Reviving Vibration Energy Harvesting and Self-Powered Sensing by a Triboelectric Nanogenerator

Textiles have been concomitant of human civilization for thousands of years. With the advances in chemistry and materials, integrating textiles with energy harvesters will provide a sustainable, environmentally friendly, pervasive, and wearable energy solution for distributed on-body electronics in the era of Internet of Things. This article comprehensively and thoughtfully reviews research activities regarding the utilization of smart textiles for harvesting energy from renewable energy sources on the human body and its surroundings. Specifically, we start with a brief introduction to contextualize the significance of smart textiles in light of the emerging energy crisis, environmental pollution, and public health. Next, we systematically review smart textiles according to their abilities to harvest biomechanical energy, body heat energy, biochemical energy, solar energy as well as hybrid forms of energy. Finally, we provide a critical analysis of smart textiles and insights into remaining challenges and future directions. With worldwide efforts, innovations in chemistry and materials elaborated in this review will push forward the frontiers of smart textiles, which will soon revolutionize our lives in the era of Internet of Things.

Smart Textiles for Electricity Generation.

Exciting advancements have been made in the field of flexible electronic devices in the last two decades and will certainly lead to a revolution in peoples’ lives in the future. However, because of the poor sustainability of the active materials in complex stress environments, new requirements have been adopted for the construction of flexible devices. Thus, hierarchical architectures in natural materials, which have developed various environment-adapted structures and materials through natural selection, can serve as guides to solve the limitations of materials and engineering techniques. This review covers the smart designs of structural materials inspired by natural materials and their utility in the construction of flexible devices. First, we summarize structural materials that accommodate mechanical deformations, which is the fundamental requirement for flexible devices to work properly in complex environments. Second, we discuss the functionalities of flexible devices induced by nature-inspired stru...

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Nature-Inspired Structural Materials for Flexible Electronic Devices

The rapid development of information technology has led to urgent requirements for high efficiency and ultralow power consumption. In the past few decades, neuromorphic computing has drawn extensive attention due to its promising capability in processing massive data with extremely low power consumption. Here, we offer a comprehensive review on emerging artificial neuromorphic devices and their applications. In light of the inner physical processes, we classify the devices into nine major categories and discuss their respective strengths and weaknesses. We will show that anion/cation migration-based memristive devices, phase change, and spintronic synapses have been quite mature and possess excellent stability as a memory device, yet they still suffer from challenges in weight updating linearity and symmetry. Meanwhile, the recently developed electrolyte-gated synaptic transistors have demonstrated outstanding energy efficiency, linearity, and symmetry, but their stability and scalability still need to be optimized. Other emerging synaptic structures, such as ferroelectric, metal–insulator transition based, photonic, and purely electronic devices also have limitations in some aspects, therefore leading to the need for further developing high-performance synaptic devices. Additional efforts are also demanded to enhance the functionality of artificial neurons while maintaining a relatively low cost in area and power, and it will be of significance to explore the intrinsic neuronal stochasticity in computing and optimize their driving capability, etc. Finally, by looking into the correlations between the operation mechanisms, material systems, device structures, and performance, we provide clues to future material selections, device designs, and integrations for artificial synapses and neurons.

A comprehensive review on emerging artificial neuromorphic devices

Flexible tactile sensors are considered as an effective way to realize the sense of touch, which can perform the synchronized interactions with surrounding environment. Here, the utilization of bionic microstructures on natural lotus leaves is demonstrated to design and fabricate new-type of high-performance flexible capacitive tactile sensors. Taking advantage of unique surface micropattern of lotus leave as the template for electrodes and using polystyrene microspheres as the dielectric layer, the proposed devices present stable and high sensing performance, such as high sensitivity (0.815 kPa-1 ), wide dynamic response range (from 0 to 50 N), and fast response time (≈38 ms). In addition, the flexible capacitive sensor is not only applicable to pressure (touch of a single hair), but also to bending and stretching forces. The results indicate that the proposed capacitive tactile sensor is a promising candidate for the future applications in electronic skins, wearable robotics, and biomedical devices.

Flexible Capacitive Tactile Sensor Based on Micropatterned Dielectric Layer.

Vertically stacked thin triboelectric nanogenerator for wind energy harvesting

Triboelectric nanogenerators with nature-replicated interface structures are presented. Effective contact areas of the triboelectric surfaces are largely enhanced because of the densely packed nano-in-micro hierarchical structures in nature. The enlarged contact area causes stronger triboelectric charge density, which results in output power increment. The interface engineering also allows the improved humidity resistance, which is an important parameter for the stable energy harvesting.

Nature‐Replicated Nano‐in‐Micro Structures for Triboelectric Energy Harvesting

A highly scalable synapse device based on a junctionless (JL) ferroelectric (FE) FinFET is presented for neuromorphic applications. The synaptic behaviors of the JL metal-ferroelectric-insulator-silicon FinFET were experimentally demonstrated after verifying the ferroelectric characteristics of the HfZrO X (HZO) film using a metal-ferroelectric-metal capacitor. The fabricated synapse showed distinguishable polarization switching behaviors with gradually controllable channel conductance. From neural network simulations using the proposed JL FE FinFET as synapses, the pattern recognition accuracy for hand-written digits was validated to be approximately 80% for neuromorphic applications.

First Demonstration of a Logic-Process Compatible Junctionless Ferroelectric FinFET Synapse for Neuromorphic Applications

A comprehensive analysis of the gate-induced drain leakage (GIDL) current of vertically stacked nanowire (VS-NW) FETs was carried out. In particular, two different operational modes of the VS-NW, an inversion mode (IM) and a junctionless mode (JM), were compared. The GIDL current of the JM-FET was considerably smaller than that of the IM-FET, and the reason for the difference was consequently determined by numerical simulations. It was found that the source of the difference between the IM-FET and JM-FET was the difference in source/drain (S/D) doping concentration, where the depletion width becomes the tunneling width, considering a long extension length at the S/D regions. The experimental results showed that the GIDL current of the NW FET was significantly controlled by longitudinal band-to-band tunneling (BTBT), rather than the transverse BTBT, as had been reported in the previous literature.

Comprehensive Analysis of Gate-Induced Drain Leakage in Vertically Stacked Nanowire FETs: Inversion-Mode Versus Junctionless Mode

A vertically integrated junctionless field-effect transistor (VJ-FET), which is composed of vertically stacked multiple silicon nanowires (SiNWs) with a gate-all-around (GAA) structure, is demonstrated on a bulk silicon wafer for the first time. The proposed VJ-FET mitigates the issues of variability and fabrication complexity that are encountered in the vertically integrated multi-NW FET (VM-FET) based on an identical structure in which the VM-FET, as recently reported, harnesses a source and drain (S/D) junction for its operation and is thus based on the inversion mode. Variability is alleviated by bulk conduction in a junctionless FET (JL-FET), where current flows through the core of the SiNW, whereas it is not mitigated by surface conduction in an inversion mode FET (IM-FET), where current flows via the surface of the SiNW. The fabrication complexity is reduced by the inherent JL structure of the JL-FET because S/D formation is not required. In contrast, it is very difficult to dope the S/D when it is...

Jae Hur

Papers

Vertically stacked thin triboelectric nanogenerator for wind energy harvesting

Nature‐Replicated Nano‐in‐Micro Structures for Triboelectric Energy Harvesting

First Demonstration of a Logic-Process Compatible Junctionless Ferroelectric FinFET Synapse for Neuromorphic Applications

Comprehensive Analysis of Gate-Induced Drain Leakage in Vertically Stacked Nanowire FETs: Inversion-Mode Versus Junctionless Mode

A Vertically Integrated Junctionless Nanowire Transistor