Related papers: Vertical GaN Diode BV Maximization through Rapid T…
Optimal Volt/VAR control (VVC) in distribution networks relies on an effective coordination between the conventional utility-owned mechanical devices and the smart residential photovoltaic (PV) inverters. Typically, a central controller…
We are the first to report the frequency response and corresponding current density of a wurtzite phase Indium Nitride (InN)-based vertical configuration Gunn diode at 1 \mu m active length. Domain growths dynamics with respect to space and…
Voltage (Volt) and reactive-power (VAR) control in transmission networks is critical for reliability and increasingly needs fast, implementable decisions. This paper presents a transmission Volt/VAR Optimization (VVO) framework that…
The growing integration of distributed energy resources into distribution systems poses challenges for voltage regulation. Dynamic VAR Compensators (DVCs) are a new generation of power electronics-based Volt/VAR compensation devices…
Voltage Overscaling (VOS) is one of the well-known techniques to increase the energy efficiency of arithmetic units. Also, it can provide significant lifetime improvements, while still meeting the accuracy requirements of inherently…
Deep ultraviolet (UV) optical emission below 250 nm (~5 eV) in semiconductors is traditionally obtained from high aluminum containing AlGaN alloy quantum wells. It is shown here that high-quality epitaxial ultrathin binary GaN quantum disks…
A Low-Power Variable Gain (VG) mm-Wave Low Noise Amplifier (LNA) is designed and simulated in a 28-nm CMOS process. The LNA utilizes a simple, yet novel, technique presented in this paper to vary the small-signal output resistance to…
High-energy-resolution GaN $\alpha$-particle detectors have significant potential for space radiation, nuclear instrumentation, and harsh-environment applications. However, existing GaN $\alpha$-particle detectors still face several key…
Although the GW approximation is recognized as one of the most accurate theories for predicting materials excited states properties, scaling up conventional GW calculations for large systems remains a major challenge. We present a powerful…
This study presents a deep neural network (DNN) framework that accelerates Direct Simulation Monte Carlo (DSMC) computations for rarefied-gas flows, while maintaining high physical fidelity. First, a fully connected deep neural network is…
This paper presents a novel algorithm to optimize energy capacity restoration of vanadium redox flow batteries (VRFBs). VRFB technologies can have their lives prolonged through a partially restoration of the lost capacity by electrolyte…
Traditionally, Volt/VAR optimization (VVO) is performed in distribution networks through legacy devices such as on-load tap changers (OLTCs), voltage regulators (VRs), and capacitor banks. With the amendment in IEEE 1547 standard,…
Recent studies reveal a significant theoretical link between variational autoencoders (VAEs) and rate-distortion theory, notably in utilizing VAEs to estimate the theoretical upper bound of the information rate-distortion function of…
Both hexagonal wurtzite and cubic zinc blend GaN phases were synthesized in GaAs by 50 keV N+ implantation at 400 deg C and subsequent annealing at 900 deg C for 15 min in N2 ambient. Crystallographic structural and Raman scattering studies…
We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power…
Purpose: Radio-frequency ablations play an important role in the therapy of malignant liver lesions. The navigation of a needle to the lesion poses a challenge for both the trainees and intervening physicians. Methods: This publication…
Indium gallium nitride (InGaN) quantum well (QW) micro- and nanoscale light-emitting diodes (LEDs) are promising for next-generation ultrafast optical interconnects and augmented/virtual reality displays. However, scaling to nanoscale…
The ubiquity of fluids in the physical world explains the need to accurately simulate their dynamics for many scientific and engineering applications. Traditionally, well established but resource intensive CFD solvers provide such…
In modern manufacturing, Visual Anomaly Detection (VAD) is essential for automated inspection and consistent product quality. Yet, increasingly dynamic and flexible production environments introduce key challenges: First, frequent product…
Stein Variational Gradient Descent (SVGD) is a popular variational inference algorithm which simulates an interacting particle system to approximately sample from a target distribution, with impressive empirical performance across various…