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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Negative differential resistance in GaN homojunction tunnel diodes and low voltage loss tunnel contacts

The current-voltage characteristics and metastability in GaN p++/n++ homojunction tunnel diodes and n++/p++/i/n tunnel-contacted diodes grown via metal modulated epitaxy have been reported on. The room temperature negative differential resistance (NDR) beginning at ~1.35 V is discussed for GaN homojunction devices grown on sapphire. The NDR vanishes, and the conductivity increases as multiple I-V sweeps are performed, thus implying that charge trapping states with long trap lifetimes exist at defect sites, and these traps play a crucial role in the tunneling mechanism. Additionally, the use of extremely high n-type (N D ~ 4.6×10 20 cm –3 ) and p-type (N A ~ 7.7×10 20 cm –3 ) doping results in a near linear characteristic with minimal rectification at current densities less than 200 A/cm 2 and soft rectification above this current density. Forward-bias tunneling and NDR are still present at 77 K. The highest silicon-doped n++/p++/i/n tunnel-contacted pin diode demonstrates a turn-on voltage of 3.12 V, only 0.14 V higher than that of the pin control diode, and an improved specific on-resistance of 3.24 ×10 –4 Ω cm 2 , which is 13% lower than that of the control pin diode.

42 ENGINEERING↗
DOE OSTI2019

Spiral waves in externally excited neuronal network: Solvable model with a monotonically differentiable magnetic flux

Spiral waves are particular spatiotemporal patterns connected to specific phase singularities representing topological wave dislocations or nodes of zero amplitude, witnessed in a wide range of complex systems such as neuronal networks. The appearance of these waves is linked to the network structure as well as the diffusion dynamics of its blocks. We report a novel form of the Hindmarsh-Rose neuron model utilized as a square neuronal network, showing the remarkable multistructure of dynamical patterns ranging from characteristic spiral wave domains of spatiotemporal phase coherence to regions of hyperchaos. The proposed model comprises a hyperbolic memductance function as the monotone differentiable magnetic flux. Hindmarsh-Rose neurons with an external electromagnetic excitation are considered in three different cases: no excitation, periodic excitation, and quasiperiodic excitation. We performed an extensive study of the neuronal dynamics including calculation of equilibrium points, bifurcation analysis, and Lyapunov spectrum. We have found the property of antimonotonicity in bifurcation scenarios with no excitation or periodic excitation and identified wide regions of hyperchaos in the case of quasiperiodic excitation. Furthermore, the formation and elimination of the spiral waves in each case of external excitation with respect to stimuli parameters are investigated. We have identified novel forms of Hindmarsh-Rose bursting dynamics. Our findings reveal multipartite spiral wave formations and symmetry breaking spatiotemporal dynamics of the neuronal model that may find broad practical applications. © 2019 Author(s).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Triple differential cross sections for electron-impact ionization of methane at intermediate energy

We report an experimental and theoretical investigation of electron-impact single ionization of the highest occupied molecular orbital 1 t 2 and the next highest occupied molecular orbital 2 a 1 states of CH 4 at an incident electron energy of 250 eV. Triple differential cross sections measured in two different laboratories were compared with results calculated within the molecular 3-body distorted wave and generalized Sturmian function theoretical models. For ionization of the 1 t 2 state, the binary peak was observed to have a single maximum near the momentum transfer direction that evolved into a double peak for increasing projectile scattering angles, as has been seen for ionization of atomic p-states. A detailed investigation of this evolution was performed. As expected because of its s-type character, for ionization of the 2 a 1 state, only a single binary peak was observed. Altogether, good agreement was found between experiment and theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The role of Mg bulk hyper-doping and delta-doping in low-resistance GaN homojunction tunnel diodes with negative differential resistance

GaN p ++ /n ++ tunnel junctions (TJs) with heavy bulk or delta Mg doping at the junction were grown via molecular beam epitaxy with a hysteresis-free and repeatable negative differential resistance (NDR). The TJ with Mg doping of 5.5 × 10 20 cm -3 shows NDR at~1.8 V and a large current density of 3.4 KA/cm 2 at -1.0 V. Atomic resolution scanning transmission electron microscopy imaging showed no additional defects despite the doping exceeding the solubility limit in GaN allowing subsequent epitaxy of series-connected layers and devices. GaN homojunction TJs grown on bulk GaN showed an improved current density and NDR stability. In addition, the effect of Mg delta doping at the junction was investigated for the first time showing a dramatic improvement in the tunneling characteristics. A metal-organic chemical vapor deposition (MOCVD) grown InGaN light-emitting diode (LED) with an MBE grown GaN homojunction tunnel contact to the MOCVD grown p-GaN layer shows superior lateral conductivity and improved luminescence uniformity, but suffers an added voltage penalty, assumed to be due to interface impurities, compared to control LED with indium-tin-oxide.

Epitaxy↗
DOE OSTI2019

Ultra-wide-bandgap AlGaN homojunction tunnel diodes with negative differential resistance

The power efficiencies of state-of-the-art Al x Ga 1-x N deep-ultraviolet (UV) emitters operating in the <300 nm wavelength region are currently limited to a few percent in part due to limitations in the series and contact resistance which result in excessive drive voltages. Al x Ga 1-x N tunnel contacts and tunnel junctions in deep-UV devices are a promising route toward increasing these efficiencies by improving the contact resistances, hole injection, and reducing optical absorption by removing undesirable p-GaN contact layers. However, due to doping inefficiencies, standalone tunnel diodes have not been realized in the form of homojunction Al x Ga 1-x N. In this work, Al x Ga 1-x N (0.19 ≤ x ≤ 0.58) homojunction tunnel diodes are fabricated with high reverse bias current densities, and one device with x = 0.19 demonstrates a negative differential resistance at ~2.4 V. Al x Ga 1-x N p++/n++/n tunnel diodes are compared to reference p++/i/n diodes to provide clarity about the role of tunneling conduction vs leakage conduction. Transmission electron microscopy verifies that heavy doping does not result in visible defects such as Mg precipitates and allows for subsequent epitaxy, critical for buried tunnel junction structures. Increasing the bandgap energy of Al x Ga 1-x N for higher Al content tunnel junctions decreases the tunnel current, but still allows sufficient conduction necessary for future improvements in deep UV emitter efficiencies.

Nitrides↗
DOE OSTI2020

Isotope effects on the high pressure viscosity of liquid water measured by differential dynamic microscopy

In this paper, differential dynamic microscopy is performed in diamond anvil cells to measure the viscosity of water along the 24 °C isotherm to high-pressure by determination of the tracer diffusion coefficient of monodisperse silica spheres of known diameter and application of the Stokes-Einstein-Sutherland equation. This technique allows liquid samples to be compressed to greater pressure prior to freezing than with other viscometry methods. The highest-pressure measurement was made at 1.67 GPa, considerably deeper into the supercompressed regime than previously reported. The effect of isotopic composition is investigated with samples of normal water, heavy water, and partially deuterated water. When data below 0.25 GPa are excluded a free volume model fits the observed viscosities well yielding a theoretical glass transition density close to that observed in very-high-density amorphous ice. The improved fit above 0.25 GPa coincides with the loss of other anomalous behaviors in liquid water caused by hydrogen bonding and represents a transition to properties closer to those of a simple liquid.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Direct observation of negative differential resistance in WS2 homojunction

Vertical tunneling junctions showing negative differential resistance (NDR) are realized in WS2 homojunction devices. Mono-/multilayered single crystalline WS2 is grown using chemical vapor deposition. NDR is observed through resonant tunneling in Au/bi-layer WS2/Au and Pt/few-layered WS2/Au tunneling junctions by back-gating at room temperature. While two-dimensional materials have been a central focus of materials research during the past decade, exploiting novel properties in diverse layers of these materials is emerging with new designs for electronic devices. Our results pave the way for novel resonant tunneling devices presenting a route to fabricate homojunction WS2 with simple fabrication techniques.

Hsu, Bo (ORCID:0000000201714211)↗
DOE OSTI2021

Optimizing the differential connection schemes for detecting 3D magnetic perturbations in DIII-D

Optimizing the differential pair connection scheme (i.e. the set of pairs) of a toroidal array of magnetic sensors dedicated to measuring slowly rotating asymmetric fields can enhance the mode number detection capability and failure-resilience. In this work the condition number obtained from singular value decomposition (SVD) of the design matrix is used as a metric to evaluate the quality of a connection scheme. A large number of possible pair connections are usually available, so evaluating all of them may require extensive use of computational resources and can be very time consuming. Alternative methods to reduce the number of pairs evaluated without losing the capabilities of toroidal mode detection are presented in this paper. Here, three examples of the applications of such analysis for the 3D magnetic diagnostic system of DIII-D are also presented: the addition of two new toroidal arrays with n > 3 detection capabilities, the modification of an existing toroidal array in the low field side of the machine to accommodate the addition of a helicon antenna, and the design of changes in several toroidal arrays in the high field side to accommodate the addition of a lower hybrid current drive antenna on the center post.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Physics-based compact modeling of electro-thermal memristors: Negative differential resistance, local activity, and non-local dynamical bifurcations

Leon Chua's Local Activity theory quantitatively relates the compact model of an isolated nonlinear circuit element, such as a memristor, to its potential for desired dynamical behaviors when externally coupled to passive elements in a circuit. However, the theory's use has often been limited to potentially unphysical toy models and analyses of small-signal linear circuits containing pseudo-elements (resistors, capacitors, and inductors), which provide little insight into required physical, material, and device properties. Furthermore, the Local Activity concept relies on a local analysis and must be complemented by examining dynamical behavior far away from the steady-states of a circuit. In this work, we review and study a class of generic and extended one-dimensional electro-thermal memristors (i.e., temperature is the sole state variable), re-framing the analysis in terms of physically motivated definitions and visualizations to derive intuitive compact models and simulate their dynamical behavior in terms of experimentally measurable properties, such as electrical and thermal conductance and capacitance and their derivatives with respect to voltage and temperature. Within this unified framework, we connect steady-state phenomena, such as negative differential resistance, and dynamical behaviors, such as instability, oscillations, and bifurcations, through a set of dimensionless nonlinearity parameters. In particular, we reveal that the reactance associated with electro-thermal memristors is the result of a phase shift between oscillating current and voltage induced by the dynamical delay and coupling between the electrical and thermal variables. We thus, demonstrate both the utility and limitations of local analyses to understand non-local dynamical behavior. Critically for future experimentation, the analyses show that external coupling of a memristor to impedances within modern sourcing and measurement instruments can dominate the response of the total circuit, making it impossible to characterize the response of an uncoupled circuit element for which a compact model is desired. However, these effects can be minimized by proper understanding of the Local Activity theory to design and utilize purpose-built instruments.

Brown, Timothy D. (ORCID:0000000347068355)↗
DOE OSTI2023

Structural inference of networked dynamical systems with universal differential equations

Networked dynamical systems are common throughout science in engineering; e.g., biological networks, reaction networks, power systems, and the like. For many such systems, nonlinearity drives populations of identical (or near-identical) units to exhibit a wide range of nontrivial behaviors, such as the emergence of coherent structures (e.g., waves and patterns) or otherwise notable dynamics (e.g., synchrony and chaos). Here, we seek to infer (i) the intrinsic physics of a base unit of a population, (ii) the underlying graphical structure shared between units, and (iii) the coupling physics of a given networked dynamical system given observations of nodal states. These tasks are formulated around the notion of the Universal Differential Equation, whereby unknown dynamical systems can be approximated with neural networks, mathematical terms known a priori (albeit with unknown parameterizations), or combinations of the two. We demonstrate the value of these inference tasks by investigating not only future state predictions but also the inference of system behavior on varied network topologies. The effectiveness and utility of these methods are shown with their application to canonical networked nonlinear coupled oscillators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Non-destructive depth-resolved characterization of residual strain fields in high electron mobility transistors using differential aperture x-ray microscopy

Localized residual stress and elastic strain concentrations in microelectronic devices often affect the electronic performance, resistance to thermomechanical damage, and, likely, radiation tolerance. A primary challenge for the characterization of these concentrations is that they exist over sub-μm length-scales, precluding their characterization by more traditional residual stress measurement techniques. Here, in this study, we demonstrate the use of synchrotron x-ray-based differential aperture x-ray microscopy (DAXM) as a viable, non-destructive means to characterize these stress and strain concentrations in a depth-resolved manner. DAXM is used to map two-dimensional strain fields between the source and the drain in a gallium nitride (GaN) layer within high electron mobility transistors (HEMTs) with sub-μm spatial resolution. Strain fields at various positions in both pristine and irradiated HEMT specimens are presented in addition to a preliminary stress analysis to estimate the distribution of various stress components within the GaN layer. γ-irradiation is found to significantly reduce the lattice plane spacing in the GaN along the sample normal direction, which is attributed to radiation damage in transistor components bonded to the GaN during irradiation.

42 ENGINEERING↗
DOE OSTI2023

Memory-based parameterization with differentiable solver: Application to Lorenz ’96

Physical parameterizations (or closures) are used as representations of unresolved subgrid processes within weather and global climate models or coarse-scale turbulent models, whose resolutions are too coarse to resolve small-scale processes. These parameterizations are typically grounded on physically based, yet empirical, representations of the underlying small-scale processes. Machine learning-based parameterizations have recently been proposed as an alternative solution and have shown great promise to reduce uncertainties associated with the parameterization of small-scale processes. Yet, those approaches still show some important mismatches that are often attributed to the stochasticity of the considered process. This stochasticity can be due to coarse temporal resolution, unresolved variables, or simply to the inherent chaotic nature of the process. To address these issues, we propose a new type of parameterization (closure), which is built using memory-based neural networks, to account for the non-instantaneous response of the closure and to enhance its stability and prediction accuracy. We apply the proposed memory-based parameterization, with differentiable solver, to the Lorenz ’96 model in the presence of a coarse temporal resolution and show its capacity to predict skillful forecasts over a long time horizon of the resolved variables compared to instantaneous parameterizations. This approach paves the way for the use of memory-based parameterizations for closure problems.

Mathematics↗
DOE OSTI2025

X-ray spectroscopy of multi-temperature plasmas using the differential emission measure formalism

We present a theoretical construct that nominally underlies spectroscopic data analysis of multi-temperature plasmas, known as the differential emission measure (DEM). From a data analytic perspective, the DEM formalism is used to derive temperature distributions from line spectra that are formed in the presence of temperature gradients and by time integrations of evolving plasmas. From a modeling perspective, DEMs are convenient intermediaries between radiation hydrodynamics simulations and spectroscopic measurements acquired in the laboratory. The DEM concept and its associated methodologies were originally developed by spectroscopists working with astrophysical data. We borrow from these earlier investigations. In this manuscript, intended primarily as a tutorial, we discuss the basic concepts, but also augment various aspects of the theory by the way of extension and example, including a detailed treatment of various weighting and averaging schemes, intended to mitigate ambiguities that often arise when reporting temperature information. We focus on high-temperature plasmas that are not in local thermodynamic equilibrium and the x-ray spectra that they produce, although the core ideas presented here are applicable to spectroscopy in other energy bands. A few examples involving the derivation and manipulation of model DEMs in simple geometries are provided.

Liedahl, Duane A. [Lawrence Livermore National Lab↗
DOE OSTI2026

A flexible and differentiable coil proxy for stellarator equilibrium optimization

Balancing plasma performance and coil cost is a significant challenge when designing a stellarator power plant. Most current stellarator designs are produced through two-stage optimization: stage-1 for the equilibrium and stage-2 for a coil design that reproduces its magnetic configuration. Because few proxies connect both stages, two-stage optimization can produce plasmas that have high-quality physical properties but overly complex coils. In recent years, single-stage optimization has increasingly been used to optimize the plasma and coils simultaneously in order to improve the plasma–coil balance. However, all existing single-stage tools are specialized for filament coils, cannot model coil systems containing permanent magnets or dipole arrays, and continue to be challenged by numerical problems. The quasi-single-stage optimization finds a middle ground by integrating a coil optimization subproblem into stage-1 optimization. We present a flexible, differentiable coil complexity proxy based on the newly developed QUADCOIL coil optimization code. QUADCOIL is fast and can target realistic coil metrics and constraints that are unavailable to codes with comparable speed. We demonstrate the effectiveness and flexibility of the QUADCOIL proxy by presenting two QSS optimization studies. The first study produces a permanent magnet solution for the MUSE stellarator with 34% fewer magnets than previous solutions. The second study produces a coil solution for the ARIES-CS stellarator with 30% reductions in both peak and root-mean-square force.

Fu, Lanke [Princeton Plasma Physics Laboratory (PP↗
DOE OSTI2016

Quantization of the Sobolev space of half-differentiable functions

A quantization of the Sobolev space V=H{sub 0}{sup 1/2}(S{sup 1},R) of half- differentiable functions on the circle, which is closely connected with string theory, is constructed. The group QS(S{sup 1}) of quasisymmetric circle homeomorphisms acts on V by reparametrizations, but this action is not smooth. Nevertheless, a quantum infinitesimal action of QS(S{sup 1}) on V can be defined, which enables one to construct a quantum algebra of observables which is associated with the system (V,QS(S{sup 1})). Bibliography: 7 titles. (paper)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Crystal structure of the WFIKKN2 follistatin domain reveals insight into how it inhibits growth differentiation factor 8 (GDF8) and GDF11

Growth differentiation factor 8 (GDF8; also known as myostatin) and GDF11 are closely related members of the transforming growth factor β (TGF-β) family. GDF8 strongly and negatively regulates skeletal muscle growth, and GDF11 has been implicated in various age-related pathologies such as cardiac hypertrophy. GDF8 and GDF11 signaling activities are controlled by the extracellular protein antagonists follistatin; follistatin-like 3 (FSTL3); and WAP, follistatin/kazal, immunoglobulin, Kunitz, and netrin domain–containing (WFIKKN). All of these proteins contain a follistatin domain (FSD) important for ligand binding and antagonism. Here, we investigated the structure and function of the FSD from murine WFIKKN2 and compared it with the FSDs of follistatin and FSTL3. Using native gel shift and surface plasmon resonance analyses, we determined that the WFIKKN2 FSD can interact with both GDF8 and GDF11 and block their interactions with the type II receptor activin A receptor type 2B (ActRIIB). Further, we solved the crystal structure of the WFIKKN2 FSD to 1.39 Å resolution and identified surface-exposed residues that, when substituted with alanine, reduce antagonism of GDF8 in full-length WFIKKN2. Furthermore, comparison of the WFIKKN2 FSD with those of follistatin and FSTL3 revealed differences in both the FSD structure and position of residues within the domain that are important for ligand antagonism. Taken together, our results indicate that both WFIKKN and follistatin utilize their FSDs to block the type II receptor but do so via different binding interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗