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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Investigation of AlGaN-Delta–GaN-Based UV Photodiodes in a Metal–Semiconductor–Metal Configuration for Efficient and Fast Solar Blind UV Sensing

Metal–semiconductor–metal (MSM) configured UV photodiodes (PD’s) were designed and fabricated on an AlGaN/GaN–based substrate for efficient and ultrafast UV detection. The purpose was to investigate the feasibility of obtaining efficient and ultrafast temporal response from these devices in the UV given the challenges associated with the formation of Schottky contacts on laterally oriented AlGaN/GaN thin films. Two sets of devices were implemented using Pt and Au as metal contacts with 5-µm finger width, 5-µm finger spacing, and a 50-µm x 50-µm active area. Spectral and voltage bias studies were done to establish the spectral profile and the effect of bias voltage on the responsivity of the detectors at 265 nm. Here, the best vertical MSM PD’s produced 0.6-A/W responsivity under 10-V bias voltage at 265 nm. Peak spectral responsivities were recorded as 1.35 A/W and 1.25 A/W at 240 nm for Pt and Au PD’s, respectively.

42 ENGINEERING↗
DOE OSTI2020

Materials Data on GaN by Materials Project

Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations

36 MATERIALS SCIENCE↗
NASA NTRS1996

A Microstructural Analysis of Orientation Variation in Epitaxial AlN on Si, Its Probable Origin, and Effect on Subsequent GaN Growth

A structural examination of aluminum nitride growth on [111] silicon was carried out using transmission electron microscopy. Electron diffraction indicates that the basal planes of the wurtzitic overlayer mimic the orientation of the close-packed planes of the substrate. However, considerable, random rotation in the basal plane and random out-of-plane tilts were evident. This article examines these issues with a structural examination of AlN and GaN/AlN on silicon and compares the findings to those reported in the literature.

GaN AlN Si epitaxial aluminum gallium nitride↗
NASA NTRS2013

Design of an Ultra-High Efficiency GaN High-Power Amplifier for SAR Remote Sensing

This work describes the development of a high-power amplifier for use with a remote sensing SAR system. The amplifier is intended to meet the requirements for the Sweep-SAR technique for use in the proposed DESDynI SAR instrument. In order to optimize the amplifier design, active load-pull technique is employed to provide harmonic tuning to provide efficiency improvements. In addition, some of the techniques to overcome the challenges of load-pulling high power devices are presented. The design amplifier was measured to have 49 dBm of output power with 75% PAE, which is suitable to meet the proposed system requirements.

active load-pull↗
DOE OSTI2024

A Dataset of CFD Simulated Industrial Furnace Images for Conditional Automatic Generation with GANs

The steel industry is constantly looking for ways to automate processes and improve efficiency. A standard practice in industry is to simulate how complex systems will operate before they are actually used. Some complex systems, including steel industry processes such as blast furnaces, require complex physics-based simulations utilizing computational fluid dynamics (CFD). These CFD physics-based simulations are very accurate but can take significant time and computational resources to process, resulting in challenges for the implementation of the models in real-world operational environments. In recent years, deep learning (DL) has been considered as a substitute for these CFD models. DL models can be trained on validated CFD simulation data and then used for industrial process inference. Previous DL-based solutions have made great contributions for industrial automation but are currently missing the additional visualization component that CFD simulations also provide. In this paper, we propose a dataset for simple DL generative approaches that can help to address this issue. The dataset and methodology under development to approach this prediction are discussed in this work.

Calix, Ricardo↗