Lightweight and flexible self-charging power systems with synchronous energy harvesting and energy storage abilities are highly desired in the era of the internet of things and artificial intelligences, which can provide stable, sustainable, and autonomous power sources for ubiquitous, distributed, and low-power wearable electronics. However, there is a lack of comprehensive review and challenging discussion on the state-of-the-art of the triboelectric nanogenetor (TENG)-based self-charging power textiles, which have a great possibility to become the future energy autonomy power sources. Herein, the recent progress of the self-charging power textiles hybridizing fiber/fabric based TENGs and fiber/fabric shaped batteries/supercapacitors is comprehensively summarized from the aspect of textile structural designs. Based on the current research status, the key bottlenecks and brighter prospects of self-charging power textiles are also discussed in the end. It is hoped that the summary and prospect of the latest research of self-charging power textiles can help relevant researchers accurately grasp the research progress, focus on the key scientific and technological issues, and promote further research and practical application process.

Conventional frame-based image sensors suffer greatly from high energy consumption and latency. Mimicking neurobiological structures and functionalities of the retina provides a promising way to build a neuromorphic vision sensor with highly efficient image processing. In this review article, we will start with a brief introduction to explain the working mechanism and the challenges of conventional frame-based image sensors, and introduce the structure and functions of biological retina. In the main section, we will overview recent developments in neuromorphic vision sensors, including the silicon retina based on conventional Si CMOS digital technologies, and the neuromorphic vision sensors with the implementation of emerging devices. Finally, we will provide a brief outline of the prospects and outlook for the development of this field.

Resistive random-access memory (RRAM), also known as memristors, having a very simple device structure with two terminals, fulfill almost all of the fundamental requirements of volatile memory, nonvolatile memory, and neuromorphic characteristics. Its memory and neuromorphic behaviors are currently being explored in relation to a range of materials, such as biological materials, perovskites, 2D materials, and transition metal oxides. In this review, we discuss the different electrical behaviors exhibited by RRAM devices based on these materials by briefly explaining their corresponding switching mechanisms. We then discuss emergent memory technologies using memristors, together with its potential neuromorphic applications, by elucidating the different material engineering techniques used during device fabrication to improve the memory and neuromorphic performance of devices, in areas such as I_ON/I_OFF ratio, endurance, spike time-dependent plasticity (STDP), and paired-pulse facilitation (PPF), among others. The emulation of essential biological synaptic functions realized in various switching materials, including inorganic metal oxides and new organic materials, as well as diverse device structures such as single-layer and multilayer hetero-structured devices, and crossbar arrays, is analyzed in detail. Finally, we discuss current challenges and future prospects for the development of inorganic and new materials-based memristors.

The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era. Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed, wide bandwidth, and massive parallelism. Here, we offer a review on the optical neural computing in our research groups at the device and system levels. The photonics neuron and photonics synapse plasticity are presented. In addition, we introduce several optical neural computing architectures and algorithms including photonic spiking neural network, photonic convolutional neural network, photonic matrix computation, photonic reservoir computing, and photonic reinforcement learning. Finally, we summarize the major challenges faced by photonic neuromorphic computing, and propose promising solutions and perspectives.

Since the invention of amorphous indium–gallium–zinc–oxide (IGZO) based thin-film transistors (TFTs) by Hideo Hosono in 2004, investigations on the topic of IGZO TFTs have been rapidly expanded thanks to their high electrical performance, large-area uniformity, and low processing temperature. This article reviews the recent progress and major trends in the field of IGZO-based TFTs. After a brief introduction of the history of IGZO and the main advantages of IGZO-based TFTs, an overview of IGZO materials and IGZO-based TFTs is given. In this part, IGZO material electron travelling orbitals and deposition methods are introduced, and the specific device structures and electrical performance are also presented. Afterwards, the recent advances of IGZO-based TFT applications are summarized, including flat panel display drivers, novel sensors, and emerging neuromorphic systems. In particular, the realization of flexible electronic systems is discussed. The last part of this review consists of the conclusions and gives an outlook over the field with a prediction for the future.

The heterogeneous integration of III–V devices with Si-CMOS on a common Si platform has shown great promise in the new generations of electrical and optical systems for novel applications, such as HEMT or LED with integrated control circuitry. For heterogeneous integration, direct wafer bonding (DWB) techniques can overcome the materials and thermal mismatch issues by directly bonding dissimilar materials systems and device structures together. In addition, DWB can perform at wafer-level, which eases the requirements for integration alignment and increases the scalability for volume production. In this paper, a brief review of the different bonding technologies is discussed. After that, three main DWB techniques of single-, double- and multi-bonding are presented with the demonstrations of various heterogeneous integration applications. Meanwhile, the integration challenges, such as micro-defects, surface roughness and bonding yield are discussed in detail.

With recent developments of deep ultraviolet (DUV) light-emitting diodes and solar-blind detectors, UV communication (UVC) shows great potential in replacing traditional wireless communication in more and more scenarios. Based on the atmospheric scattering of UV radiation, UVC has gained considerable attention due to its non-line-of-sight ability, omnidirectional communication links and low background noise. These advantages make UVC an ideal option for covert secure communication, especially for military communication. In this review, we present the history and working principle of UVC with a special focus on its light sources and detectors. Comprehensive comparison and application of its light sources and detectors are provided to the best of our knowledge. We further discuss the future application and outlook of UVC. Hopefully, this review will offer valuable insights into the future development of UVC.

Memristors are now becoming a prominent candidate to serve as the building blocks of non-von Neumann in-memory computing architectures. By mapping analog numerical matrices into memristor crossbar arrays, efficient multiply accumulate operations can be performed in a massively parallel fashion using the physics mechanisms of Ohm’s law and Kirchhoff’s law. In this brief review, we present the recent progress in two niche applications: neural network accelerators and numerical computing units, mainly focusing on the advances in hardware demonstrations. The former one is regarded as soft computing since it can tolerant some degree of the device and array imperfections. The acceleration of multiple layer perceptrons, convolutional neural networks, generative adversarial networks, and long short-term memory neural networks are described. The latter one is hard computing because the solving of numerical problems requires high-precision devices. Several breakthroughs in memristive equation solvers with improved computation accuracies are highlighted. Besides, other nonvolatile devices with the capability of analog computing are also briefly introduced. Finally, we conclude the review with discussions on the challenges and opportunities for future research toward realizing memristive analog computing machines.

Polarization-resolved photodetectors, a significant branch of photodetection, can more effectively distinguish the target from the background by exploiting polarization-sensitive characteristics. However, due to the absence of intrinsic polarized absorption properties of many materials, there is still a great challenge to develop the high-performance polarization-resolved photodetectors. Here, we report a van der Waals heterojunction (vdWH) ReSe₂/WSe₂ photodetector, which performs a high responsivity of ~0.28 A/W and a high detectivity of 1.1 × 10¹² Jones under the illumination of 520 nm laser at room temperature. Remarkably, scanning photocurrent mapping (SPCM) measurements demonstrate the photoresponse of devices closely depend on the polarized angle of the incident light, indicating the effective polarized light detection. This work paves the way to develop high-performance polarization-resolved photodetectors based on two-dimensional (2D) materials.

Herein, high-quality n-ZnO film layer on c-sapphire and well-crystallized tetragonal p-BiOCl nanoflakes on Cu foil are prepared, respectively. According to the absorption spectra, the bandgaps of n-ZnO and p-BiOCl are confirmed as ~3.3 and ~3.5 eV, respectively. Subsequently, a p-BiOCl/n-ZnO heterostructural photodetector is constructed after a facile mechanical bonding and post annealing process. At –5 V bias, the photocurrent of the device under 350 nm irradiation is ~800 times higher than that in dark, which indicates its strong UV light response characteristic. However, the on/off ratio of In–ZnO–In photodetector is ~20 and the Cu–BiOCl–Cu photodetector depicts very weak UV light response. The heterostructure device also shows a short decay time of 0.95 s, which is much shorter than those of the devices fabricated from pure ZnO thin film and BiOCl nanoflakes. The p-BiOCl/n-ZnO heterojunction photodetector provides a promising pathway to multifunctional UV photodetectors with fast response, high signal-to-noise ratio, and high selectivity.

With the growing market of wearable devices for smart sensing and personalized healthcare applications, energy storage devices that ensure stable power supply and can be constructed in flexible platforms have attracted tremendous research interests. A variety of active materials and fabrication strategies of flexible energy storage devices have been intensively studied in recent years, especially for integrated self-powered systems and biosensing. A series of materials and applications for flexible energy storage devices have been studied in recent years. In this review, the commonly adopted fabrication methods of flexible energy storage devices are introduced. Besides, recent advances in integrating these energy devices into flexible self-powered systems are presented. Furthermore, the applications of flexible energy storage devices for biosensing are summarized. Finally, the prospects and challenges of the self-powered sensing system for wearable electronics are discussed.

Robust quantum cascade laser (QCL) enduring high temperature continuous-wave (CW) operation is of critical importance for some applications. We report on the realization of lattice-matched InGaAs/InAlAs/InP QCL materials grown by metal-organic chemical vapor deposition (MOCVD). High interface quality structures designed for light emission at 8.5 μm are achieved by optimizing and precise controlling of growth conditions. A CW output power of 1.04 W at 288 K was obtained from a 4 mm-long and 10 μm-wide coated laser. Corresponding maximum wall-plug efficiency and threshold current density were 7.1% and 1.18 kA/cm², respectively. The device can operate in CW mode up to 408 K with an output power of 160 mW.

To prevent and mitigate environmental degradation, high-performance and cost-effective electrochemical flexible energy storage systems need to be urgently developed. This demand has led to an increase in research on electrode materials for high-capacity flexible supercapacitors and secondary batteries, which have greatly aided the development of contemporary digital communications and electric vehicles. The use of layered double hydroxides (LDHs) as electrode materials has shown productive results over the last decade, owing to their easy production, versatile composition, low cost, and excellent physicochemical features. This review highlights the distinctive 2D sheet-like structures and electrochemical characteristics of LDH materials, as well as current developments in their fabrication strategies for expanding the application scope of LDHs as electrode materials for flexible supercapacitors and alkali metal (Li, Na, K) ion batteries.