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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Propulsion System Design using a Dual 3-Phase PM Synchronous Reluctance Machine with X-Type Multi-Level GaN Inverter

— A propulsion system design is exhibited here that comprises of an X-type GaN power module based dual multi-level inverter and a PM Synchronous Reluctance motor. With the critical benefits of multi-level operation, namely low common mode EMI noise, low switching loss, low current Total Harmonic Distortion (THD), smoother torque and lower iron loss, this topology targets high system-level efficiency and high power density while using reduced rare earth (RE) elements in its motor. General Motors and Purdue University jointly designed and developed this 800V class, highly scalable traction drive that can deliver 200+ kW of power suitable for C-SUV to truck vehicle class. The 3-phase electric machine design utilizes dual winding with 6 terminals to work in line with the GaN X-type inverter, and results in a tractive solution that ensures higher machine efficiency while reducing cost and uncertainty related to use and availability of heavy rare earth/rare earth elements in its rotor.

MOMEN, FAIZUL [General Motors LLC, Detroit, MI (Un↗
DOE OSTI2023

A riming‐dependent parameterization of scattering by snowflakes using the self‐similar Rayleigh–Gans approximation

Abstract Riming is a key process of precipitation formation in ice‐containing clouds, but quantifying riming from observations is challenging, limiting our ability to evaluate the riming process in numerical weather models. One challenge for radar observations is that riming changes both the physical properties (mass, area cross‐section) and scattering properties of ice particles. These changes need to be implemented consistently as a function of riming in radar forward operators, which are required for retrievals and model evaluation in observation space. In this study, mass–size, cross‐section area–size, and backscattering cross‐section relations are developed as a function of the normalized rime mass for aggregates composed of various monomer types (columns, dendrites, needles, plates, and rosettes). The proposed framework allows us to simulate scattering properties of aggregated ice particles consistently as a function of riming in retrievals and radar forward operators. The parameterizations are developed from a large data set of simulated rimed aggregates of different sizes and monomer crystal types. The backscattering cross‐section parameterization (the “riming‐dependent parameterization”) is evaluated for radar frequencies of 35.6 and 94.0 GHz and is based on the Self‐Similar Rayleigh–Gans approximation (SSRGA), which is increasingly used to calculate microwave scattering of ice crystals and snowflakes. Compared with parameterizations from the literature that do not consider riming, the riming‐dependent parameterization leads to significantly smaller biases in terms of backscattering cross‐section. When using the particle masses and scattering properties of the individual particles simulated by the aggregation and riming model as a reference, the bias of our parameterization is below 1 dB when integrating over an exponential particle size distribution with sizes from 0.1–10 mm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Defect suppression in wet-treated etched-and-regrown nonpolar m-plane GaN vertical Schottky diodes: A deep-level optical spectroscopy analysis

In this work, steady-state photocapacitance (SSPC) was conducted on nonpolar m-plane GaN n-type Schottky diodes to evaluate the defects induced by inductively coupled plasma (ICP) dry etching in etched-and-regrown unipolar structures. An ~10× increase in the near-midgap Ec – 1.9 eV level compared to an as-grown material was observed. Defect levels associated with regrowth without an etch were also investigated. The defects in the regrown structure (without an etch) are highly spatially localized to the regrowth interface. Subsequently, by depth profiling an etched-and-regrown sample, we show that the intensities of the defect-related SSPC features associated with dry etching depend strongly on the depth away from the regrowth interface, which is also reported previously. A photoelectrochemical etching (PEC) method and a wet AZ400K treatment are also introduced to reduce the etch-induced deep levels. A significant reduction in the density of deep levels is observed in the sample that was treated with PEC etching after dry etching and prior to regrowth. An ~2× reduction in the density of Ec – 1.9 eV level compared to a reference etched-and-regrown structure was observed upon the application of PEC etching treatment prior to the regrowth. The PEC etching method is promising for reducing defects in selective-area doping for vertical power switching structures with complex geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of high-dose gamma-ray irradiation on electrical characteristics of N-polar and Ga-polar GaN p–n diodes

We investigate the impact of high-dose gamma-ray irradiation on the electrical performance of Ga-polar and N-polar GaN-based p-n diodes grown by metalorganic chemical vapor deposition. We compare the current density-voltage (J-V), capacitance-voltage (C-V), and circular transfer length method (CTLM) characteristics of the p-n diodes fabricated on Ga-polar and N-polar orientations before and after irradiation. The relative turn-on voltage increases for the Ga-polar diodes with increasing irradiation dose, while it increases initially and then starts to decrease for the N-polar diodes. The p-contact total resistance increases for Ga-polar and decreases for N-polar samples, which we attribute to the formation of point defects and additional Mg activation after irradiation. The J-V characteristics of most of the tested diodes recovered over time, suggesting the changes in the J-V characteristics are temporary and potentially due to metastable occupancy of traps after irradiation. X-ray photoelectron spectroscopy (XPS) and photoluminescence (PL) measurements reveal the existence of different types of initial defects and surface electronic states on Ga-polar and N-polar samples. Gallium vacancies (V Ga ) are dominant defects in Ga-polar samples, while nitrogen vacancies (V N ) are dominant in N-polar samples. The presence of a higher concentration of surface states on Ga-polar surfaces compared to N-polar was confirmed by calculating the band bending and the corresponding screening effect due to opposite polarization bound charge and ionized acceptors at the surface. The difference in surface stoichiometry in these two orientations is responsible for the different behavior in electrical characteristics after gamma-ray interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effect of Illumination Area on the Ultrafast Temporal Response of MSM GaN Photodiodes

We investigate the influence of spatial illumination profiles on the temporal response of metal–semiconductor–metal GaN photodiodes. Using both simulation and experimental measurements, we compare the response curves under two scenarios: illumination confined to the active area between electrodes and extended illumination beyond the contacts. The results show that limiting the beam illumination to the active region significantly sharpens the response, reducing the long decay tails associated with slow carrier drift from peripheral regions. As a result, the experimental data closely match simulation predictions, confirming that illumination geometry plays a critical role in optimizing photodiode performance for ultrafast detection applications.

Carrier drift time↗
DOE OSTI2024

Switching Modes for Reduction of Peak Voltage Transients in GaN-Based Three Level ANPC Inverter

The switching pole voltage can transition between P,0, and N states in a three-level active neutral point clamped (ANPC) inverter. State transitions between 0-P and 0-N can be realized with different switching modes. Three switching modes- Short 1 , Short 2 , and Full are studied considering the effect of capacitive current paths. The role of clamping and inner switch on/off conditions is determined using simplified equivalent circuit models. Short 2 with clamping switch off is beneficial for turn-on overvoltage suppression but results in high turn-off overvoltage. Full mode with a parallel current sharing path is effective for turn-off overvoltage suppression but leads to high turn-on overvoltage. Hence, a Modified Full mode is proposed to achieve the simultaneous objective of overvoltage suppression at both turn-on and turn-off transient during high load currents. This benefits 3L ANPC operation at a low power factor with a high load current at fundamental voltage zero crossing points. Here, a 650V GaN-based three-level ANPC inverter prototype is designed and used to evaluate the switching modes and overvoltage suppression strategies through double pulse tests and continuous operation.

42 ENGINEERING↗
DOE OSTI2023

Bayesian GAN-Based False Data Injection Attack Detection in Active Distribution Grids With DERs

Advancements in information and communication technologies have revolutionized monitoring and control capabilities within smart grids. However, it also brings new vulnerabilities to data acquisition systems and state estimation functions, which attackers can subtly tamper with the measurement data through compromising the communication network. Moreover, the high penetration of renewable energy sources with the inherited characteristics of uncertainty and variability further complicates the design of effective intrusion detection systems. In this paper, a Bayesian deep learning-based approach is developed to detect cyber attacks and maintain the security of smart grids. Our method specifically addresses the prevalent issue of imbalanced data in real power systems, which arises from the predominance of normal system operations over compromised or attacked states. Employing a novel Bayesian GAN-based technique, our approach successfully discriminates between secure and compromised measurement data, even in scenarios with significant data imbalance. Furthermore, the proposed method accommodates various practical application factors, ensuring accurate intrusion detection despite the presence of measurement noise. The feasibility and effectiveness of the proposed detection mechanism are validated by testing on IEEE 13-node and 123-node test systems. Simulation results and comparisons with literature methods demonstrate the superiority of proposed cybersecurity solutions.

Bayesian GAN↗
DOE OSTI2020

Materials Data on GaN by Materials Project

GaN is Halite, Rock Salt structured and crystallizes in the cubic Fm-3m space group. The structure is three-dimensional. Ga3+ is bonded to six equivalent N3- atoms to form a mixture of edge and corner-sharing GaN6 octahedra. The corner-sharing octahedral tilt angles are 0°. All Ga–N bond lengths are 2.14 Å. N3- is bonded to six equivalent Ga3+ atoms to form a mixture of edge and corner-sharing NGa6 octahedra. The corner-sharing octahedral tilt angles are 0°.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on GaN by Materials Project

GaN is Wurtzite structured and crystallizes in the hexagonal P6_3mc space group. The structure is three-dimensional. Ga3+ is bonded to four equivalent N3- atoms to form corner-sharing GaN4 tetrahedra. All Ga–N bond lengths are 1.97 Å. N3- is bonded to four equivalent Ga3+ atoms to form corner-sharing NGa4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Materials Data on GaN by Materials Project

GaN is Zincblende, Sphalerite structured and crystallizes in the cubic F-43m space group. The structure is three-dimensional. Ga3+ is bonded to four equivalent N3- atoms to form corner-sharing GaN4 tetrahedra. All Ga–N bond lengths are 1.97 Å. N3- is bonded to four equivalent Ga3+ atoms to form corner-sharing NGa4 tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lossless Phonon Transition Through GaN‐Diamond and Si‐Diamond Interfaces

Abstract Advancing Silicon (Si) technology beyond Moore's law through 3D architectures requires highly efficient heat management methods compatible with foundry processes. While continued increases in transistor density can be achieved through 3D architectures, self‐heating in the upper tiers degrades the performance. Self‐heating is a critical problem for high‐power, high‐frequency, wide bandgap, and ultra‐wide bandgap devices as well. Diamond, known for its exceptional thermal conductivity, offers a viable solution in both these cases. Since thermal boundary resistance (between the channel/junction and diamond plays a crucial role in overall thermal resistance, this study investigates various dielectrics for interface engineering, such as Silicon dioxide (SiO 2 ), amorphous‐ Silicon Carbide (a‐SiC), and Silicon Nitride (SiN x ), to make a phonon bridge at gallium nitride (GaN)‐diamond and Si‐diamond interfaces. The a‐SiC interlayer reduces diamond/GaN (<5 m 2 K per GW) and diamond/Si (<2 m 2 K per GW) thermal boundary resistances by linking low‐ and high‐frequency phonons, boosting phonon transport through the interface. Engineered interfaces enhance heat spreading from the channel/junction and rule out premature failure.

Malakoutian, Mohamadali↗
DOE OSTI2022

First principles thermal transport modeling in GaN and related materials

Gallium nitride is a wide bandgap material utilized in a variety of technologies, including high-power electronics and light-emitting diodes, partly due to its favorable thermal properties. This chapter describes modern first-principles-based modeling of phonons and lattice thermal conductivity (k) of GaN, III-nitrides and related materials. In particular, we describe the theoretical underpinnings of calculating phonon dispersions, intrinsic phonon interactions, and other lattice dynamical properties from quantum perturbation theory and density functional theory (DFT) methods. Description of how these methods are then coupled with the Peierls-Boltzmann transport (PBT) equation to determine phonon distributions and lifetimes relevant for thermal transport is given. These theoretical and numerical methods have demonstrated quantitative accuracy and predictive power for calculating pristine k and defect-limited k from first principles for a variety of materials. We present a review of the literature utilizing DFT-PBT methods to understand novel k behaviors in III-nitrides and related materials.

Lindsay, Lucas↗
DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2023

Non-planar growth of high Al-mole-fraction AlGaN on patterned GaN platforms for mitigating strain-induced cracks beyond the critical layer thickness

Non-planar growth of Al x Ga 1-x N epitaxial layers with an average alloy composition up to Al-mole-fraction of x ~ 0.21 was performed on patterned c-plane GaN on (0001) sapphire substrates with stripe-shaped mesa structures. This approach successfully realized the growth of crack-free AlGaN layers on the top of mesas with layer thicknesses greater than the expected critical layer thickness by relaxing the in-plane stress on the top of the mesa. The effectiveness of the relaxation strongly depends on the width and depth of the stripe mesa. In conclusion, the relaxation of in-plane stress and resultant suppression of cracks in AlGaN layer are qualitatively discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Epitaxial growth of rock salt MgZrN 2 semiconductors on MgO and GaN

Ternary nitride compound semiconductors have attracted recent attention as electronic materials since their properties can be tuned by cation stoichiometry and ordering. A recently discovered example is MgZrN 2 , a ternary analog to the rock salt semiconductor ScN. MgZrN 2 has a larger bandgap and stronger dielectric response than the binary compound. Polycrystalline thin films of MgZrN 2 have been studied, but demonstration of high-quality growth is still required to establish its suitability for technological applications. Here, we report on epitaxial growth of MgZrN 2 thin films on (100) and (111) MgO substrates and (001) GaN templates. The MgZrN 2 composition is confirmed by Rutherford backscattering spectrometry, showing no oxygen in the film except for a thin surface oxide layer. Epitaxial growth results in MgZrN 2 with x-ray diffraction rocking curves with a full-width at half-maximum in the range of 0.3–3.0°, depending on the substrate. Transmission electron microscopy analysis of the MgZrN 2 film grown on a (111) MgO substrate confirms epitaxial growth and shows a sharp film/substrate interface. In-plane temperature-dependent Hall effect measurements show that the material is an n-type semiconductor with a relatively high concentration ( n 300K ≈ 10 19 –10 20 cm -3 ) of thermally activated electrons. Room-temperature transport measurements show a conductivity of 25 S cm -1 and a Seebeck coefficient of -80 μ V K -1 . Overall, these results provide an important step toward integration of rock salt MgZrN 2 with other technological nitrides for device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Local electric field measurement in GaN diodes by exciton Franz–Keldysh photocurrent spectroscopy

The eXciton Franz–Keldysh (XFK) effect is observed in GaN p–n junction diodes via the spectral variation of photocurrent responsivity data that redshift and broaden with increasing reverse bias. Photocurrent spectra are quantitatively fit over a broad photon energy range to an XFK model using only a single fit parameter that determines the line shape and the local bias (V l ), uniquely determining the local electric field maximum and depletion widths. As expected, the spectrally determined values of V l vary linearly with the applied bias (V) and reveal a large reduction in the local electric field due to electrostatic non-uniformity. The built-in bias (V bi ) is estimated by extrapolating V l at V=0, which, when compared with independent C-V measurements, indicates an overall ±0.31 V accuracy of V l . This demonstrates sub-bandgap photocurrent spectroscopy as a local probe of electric field in wide bandgap diodes that can be used to map out regions of device breakdown (hot spots) for improving electrostatic design of high-voltage devices.

42 ENGINEERING↗