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.

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Purpose The purpose of this study is to demonstrate a pseudomorphic High Electron Mobility Transistor (pHEMT) cutoff frequency (fT) and maximum oscillation frequency (fmax) are determined by the role of its gate length (Lg). Theoretically, to obtain an Lg of 1 µm, the gate’s resist opening must be 1 µm wide. However, after the coat-expose-develop (C-E-D) process, the Lg became 13% larger after metal evaporation. This enlargement is due to both resist thickness and its profile. Design/methodology/approach This research aims to optimize the 1-µm Lg InGaAs-InAlAs pHEMT C-E-D process, where the diluted AZ®nLOF™ 2070 resist with AZ® EBR solvent technique has been used to solve the Lg enlargement problem. The dilution theoretically allows the changing of a resist thickness to different film thickness using the same coating parameters. Here, for getting a new resist, which is simply called AZ 0.5 µm, the experiment’s important parameters such as the coater’s spin speed of 3,000 rpm and soft bake at 110°C for 5 min are executed. Findings The newly mixed AZ 0.5 µm resist has presented a high resolution and undercut profile rather than standard AZ 1 µm resist. Hence, the Lg metallization after using AZ 0.5 µm optimized process showed better results than AZ 1 µm which used the standard process. Originality/value The outcome of the optimization has reached that it is possible to get a nearly sub-µm range gate’s opening using a diluted resist, and at the same time retaining a high resolution and undercut profile.

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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.

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This paper 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.INDEX TERMS system-on-a-chip (SoC), clock distribution, deep sub-micrometer, artificial intelligence, hybrid meta-heuristic.