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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Role of E × B Drift in Divertor Detachment Control via Boron Powder Injection on EAST

Here, the effects of B powder injection on plasma detachment about EAST discharge were studied by using SOLPS-ITER code package with the effects of E × B drifts considered. The simulation results show that plasma detachment occurs at the inner target in favourable toroidal magnetic field (B t ) direction at a relatively low B powder flow rate, one order of magnitude lower than that at the outer target. In a similar scenario with unfavourable B t , it is found that the detachment thresholds of B flow rate for both the inner and outer targets are close and of the same order as that for the outer target with favourable Bt. In favourable B t direction at B powder flow rate of 1.2 × 10 21 atoms/s, a localized, broadened high-density region is formed near the inner target benefitted by the injection location and the E × B drift, and a radiation-intensified zone, mostly contributed by B 1+ and B 2+ , occurs there. The E × B drift facilitates plasma detachment at the inner target and simultaneously amplifies the in–out divertor asymmetry. In addition, the simulation results with three different injection locations show that the injection from outer strike point leads to the lowest Z eff inside the separatrix and has an intermediate flow rate for detachment at the outer target, comparing with the X-point and upstream locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Optimal decision trees for categorical data via integer programming

Decision trees have been a very popular class of predictive models for decades due to their interpretability and good performance on categorical features. However, they are not always robust and tend to overfit the data. Additionally, if allowed to grow large, they lose interpretability. In this paper, we present a mixed integer programming formulation to construct optimal decision trees of a prespecified size. We take the special structure of categorical features into account and allow combinatorial decisions (based on subsets of values of features) at each node. Our approach can also handle numerical features via thresholding. Here we show that very good accuracy can be achieved with small trees using moderately-sized training sets. The optimization problems we solve are tractable with modern solvers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Characterization of the Thermal Properties of Ir/Pt Bilayer Transition Edge Sensors

In this work, we are developing a low-T c TES-based large-area and low-threshold detector targeting a variety of potential applications. The detector consists of a 50.8-mm-diameter Si wafer as the substrate and radiation absorber, a single Ir/Pt bilayer TES sensor in the center, and normal metal Au pads added to the TES to strengthen the TES–absorber thermal coupling. Tight TES–absorber thermal coupling improves detector sensitivity and response uniformity. Here, we report on the electron–phonon (e–ph) coupling strengths for the Ir/Pt bilayer and Au that are measured with our prototype detectors and TES devices. We found that a second weak thermal link besides the one due to e–ph coupling in Ir/Pt or Au was required to explain our data. With the effects of the second weak link accounted for, the extracted e–ph coupling constant Σ for Ir/Pt bilayer in the T c range between 32 and 70 mK is 1.9×10 8 WK -5 m -3 , and Σ’s for Au at 40 mK and 55 mK are 2.2×10 9 WK -5 m -3 and 3.2×10 9 WK -5 m -3 , respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Characterization of the Superconducting Microwave Properties of Aluminum Manganese

A microwave kinetic inductance detector (MKID) is a superconducting pair breaking detector that offers a number of unique advantages for realizing large-format arrays of ultra-sensitive detectors, such as inherent multiplexibility and relative ease of fabrication. With the detection threshold being set by the Cooper pair binding energy, and correspondingly, the superconducting critical temperature (T c ), typically well-understood MKID materials such as aluminum (Al) present a lower limit on the operating frequency. Aluminum manganese (Al-Mn) is a promising candidate material for MKIDs because it can be fabricated with nearly identical processing as pure Al, but allows for control of the T c , with varying levels of Mn doping or post-deposition heat treatment. In this study, we present initial results from an early characterization of AlMn using a series of lumped-element superconducting microwave resonators, including measurements of T c , internal quality factor, and noise performance over a range of Mn doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Tuning the Superconducting Transition Temperature of Co-sputtered Iridium and Platinum Films

A superconducting film with a tunable low transition temperature (Tc) is required in high-resolution Transition-Edge Sensor (TES) detectors, which have applications including dark matter detection, low threshold coherent elastic neutrino nucleus scattering measurement, and X-ray spectroscopy. We have been investigating a new approach to tune the Tc of superconducting thin films fabricated by co-sputtering Iridium and Platinum. The effects of Pt concentration and deposition parameters on the films' structural, electrical, and superconducting properties have been studied. AFM and XRD techniques and low temperature resistance measurements have been utilized for film characterization. By varying the Pt concentration and deposition parameters when co-sputtering, we have successfully achieved controllable tuning of Tc in the range of 30-200 mK. The experimental results demonstrate co-sputtering as a viable method for controlling the Tc of Ir-based thin films that can be applied to fabricating high-resolution TESs.

Yefremenko, V. G.↗
DOE OSTI2024

Modeling and Characterization of TES-Based Detectors for the Ricochet Experiment

Coherent elastic neutrino-nucleus scattering (CE nu NS) offers a valuable approach in searching for physics beyond the standard model. The Ricochet experiment aims to perform a precision measurement of the CE nu NS spectrum at the Institut Laue-Langevin nuclear reactor with cryogenic solid-state detectors. The experiment plans to employ an array of cryogenic thermal detectors, each with a mass of around 30 g and an energy threshold of below 100 eV. The array includes nine detectors read out by transition-edge sensors (TES). These TES-based detectors will also serve as demonstrators for future neutrino experiments with thousands of detectors. In this article, we present an update on the characterization and modeling of a prototype TES detector.

Chang, C. L.↗
DOE OSTI2025

Robust Implicit Adaptive Low Rank Time-Stepping Methods for Matrix Differential Equations

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac–Frenkel time-dependent variational principle. In recent years, it has attracted a lot of attention due to its wide applicability. Our schemes are inspired by the three-step procedure used in the rank adaptive version of the unconventional robust integrator (the so called BUG integrator) (Ceruti et al. in BIT Numer Math 62(4):1149–1174, 2022) for DLRA. First, a prediction (basis update) step is made computing the approximate column and row spaces at the next time level. Second, a Galerkin evolution step is invoked using an implicit solves for the small core matrix. Finally, a truncation is made according to a prescribed error threshold. Since the DLRA is evolving the differential equation projected on to the tangent space of the low rank manifold, the error estimate of the BUG integrator contains the tangent projection (modeling) error which cannot be easily controlled by mesh refinement. This can cause convergence issue for equations with cross terms. To address this issue, we propose a simple modification, consisting of merging the row and column spaces from the explicit step truncation method together with the BUG spaces in the prediction step. In addition, we propose an adaptive strategy where the BUG spaces are only computed if the residual for the solution obtained from the prediction space by explicit step truncation method, is too large. Here, we prove stability and estimate the local truncation error of the schemes under assumptions. We benchmark the schemes in several tests, such as anisotropic diffusion, solid body rotation and the combination of the two, to show robust convergence properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Graphene reinforced UHMWPE fibers

Thermoplastic polymers are increasingly used in electric vehicles, hydrogen fuel cell vehicles, and other decarbonization applications due to their lightweight and formability. Higher-strength polymers are needed to supplant metals in the vehicle structure, thereby reducing mass and improving efficiency. Ultra-high molecular weight polyethylene (UHMWPE) fibers possess one of the highest strength-to-weight ratios of technical polymers, and further improvement via reinforcement by nanofillers, such as graphene, will expand their performance envelope. Here, in this work, UHMWPE/graphene nanocomposite fibers were gel spun and characterized for their morphological, microstructural, thermal, and mechanical properties. The addition of a low fraction of graphene improved the tensile strength of the fibers by 25% and tensile modulus by 32%. Differential scanning calorimetry showed an increase in melting temperature and degree of crystallinity, which indicates improved coordination of the molecular chains induced by the addition of graphene. The reinforcement also affected the cross-sectional shape of the fibers; the aspect ratio of the fibers’ elliptical shape declined with increasing graphene content showing the skeletal effect of the graphene nanofillers in the polymer matrix. The reinforcing effect of graphene declined above a threshold concentration, and theoretical modeling was applied to demonstrate that increased agglomerates led to reduced properties. This work demonstrates a simple, effective method to produce graphene-reinforced UHMWPE fibers and lays a foundation for understanding the potential for leveraging graphene to form ultra-high-performance nanocomposite fibers for myriad engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Alpha/beta-gated gamma–gamma spectroscopy of mixed fission products for trace analysis

This experiment demonstrated that some hard-to-detect fission products can be quantified directly from mixed fission product samples using advanced radio-emission spectroscopy techniques. A gamma/gamma coincidence detector was combined with a custom liquid scintillation counter to evaluate the benefits of alpha and beta coincident and anti-coincident analysis of mixed fission product samples. Reduction factors in the minimum detectable activity (MDA) relative to traditional gamma counting were quantified for a set of radionuclides. For isotopes like 91Y, 144Ce, 147Nd, and 153Sm MDA reductions of factors of 1-2 were observed using optimized beta thresholds. Using beta anti-coincidence counting reductions of factors 3-5 were observed for isotopes like 89Sr, 95mNb, 115Cd, and 137Cs and factors of 5-7 for isotopes like 235U using alpha coincidence counting. The selectivity of gamma/gamma coincidence and reduction in backgrounds using beta gating were also demonstrated with 136Cs and 153Sm. The improvements observed in the detection sensitivity of fission products and actinides achieved by combining time-correlated radiation signatures is significant and of value to applications such as nuclear fission physics, environmental monitoring for nuclear waste, reactor accidental releases, and nuclear forensics.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

A persistent adjoint method with dynamic time-scaling and an application to mass action kinetics

In this article, we consider an optimization problem where the objective function is evaluated at the fixed-point of a contraction mapping parameterized by a control variable, and optimization takes place over this control variable. Since the derivative of the fixed-point with respect to the parameter can usually not be evaluated exactly, an adjoint dynamical system can be used to estimate gradients. Using this estimation procedure, the optimization algorithm alternates between derivative estimation and an approximate gradient descent step. We analyze a variant of this approach involving dynamic time-scaling, where after each parameter update the adjoint system is iterated until a convergence threshold is passed. Here, we prove that, under certain conditions, the algorithm can find approximate stationary points of the objective function. We demonstrate the approach in the settings of an inverse problem in chemical kinetics, and learning in attractor networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A simple way to integrate distributed storage into a wholesale electricity market

Abstract Current plans to decarbonize the electric supply system imply that the generation from wind and solar sources will grow substantially. This growth will increase the uncertainty of system operations due to the inherent variability of these renewable sources, and as a result, more reserve capacity will be required to provide the ramping (flexibility) needed for reliable operations. This paper assumes that all of the increased uncertainty comes from wind farms on the grid, and it shows how distributed storage managed locally by aggregators can provide the ramping needed without introducing a separate market for flexibility. This can be accomplished when the aggregators minimize the expected daily cost of the energy purchased from the grid for their customers by submitting optimal bids into the wholesale market with high and low price thresholds for discharging and charging the storage. This model is illustrated using a stochastic multi-period security constrained optimal power flow together with realistic data for a reduction of the network in the Northeast Power Coordinating Council region of the United States. The results show that the bidding strategy for distributed storage provides ramping to the grid just as effectively as storage managed by a system operator.

Lamadrid, Alberto J.↗
DOE OSTI2021

Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation

Abstract We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold. To efficiently reconstruct the level set, we investigate Gaussian process (GP) metamodels. Our focus is on strongly stochastic simulators, in particular with heavy-tailed simulation noise and low signal-to-noise ratio. To guard against noise misspecification, we assess the performance of three variants: (i) GPs with Student- t observations; (ii) Student- t processes (TPs); and (iii) classification GPs modeling the sign of the response. In conjunction with these metamodels, we analyze several acquisition functions for guiding the sequential experimental designs, extending existing stepwise uncertainty reduction criteria to the stochastic contour-finding context. This also motivates our development of (approximate) updating formulas to efficiently compute such acquisition functions. Our schemes are benchmarked by using a variety of synthetic experiments in 1–6 dimensions. We also consider an application of level set estimation for determining the optimal exercise policy of Bermudan options in finance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Roles of Solvent in the Catalytic Hydrogen Release from Liquid Organic Hydrogen Carriers: Chemical, Thermodynamical and Technological Aspects

A Liquid Organic Hydrogen Carrier (LOHC) enables the storage and transport of hydrogen at ambient pressures and temperatures in a safe and convenient form using current infrastructure. However, it is challenging to directly compare reactivity and selectivity for hydrogen release, especially when comparing the catalytic efficiencies of neat LOHCs to highly diluted LOHCs in different solvents, reaction conditions, and catalysts. This work evaluates the role of solvents in catalysis and quantifies the energy efficiency of the overall process. The presence of solvent dilutes the volumetric density of available hydrogen, but may be necessary to achieve optimal catalysts stability, reactivity, and product selectivity. With respect to the reaction conditions as determined by thermodynamics, solvents with higher vapor pressures than that of the carrier can cause the erroneous impression of a more favorable reaction equilibrium. Concerning energy efficiency, solvents can result in increased energy demand for hydrogen release as the inert solvent must be heated to reaction temperatures required for release of H 2 from the LOHC. Further, this work recommends that investigations of catalyst reactivity should be carried out at different ratios of solvent to LOHC to understand how the reactivity changes and what the implications are for maximizing energy density and catalyst stability and reactivity. Investigations should also consider how these implications will affect the technical needs of applications intended for the LOHC system. Based on the results of this study, it is advised to focus research activities on LOHC systems with a gravimetric solvent content below about 50% as the thermodynamic disadvantages become very pronounced beyond this threshold.

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

Submonolayer Quantum-Dot Based Saturable Absorber for Femtosecond Pulse Generation

Semiconductor saturable absorber mirrors (SESAMs) enable passive modelocking of several ultrafast solid-state lasers. Conventionally, SESAMs in the 1-µm wavelength range have employed InGaAs quantum wells (QWs) as absorbers. Here we demonstrate a SESAM based on InAs/GaAs submonolayer quantum dots (SML QDs) capable of generating femtosecond pulses by passively modelocking a vertical-external-cavity surface-emitting laser (VECSEL). Structural measurements are carried out to verify the quality and composition of the QDs. Modelocking experiments with a VECSEL and the QD SESAM in a ring cavity configuration yield pulses as short as 185 fs at 1025 nm. Compared to a traditional QW absorber, SML QD SESAMs exhibit ~ 25% faster recovery times. This also translates to slower power degradation rates or higher damage thresholds in SML QD SESAMs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Influence of Residual Stress on Fatigue Crack Growth Rates in Stainless Steel Processed by Different Additive Manufacturing Methods

The properties and microstructure of Type 304L stainless steel produced by two additive manufacturing (AM) methods—directed energy deposition (DED) and powder bed fusion (PBF)—are evaluated and compared. Localized heating and steep temperature gradients of AM processes lead to significant residual stress and distinctive microstructures, which may be process-specific and influence mechanical behavior. Test data show that materials produced by DED and PDF have small differences in tensile strengths but clear differences in residual stress and microstructural features. Measured fatigue crack growth rates (FCGRs) for cracks propagating parallel to and perpendicular to the build directions differ between the two AM materials. To separate the influences of residual stress and microstructure, K-control test procedures with decreasing and constant stress intensity factor ranges are used to measure FCGRs in the near-threshold regime (crack growth rates ≤ 1 × 10 −8 m/cycle). Residual stress is quantified by the residual stress intensity factor, K res , measured by the online crack compliance method. Correcting the FCGR data for differences in K res brings results for specimens of the two AM materials into agreement with each other and with results for wrought specimens, when the latter are corrected for crack closure. Differences in microstructure and tensile strength have an insignificant influence on FCGRs in these tests.

additive manufacturing↗
DOE OSTI2021

Advances in Processing, Manufacturing, and Applications of Magnetic Materials

Magnetic materials are increasingly important for many green energy technologies. Probably, the best known of these are permanent magnets. They are used to supply a magnetic field and are widely used in actuators, motors, generators, data storage, and sensors. These are “hard magnets,” meaning that they retain a large permanent magnetization (difficult to be demagnetized), which is what makes them so useful in motors where an opposing magnetic field can be used to push against them. A coercivity (resistance to demagnetization) of ~400 Oe (32,000 A/m) or more is typically the threshold value for a hard magnet and is typical of isotropic sintered ferrite (SrFe 12 O 19 ) such as found in many “refrigerator magnets.” Comparably important soft magnets are useful for directing magnetic fields and can be very easily (de)magnetized. As such, they typically have a coercivity < 12.5 Oe (1000 A/m), and specialized very soft magnets can have coercivities < 0.00125 Oe (1 A/m). Some common applications include coil cores, transformer cores, and magnetic shielding. Additionally, they are important for many AC electrical applications such as inductors, filters, and resonators, particularly at high frequencies up to and including microwaves.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Enhanced Radiation Damage Tolerance of Amorphous Interphase and Grain Boundary Complexions in Cu-Ta

Amorphous interfacial complexions are particularly resistant to radiation damage and have been primarily studied in alloys with good glass-forming ability, yet recent reports suggest that these features can form even in immiscible alloys such as Cu-Ta under irradiation. In this work, the mechanisms of damage production and annihilation due to primary knock-on atom collisions are investigated for amorphous interphase and grain boundaries in a Cu-Ta alloy using atomistic simulations. Amorphous complexions, in particular amorphous interphase complexions that separate Cu and Ta grains, result in less residual defect damage than their ordered counterparts. Stemming from the nanophase chemical separation in this alloy, the amorphous complexions exhibit a highly heterogeneous distribution of atomic excess volume, as compared to a good glass former like Cu-Zr. Complexion thickness, a tunable structural descriptor, plays a vital role in damage resistance. Thicker interfacial films are more damage-tolerant because they alter the defect production rate due to differences in intrinsic displacement threshold energies during the collision cascade. Overall, the findings of this work highlight the importance of interfacial engineering in enhancing the properties of materials operating in radiation-prone environments and the promise of amorphous complexions as particularly radiation damage-tolerant microstructural features.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗