric poly(vinylidene fluoride) with bimorph structures, uninterrupted thermomechanoelectrical energy conversion has been achieved from the low-grade heat source. Utilizing the rapid thermal transport capability, multifinger soft grippers are assembled with bimorph actuators, demonstrating fast response, large displacement, and adaptive grip when driven by low-temperature heaters.

Architected Materials for Additive Manufacturing: A Comprehensive Review

One of the main advantages of Additive Manufacturing (AM) is the ability to produce topologically optimized parts with high geometric complexity. In this context, a plethora of architected materials was investigated and utilized in order to optimize the 3D design of existing parts, reducing their mass, topology-controlling their mechanical response, and adding remarkable physical properties, such as high porosity and high surface area to volume ratio. Thus, the current re-view has been focused on providing the definition of architected materials and explaining their main physical properties. Furthermore, an up-to-date classification of cellular materials is presented containing all types of lattice structures. In addition, this research summarized the developed methods that enhance the mechanical performance of architected materials. Then, the effective mechanical behavior of the architected materials was investigated and compared through the existing literature. Moreover, commercial applications and potential uses of the architected materials are presented in various industries, such as the aeronautical, automotive, biomechanical, etc. The objectives of this comprehensive review are to provide a detailed map of the existing architected materials and their mechanical behavior, explore innovative techniques for improving them and highlight the comprehensive advantages of topology optimization in industrial applications utilizing additive manufacturing and novel architected materials.

Mechanical Sensors for Cardiovascular Monitoring: From Battery-Powered to Self-Powered

Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.

Mechanical integrated circuit materials

Recent developments in autonomous engineered matter have introduced the ability for intelligent materials to process environmental stimuli and functionally adapt^1-4. To formulate a foundation for such an engineered living material paradigm, researchers have introduced sensing^5-11 and actuating^12-16 functionalities in soft matter. Yet, information processing is the key functional element of autonomous engineered matter that has been recently explored through unconventional techniques with limited computing scalability^17-20. Here we uncover a relation between Boolean mathematics and kinematically reconfigurable electrical circuits to realize all combinational logic operations in soft, conductive mechanical materials. We establish an analytical framework that minimizes the canonical functions of combinational logic by the Quine-McCluskey method, and governs the mechanical design of reconfigurable integrated circuit switching networks in soft matter. The resulting mechanical integrated circuit materials perform higher-level arithmetic, number comparison, and decode binary data to visual representations. We exemplify two methods to automate the design on the basis of canonical Boolean functions and individual gate-switching assemblies. We also increase the computational density of the materials by a monolithic layer-by-layer design approach. As the framework established here leverages mathematics and kinematics for system design, the proposed approach of mechanical integrated circuit materials can be realized on any length scale and in a wide variety of physics.

Multifunctional Triboelectric Nanogenerator-enabled Structural Elements for Next Generation Civil Infrastructure Monitoring Systems

There is a critical shortage in research needed to explore a new class of multifunctional structural components that respond to their environment, empower themselves and self-monitor their condition. Here, we propose the novel concept of triboelectric nanogenerator-enabled structural elements (TENG-SEs) to build the foundation for the next generation civil infrastructure systems with intrinsic sensing and energy harvesting functionalities. In order to validate the proposed concept, we develop proof-of-concept multifunctional composite rebars with built-in triboelectric nanogenerator mechanisms. The developed prototypes function as structural reinforcements, nanogenerators and distributed sensing mediums under external mechanical vibrations. Experiential and theoretical studies are performed to verify the electrical and mechanical performance of the developed self-powering and self-sensing composite structural components. We demonstrate the capability of the embedded structural elements to detect damage patterns in concrete beams at multiscale. Finally, we discuss how this new class of TENG-SEs could revolutionize the large-scale distributed monitoring practices in civil infrastructure and construction fields.

Mechanical Metamaterials Gyro-Structure Piezoelectric Nanogenerators for Energy Harvesting under Quasi-Static Excitations in Ocean Engineering

In this study, we develop the mechanical metamaterial-enabled piezoelectric nanogenerators in the gyro-structure, which is reported as a novel green energy solution to generate electrical power under quasi-static excitations (i.e., <1 Hz) such as in the ocean environment. The plate-like mechanical metamaterials are designed with a hexagonal corrugation to improve their mechanical characteristics (i.e., effective bending stiffnesses), and the piezoelectric trips are bonded to the metaplates. The piezo-metaplates are placed in the sliding cells to obtain the post-buckling response for energy harvesting under low-frequency ocean motions. The corrugated mechanical metamaterials are fabricated using the three-dimensional additive manufacturing technique and are bonded with polyvinylidene fluoride strips, and the nanogenerator samples are investigated under the quasi-static loading. Theoretical and numerical models are developed to obtain the electrical power, and satisfactory agreements are observed. Optimization is conducted to maximize the generated electrical power with respect to the geometric consideration (i.e., changing the corrugation pattern of the mechanical metamaterials) and the material consideration (i.e., changing the mechanical metamaterials to anisotropic). In the end, we consider the piezoelectric nanogenerators as a potential green solution for the energy issues in other fields.