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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Structural breakdown in high power GaN-on-GaN p-n diode devices stressed to failure

The morphology of GaN-on-GaN vertical p-i-n diode devices after reverse-bias electrical stressing to breakdown has been investigated. All failed devices had irreversible structural damage, showing large surface craters that were ∼15–35 μm deep with lengthy surface cracks. Cross-sectional electron micrographs of failed devices showed substantial concentrations of threading dislocations around the cracks and near the crater surfaces. Progressive ion-milling across damaged devices revealed high densities of threading dislocations and the presence of voids beneath the surface cracks; these features were not observed in any unstressed devices. These results should serve as a useful reference for future reliability studies of vertical high-power GaN devices.

Peri, Prudhvi (ORCID:000000022338441X)↗
DOE OSTI2020

Lateral and vertical growth of Mg-doped GaN on trench-patterned GaN films

Growth of Mg-doped GaN on trench-patterned GaN films consists of competing lateral and vertical growth fronts that result in regions with different electronic properties. Under typical growth conditions, lateral growth from the trench sidewall occurs at a faster rate than vertical growth from the trench base. When the trench width is sufficiently narrow, the growth fronts from opposite sidewalls coalesce and lead to eventual planarization of the top surface. Secondary electron imaging and cathodoluminescence mapping are used to correlate the morphology and the optical properties of regions resulting from lateral and vertical growth. For our growth conditions, the lateral-to-vertical growth rate ratio is found to be about 2.

Su, Po-Yi (ORCID:000000018339783X)↗
DOE OSTI2023

Detection of hot electrons originating from an upper valley at ∼1.7eV above the Γ valley in wurtzite GaN using electron emission spectroscopy

Using electron emission spectroscopy, measurement and analysis were conducted on the energy distribution of vacuum emitted electrons from electrically driven InGaN/GaN green (peak wavelengths 𝜆 ≈ 515nm) light-emitting diodes (LEDs) with and without a prewell superlattice (SL). Here, we report on the detection of a high-energy upper valley at ∼ 1.7eV above the Γ valley from samples with no prewell SL. We propose that these upper valley electrons originate predominantly from trap-assisted Auger recombination (TAAR) in green LEDs, as the intensity of these peaks is found to have quadratic dependence on the carrier density 𝑛 [see Espenlaub et al., J. Appl. Phys. 126, 184502 (2019)]. The high-energy upper valley peak was not observed in the sample with a prewell SL which is attributed to gettering by the prewell SL of still unidentified impurities that act as TAAR centers.

carrier generation & recombination↗
DOE OSTI2022

Effective Selective Area Doping for GaN Vertical Power Transistors Enabled by Innovative Materials Engineering

GaN vertical power transistors have emerged as promising candidates for future high efficiency high power electronic applications, with the potential to outperform conventional GaN lateral power devices in terms of power, breakdown, and avalanche characteristics. However, the development of current GaN vertical power transistors is seriously hindered by the poor materials performance of selective area doped p-n junctions. A mechanistic understanding of these fundamental materials issues is essential in order to achieve high performance selective area doped p-n junctions and consequently to advance the GaN vertical power transistor technology. To address this challenge, we carried out a comprehensive research program that advance fundamental knowledge in the selective area doping for GaN materials, and which will lead to the development of high performance GaN vertical power transistors. First, we developed innovative fabrication processes, including novel surface etching, surface passivation, and metalorganic chemical vapor deposition (MOCVD) growth, which provided enhanced opportunities for solving the unique challenges of selective area doping in GaN materials. Second, we performed a fundamental materials study using powerful characterization methods including transmission electron microscopy (TEM), ultraviolet (UV-), x-ray and angle-resolved photoelectron spectroscopy (UPS/XPS/ARPES), electron holography, and cathodoluminescence (CL); Third, we investigated several related issues, including Mg incorporation, polarization effects in carrier transport, and non-ideal material effects, which have rarely been explored so far. At the end of this project, we successfully demonstrated (1) fundamental understanding of selective area etching, regrowth, and doping of GaN, and associated knowledge on defects, interface, and breakdown properties. (2) Effective etch and regrowth processing recipes to achieve etch/regrowth GaN p-n diodes with very low leakage of 3.5 nA at 600 V, which meets the ARPA-E target. (2) High performance vertical GaN p-n didoes and vertical junction termination extension (JTE) devices with breakdown voltage of ~ 2 kV, and breakdown electric field of ~ 3.5 MV/cm, which are close to the performance limit of GaN. The successful outcome has resulted in new fundamental understandings in the selective area doping and regrowth process for GaN, which will lead to groundbreaking GaN vertical transistors for high performance next generation power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Exceptional Thermochemical Stability of Graphene on N-Polar GaN for Remote Epitaxy

In this study, we investigate the thermochemical stability of graphene on the GaN substrate for metal–organic chemical vapor deposition (MOCVD)-based remote epitaxy. Despite excellent physical properties of GaN, making it a compelling choice for high-performance electronic and light-emitting device applications, the challenge of thermochemical decomposition of graphene on a GaN substrate at high temperatures has obstructed the achievement of remote homoepitaxy via MOCVD. Our research uncovers an unexpected stability of graphene on N-polar GaN, thereby enabling the MOCVD-based remote homoepitaxy of N-polar GaN. Our comparative analysis of N- and Ga-polar GaN substrates reveals markedly different outcomes: while a graphene/N-polar GaN substrate produces releasable microcrystals (μCs), a graphene/Ga-polar GaN substrate yields nonreleasable thin films. We attribute this discrepancy to the polarity-dependent thermochemical stability of graphene on the GaN substrate and its subsequent reaction with hydrogen. Evidence obtained from Raman spectroscopy, electron microscopic analyses, and overlayer delamination points to a pronounced thermochemical stability of graphene on N-polar GaN during MOCVD-based remote homoepitaxy. Molecular dynamics simulations, corroborated by experimental data, further substantiate that the thermochemical stability of graphene is reliant on the polarity of GaN, due to different reactions with hydrogen at high temperatures. In conclusion, based on the N-polar remote homoepitaxy of μCs, the practical application of our findings was demonstrated in fabrication of flexible light-emitting diodes composed of p–n junction μCs with InGaN heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Interactively Assessing Disentanglement in GANs

Abstract Generative adversarial networks (GAN) have witnessed tremendous growth in recent years, demonstrating wide applicability in many domains. However, GANs remain notoriously difficult for people to interpret, particularly for modern GANs capable of generating photo‐realistic imagery. In this work we contribute a visual analytics approach for GAN interpretability, where we focus on the analysis and visualization of GAN disentanglement. Disentanglement is concerned with the ability to control content produced by a GAN along a small number of distinct, yet semantic, factors of variation. The goal of our approach is to shed insight on GAN disentanglement, above and beyond coarse summaries, instead permitting a deeper analysis of the data distribution modeled by a GAN. Our visualization allows one to assess a single factor of variation in terms of groupings and trends in the data distribution, where our analysis seeks to relate the learned representation space of GANs with attribute‐based semantic scoring of images produced by GANs. Through use‐cases, we show that our visualization is effective in assessing disentanglement, allowing one to quickly recognize a factor of variation and its overall quality. In addition, we show how our approach can highlight potential dataset biases learned by GANs.

Jeong, Sangwon↗