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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pulsed Power Supply for Magnet Quench Training

Superconducting magnets typically go through aseries of spontaneous “training” quenches as their current isincreased towards its design value. To decrease the number ofthese quenches, a device has been designed to boost the magnetcurrent at the moment a quench has been detected and beforemagnet protection has been initiated. The aim of the boost is todrive the magnet coil further along towards its maximum currentwith each training quench, and hence reduce the number ofquenches required.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Spinel Cu–Mn–Cr Oxide Nanoparticle-Pigmented Solar Selective Coatings Maintaining >94% Efficiency at 750 °C

High-temperature concentrating solar power (CSP) system is capable of harvesting and storing solar energy as heat towards cost-effective dispatchable solar electricity. Solar selective coating is a critical component to boost its efficiency by maximizing solar absorptance and minimizing thermal emittance losses. However, maintaining a high solar-thermal conversion efficiency >90% for long-term operation at ≥750 ºC remains a significant challenge. Herein, we report spray-coated spinel Cu-Mn-Cr oxide nanoparticle-pigmented solar selective coatings on Inconel tube sections maintaining ≥94% efficiency at 750 ºC and ≥92.5% at 800 ºC under 1000x solar concentration after 60 simulated day-night thermal cycles in air, each cycle comprising 12h at 750 ºC/800 ºC and 12h cooling to 25 ºC. The solar spectral selectivity is intrinsic to the band-to-band and d-d transitions of non-stoichiometric spinel Cu-Mn-Cr oxide nanoparticles. Furthermore, this feature offers a large fabrication tolerance in nanoparticle volume fraction and coating thickness, facilitating low-cost and scalable spray-coated high-efficiency solar selective absorbers for high-temperature CSP systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Recursive Blind Forecasting of Photovoltaic Generation and Consumer Load for Microgrids

Existing forecasting frameworks that predict time-series photovoltaic (PV) generation and consumer load for micro-grids' operation and control assume near-continuous availability of real-time predictors from the field. The incoming data are used to periodically re-train the models and update forecast snapshots over a moving horizon window. However, such frameworks are not resilient to disruptions in data availability caused by losses in communications between the field sensors and data loggers. This paper bridges the shortcoming by leveraging a previously proposed forecasting framework that is resilient to abrupt changes in data quality caused by communication losses. Assuming no availability of real-time field system data, which is typical in extreme weather events such as hurricanes, the framework uses lightweight recursive time-series models to independently forecast solar irradiance, ambient temperature, PV power, and consumer load for three horizon windows: 24 hours, 12 hours, and 1 hour. Four types of ensemble-based regression trees-simple gradient boosted trees (GBR), GBR with an adaptive component (A-GBR), random forests (RF), and extra trees (ExTR)-are leveraged and their performances are compared against a simple historical weekly mean. Numerical results show that A-GBR performs better on average by 32% for 24-hour horizon and 39% for 12-hour horizon, whereas ExTR outdoes the other models on average by 10% for 1-hour horizon.

Sundararajan, Aditya↗
DOE OSTI2020

W.A. Parish Post-Combustion CO 2 Capture and Sequestration Demonstration Project (Final Technical Report)

The Petra Nova Project (Project) is a commercial scale post-combustion carbon capture project developed by a joint venture between NRG Energy, Inc. (NRG) and JX Nippon Oil Exploration (EOR) Limited (JX). The Project is designed to separate and capture carbon dioxide (CO2) from an existing coal-fired unit’s flue gas slipstream at NRG’s W.A. Parish Electric Generating Station (WAP) located southwest of Houston, Texas. The captured CO2 is dried, compressed, and transported via an 81-mile pipeline to the West Ranch oilfield (West Ranch) in Jackson County, Texas, where it is injected to boost oil production. The Project, which is partially funded by a grant (Grant) from the United States (U.S.) Department of Energy (DOE) under the Clean Coal Power Initiative (CCPI) Round 3, uses the Kansai Mitsubishi Carbon Dioxide Recovery advanced amine-based CO 2 absorption technology (KM-CDR Process®), which was jointly developed by Mitsubishi Heavy Industries, Ltd. (MHI) and the Kansai Electric Power Co. Inc., to treat and capture at least ninety percent (90%) of the CO 2 from a 240-megawatt equivalent (MWe) flue gas slipstream off of Unit 8 at WAP. When operating at full capacity, the Project captures approximately 5,200 short tons of CO 2 per day, which would otherwise be emitted into the atmosphere, representing the largest commercial scale deployment of post-combustion CO2 capture technology at a coal power plant to date. Under the Grant, the Project was managed in 3 phases: (1) Phase 1: Project Definition / Front End Engineering Design (FEED) (2) Phase 2: Detailed Engineering, Procurement & Construction (3) Phase 3: Demonstration and Monitoring. On December 29, 2016, commercial operation of the Project was achieved, ending Phase 2 and starting Phase 3, a 3-year demonstration period running from January 1, 2017 through December 31, 2019. The key objectives of Phase 3 were to (a) demonstrate the specific advanced technologies constructed during Phase 2 and (b) monitor the injected CO 2 at West Ranch to demonstrate technologies and protocols for monitoring, verification, and accounting (MVA). As of the end of Phase 3, Petra Nova captured 3,904,978 short tons of CO 2 (3,542,537 metric tons) that was transported to West Ranch. To support the DOE obligation to monitor, verify, and account for the sequestered CO 2 at West Ranch, Petra Nova contracted with the Bureau of Economic Geology (in the Jackson School of Geosciences at The University of Texas at Austin) to (a) design a monitoring program, (b) draft an MVA Plan for DOE review and approval, and (c) working with Petra Nova and the operator of West Ranch to manage and report on the MVA activity. This report discussed the technical aspects of the project during each of the 3 phases of the project as identified above.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Monitoring Operational States of a Nuclear Reactor Using Seismoacoustic Signatures and Machine Learning

Monitoring nuclear reactors is an important safety and security task with growing requirements. We explore the possibility of using seismic and acoustic data for inferring the power level of an operating reactor. Continuous data recorded at a single seismoacoustic station that is located about 50 m away from a research reactor was visualized and analyzed. The data show a clear correlation between seismoacoustic features and reactor main operational states. We designed a workflow that includes two machine learning (ML) models to classify the reactor operational states (OFF, transition, and ON) and estimate reactor power levels (10%, 30%, 50%, 70%, and 90%). We applied and compared five ML algorithms for the reactor OFF-transition-ON and four approaches for the power level classification. We also compared the performance of ML models trained with seismic-only, acoustic-only, and both types of data. Five-fold cross validations were implemented to assure a thorough evaluation of the model performances. Additionally, the results show the extreme boosting gradient algorithm worked best for the first model, whereas random forests performed best for the second model. Combining seismic and acoustic data leads to better performance than using a single type of data. Seismic data contributed more than acoustic data for both models. We reached an accuracy of 0.98 for reactor OFF and ON. The accuracies for the transition state and power levels are less optimal with a minimum accuracy of 0.66. However, our results suggest seismic and acoustic data contain useful information about the transition state as well as power levels. Seismic and acoustic data could be integrated with other observations to improve monitoring performance.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Single Cobalt Sites Dispersed in Hierarchically Porous Nanofiber Networks for Durable and High-Power PGM-Free Cathodes in Fuel Cells

Increasing catalytic activity and durability of atomically dispersed metal–nitrogen–carbon (M–N–C) catalysts for the oxygen reduction reaction (ORR) cathode in proton-exchange-membrane fuel cells remains a grand challenge. In this study, a high-power and durable Co–N–C nanofiber catalyst synthesized through electrospinning cobalt-doped zeolitic imidazolate frameworks into selected polyacrylonitrile and poly(vinylpyrrolidone) polymers is reported. The distinct porous fibrous morphology and hierarchical structures play a vital role in boosting electrode performance by exposing more accessible active sites, providing facile electron conductivity, and facilitating the mass transport of reactant. The enhanced intrinsic activity is attributed to the extra graphitic N dopants surrounding the CoN 4 moieties. The highly graphitized carbon matrix in the catalyst is beneficial for enhancing the carbon corrosion resistance, thereby promoting catalyst stability. The unique nanoscale X-ray computed tomography verifies the well-distributed ionomer coverage throughout the fibrous carbon network in the catalyst. The membrane electrode assembly achieves a power density of 0.40 W cm –2 in a practical H 2 /air cell (1.0 bar) and demonstrates significantly enhanced durability under accelerated stability tests. The combination of the intrinsic activity and stability of single Co sites, along with unique catalyst architecture, provide new insight into designing efficient PGM-free electrodes with improved performance and durability.

25 ENERGY STORAGE↗
DOE OSTI2020

NH 4 OH Looping with Membrane CO 2 Absorber and Distributed Stripper for Enhanced Algae Growth

The University of Kentucky Center for Applied Energy (UK CAER) has devised a unique, integrated CO2 capture and utilization technology. CO2 from coal-fired power generation flue gas is first captured at half the operating cost of a typical aqueous CO2 capture system (CCS), distributed in an aqueous stream and then fixed by algae in bioreactors where the algae production is increased by 50% over that with a typical intermittent nutrient feeding system. Lower CCS operating cost is achieved by eliminating the flue gas pretreatment step for cooling and SO2 removal, eliminating steam extraction from the power generation steam cycle for solvent regeneration, and eliminating CO2 compression. Higher algae production is achieved by continuous, just-in-time nutrient feed to the bioreactors directly from a distributed solvent regenerator, which maintains the bioreactor pH for optimum growth. The process starts with a uniquely configured membrane absorber, where the flue gas is indirectly contacted with an ammonium hydroxide (NH4OH) solvent. Dissolved NH3 is attractive for both CO2 capture and as an algae nutrient. For CO2 capture it is inexpensive, has a low regeneration energy, is thermally- and oxidatively-stable and has a viscosity near that of water, which makes is easy to transport. Numerous studies have shown that the scrubbing capacity of NH3 is approximately 0.9-1.2 kg of CO2/kg of NH3, with a CO2 removal efficiency of ~99% and half the solvent regeneration energy than that of 30 wt% MEA[1, 2, 3]. NH3 is attractive as an algae nutrient due to its low cost. The rich NH4OH solvent is pumped to a set of distributed regenerators which are co-located with the algae bioreactors. Solvent pumping, transport and distribution reduces the balance of plant (BOP) cost compared to a typical aqueous CCS related to the flue gas duct and boost fan required to transport the flue gas. The energy required for the distributed solvent regeneration is supplied by solar-thermal panels eliminating the need for steam extraction from the power generation steam cycle. After solvent regeneration, the product stream contains both the CO2 captured from the flue gas and volatized NH3 from the solvent. This product stream is fed directly to the bioreactors, eliminating the need for compression of the CO2 stream. The relative amounts of CO2 and NH3 in the product stream are adjusted and controlled by a controlling the regeneration conditions (pressure and temperature). The continuous feed of the right ratio of nutrients overcomes the typical inhibition of algae growth resulting from frequent pH swings in the bioreactor due to unbalanced (intermittent) feeding systems for CO2 and N. Also, because the regenerators will operate at pressure and be located in close proximity to the bioreactors, there is no worry about pressure drop when sparging the gas into the algae. Sparging produces small bubbles which is beneficial for mass transfer efficiency. One known challenge when using an NH4OH solvent is high NH3 emission. Hydrophobic membranes are used for CO2 capture using an aqueous NH3 solution[4, 5] without the direct contact between flue gas and aqueous solution. Additionally, UK CAER CO2 capture and utilization process manages NH3 slip in three extra measures. First, NH3 slip is minimized by working with minimal species partial pressure, which is proportional to the concentration in the liquid. Hence, lowering the capture solvent concentration will lower the NH3 partial pressure. Second, UK CAER’s previous work has demonstrated that the addition of Zn2+ into NH3 solutions to chelate the NH3 can reduce NH3 volatility. Third, the configuration of the membrane CO2 absorber utilizes condensed water from the flue gas to continually wash the gas-side of the membrane to reduce fouling and recapture NH3 slip. Additional details about the UK CAER unique, integrated CO2 capture and utilization technology will be presented along with technology development plans. Diao, N., Q. Li, and Z. Fang. 2004. Heat transfer in ground heat exchangers with groundwater advection. International Journal of Thermal Sciences. 43: 1203-1211, He, Q., M. Chen, L. Meng, K. Liu, and W. Pan. 2004. Study on Carbon Dioxide Removal from Flue Gas by Absorption of Aqueous Ammonia. Western Kentucky University. Yeh, A.C., and H. Bai. 1999. Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse gas emissions. The Science of the Total Environment. 228: 121-133, Villeneuve, K., D. Roizard, J.C. Remigy, M. Iacono, and S. Rode. 2018. CO2 capture by aqueous ammonia with hollow fiber membrane contactors: Gas phase reactions and performance stability. Separation and Purification Technology, 199: 189-197, Toro Molina, C., and C. Bouallou. 2016. Carbon dioxide absorption by ammonia intensified with membrane contactors. Clean Techn Environ Policy 18, 2133–2146 (2016)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Boosting the performance of Brillouin amplification at sub-quarter-critical densities via reduction of parasitic Raman scattering

Brillouin amplification of laser pulses in plasma has been shown to be a promising approach to produce picosecond pulses of petawatt power. A key challenge is preservation of the quality of the amplified pulse, which requires control of parasitic instabilities that accompany the amplification process. At high plasma densities (> cr /4), ponderomotive filamentation has been identified as the biggest threat to the integrity of the amplifying pulse. It has therefore been proposed to perform Brillouin scattering at densities below n cr /4 to reduce the influence of filamentation. However, parasitic Raman scattering can become a problem at such densities, contrary to densities above n cr /4 where it is forbidden. In this paper, we investigate the influence of parasitic Raman scattering on Brillouin amplification at densities below n cr /4. We expose the specific problems posed by both Raman backward and forward scattering, and how both types of scattering can be mitigated, leading to an increased performance of the Brillouin amplification process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Variational Self-Consistent Theory for Beam-Loaded Cavities

A new variational theory is presented for beam loading in microwave cavities. The beam{field interaction is formulated as a dynamical interaction whose stationarity according to Hamilton’s principle will naturally lead to steady-state solutions that indicate how a cavity’s resonant frequency, Q and optimal coupling coefficient will detune as a result of the beam loading. A driven cavity Lagrangian is derived from first principles, including the effects of cavity wall losses, input power and beam interaction. The general formulation is applied to a typical klystron input cavity to predict the appropriate detuning parameters required to maximize the gain (or modulation depth) in the average Lorentz factor boost, (Δ γ). Numerical examples are presented, showing agreement with the general detuning trends previously observed in the literature. The developed formulation carries several advantages for beam-loaded cavity structures. It provides a self-consistent model for the dynamical (nonlinear) beam{field interaction, a procedure for maximizing gain under beam-loading conditions, and a useful set of parameters to guide cavity-shape optimization during the design of beam-loaded systems. Enhanced clarity of the physical picture underlying the problem seems to be gained using this approach, allowing straightforward inclusion or exclusion of different field configurations in the calculation and expressing the final results in terms of measurable quantities. Two field configurations are discussed for the klystron input cavity, using finite magnetic confinement or no confinement at all. Formulating the problem in a language that is directly accessible to the powerful techniques found in Hamiltonian dynamics and canonical transformations may potentially carry an additional advantage in terms of analytical computational gains, under suitable conditions

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

A Machine Learning-based Reliability Evaluation Model for Integrated Power-Gas Systems

This article proposes a hybrid machine learning method for the reliability evaluation of integrated power-gas systems (IPGS) under the uncertain component failure probability distributions. The Random Forest (RF) method is designed to select important features to solve the insufficient quantity of data and the curse of dimensionality problems. The Extreme Gradient Boosting (XGBoost) regression algorithm is developed to quantify the relationship between the uncertain parameters and reliability metrics. Moreover, a ten-fold cross-validation method is employed to further improve the accuracy of the regression model. Simulation results on three test systems show that the proposed method can achieve high accuracy for the reliability evaluation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Highly Effective Polysulfide-Trapping Approach for the Development of High Energy Density, Scalable Lithium-Sulfur Batteries

Lithium-sulfur (Li-S) batteries are identified as one of the most promising next-generation battery technologies owing to their high theoretical specific energy, sustainability, and affordability. However, the commercialization of Li-S batteries has been hindered by severe technical challenges, including the lithium polysulfide (PS) dissolution/shuttling effect, a major cause of fast capacity degradation over cycling. We demonstrated that, for the first time, nanolayer polymer coated high surface area porous carbons (NPCs) were coated directly on sulfur electrodes (NPC-S), which led to a high specific capacity of ∼1,600 mAh g −1 approaching the theoretical specific capacity limit in the NPC-S based Li-S batteries. The NPC-S based Li-S batteries maintained their large initial specific capacity gain compared with the Baseline-S based Li-S batteries (control) over extended cycles. A follow-on study indicated that the NPC-S approach is a necessary and critical step to boost the near-theoretical specific capacity while being stabilized over long cycles with a synergistic strategy. Our experimental and computational results suggest that NPC coated on sulfur electrodes provides not only an effective and strong PS-trapping power but also an increased redox reaction kinetics for sulfur ↔ PS’s conversions during battery charge and discharge, rendering the realization of near-theoretical discharge specific capacity in the NPC-S based Li-S batteries. The findings presented in this study may inspire a new, simple, low-cost, and commercially scalable approach, without adding any appreciable dead weight or volume to the batteries, in the effort to tackle the technical challenges facing SOA Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

A PCB-Embedded 1.2 kV SiC MOSFET Half-Bridge Package for a 22 kW AC–DC Converter

This article presents the design and analysis of a double-side-cooled printed circuit board (PCB) embedded silicon carbide (SiC) MOSFET half-bridge package with low loop inductances and an integrated gate driver. The 1.2 kV SiC MOSFET dies used in the half-bridge package are embedded in the PCB using AT&S's patented technique. The dies are cooled and electrically connected to traces in the PCB through copper-filled microvias. The design methodology accounts for both electrical and thermal performance, limiting the power-loop inductance to 2.3 nH and the maximum package temperature to less than the 175 °C limit. The integration of the gate drive circuitry allows for a high power density and 2.2 nH gate-loop inductances. At 0.12 K/W, the measured junction-to-case thermal resistance with double-sided cooling is 57% lower than that of a TO-247 package. Under similar operating conditions, the PCB-embedded half-bridge package also achieves a 5.6 times lower voltage overshoot and a 0.5% higher peak efficiency than a TO-247-based half-bridge. This article reports the first demonstration of PCB-embedded 1.2 kV SiC MOSFET packages in buck, boost, and ac–dc converters. Furthermore, the prototype three-phase ac–dc converter for an electric vehicle on-board charger is composed of six PCB-embedded half-bridge packages and achieves an efficiency of 98.2% and a power density of 182 W/in 3 .

42 ENGINEERING↗
DOE OSTI2023

Boosting the performances of protonic solid oxide fuel cells for co-production of propylene and electricity from propane by integrating thermo- and electro- catalysis

Protonic solid oxide fuel cells (p-SOFC) integrated with clean thermal energy sources are promising platforms for decarbonized chemical production in addition to power generation, such as on-purpose propylene production from propane dehydrogenation (PDH). The catalytic performance of the conventional nickel-cermet-based anode materials in p-SOFC for propane conversion is restrained by their low active surface area and proneness to coking. In this work, by integration of a highly efficient industry-relevant thermal catalyst PtGa/ZSM-5 for PDH reaction, we demonstrate that both the electrochemical and catalytic performance of the propane-fueled p-SOFC can be effectively enhanced. The PtGa catalyst integrated p-SOFC exhibits a peak power density of 93 mW cm -2 at 600°C, which is greater by about 100% and 50% than that without catalyst or with a perovskite-based (Pr 0.3 Sr 0.7 ) 0.9 Ni 0.1 Ti 0.9 O 3 (PSNT) catalyst layer, respectively. The PDH activity and olefin selectivity of the PtGa catalyst is also significantly higher than that of the PSNT catalyst. In addition, much improved coke tolerance and propylene selectivity (over 90%) compared to the catalyst-free Ni-cermet anode materials were achieved by integrating the industrial catalyst layer. The propane conversion can be further improved by an applied current density, whereas the olefin selectivity is almost unaltered. The excellent performance of the PtGa catalyst integrated p-SOFC is attributed to the high surface area, intrinsically high catalytic activity, selectivity, and anti-coking properties of the catalytic layer for propane conversion. In conclusion, this work provides a general approach and a case study for boosting the performances of p-SOFCs in chemical production by integrating thermo- and electro- catalysis.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Quantum Chemical Density Matrix Renormalization Group Method Boosted by Machine Learning

The use of machine learning (ML) to refine low-level theoretical calculations to achieve higher accuracy is a promising and actively evolving approach known as Δ-ML. The density matrix renormalization group (DMRG) is a powerful variational approach widely used for studying strongly correlated quantum systems. High computational efficiency can be achieved without compromising accuracy. Here, we demonstrate the potential of a simple ML model to significantly enhance the performance of the quantum chemical DMRG method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optimized molecular aggregation via incorporating fluorinated unit in the polymer donor for 17.3% efficiency organic solar cells

Regulating molecular aggregation state via chemical modification of photovoltaic materials to optimize the blend morphology is an effective and challenging strategy to improve the photovoltaic performance of organic solar cells (OSCs). Here, in this work, we demonstrate a random terpolymerization strategy by incorporating 1,3-bis(5-bromo-4-fluorothiophen-2-yl)-5,7-bis(2-ethylhexyl)-4H,8H-benzo[1,2-c:4,5-c']bisthiophene-4,8-dione (BFT, 30 mol%) unit with fluorinated π-bridges into the molecular backbone of PM6 and develop a terpolymer PF1. Benefiting from the strong electronegativity of fluorine atom and noncovalent interaction of F---S, the energy levels, molecular ordering, and aggregation properties of the polymer donors are precisely regulated. Notably, in the active layer film based on PF1: Y6, the π-π stacking distance can reduce to 3.51 Å, which is significantly smaller than that of PM6:Y6 (3.65 Å) and boosts the effective exciton dissociation and charge transport, thereby effectively optimize the photovoltaic properties of the related devices. As a result, the PF1:Y6-based OSCs achieved a power conversion efficiency (PCE) of up to 17.3%, which is much higher than that of the controlled OSCs based on PM6:Y6 (PCE = 16.2%). These results demonstrate high-efficiency OSCs enabled by regulating molecular aggregation via terpolymerization strategy.

14 SOLAR ENERGY↗
DOE OSTI2023

Interpretable boosted-decision-tree analysis for the Majorana Demonstrator

The Majorana Demonstrator is a leading experiment searching for neutrinoless double-beta decay with high purity germanium detectors (HPGe). Machine learning provides a new way to maximize the amount of information provided by these detectors, but the data-driven nature makes it less interpretable compared to traditional analysis. An interpretability study reveals the machine's decision-making logic, allowing us to learn from the machine to feedback to the traditional analysis. In this work, we have presented the first machine learning analysis of the data from the Majorana Demonstrator; this is also the first interpretable machine learning analysis of any germanium detector experiment. Two gradient boosted decision tree models are trained to learn from the data, and a game-theory-based model interpretability study is conducted to understand the origin of the classification power. By learning from data, this analysis recognizes the correlations among reconstruction parameters to further enhance the background rejection performance. By learning from the machine, this analysis reveals the importance of new background categories to reciprocally benefit the standard Majorana analysis. This model is highly compatible with next-generation germanium detector experiments like LEGEND since it can be simultaneously trained on a large number of detectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A study on the impact of mid-gap defects on vertical GaN diodes

GaN is a favorable martial for future efficient high voltage power switches. GaN has not dominated the power electronics market due to immature substrate, homoepitaxial growth, and immature processing technology. Understanding the impact of the substrate and homoepitaxial growth on the device performance is crucial for boosting the performance of GaN. Here, we studied vertical GaN PiN diodes that were fabricated on non-homogenous Hydride Vapor Phase Epitaxy (HVPE) substrates from two different vendors. We show that defects which stemmed from growth techniques manifest themselves as leakage hubs. Different non-homogenous substrates showed different distribution of those defects spatially with the lesser quality substrates clustering those defects in clusters that causes pre-mature breakdown. Energetically these defects are mostly mid-gap around 1.8Ev with light emission spans from 450nm to 700nm. Photon emission spectrometry and hyperspectral electroluminescence were used to locate these defects spatially and energetically.

42 ENGINEERING↗
DOE OSTI2021

From crystal color symmetry to quantum spacetime

More than one hundred years after the inception of relativistic physics, the concept of time remains incompletely understood. Relativity provides means to perform calculations of geometrical properties of spacetime, such as distances or curvature, and to interpret them in terms of physical observations, for instance as time dilation or gravitational effects. However, an intuitive understanding of spacetime is complicated, not so much because it is four-dimensional (which, after all, can be evaded by visualizing twodimensional cross sections) but mainly because its geometry does not obey Euclid’s axioms even in the absence of curvature. Through a well defined and clever transformation (RBS: renormalized blended spacetime), Venkatraman Gopalan (2021) has demonstrated how the hyperbolic geometry in Minkowski spacetime can be mapped to a circular Euclidean geometry. In particular, Lorentzian boosts become Euclidean rotations which enables new frontiers of exploration in color symmetry and magnetic crystals. His idea of general relativistic spacetime crystals and how to obtain them is both powerful and broad, although the notion of relativistic crystals and lattices in two dimensions has existed for a while (Janner & Ascher, 1969a,b). Finally, the breadth of this new work is underlined by the present opinion piece, written by two co-authors with distinct yet connected areas of expertise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗