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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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Hall voltage sign reversal in thin superconducting films
A novel approach to the superconducting Hall effect is developed, based on the opposing drift of the thermally excited quasi-particles. These collide quasi-elastically with the hydrodynamics superfluid velocity field circulating for outside the core of a vortex, thereby transferring momentum to the latter. The predicted Hall angle, by BCS theory, is of the order of kBTc divided by the Fermi energy, has sign opposite to that in the normal state because of the backflow, and disappears at low temperature.
Reliable operation of Cr 2 O 3 :Mg/ $β$-Ga 2 O 3 p–n heterojunction diodes at 600 °C
Beta gallium oxide (β-Ga 2 O 3 )-based semiconductor heterojunctions have recently demonstrated improved performance at high voltages and elevated temperatures and are, thus, promising for applications in power electronic devices and harsh environment sensors. However, the long-term reliability of these ultra-wideband gap (UWBG) semiconductor devices remains barely addressed and may be strongly influenced by chemical reactions at the p–n heterojunction interface. Here, we experimentally demonstrate operation and evaluate the reliability of Cr 2 O 3 :Mg/β-Ga 2 O 3 p–n heterojunction diodes during extended operation at 600 °C, as well as after 30 repeated cycles between 25 and 550 °C. The calculated pO 2 -temperature phase stability diagram of the Ga-Cr-O material system predicts that Ga 2 O 3 and Cr 2 O 3 should remain thermodynamically stable in contact with each other over a wide range of oxygen pressures and operating temperatures. The fabricated Cr 2 O 3 :Mg/β-Ga 2 O 3 p–n heterojunction diodes show room-temperature on/off ratios >104 at ±5 V and a breakdown voltage (V Br ) of -390 V. The leakage current increases with increasing temperature up to 600 °C, which is attributed to Poole–Frenkel emission with a trap barrier height of 0.19 eV. Over the course of a 140-h thermal soak at 600 °C, both the device turn-on voltage and on-state resistance increase from 1.08 V and 5.34 mΩ cm 2 to 1.59 V and 7.1 mΩ cm 2 , respectively. This increase is attributed to the accumulation of Mg and MgO at the Cr 2 O 3 /Ga 2 O 3 interface as observed from the time-of-flight secondary ion mass spectrometry analysis. These findings inform future design strategies of UWBG semiconductor devices for harsh environment operation and underscore the need for further reliability assessments for β-Ga 2 O 3 -based devices.
Identification and characterization of deep nitrogen acceptors in β-Ga 2 O 3 using defect spectroscopies
The ability to achieve highly resistive beta-phase gallium oxide (β-Ga 2 O 3 ) layers and substrates is critical for β-Ga 2 O 3 high voltage and RF devices. To date, the most common approach involves doping with iron (Fe), which generates a moderately deep acceptor-like defect state located at E C -0.8 eV in the β-Ga 2 O 3 bandgap. Recently, there has been growing interest in alternative acceptors, such as magnesium (Mg) and nitrogen (N), due to their predicted deeper energy levels, which could avoid inadvertent charge modulation during device operation. In this work, a systematic study that makes direct correlations between the introduction of N using ion implantation and the observation of a newly observed deep level at E C -2.9 eV detected by deep-level optical spectroscopy (DLOS) is presented. The concentration of this state displayed a monotonic dependence with N concentration over a range of implant conditions, as confirmed by secondary ion mass spectrometry (SIMS). With a near 1:1 match in absolute N and E C -2.9 eV trap concentrations from SIMS and DLOS, respectively, which also matched the measured removal of free electrons from capacitance-voltage studies, this indicates that N contributes a very efficiently incorporated compensating defect. Density functional theory calculations confirm the assignment of this state to be an N (0/-1) acceptor with a configuration of N occupying the oxygen site III [N O(III) ]. The near ideal efficiency for this state to compensate free electrons and its location toward the midgap region of the β-Ga 2 O 3 bandgap demonstrates the potential of N doping as a promising approach for producing semi-insulating β-Ga 2 O 3 .
Fundamental Thermodynamic, Kinetic, and Mechanical Properties of Lithium and Its Alloys
Lithium alloying reactions are beneficial in promoting uniform plating and stripping of lithium metal in all-solid-state batteries. First-principles calculations are performed to predict thermodynamic, kinetic, and mechanical properties of lithium and several important Li–M alloys (M = Mg, Ag, Zn, Al, Ga, In, Sn, Sb, and Bi). While the Li–Mg binary system forms a solid solution, most other lithium–metal alloys prefer stoichiometric intermetallic compounds with common local motifs that enable fast Li diffusion. Lithium and Li-rich alloys exhibit an unusually flat energy landscape along paths that connect BCC to close-packed structures like FCC and HCP, with important implications for mechanical properties. Very low migration barriers for Li diffusion that rival those of superion conductors are predicted, both in pure Li and in Li–M intermetallics. However, vacancy concentration, which is crucial for substitutional diffusion, is predicted to be low in metallic Li and most Li–M intermetallics. Compounds such as B32 LiAl and LiGa as well as D0 3 Li 3 Sb and Li 3 Bi exhibit structural vacancies at higher ends of their voltage windows, which together with low migration barriers leads to exceptionally high Li mobilities. In the Li–Mg solid solution, the addition of Mg is found to decrease the vacancy tracer diffusion coefficient by an order of magnitude.
CCM vs. CRM Design Optimization of a Boost-derived Parallel Active Power Decoupler for Microinverter Applications
Single-phase inverter or rectifier systems often make use of an auxiliary active power decoupler (APD) to balance the mismatch between steady DC power and fluctuating AC power. This paper deals with efficiency and size optimization of a parallel boost-type APD circuit for PV microinverter applications. Specifically, design of an eGaNFET-based, 400 W APD circuit, employing planar inductor and operating in either continuous conduction mode (CCM) or critical conduction mode (CRM) is considered. Available design variables including inductance value, inductor core geometry, capacitor voltage, switching frequency, and modulation scheme (CCM vs. CRM) are explored to identify Pareto-optimal configurations, which can achieve low California Energy Commission (CEC) efficiency drop while also reducing the footprint area of the inductor. The theoretical study predicts that the optimal CRM design can achieve 37% reduced inductor size, while operating with similar efficiency drop, compared to the optimal CCM design. Experimental results, obtained using two separate 40 V, 400 W hardware prototypes for CCM and CRM, are presented to verify the analyses.
Effects of opposing voltage and magnetic fields on charged particle motion
The motion of charged particles was examined in the case of a homogeneous magnetic field together with an orthogonal electric field which has a gradient opposing voltage parallel to the electric field. Two regimes result: in one of these, the particles' rate of gyration is changed from the conventional gyrofrequency; in the other, acceleration of the particle takes place. Applied to a plasma, the theory predicts new electric currents orthogonal to magnetic fields.
Laboratory study of the temporal evolution of the current-voltage characteristic of a probe in the wake of an object immersed in a pulsed flowing plasma
Measurements of the current-voltage characteristics of a Langmuir probe in the near wake of a disk immersed in a pulsed flowing plasma were made. A 1 cm diameter biasable sphere was placed in the ion-free near wake region of a 10 cm diameter disk immersed in a Mach 8 pulsed flowing plasma. The current-voltage characteristic of the sphere was observed as a function of time as the sphere bias was scanned from -5000 V to +1000 V. The collected current is found to be monotonically increasing with increasing positive bias voltage but exhibits a threshold voltage for current collection as the bias voltage becomes more negative. Potential measurements in the wake region were made for a sphere bias voltages below, at, and above the current collection threshold for a number of times during the wake formation period. The time evolution of the potential profile is shown to change as the sheath around the biased sphere is established. Predictions from the particle trajectory code SIMION are compared with data, showing excellent agreement in the prediction of the current collection threshold.
Network-cognizant voltage droop control
The present disclosure provides techniques for network-cognizant droop control in power systems, such as a power distribution system. An example device includes a processor configured to determine, based on (i) a model representing a structure of a power system that includes a plurality of energy resources and (ii) an indication of predicted uncontrollable power injections in the power system, for each controllable energy resource in the plurality of energy resources, a respective value of a first droop coefficient and a respective value of a second droop coefficient. The processor may be further configured to cause at least one controllable energy resource in the plurality of energy resources to modify an output power of the at least one energy resource based on the respective value of the first droop coefficient and the respective value of the second droop coefficient.
Predicting electrochemical breakdown in terrestrial photovoltaic modules
Electrochemical corrosion of PV cells can cause a cell-to-frame short circuit with two undesirable resuits: (1) catastrophic loss of source-circuit power; and (2) high field maintenance (module replacement) costs. Parameter dependencies are determined and encapsulated two-cell coupons are exposed to a range of voltage differences, temperatures, and relative humidities. Material relative performance is assessed. Nine different metallization-encapsulation combinations are tested.
Verification and validation of the open-source plasma fluid code: Zapdos
Zapdos is an open-source finite element plasma fluid solver based on the MOOSE multiphysics framework. This paper outlines Zapdos verification, benchmarking, and validation efforts for 1D and 2D RF capacitively coupled plasma discharge models for mid-range pressures (0.1 - 1 Torr). The verification process involved using the method of manufactured solutions to assess Zapdos spatial and temporal error convergence. L2 errors ranged from 10 -2 to 10 -4 , while the convergence’s slope were in agreement with the predicted slopes for the tested variable and time integration orders. The benchmarking process involved comparisons to previously results from the validated finite element code, LSODI. These works included 1D and 2D simulations for a range of plasma parameters (densities, temperatures, voltage, etc.). For the 1D cases, Zapdos and LSODI results were in very good agreement. In the 2D cases, variable behaviors matched, with slight discrepancies in peak values. The validation process involved comparisons to experimental works including electron density measurements by microwave interferometry and metastable density measurements by planar laser-induced fluorescence imaging. Results shown reasonable agreement at higher pressure, with results starting to diverge at low pressures. Furthermore, probable causes for this diverges are the limitation of the fluid assumption for plasmas at low pressure, or the need for more robust boundary conditions. Overall, Zapdos shown reasonable results for the verification, benchmarking, and validation efforts, and Zapdos can be downloaded at https://github.com/shannon-lab/zapdos.
Exploring transport mechanisms in atomic precision advanced manufacturing enabled pn junctions
We investigate the different transport mechanisms that can occur in pn junction devices made using atomic precision advanced manufacturing at temperatures ranging from cryogenic to room temperature. We first elucidate the potential cause of the anomalous behavior observed in the forward-bias response of these devices in recent cryogenic temperature measurements, which deviates from the theoretical response of a silicon Esaki diode. These anomalous behaviors include current suppression at low voltages in the forward-bias response and a much lower valley voltage at cryogenic temperatures than theoretically expected for a silicon diode. To investigate the potential causes of these anomalies, we studied the effects of a few possible transport mechanisms, including band-to-band tunneling, bandgap narrowing, potential impact of non-Ohmic contacts, band quantization, impact of leakage, and inelastic trap-assisted tunneling, through semi-classical simulations. We find that a combination of two sets of band-to-band tunneling (BTBT) parameters can qualitatively approximate the shape of the tunneling current at low bias. This can arise from band quantization and realignment due to the strong potential confinement in δ-layers. We also find that the lower-than-theoretically-expected valley voltage can be attributed to modifications in the electronic band structure within the δ-layer regions, leading to a significant bandgap narrowing induced by the high density of dopants. Finally, we extend our analyses to room temperature operation and predict that trap-assisted tunneling (TAT) facilitated by phonon interactions may become significant, leading to a complex superposition of BTBT and TAT transport mechanisms in the electrical measurements.
A control oriented comprehensive degradation model for battery energy storage system life prediction
In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.
Towards a Deeper Fundamental Understanding of (Al,Sc)N Ferroelectric Nitrides
Density functional theory (DFT) calculations, within the virtual crystal alloy approximation, are performed, along with the development of a Landau-type model employing a symmetry-allowed analytical expression of the internal energy and having parameters determined from first principles, to investigate properties and energetics of Al1-xScxN ferroelectric nitrides in their hexagonal forms. These DFT computations and this model predict the existence of two different types of minima, namely, the fourfold-coordinated wurtzite (WZ) polar structure and a five-fold coordinated paraelectric hexagonal phase (denoted as H5), for any Sc composition up to 40%. The H5 minimum progressively becomes the lowest-energy state within hexagonal symmetry as the Sc concentration increases from 0 to 0.4. Furthermore, the model points to several key findings. Examples include the crucial role of the coupling between polarization and strains to create the WZ minimum, in addition to polar and elastic energies, and that the origin of the H5 state overcoming the WZ phase as the global minimum within hexagonal symmetry when increasing the Sc composition mostly lies in the compositional dependency of only two parameters-one linked to the polarization and another one being purely elastic in nature. Other examples are that forcing Al1-xScxN systems to have no or a weak change in lattice parameters when heating them allows us to reproduce their finite-temperature polar properties well and that a value of the axial ratio close to that of the ideal WZ structure implies a large polarization at low temperatures but not necessarily at high temperatures because of the ordered-disordered character of the temperature-induced formation of the WZ state. Such findings should allow for a better fundamental understanding of (Al,Sc)N ferroelectric nitrides, which may be used to design efficient devices having, e.g., low operating voltages.
A Virtual Space Vector Model Predictive Control for a Seven-Level Hybrid Multilevel Converter
This paper proposes a virtual space vector (VSV) model predictive control (MPC) for a three-phase seven-level (7L) hybrid multilevel converter (HMC), where each phase consists of an active-neutral-point-clamped converter with a floating H-bridge. To achieve the best current tracking, which is the primary goal of the proposed algorithm, a novel geometrical positioning approach is proposed to select the optimal voltage vector among all the realspace vectors and VSVs. Then, all the possible switching sequences that belong to the optimal voltage vector are evaluated to realize the dc capacitor voltage balancing and common-mode voltage reduction. Through an external modulator, the optimal voltage vector can be synthesized by using either one-, three-, or seven-segment switching sequence. Compared with the conventional MPC, the proposed VSV-MPC can reduce not only the computational burden but also the current THD. Both simulation and experimental results obtained on silicon carbide based 7L-HMC prototype are presented to validate the feasibility and effectiveness of the proposed VSVMPC strategy.
Applying Sensor-Based Phase Identification With AMI Voltage in Distribution Systems
Not Available
Closed-loop optimization of fast-charging protocols for batteries with machine learning
Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.
Thermal conductivity of rutile germanium dioxide
Power electronics seek to improve power conversion of devices by utilizing materials with a wide bandgap, high carrier mobility, and high thermal conductivity. Due to its wide bandgap of 4.5 eV, b-Ga 2 O 3 has received much attention for high-voltage electronic device research. However, it suffers from inefficient thermal conduction that originates from its low-symmetry crystal structure. Rutile germanium oxide (r-GeO 2 ) has been identified as an alternative ultra-wide-bandgap (4.68 eV) semiconductor with predicted high electron mobility and ambipolar dopability; however, its thermal conductivity is unknown. Here, we characterize the thermal conductivity of r-GeO 2 as a function of temperature by first-principles calculations, experimental synthesis, and thermal characterization. The calculations predict an anisotropic phonon-limited thermal conductivity for r-GeO 2 of 37W m –1 K –1 along the a direction and 58W m –1 K –1 along the c direction at 300K where the phonon-limited thermal conductivity predominantly occurs via the acoustic modes. Experimentally, we measured the value of 51W m –1 K –1 at 300K for hot-pressed, polycrystalline r-GeO2 pellets. The measured value is close to our directionally averaged theoretical value, and the temperature dependence of ~1/T is also consistent with our theory prediction, indicating that thermal transport in our r-GeO 2 samples at room temperature and above is governed by phonon scattering. Furthermore, our results reveal that high-symmetry UWBG materials, such as r-GeO 2 , may be the key to efficient power electronics.