A new generation of high-efficiency power devices is being developed using wide bandgap (WBG) semiconductors, like GaN and SiC, which are emerging as attractive alternatives to silicon. The recent interest in GaN has been piqued by its excellent material characteristics, including its high critical electric field, high saturation velocity, high electron mobility, and outstanding thermal stability. Therefore, the superior performance is represented by GaN-based high electron mobility transistor (HEMT) devices. They can perform at higher currents, voltages, temperatures, and frequencies, making them suitable devices for the next generation of high-efficiency power converter applications, including electric vehicles, phone chargers, renewable energy, and data centers. Thus, this review article will provide a basic overview of the various technological and scientific elements of the current GaN HEMTs technology. First, the present advancements in the GaN market and its primary application areas are briefly summarized. After that, the GaN is compared with other devices, and the GaN HEMT device’s operational material properties with different heterostructures are discussed. Then, the normally-off GaN HEMT technology with their different types are considered, especially on the recessed gate metal insulator semiconductor high electron mobility transistor (MISHEMT) and p-GaN. Hereafter, this review also discusses the reliability concerns of the GaN HEMT which are caused by trap effects like a drain, gate lag, and current collapse with numerous types of degradation. Eventually, the breakdown voltage of the GaN HEMT with some challenges has been studied.

Alongside the development of high-speed rail, rail flaw detection is of great importance to ensure railway safety, especially for improving the speed and load of the train. Several conventional inspection methods such as visual, acoustic, and electromagnetic inspection have been introduced in the past. However, these methods have several challenges in terms of detection speed and accuracy. Combined inspection methods have emerged as a promising approach to overcome these limitations. Nondestructive testing (NDT) techniques in conjunction with artificial intelligence approaches have tremendous potential and viability because it is highly possible to improve the detection accuracy which has been proven in various conventional nondestructive testing techniques. With the development of information technology, communication technology, and sensor technology, rail health monitoring systems have been evolving, and have become equally significant and challenging because they can achieve real-time detection and give a risk warning forecast. This paper provides an in-depth review of traditional nondestructive techniques for rail inspection as well as the development of using machine learning approaches, combined nondestructive techniques, and rail health monitoring systems.

It is only recently that the electric vehicle (EV) has evolved into a contemporary invention. There has been a rapid acceleration in the development of EVs in a number of nations in order to lessen their reliance on oil and their contribution to environmental pollution. In the tangible world, fully EVs do not release any carbon dioxide (CO2) emissions from their tailpipes, unlike any other conventional vehicles. This results in a 50%–70% CO2 reduction in air pollution per year. The achievement of electrification in transportation has led to a reduction in the weight and size of the vehicles as the need for internal combustion engines can be eliminated. Wide bandgap materials such as silicon carbide (SiC) and gallium nitride (GaN) offer advantages in the manufacturing of EVs. Beginning the late 2000s, the EV industry has begun to adopt GaN devices in their manufacturing processes. The semiconductor material GaN stands out as a material for power electronic systems in EVs owing to its high switching frequency, higher temperature limit, and high voltage breakdown. This review aims to provide a comprehensive overview of semiconductor GaN materials for EV applications, which could be useful to provide insights for researchers and scientists to accelerate their innovation for the improvement of EVs. This review begins with an introduction to EVs, followed by the anticipated demand for EVs. The application of GaN devices in EVs, compared to the traditional Si and SiC devices, which are the primary power devices in current EVs, is discussed. The recent advancement in GaN devices that are capable of being used in various components of a fully automated EV, such as the battery, energy storage system, auxiliary power unit, and motor drive, in addition to their use in different non-automotive vehicles such as electric aircraft, electric ships, electric railways, electric submarines, and heavy duty vehicles, is also discussed. Finally, the challenges posed by GaN devices and potential solutions to overcome these shortcomings have been addressed.

Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to inspect CFRP components. However, the restricted field penetration within the CFRP makes conventional NDT approaches ineffective. Recently, microwave techniques have been developed to address the challenges associated with CFRP inspection by providing better material penetration and more precise results. This paper offers a review of the primary NDT methods employed to inspect CFRP composites, emphasizing microwave-based NDT techniques and their key features.

An analytical model for depletion-mode MOSHEMTs for high-temperature applications is compared against the experimental GaN HEMT data of the AlGaN/GaN MOSHEMT for temperature dependence of 2DEG simulated at 75 °C and 125 °C. Both temperatures reduce the 2DEG density by 4 % in the GaN HEMT and 3 % in the AlGaN/GaN MOSHEMT. The cause of this diminishing effect is determined to be the decrease of the conduction band offset at high temperatures. Additionally, the device performance degrades at high temperatures due to the immature behaviour of GaN material when it operates at high-power dissipation with poor thermal conductivity. The simulated AlGaN/GaN MOSHEMT performance is comparatively improved compared to the experimental AlGaN/GaN HEMT devices. This improvement could be used to understand the nature of the 2DEG density vs the temperature, hence could enhance the experimental performance of the AlGaN/GaN MOSHEMT.

This article recommends a practical technique to design full chip (FC) clock tree of a complex system-on-chip (SoC). In the new business environment, the market prefers a highly integrated but low power SoC with fast design productivity and low development cost. We observed that many techniques proposed in the prior arts are no longer practical or enough. With that, we introduce a flexible FC Clock network topology and a synthesis algorithm that utilize a hybrid meta-heuristic technique to search for near optimum solution in shorter turn-around time. Our work on a 10nm SoC product showed that the topology and algorithm managed to produce averagely 16.98% better global skew, 42.75% less divergence on critical clock paths and with 64.5% shorter clock balancing phase compared to a conventional ASIC methodology.