Beta gallium oxide (β-Ga₂O₃) has attracted significant attention for applications in power electronics due to its ultra-wide bandgap of ~ 4.8 eV and the large critical electric field of 8 MV/cm. These properties yield a high Baliga’s figures of merit (BFOM) of more than 3000. Though β-Ga₂O₃ possesses superior material properties, the lack of p-type doping is the main obstacle that hinders the development of β-Ga₂O₃-based power devices for commercial use. Constructing heterojunctions by employing other p-type materials has been proven to be a feasible solution to this issue. Nickel oxide (NiO) is the most promising candidate due to its wide band gap of 3.6–4.0 eV. So far, remarkable progress has been made in NiO/β-Ga₂O₃ heterojunction power devices. This review aims to summarize recent advances in the construction, characterization, and device performance of the NiO/β-Ga₂O₃ heterojunction power devices. The crystallinity, band structure, and carrier transport property of the sputtered NiO/β-Ga₂O₃ heterojunctions are discussed. Various device architectures, including the NiO/β-Ga₂O₃ heterojunction pn diodes (HJDs), junction barrier Schottky (JBS) diodes, and junction field effect transistors (JFET), as well as the edge terminations and super-junctions based on the NiO/β-Ga₂O₃ heterojunction, are described.

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.

In order to perform automated calculations of defect and dopant properties in semiconductors and insulators, we developed a software package, the Defect and Dopant ab-initio Simulation Package (DASP), which is composed of four modules for calculating: (i) elemental chemical potentials, (ii) defect (dopant) formation energies and charge-state transition levels, (iii) defect and carrier densities and (iv) carrier dynamics properties of high-density defects. DASP uses the materials genome database for quick determination of competing secondary phases when calculating the elemental chemical potential that stabilizes compound semiconductors. DASP calls the ab-initio software to perform the total energy, structural relaxation and electronic structure calculations of the defect supercells with different charge states, based on which the defect formation energies and charge-state transition levels are calculated. Then DASP can calculate the equilibrium densities of defects and electron and hole carriers as well as the Fermi level in semiconductors under different chemical potential conditions and growth/working temperature. For high-density defects, DASP can calculate the carrier dynamics properties such as the photoluminescence (PL) spectrum and carrier capture cross sections which can interpret the deep level transient spectroscopy (DLTS). Here we will show three application examples of DASP in studying the undoped GaN, C-doped GaN and quasi-one-dimensional SbSeI.

With the rapid technological innovation in materials engineering and device integration, a wide variety of textile-based wearable biosensors have emerged as promising platforms for personalized healthcare, exercise monitoring, and pre-diagnostics. This paper reviews the recent progress in sweat biosensors and sensing systems integrated into textiles for wearable body status monitoring. The mechanisms of biosensors that are commonly adopted for biomarkers analysis are first introduced. The classification, fabrication methods, and applications of textile conductors in different configurations and dimensions are then summarized. Afterward, innovative strategies to achieve efficient sweat collection with textile-based sensing patches are presented, followed by an in-depth discussion on nanoengineering and system integration approaches for the enhancement of sensing performance. Finally, the challenges of textile-based sweat sensing devices associated with the device reusability, washability, stability, and fabrication reproducibility are discussed from the perspective of their practical applications in wearable healthcare.

In this work, we design and fabricate a deep ultraviolet (DUV) light-emitting array consisting of 10 × 10 micro-LEDs (μ-LEDs) with each device having 20 μm in diameter. Strikingly, the array demonstrates a significant enhancement of total light output power by nearly 52% at the injection current of 100 mA, in comparison to a conventional large LED chip whose emitting area is the same as the array. A much higher (~22%) peak external quantum efficiency, as well as a smaller efficiency droop for μ-LED array, was also achieved. The numerical calculation reveals that the performance boost can be attributed to the higher light extraction efficiency at the edge of each μ-LED. Additionally, the far-field pattern measurement shows that the μ-LED array possesses a better forward directionality of emission. These findings shed light on the enhancement of the DUV LEDs performance and provide new insights in controlling the light behavior of the μ-LEDs.

Diamond, as an ultra-wide bandgap semiconductor, has become a promising candidate for next-generation microelectronics and optoelectronics due to its numerous advantages over conventional semiconductors, including ultrahigh carrier mobility and thermal conductivity, low thermal expansion coefficient, and ultra-high breakdown voltage, etc. Despite these extraordinary properties, diamond also faces various challenges before being practically used in the semiconductor industry. This review begins with a brief summary of previous efforts to model and construct diamond-based high-voltage switching diodes, high-power/high-frequency field-effect transistors, MEMS/NEMS, and devices operating at high temperatures. Following that, we will discuss recent developments to address scalable diamond device applications, emphasizing the synthesis of large-area, high-quality CVD diamond films and difficulties in diamond doping. Lastly, we show potential solutions to modulate diamond’s electronic properties by the “elastic strain engineering” strategy, which sheds light on the future development of diamond-based electronics, photonics and quantum systems.

The utilization of solar energy to drive energy conversion and simultaneously realize pollutant degradation via photocatalysis is one of most promising strategies to resolve the global energy and environment issues. During the past decade, graphite carbon nitride (g-C₃N₄) has attracted dramatically growing attention for solar energy conversion due to its excellent physicochemical properties as a photocatalyst. However, its practical application is still impeded by several limitations and shortcomings, such as high recombination rate of charge carriers, low visible-light absorption, etc. As an effective solution, the electronic structure tuning of g-C₃N₄ has been widely adopted. In this context, firstly, the paper critically focuses on the different strategies of electronic structure tuning of g-C₃N₄ like vacancy modification, doping, crystallinity modulation and synthesis of a new molecular structure. And the recent progress is reviewed. Finally, the challenges and future trends are summarized.

This study presents an overview on graphene synthesis, fabrication and different characterization techniques utilized in the production. Since its discovery in 2004 by Andre Geim and Kostya Novoselov several research articles have been published globally to this effect, owing to graphene’s extraordinary, and exclusive characteristics which include optical transparency, excellent thermal, and mechanical properties. The properties and applications of this two-dimensional carbon crystal composed of single-layered material have created new avenues for the development of high-performance future electronics and technologies in energy storage and conversion for the sustainable energy. However, despite its potential and current status globally the difficulty in the production of monolayer graphene sheet still persists. Therefore, this review highlighted two approaches in the synthesis of graphene, which are the top-down and bottom-up approaches and examined the advantages and failings of the methods involved. In addition, the prospects and failings of these methods are investigated, as they are essential in optimizing the production method of graphene vital for expanding the yield, and producing high-quality graphene.

In this work, we propose to reveal the subsurface damage (SSD) of 4H-SiC wafers by photo-chemical etching and identify the nature of SSD by molten-alkali etching. Under UV illumination, SSD acts as a photoluminescence-black defect. The selective photo-chemical etching reveals SSD as the ridge-like defect. It is found that the ridge-like SSD is still crystalline 4H-SiC with lattice distortion. The molten-KOH etching of the 4H-SiC wafer with ridge-like SSD transforms the ridge-like SSD into groove lines, which are typical features of scratches. This means that the underlying scratches under mechanical stress give rise to the formation of SSD in 4H-SiC wafers. SSD is incorporated into 4H-SiC wafers during the lapping, rather than the chemical mechanical polishing (CMP).

Artificial intelligence (AI) processes data-centric applications with minimal effort. However, it poses new challenges to system design in terms of computational speed and energy efficiency. The traditional von Neumann architecture cannot meet the requirements of heavily data-centric applications due to the separation of computation and storage. The emergence of computing in-memory (CIM) is significant in circumventing the von Neumann bottleneck. A commercialized memory architecture, static random-access memory (SRAM), is fast and robust, consumes less power, and is compatible with state-of-the-art technology. This study investigates the research progress of SRAM-based CIM technology in three levels: circuit, function, and application. It also outlines the problems, challenges, and prospects of SRAM-based CIM macros.

For the non-stop demands for a better and smarter society, the number of electronic devices keeps increasing exponentially; and the computation power, communication data rate, smart sensing capability and intelligence are always not enough. Hardware supports software, while the integrated circuit (IC) is the core of hardware. In this long review paper, we summarize and discuss recent trending IC design directions and challenges, and try to give the readers big/cool pictures on each selected small/hot topics. We divide the trends into the following six categories, namely, 1) machine learning and artificial intelligence (AI) chips, 2) communication ICs, 3) data converters, 4) power converters, 5) imagers and range sensors, 6) emerging directions. Hope you find this paper useful for your future research and works.

We demonstrate in-plane field-free-switching spin-orbit torque (SOT) magnetic tunnel junction (MTJ) devices that are capable of low switching current density, fast speed, high reliability, and, most importantly, manufactured uniformly by the 200-mm-wafer platform. The performance of the devices is systematically studied, including their magnetic properties, switching behaviors, endurance and data retention. The successful integration of SOT devices within the 200-mm-wafer manufacturing platform provides a feasible way to industrialize SOT MRAMs. It is expected to obtain excellent performance of the devices by further optimizing the MTJ film stacks and the corresponding fabrication processes in the future.

Two-dimensional (2D) materials have attracted considerable interest thanks to their unique electronic/physical–chemical characteristics and their potential for use in a large variety of sensing applications. However, few-layered nanosheets tend to agglomerate owing to van der Waals forces, which obstruct internal nanoscale transport channels, resulting in low electrochemical activity and restricting their use for sensing purposes. Here, a hybrid MXene/rGO aerogel with a three-dimensional (3D) interlocked network was fabricated via a freeze-drying method. The porous MXene/rGO aerogel has a lightweight and hierarchical porous architecture, which can be compressed and expanded several times without breaking. Additionally, a flexible pressure sensor that uses the aerogel as the sensitive layer has a wide response range of approximately 0–40 kPa and a considerable response within this range, averaging approximately 61.49 kPa^–1. The excellent sensing performance endows it with a broad range of applications, including human-computer interfaces and human health monitoring.

Hyperdoping that introduces impurities with concentrations exceeding their equilibrium solubility has been attracting great interest since the tuning of semiconductor properties increasingly relies on extreme measures. In this review we focus on hyperdoped silicon (Si) by introducing methods used for the hyperdoping of Si such as ion implantation and laser doping, discussing the electrical and optical properties of hyperdoped bulk Si, Si nanocrystals, Si nanowires and Si films, and presenting the use of hyperdoped Si for devices like infrared photodetectors and solar cells. The perspectives of the development of hyperdoped Si are also provided.

Advanced electronic materials are the fundamental building blocks of integrated circuits (ICs). The microscale properties of electronic materials (e.g., crystal structures, defects, and chemical properties) can have a considerable impact on the performance of ICs. Comprehensive characterization and analysis of the material in real time with high-spatial resolution are indispensable. In situ transmission electron microscope (TEM) with atomic resolution and external field can be applied as a physical simulation platform to study the evolution of electronic material in working conditions. The high-speed camera of the in situ TEM generates a high frame rate video, resulting in a large dataset that is beyond the data processing ability of researchers using the traditional method. To overcome this challenge, many works on automated TEM analysis by using machine-learning algorithm have been proposed. In this review, we introduce the technical evolution of TEM data acquisition, including analysis, and we summarize the application of machine learning to TEM data analysis in the aspects of morphology, defect, structure, and spectra. Some of the challenges of automated TEM analysis are given in the conclusion.

With rapid advancement and deep integration of artificial intelligence and the internet-of-things, artificial intelligence of things has emerged as a promising technology changing people’s daily life. Massive growth of data generated from the devices challenges the AIoT systems from information collection, storage, processing and communication. In the review, we introduce volatile threshold switching memristors, which can be roughly classified into three types: metallic conductive filament-based TS devices, amorphous chalcogenide-based ovonic threshold switching devices, and metal-insulator transition based TS devices. They play important roles in high-density storage, energy efficient computing and hardware security for AIoT systems. Firstly, a brief introduction is exhibited to describe the categories (materials and characteristics) of volatile TS devices. And then, switching mechanisms of the three types of TS devices are discussed and systematically summarized. After that, attention is focused on the applications in 3D cross-point memory technology with high storage-density, efficient neuromorphic computing, hardware security (true random number generators and physical unclonable functions), and others (steep subthreshold slope transistor, logic devices, etc.). Finally, the major challenges and future outlook of volatile threshold switching memristors are presented.

Indium-tin-zinc oxide (ITZO) thin-film transistor (TFT) technology holds promise for achieving high mobility and offers significant opportunities for commercialization. This paper provides a review of progress made in improving the mobility of ITZO TFTs. This paper begins by describing the development and current status of metal-oxide TFTs, and then goes on to explain the advantages of selecting ITZO as the TFT channel layer. The evaluation criteria for TFTs are subsequently introduced, and the reasons and significance of enhancing mobility are clarified. This paper then explores the development of high-mobility ITZO TFTs from five perspectives: active layer optimization, gate dielectric optimization, electrode optimization, interface optimization, and device structure optimization. Finally, a summary and outlook of the research field are presented.