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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Temporal Stability of Magnetization of ε-In{sub 0.24}Fe{sub 1.76}O{sub 3} Nanoparticles

The kinetics of spontaneous demagnetization in nanoparticles of the exotic epsilon-phase of indium-doped iron(III) oxide (ε-In{sub 0.24}Fe{sub 1.76}O{sub 3}) has been studied using the method of accelerated testing of magnets for temporal stability in a magnetization-reversal field. Time dependences of the magnetization of nanoparticles measured in a wide range of magnetic fields exhibited rectification in semilogarithmic coordinates. The dependence of the magnetic viscosity on the magnetic field has been measured and used for determining the fluctuation field and activation volume. A relationship between the magnetic viscosity and magnetic noise caused by random thermoinduced magnetization reversal in separate nanoparticles is established.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Regenerable immobilized aminosilane sorbents for carbon dioxide capture applications

A method for the separation of carbon dioxide from ambient air and flue gases is provided wherein a phase separating moiety with a second moiety are simultaneously coupled and bonded onto an inert substrate to create a mixture which is subsequently contacted with flue gases or ambient air. The phase-separating moiety is an amine whereas the second moiety is an aminosilane, or a Group 4 propoxide such as titanium (IV) propoxide (tetrapropyl orthotitanate, C.sub.12H.sub.28O.sub.4Ti). The second moiety makes the phase-separating moiety insoluble in the pores of the inert substrate. The new sorbents have a high carbon dioxide loading capacity and considerable stability over hundreds of cycles. The synthesis method is readily scalable for commercial and industrial production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The zero-multipole summation method for estimating electrostatic interactions in molecular dynamics: Analysis of the accuracy and application to liquid systems

In the preceding paper [I. Fukuda, J. Chem. Phys. 139, 174107 (2013)], the zero-multipole (ZM) summation method was proposed for efficiently evaluating the electrostatic Coulombic interactions of a classical point charge system. The summation takes a simple pairwise form, but prevents the electrically non-neutral multipole states that may artificially be generated by a simple cutoff truncation, which often causes large energetic noises and significant artifacts. The purpose of this paper is to judge the ability of the ZM method by investigating the accuracy, parameter dependencies, and stability in applications to liquid systems. To conduct this, first, the energy-functional error was divided into three terms and each term was analyzed by a theoretical error-bound estimation. This estimation gave us a clear basis of the discussions on the numerical investigations. It also gave a new viewpoint between the excess energy error and the damping effect by the damping parameter. Second, with the aid of these analyses, the ZM method was evaluated based on molecular dynamics (MD) simulations of two fundamental liquid systems, a molten sodium-chlorine ion system and a pure water molecule system. In the ion system, the energy accuracy, compared with the Ewald summation, was better for a larger value of multipole moment l currently induced until l ≲ 3 on average. This accuracy improvement with increasing l is due to the enhancement of the excess-energy accuracy. However, this improvement is wholly effective in the total accuracy if the theoretical moment l is smaller than or equal to a system intrinsic moment L. The simulation results thus indicate L ∼ 3 in this system, and we observed less accuracy in l = 4. We demonstrated the origins of parameter dependencies appearing in the crossing behavior and the oscillations of the energy error curves. With raising the moment l we observed, smaller values of the damping parameter provided more accurate results and smoother behaviors with respect to cutoff length were obtained. These features can be explained, on the basis of the theoretical error analyses, such that the excess energy accuracy is improved with increasing l and that the total accuracy improvement within l ⩽ L is facilitated by a small damping parameter. Although the accuracy was fundamentally similar to the ion system, the bulk water system exhibited distinguishable quantitative behaviors. A smaller damping parameter was effective in all the practical cutoff distance, and this fact can be interpreted by the reduction of the excess subset. A lower moment was advantageous in the energy accuracy, where l = 1 was slightly superior to l = 2 in this system. However, the method with l = 2 (viz., the zero-quadrupole sum) gave accurate results for the radial distribution function. We confirmed the stability in the numerical integration for MD simulations employing the ZM scheme. This result is supported by the sufficient smoothness of the energy function. Along with the smoothness, the pairwise feature and the allowance of the atom-based cutoff mode on the energy formula lead to the exact zero total-force, ensuring the total-momentum conservations for typical MD equations of motion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enriched immersed finite element and isogeometric analysis: algorithms and data structures

Immersed finite element methods provide a convenient analysis framework for problems involving geometrically complex domains, such as those found in topology optimization and microstructures for engineered materials. However, their implementation remains a major challenge due to, among other things, the need to apply nontrivial stabilization schemes and generate custom quadrature rules. This article introduces the robust and computationally efficient algorithms and data structures comprising an immersed finite element preprocessing framework. The input to the preprocessor consists of a background mesh and one or more geometries defined on its domain. The output is structured into groups of elements with custom quadrature rules formatted such that common finite element assembly routines may be used without or with only minimal modifications. The key to the preprocessing framework is the construction of material topology information, concurrently with the generation of a quadrature rule, which is then used to perform enrichment and generate stabilization rules. While the algorithmic framework applies to a wide range of immersed finite element methods using different types of meshes, integration, and stabilization schemes, the preprocessor is presented within the context of the extended isogeometric analysis. This method utilizes a structured B-spline mesh, a generalized Heaviside enrichment strategy considering the material layout within individual basis functions’ supports, and face-oriented ghost stabilization. Using a set of examples, the effectiveness of the enrichment and stabilization strategies is demonstrated alongside the preprocessor’s robustness in geometric edge cases. Additionally, the performance and parallel scalability of the implementation are evaluated.

Computer implementation↗
DOE OSTI2022

Aluminum alloy compositions and methods of making and using the same

The present disclosure concerns embodiments of aluminum alloy compositions exhibiting microstructural stability and strength at high temperatures. The disclosed aluminum alloy compositions comprise particular combinations of components that contribute the ability of the compositions to exhibit improved microstructural stability and hot tearing resistance as compared to conventional alloys. Also disclosed herein are embodiments of methods of making and using the alloys.

Shyam, Amit↗
DOE OSTI2018

Improvement of stability of Nb 3 Sn superconductors by introducing high specific heat substances

High-J c Nb 3 Sn conductors have low stability against perturbations, which accounts for the slow training rates of high-field Nb 3 Sn magnets. While it is known that adding substances with high specific heat (C) into Nb 3 Sn wires can increase their overall specific heat and thus improve their stability, there has not been a practical method that is compatible with the fabrication of long-length conductors. In this work, we put forward a scheme to introduce such substances to distributed-barrier Nb 3 Sn wires, which adds minimum difficulty to the wire manufacturing process. Multifilamentary wires using a mixture of Cu and high-C Gd 2 O 3 powders have been successfully fabricated along this line. Measurements showed that addition of Gd 2 O 3 had no negative effects on residual resitivity ratio or non-Cu J c , and that flux jumps were remarkably reduced, and minimum quench energy values at 4.2 K, 14 T were increased by a factor of three, indicating that stability was significantly improved. We also discussed the influences of the positioning of high-C substances and their thermal diffusivity on their effectiveness in reducing the superconductor temperature rise against perturbations. Based on these results, we proposed an optimized conductor architecture to maximize the effectiveness of this approach.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Carbon sequestration into lime-stabilized soils: Engineering and mineralogical characterization

Stabilizing weak clayey soils with lime is an effective method for improving the mechanical properties of soil. However, lime production is an energy-intensive process producing significant CO 2 emissions in lime-stabilized soils, which can be counteracted through accelerated carbonation that enhances its engineering performance. The present study evaluates accelerated carbonation of lime-treated soils by adding gaseous (CO 2 -rich gas), liquid (water-CO 2 mixture), and solid (sodium bicarbonate) CO 2 sources. Results indicated that samples carbonated with gaseous CO 2 exhibited 100% lime carbonation, while samples treated with solid and aqueous sources of CO 2 had a mean lime carbonation of 60% and 40%, respectively. Further, all lime-treated-carbonated samples exhibited a mean 50% increase in unconfined compressive strength compared to the untreated samples after a 7-day curing period. Durability evaluation through cyclic wetting and drying indicated that the carbonated samples had higher durability than the untreated samples. X-ray computed tomography showed that adding solid and liquid sources of CO 2 facilitated the flocculation of montmorillonite, reducing the porosity. However, a higher dosage of solid CO 2 induced clay dispersion, increasing the porosity. X-ray diffraction and thermogravimetric analysis verified CO 2 sequestration through the formation of calcite, a thermodynamically stable polymorph of calcium carbonate.

58 GEOSCIENCES↗
DOE OSTI2017

Demonstration of a Rapid HPLC-ICPMS Direct Coupling Technique Using IDMS- Project Report: Part II

Researchers working on chemical separations and inductively coupled plasma mass spectrometry have developed a rapid separation–direct analysis scheme to determine both concentration and isotopics of a suite of elements down to the low picogram level, with the ultimate goal of performing rapid analysis of postdetonation nuclear materials. The second phase in method development has shown that both the sensitivity and stability to achieve the precise, low-level analyses required can be maintained even when present in complex silicon- and uranium-based matrices. The methods analyte list has been expanded to incorporate a number of new analytes, notably the actinides plutonium, americium, curium, neptunium, and thorium and the key fission product zirconium. Key nonnatural fission product isotopic ratios in irradiated highly enriched uranium targets have been successfully measured at the low picogram level. The accuracy of these ratios was confirmed using an isotopic depletion and decay modeling software to within 1–2%.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2014

Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+}: A novel blue emitting phosphor for white LEDs

Graphical abstract: Under the 350 nm radiation excitation, Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} has a broad blue emission band. When the temperature turned up to 150 °C, the emission intensity of Ba{sub 1.97}B{sub 2}O{sub 5}:0.03Ce{sup 3+} is 63.4% of the initial value at room temperature. The activation energy ΔE is calculated to be 0.25 eV, which prove the good thermal stability of Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+}. All the properties indicate that Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} may have potential application in white LEDs. - Highlights: • Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} has a broad blue emission band under the 350 nm radiation excitation. • Emission intensity of Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} is 63.4% (150 °C) of the initial value (30 °C). • The activation energy ΔE for thermal quenching is 0.25 eV. - Abstract: A novel blue emitting phosphor Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} is synthesized by a high temperature solid state method. The luminescent property and the thermal stability of Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} are investigated. Under the 350 nm radiation excitation, Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} has a broad blue emission band, and the peak locates at 417 nm which is assigned to the 5d{sup 1}–4f{sup 1} transition of Ce{sup 3+}. It is further proved that the dipole–dipole interaction results in the concentration quenching of Ce{sup 3+} in Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+}. When the temperature turned up to 150 °C, the emission intensity of Ba{sub 1.97}B{sub 2}O{sub 5}:0.03Ce{sup 3+} is 63.4% of the initial value at room temperature. The activation energy ΔE is calculated to be 0.25 eV, which prove the good thermal stability of Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+}. All the properties indicate that Ba{sub 2}B{sub 2}O{sub 5}:Ce{sup 3+} may have potential application in white LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Computational Flame Diagnostics for Direct Numerical Simulations with Detailed Chemistry of Transportation Fuels

The goal of the proposed research is to create computational flame diagnostics (CFLD) that are rigorous numerical algorithms for systematic detection of critical flame features, such as ignition, extinction, and premixed and non-premixed flamelets, and to understand the underlying physicochemical processes controlling limit flame phenomena, flame stabilization, turbulence-chemistry interactions and pollutant emissions etc. The goal has been accomplished through an integrated effort on mechanism reduction, direct numerical simulations (DNS) of flames at engine conditions and a variety of turbulent flames with transport fuels, computational diagnostics, turbulence modeling, and DNS data mining and data reduction. The computational diagnostics are primarily based on the chemical explosive mode analysis (CEMA) and a recently developed bifurcation analysis using datasets from first-principle simulations of 0-D reactors, 1-D laminar flames, and 2-D and 3-D DNS (collaboration with J.H. Chen and S. Som at Argonne, and C.S. Yoo at UNIST). Non-stiff reduced mechanisms for transportation fuels amenable for 3-D DNS are developed through graph-based methods and timescale analysis. The flame structures, stabilization mechanisms, local ignition and extinction etc., and the rate controlling chemical processes are unambiguously identified through CFLD. CEMA is further employed to segment complex turbulent flames based on the critical flame features, such as premixed reaction fronts, and to enable zone-adaptive turbulent combustion modeling.

42 ENGINEERING↗
DOE OSTI2016

Suppression of photo-bias induced instability for amorphous indium tungsten oxide thin film transistors with bi-layer structure

This study investigates the instability induced by bias temperature illumination stress (NBTIS) for an amorphous indium-tungsten-oxide thin film transistor (a-IWO TFT) with SiO{sub 2} backchannel passivation layer (BPL). It is found that this electrical degradation phenomenon can be attributed to the generation of defect states during the BPL process, which deteriorates the photo-bias stability of a-IWO TFTs. A method proposed by adding an oxygen-rich a-IWO thin film upon the a-IWO active channel layer could effectively suppress the plasma damage to channel layer during BPL deposition process. The bi-layer a-IWO TFT structure with an oxygen-rich back channel exhibits superior electrical reliability of device under NBTIS.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A flexible nonlinear diffusion acceleration method for the S N transport equations discretized with discontinuous finite elements

This paper presents a flexible nonlinear diffusion acceleration (NDA) method that discretizes both the S N transport equation and the diffusion equation using the discontinuous finite element method (DFEM). The method is flexible in that the diffusion equation can be discretized on a coarser mesh with the only restriction that it is nested within the transport mesh and the FEM shape function orders of the two equations can be different. The consistency of the transport and diffusion solutions at convergence is defined by using a projection operator mapping the transport into the diffusion FEM space. The diffusion weak form is based on the modified incomplete interior penalty (MIP) diffusion DFEM discretization that is extended by volumetric drift, interior face, and boundary closure terms. In contrast to commonly used coarse mesh finite difference (CMFD) methods, the presented NDA method uses a full FEM discretized diffusion equation for acceleration. Suitable projection and prolongation operators arise naturally from the FEM framework. Via Fourier analysis and numerical experiments for a one-group, fixed source problem the following properties of the NDA method are established for structured quadrilateral meshes: (1) the presented method is unconditionally stable and effective in the presence of mild material heterogeneities if the same mesh and identical shape functions either of the bilinear or biquadratic type are used, (2) the NDA method remains unconditionally stable in the presence of strong heterogeneities, (3) the NDA method with bilinear elements extends the range of effectiveness and stability by a factor of two when compared to CMFD if a coarser diffusion mesh is selected. In addition, the method is tested for solving the C5G7 multigroup, eigenvalue problem using coarse and fine mesh acceleration. Finally, while NDA does not offer an advantage over CMFD for fine mesh acceleration, it reduces the iteration count required for convergence by almost a factor of two in the case of coarse mesh acceleration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Basis adaptive sample efficient polynomial chaos (BASE-PC)

For a large class of orthogonal basis functions, there has been a recent identification of expansion methods for computing accurate, stable approximations of a quantity of interest. Here this paper presents, within the context of uncertainty quantification, a practical implementation using basis adaptation, and coherence motivated sampling, which under assumptions has satisfying guarantees. This implementation is referred to as Basis Adaptive Sample Efficient Polynomial Chaos (BASE-PC). A key component of this is the use of anisotropic polynomial order which admits evolving global bases for approximation in an efficient manner, leading to consistently stable approximation for a practical class of smooth functionals. This fully adaptive, non-intrusive method, requires no a priori information of the solution, and has satisfying theoretical guarantees of recovery. A key contribution to stability is the use of a presented correction sampling for coherence-optimal sampling in order to improve stability and accuracy within the adaptive basis scheme. Theoretically, the method may dramatically reduce the impact of dimensionality in function approximation, and numerically the method is demonstrated to perform well on problems with dimension up to 1000.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Effect of Fluoroethylene Carbonate Additives on the Initial Formation of the Solid Electrolyte Interphase on an Oxygen-Functionalized Graphitic Anode in Lithium-Ion Batteries

The formation of a solid electrolyte interphase (SEI) at the electrode/electrolyte interface substantially affects the stability and lifetime of lithium-ion batteries (LIBs). One of the methods to improve the lifetime of LIBs is by the inclusion of additive molecules to stabilize the SEI. To understand the effect of additive molecules on the initial stage of SEI formation, in this work we compare the decomposition and oligomerization reactions of a fluoroethylene carbonate (FEC) additive on a range of oxygen-functionalized graphitic anodes to those of an ethylene carbonate (EC) organic electrolyte. A series of density functional theory (DFT) calculations augmented by ab initio molecular dynamics (AIMD) simulations reveal that EC decomposition on an oxygen-functionalized graphitic ($11\bar{2}0$) edge facet through a nucleophilic attack on an ethylene carbon site (C E ) of an EC molecule (S2 mechanism) is spontaneous during the initial charging process of LIBs. However, decomposition of EC through a nucleophilic attack on a carbonyl carbon (C C ) site (S1 mechanism) results in alkoxide species regeneration that is responsible for continual oligomerization along the graphitic surface. In contrast, FEC prefers to decompose through an S1 pathway, which does not promote alkoxide regeneration. Including FEC as an additive is thus able to suppress alkoxide regeneration and results in a smaller and thinner SEI layer that is more flexible toward lithium intercalation during the charging/discharging process. In addition, we find that the presence of different oxygen functional groups at the surface of graphite dictates the oligomerization products and the LiF formation mechanism in the SEI.

25 ENERGY STORAGE↗
DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Assessment of software methods for estimating protein-protein relative binding affinities

A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations. By contrast, non-rigorous methods use less exhaustive statistical mechanics, allowing for more efficient calculations. However, it is unclear if such methods retain enough accuracy to replace rigorous methods in binding affinity calculations. This trade-off between accuracy and computational expense makes it difficult to determine the best method for a particular system or study. Here, eight non-rigorous computational methods were assessed using eight antibody-antigen and eight non-antibody-antigen complexes for their ability to accurately predict relative binding affinities (ΔΔG) for 654 single mutations. In addition to assessing accuracy, we analyzed the CPU cost and performance for each method using a variety of physico-chemical structural features. This allowed us to posit scenarios in which each method may be best utilized. Most methods performed worse when applied to antibody-antigen complexes compared to non-antibody-antigen complexes. Rosetta-based JayZ and EasyE methods classified mutations as destabilizing (ΔΔG < -0.5 kcal/mol) with high (83–98%) accuracy and a relatively low computational cost for non-antibody-antigen complexes. Some of the most accurate results for antibody-antigen systems came from combining molecular dynamics with FoldX with a correlation coefficient (r) of 0.46, but this was also the most computationally expensive method. Overall, our results suggest these methods can be used to quickly and accurately predict stabilizing versus destabilizing mutations but are less accurate at predicting actual binding affinities. This study highlights the need for continued development of reliable, accessible, and reproducible methods for predicting binding affinities in antibody-antigen proteins and provides a recipe for using current methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Orphaned oil and gas well methane emission rates quantified using Gaussian plume inversions of ambient observations

Abstract. Annually, ∼ 3.6 million abandoned oil and gas wells in the US emit a combined ∼ 2.6 Tg methane (CH4), adversely affecting climate and regional air quality. However, these estimates depend on emission factors derived from measuring subpopulations of wells that vary by orders of magnitude due to very limited field sampling and poorly characterized distributions. Currently, US protocols to remediate orphaned wells lacks standardized quantification methods needed to both prioritize plugging and account for emission reductions. Therefore, sensitive, reliable, affordable, and scalable CH4 flux quantification methods are needed. We report the use of a simple Gaussian plume method where the dispersion parameters are constrained by in situ ground measurements of CH4 concentration at four locations 7.5–49 m downwind of the orphan well as well as local winds to estimate the leak rate from an orphan well. We derive a flux of 10.53 ± 1.16 kg CH4 h−1 during a venting procedure in April 2023 that agrees with the directly measured volumetric flow rate of 9.00 ± 0.25 kg CH4 h−1. This is 71 % greater than the 5.3 kg CH4 h−1 flux measured 7 months prior. Additionally, we discovered a secondary leak through the surface casing inferred as 0.43–0.67 kg CH4 h−1 both by our ground Gaussian analysis and by transecting the plume with an uncrewed aerial system (UAS). We show that in situ determination of the dispersion parameters used in our Gaussian inversions allows us to measure methane emissions to 15 % accuracy, significantly reducing errors when compared to the standard practice of assuming stability class. Our results help develop simpler methods and protocols for robust orphan well emission quantification that can be used for reporting.

Follansbee, Emily↗