The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life, for example, healthcare monitoring and treatment, ambient monitoring, soft robotics, prosthetics, flexible display, communication, human‐machine interactions, and so on. According to the development in recent years, the next‐generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence (AI) and internet of things (IoT), to achieve a higher level of comfort, convenience, connection, and intelligence. Herein, this review provides an opportune overview of the recent progress in wearable electronics, photonics, and systems, in terms of emerging materials, transducing mechanisms, structural configurations, applications, and their further integration with other technologies. First, development of general wearable electronics and photonics is summarized for the applications of physical sensing, chemical sensing, human‐machine interaction, display, communication, and so on. Then self‐sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage technologies. Next, technology fusion of wearable systems and AI is reviewed, showing the emergence and rapid development of intelligent/smart systems. In the last section of this review, perspectives about the future development trends of the next‐generation wearable electronics/photonics are provided, that is, toward multifunctional, self‐sustainable, and intelligent wearable systems in the AI/IoT era.

The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics. Gait reveals sensory information in daily life containing personal information, regarding identification and healthcare. Current wearable electronics of gait analysis are mainly limited by high fabrication cost, operation energy consumption, or inferior analysis methods, which barely involve machine learning or implement nonoptimal models that require massive datasets for training. Herein, we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory data. The sock equipped with self-powered functionality also can be used as wearable sensors to deliver information, regarding the identity, health status, and activity of the users. To further address the issue of ineffective analysis methods, an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed, which produces a 93.54% identification accuracy of 13 participants and detects five different human activities with 96.67% accuracy. Toward practical application, we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring, healthcare, identification, and future smart home applications.

Midinfrared (MIR), which covers numerous molecular vibrational fingerprints, has attracted enormous research interest due to its promising potential for label-free and damage-free sensing. Despite intense development efforts, the realization of waveguide-integrated on-chip sensing system has seen very limited success to date. The huge lattice mismatch between silicon and the commonly used detection materials such as HgCdTe, III–V, or II–VI compounds has been the key bottleneck that hinders their integration. Here, we realize an integration of silicon-on-insulator (SOI) waveguides with black phosphorus (BP) photodetectors. When operating near BP’s cutoff wavelength where absorption is weak, the light–BP interaction is enhanced by exploiting the optical confinement in the Si waveguide and grating structure to overcome the limitation of absorption length constrained by the BP thickness. Devices with different BP crystal orientation and thickness are compared in terms of their responsivity and noise equivalent power (NEP). Spectral photoresponse from 3.68 to 4.03 μm was investigated. Additionally, power-dependent responsivity and gate-tunable photocurrent were also studied. At a bias of 1 V, the BP photodetector achieved a responsivity of 23 A/W at 3.68 μm and 2 A/W at 4 μm and a NEP less than 1 nW/Hz1/2 at room temperature. The integration of passive Si photonics and active BP photodetector is envisaged to offer a potential pathway toward the realization of integrated on-chip systems for MIR sensing applications.

Silicon photonic integrated circuits for telecommunication and data centers have been well studied in the past decade, and now most related efforts have been progressing toward commercialization. Scaling up the silicon-oninsulator (SOI)-based device dimensions in order to extend the operation wavelength to the short mid-infrared (MIR) range (2-4 μm) is attracting research interest, owing to the host of potential applications in lab-on-chip sensors, free space communications, and much more. Other material systems and technology platforms, including silicon-on-silicon nitride, germanium-on-silicon, germanium-on-SOI, germanium-on-silicon nitride, sapphireon-silicon, SiGe alloy-on-silicon, and aluminum nitride-on-insulator are explored as well in order to realize low-loss waveguide devices for different MIR wavelengths. In this paper, we will comprehensively review silicon photonics for MIR applications, with regard to the state-of-the-art achievements from various device demonstrations in different material platforms by various groups. We will then introduce in detail of our institute's research and development efforts on the MIR photonic platforms as one case study. Meanwhile, we will discuss the integration schemes along with remaining challenges in devices (e.g., light source) and integration. A few application-oriented examples will be examined to illustrate the issues needing a critical solution toward the final production path (e.g., gas sensors). Finally, we will provide our assessment of the outlook of potential future research topics and engineering challenges along with opportunities.

With the fast development of the fifth-generation cellular network technology (5G), the future sensors and microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS) are presenting a more and more critical role to provide information in our daily life. This review paper introduces the development trends and perspectives of the future sensors and MEMS/NEMS. Starting from the issues of the MEMS fabrication, we introduced typical MEMS sensors for their applications in the Internet of Things (IoTs), such as MEMS physical sensor, MEMS acoustic sensor, and MEMS gas sensor. Toward the trends in intelligence and less power consumption, MEMS components including MEMS/NEMS switch, piezoelectric micromachined ultrasonic transducer (PMUT), and MEMS energy harvesting were investigated to assist the future sensors, such as event-based or almost zero-power. Furthermore, MEMS rigid substrate toward NEMS flexible-based for flexibility and interface was discussed as another important development trend for next-generation wearable or multi-functional sensors. Around the issues about the big data and human-machine realization for human beings’ manipulation, artificial intelligence (AI) and virtual reality (VR) technologies were finally realized using sensor nodes and its wave identification as future trends for various scenarios.

Triboelectric nanogenerator (TENG) technology is a promising research field for energy harvesting and nanoenergy and nanosystem (NENS) in the aspect of mechanical, electrical, optical, acoustic, fluidic, and so on. This review systematically reports the progress of TENG technology, in terms of energy-boosting, emerging materials, self-powered sensors, NENS, and its further integration with other potential technologies. Starting from TENG mechanisms including the ways of charge generation and energy-boosting, we introduce the applications from energy harvesters to various kinds of self-powered sensors, that is, physical sensors, chemical/gas sensors. After that, further applications in NENS are discussed, such as blue energy, human-machine interfaces (HMIs), neural interfaces/implanted devices, and optical interface/wearable photonics. Moving to new research directions beyond TENG, we depict hybrid energy harvesting technologies, dielectric-elastomer-enhancement, self-healing, shape-adaptive capability, and self-sustained NENS and/or internet of things (IoT). Finally, the outlooks and conclusions about future development trends of TENG technologies are discussed toward multifunctional and intelligent systems.

No abstract

Tunable metamaterial devices have experienced explosive growth in the past decades, driving the traditional electromagnetic (EM) devices to evolve into diversified functionalities by manipulating EM properties such as amplitude, frequency, phase, polarization, and propagation direction. However, one of the bottlenecks of these rapidly developed metamaterials technologies is limited tunability caused by the intrinsic frequency‐dependent property of exotic tunable material. To overcome such limitation, the microelectromechanical system (MEMS) enabling micro/nanoscale manipulation is developed to actively control “meta‐atom” in terahertz and infrared region, which brings frequency‐scalable tunability and complementary metal‐oxide‐semiconductor‐compatible functional meta‐devices. Beyond tunability, novel chemical sensing platforms of molecular identification and dynamic monitoring of the biochemical process can be achieved by integrating micro/nanofluidics channels with metamaterial resonators. Additionally, incorporating metamaterial absorbers with MEMS resonators brings another research interest in MEMS zero‐power devices and radiation sensors. Furthermore, moving from 2D metasurfaces to 3D metamaterials, enhanced EM properties like novel resonance mode, giant chirality, and 3D manipulation reinforce the application in biochemical and physical sensors as well as functional meta‐devices, paving the way to realize multi‐functional sensing and signal processing on a hybrid smart‐sensor microsystem for booming healthcare, environmental monitoring, and the Internet of Things applications.