This work explores the principle of utilizing gallium nitride devices as a gate driver for silicon carbide power devices. As silicon has long reached its performance limits, Wide Bandgap semiconductors such as gallium nitride and silicon carbide have emerged as promising alternatives due to their superior characteristics. However, few publications suggest using a gallium nitride-based gate driver for silicon carbide, high-voltage power devices. Unlike standard voltage source gate drivers, this paper proposes a novel bi-polar current source resonant gate driver topology using gallium nitride transistors as a gate drive circuit for silicon carbide power switching. The driver receives a single input supply and pulsed width modulation signal, producing a high current bi-polar gate driving signal. The gate driver is validated by employing the proposed gate driver to a high-power silicon carbide transistor in a resonant boost converter. The experimental results show that the new gate driver recovers the gate charge wasted energy and provides high performances in varying high voltage loads at a 2.5 MHz switching frequency while reducing the gate losses by 26%.

Schmitt Triggers are essential building blocks in noise-resilient systems and are useful in managing switching behavior in low-power designs. Yet, as CMOS technologies scale down, their designs become increasingly challenging. This paper presents a comprehensive investigation into the performance and reliability of multiple Schmitt Trigger topologies across two CMOS technology nodes (180 nm and 45 nm), with a particular focus on transistor sizing and layout optimization through multi-finger transistor structures. A series of pre-layout and post-layout simulations reveal that fingered implementations significantly enhance hysteresis robustness, switching speed, and delay consistency in PVT variations. Notably, post-layout results in 45 nm technology demonstrate remarkable improvements in both speed and power efficiency. This highlights the inadequacy of schematic-level models to predict the true behavior of fingered transistor configurations. Additionally, we explored the implications of finger designs on reliability concerns including electromigration and IR drop to determine the tradeoff between interconnect reliability optimization and internal routing. The findings establish practical design guidelines for optimizing number of fingers based on device width and technology node, offering new insights into layout-aware Schmitt Trigger design for high-performance and area-constrained applications.

Power converters are increasingly pushing toward higher switching frequencies, with current designs typically operating between tens of kilohertz and a few megahertz. The commercialization of gallium nitride (GaN) power transistors has opened new possibilities, offering performance far beyond the limitations of conventional silicon devices. Despite this promise, the potential of GaN technology remains underutilized. This paper explores the feasibility of achieving sub-gigahertz switching frequencies using GaN-based switch-mode power converters, a regime currently inaccessible to silicon-based counterparts. To reach such operating speeds, it is essential to understand and quantify the intrinsic frequency limitations imposed by GaN device physics and associated parasitics. Existing power conversion topologies and control techniques are unsuitable at these frequencies due to excessive switching losses and inadequate drive capability. This work presents a detailed, systematic study of GaN transistor behavior at high frequencies, aiming to identify both fundamental and practical switching limits. A compact analytical model is developed to estimate the maximum soft-switching frequency, considering only intrinsic device parameters. Under idealized converter conditions, this upper bound is derived as a function of internal losses and the system’s target efficiency. From this, a soft-switching figure of merit is proposed to guide the design and layout of GaN field-effect transistors for highly integrated power systems. The key contribution of this study lies in its analytical insight into the performance boundaries of GaN transistors, highlighting the roles of parasitic elements and loss mechanisms. These findings provide a foundation for developing next-generation, high-frequency, chip-scale power converters.

Time-dependent dielectric breakdown (TDDB) is an important failure mechanism that affects semiconductor device reliability. The degradation lifetime depends strongly on both electric field and temperature, yet these dependencies are commonly treated using separate empirical acceleration factors. This work develops a thermodynamic description in which electrical stress changes the accessible microscopic states of the dielectric and therefore contributes an entropic term to the Gibbs free energy. The resulting formulation separates the field-independent activation barrier, $E_a$, from a field-dependent entropic contribution characterized by $\alpha$. This relation predicts a linear decrease in apparent activation energy with the logarithm of the electric field. Published TDDB data for SiO₂, high-k, low-k, and Cu/low-k dielectric systems exhibit this behavior. Independent temperature- and field-dependent measurements from the same source yield a common entropic field-energy scale of approximately 1.2 eV. A one-second reference field, $E_{1sec}$, provides a physical time anchor that allows field and temperature acceleration to be compared without assuming a common pre-exponential factor across temperatures. For an absolute time temperature series, independently extracted values of $\alpha$ vary by 11.9% across three temperatures, while a fixed α produces a normalized relation with R² ≈ 0.97. The parameters $E_a$, $\alpha$, and $E_{1sec}$ provide a compact thermodynamic representation of field- and temperature-dependent TDDB kinetics across the datasets examined here.

Switch-mode power converters commonly operate at switching frequencies from kilohertz to a few megahertz, traditionally relying on silicon-based transistors and control circuitry. However, parasitic limitations in silicon devices constrain further frequency scaling. This article presents a fully gallium nitride (GaN)-based dc–dc converter designed for high-frequency operation. The proposed architecture employs a GaN-based ring oscillator for on-chip pulsewidth modulation generation and includes all converter modules operating within the 8–43 MHz range. Experimental results validate the proposed design, demonstrating its feasibility and performance in high-frequency power conversion. The findings support the development of integrated GaN-based power conversion systems for advanced system-on-chip applications.

Power-law exponents are widely used to describe time-dependent transistor degradation and to extrapolate accelerated measurements toward operating conditions. Their physical interpretation, however, depends on the baseline from which degradation is measured. This study examines baseline sensitivity using published gate-all-around (GAA) transistor degradation data and a zero-curvature baseline reconstruction rule. In a primary dataset of 24 degradation curves, each curve yields one admissible zero-curvature root, shifting the median nominal exponent n = 0.550 to a reconstructed value 1/m = 0.346. Within an established phenomenological framework, this shift changes the inferred correlation parameter from χ = −0.820 to χ = −1.899. The apparent decrease in the local exponent with accumulated degradation appears in 19 of the 24 nominal curves but remains in only 5 curves after baseline reconstruction and is not robust under cross-fitted analysis. Across 26 eligible external nanowire curves (≥5 time points, out of 32 total curves), 19 curves yield a single admissible zero-curvature root. These roots remain numerically stable under single-point deletion (median relative change in m of 2.97% across 15 eligible curves) without systematically improving the secondary log–log fit. Numerical root stability therefore does not establish physical baseline validity. Consequently, the empirical exponent remains a useful kinetic descriptor, but it does not by itself distinguish between HCI- and BTI-like behavior or establish a transition between them.