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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Fast-, Light-Cured Scintillating Plastic for 3D-Printing Applications

Additive manufacturing techniques enable a wide range of possibilities for novel radiation detectors spanning simple to highly complex geometries, multi-material composites, and metamaterials that are either impossible or cost prohibitive to produce using conventional methods. The present work identifies a set of promising formulations of photocurable scintillator resins capable of neutron-gamma pulse shape discrimination (PSD) to support the additive manufacturing of fast neutron detectors. The development of these resins utilizes a step-by-step, trial-and-error approach to identify different monomer and cross-linker combinations that meet the requirements for 3D printing followed by a 2-level factorial parameter study to optimize the radiation detection performance, including light yield, PSD, optical clarity, and hardness. The formulations resulted in hard, clear, PSD-capable plastic scintillators that were cured solid within 10 s using 405 nm light. The best-performing scintillator produced a light yield 83% of EJ-276 and a PSD figure of merit equaling 1.28 at 450–550 keVee.

Frandsen, Brian G. (ORCID:0000000319964320)↗
DOE OSTI2019

Perfect control of photoelectron anisotropy for randomly oriented ensembles of molecules by XUV REMPI and polarization shaping

In this work, we report two schemes to generate perfect anisotropy in the photoelectron angular distribution of a randomly oriented ensemble of polyatomic molecules. In order to exert full control over the anisotropy of photoelectron emission, we exploit interferences between single-photon pathways and a manifold of resonantly enhanced two-photon pathways. These are shown to outperform nonsequential (ω, 2ω) bichromatic phase control for the example of CHFClBr molecules. We are able to optimize pulses that yield anisotropic photoelectron emission thanks to a very efficient calculation of photoelectron momentum distributions. Finally, this is accomplished by combining elements of quantum chemistry, variational scattering theory, and time-dependent perturbation theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modeling and Characterization of Surface Discharges in Insulating Material for Spacers: Electrode Shape, Discharge Mode, and Revision of the Creepage Concept

In the design of MV AC and DC spacers, the predominant factors are surface and interface conditions. Design is generally carried out on specifications and standards which are based on long-term experience and lab testing. However, the diffusion of power electronics with a trend to increase electric field, switching frequency, and rise time to achieve higher power density calls for an innovative, global approach to optimized insulation system design. A new methodology, based on field simulation, discharge modeling, and partial discharge inception measurements, called the three-leg approach, can form the basis to optimize insulation design for any type of supply voltage waveform. This paper focuses on the influence of the type of electrode on the inception and phenomenology of surface discharges and, as a consequence, on the interpretation of the results used for application of the three-leg approach. It is demonstrated that a typical electrode system used for insulating material testing can generate both gas and surface discharges at the triple point, when the electrodes have a smooth profile that is used to avoid corona or flashover. Hence, testing partial discharge may not provide a straightforward indication of the surface discharge inception and, thus, be partially misleading for insulation design. Another takeover is that such analysis must benefit from PD testing tools endowed with analytics able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona, since design and remedy actions can be taken, and adequate insulating materials developed, only knowing the type of source generating PD. Hence, testing partial discharge may not provide a straightforward indication of surface discharge inception and, thus, be partially misleading for insulation design. In addition to the importance of the three-leg approach to favor reliable and optimized design of insulation systems, there is a clear need to have a PD testing tool endowed with analytics. It should preferably be able to provide automatic identification of the type of defect generating PD, i.e., internal, surface, and corona.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ink-based laser powder bed fusion of barium titanate

Barium titanate (BTO) is a lead-free functional ceramic that is widely used in sensors, transducers, and actuators. The increasing demand for complex geometries and quick design iterations motivates the use of additive manufacturing techniques. Laser powder bed fusion (L-PBF) additive manufacturing technique enables the net-shape or near-net-shape fabrication of metals and alloys. Ceramic L-PBF remains challenging due to their high melting temperature. Here, to address this challenge, a nanoparticle ink feedstock was incorporated into the L-PBF process to allow low power melting of BTO. Key print parameters (i.e. laser power, scanning speed, and hatching spacing) were optimized to fabricate millimeter-scale BTO parts. The printed BTO samples possessed an inhomogeneous equiaxed-columnar-cellular microstructure. Semiconducting current-voltage behavior was observed in as-printed samples, which was attributed to the creation of oxygen vacancies. The piezoelectric d 33 coefficient was measured to be 4.6 pC/N.

Dielectrics↗
DOE OSTI2022

Unconventional short-range structural fluctuations in cuprate superconductors

Abstract The interplay between structural and electronic degrees of freedom in complex materials is the subject of extensive debate in physics and materials science. Particularly interesting questions pertain to the nature and extent of pre-transitional short-range order in diverse systems ranging from shape-memory alloys to unconventional superconductors, and how this microstructure affects macroscopic properties. Here we use neutron and X-ray diffuse scattering to uncover universal structural fluctuations in La 2-x Sr x CuO 4 and Tl 2 Ba 2 CuO 6+δ , two cuprate superconductors with distinct point disorder effects and with optimal superconducting transition temperatures that differ by more than a factor of two. The fluctuations are present in wide doping and temperature ranges, including compositions that maintain high average structural symmetry, and they exhibit unusual, yet simple scaling behaviour. The scaling regime is robust and universal, similar to the well-known critical fluctuations close to second-order phase transitions, but with a distinctly different physical origin. We relate this behaviour to pre-transitional phenomena in a broad class of systems with structural and magnetic transitions, and propose an explanation based on rare structural fluctuations caused by intrinsic nanoscale inhomogeneity. We also uncover parallels with superconducting fluctuations, which indicates that the underlying inhomogeneity plays an important role in cuprate physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Additive Manufacture of Multi-Functional, Large-Scale Components

The poster summarizes the main results for a LDRD focused on developing a arc-based additive manufacturing (AM) system capable of fabricating large components with a composition gradient otherwise known as functionally graded materials (FGMs). FGMs are capable of addressing local extreme conditions in an optimal and cost-effective manner. The AM system (referred to as multi-Wire Arc Additive Manufacturing or m-WAAM) consisted of modifying a standard automated gas tungsten arc welding system to deliver multiple welding wires to the weld pool at controlled rates to deposit desired alloy compositions at critical locations. Numerous shapes and composition gradients were fabricated with the system and the effect of various deposition parameters on the nature of the composition profile were evaluated. Additionally, heat treatment of the FGM was performed to develop graded microstructures which should enhance dynamic impact performance of inexpensive steels. The project highlights the potential of m-WAAM to efficiently fabricate FGMs. However, this project only explored the science behind the technique and additional development work will be required to develop a fully-functional system that can build more complex components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlled Synthesis of SnO 2 Nanocrystals with Tunable Band Gaps

Tin(IV) oxide nanocrystals (SnO 2 NCs) have significant potential in various applications, with their performance closely related to their band gap. The band gap is influenced by the size and shape of the NCs, which can be precisely controlled by adjusting reaction conditions. In this study, we present deliberately designed synthesis protocols to produce high-quality SnO 2 NCs with tunable band gaps using different methods. Key factors affecting the synthesis include control of the oxidizing agent, reaction temperature, solvent selection, and reaction time optimization. The resulting NCs were characterized by using TEM, XRD, XPS, and optical spectroscopy. Notably, SnO 2 NCs synthesized by controlling the oxidizing agent (air injection) in a hot organic solution were smaller in size and exhibited abundant oxygen vacancies. In contrast, extending the reaction time or using ethanol as a solvent in hydrothermal systems facilitated larger spherical or rod-like SnO 2 NCs with fewer oxygen vacancies. Further analysis of the band gap and valence band maximum energy revealed that the abundant vacancies in SnO 2 NCs synthesized with the air-controlled hot organic solution method resulted in a narrower band gap and an upshifted valence band. These synthetic strategies illustrate the potential for deliberately designing SnO 2 NCs with optimized electronic structures for various applications.

band gap↗
DOE OSTI2018

Synthesis of Highly Oriented Zinc-Oxide Films on Amorphous Substrates by the Method of Direct-Current Magnetron Sputtering

We describe the technology of obtaining highly oriented zinc-oxide (ZnO) films on amorphous substrates at high growth rates (up to 7 nm/s) by means of direct-current magnetron sputtering. It is suggested to optimize the substrate position with respect to magnetron and consider the floating potential to which the substrate is charged in magnetron discharge plasma as one of the main technological parameters. Electrondiffraction study of the structural characteristics of the obtained ZnO films showed that increase in the substrate temperature was accompanied by transformation of the crystallite shape from platelike to columnar.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Status of the CBETA splitter common magnet design

The two common dipole magnets in each of the two CBETA splitter sections serve to direct the beams of 42, 78, 114 and 150 MeV from the linac or FFAG return loop exit into the separate splitter lines for path length adjustment and to direct the beams from the splitter into the linac or FFAG return loop entrance. Here we report the results of design and tracking studies based on the Opera V18R2 software. The choice of the H-magnet design included consideration of using the coil design developed for the internal splitter H-dipoles by Elytt Energy. Considerations of transverse space constraints and the bend angle of about 30 degrees for the 42-MeV beam led to the adoption of a T-shape for the pole. The XYZ magnet dimensions are 34 × 42 × 16 cm. The central field value is 3.6-3.9 kG, but the magnet can operate as high as 4.9 kG, allowing for tests of a beam energy as high as 54 MeV in the S1 splitter line. We include results of tracking studies showing optimal placement of the magnets based on bend angle uniformity for the four beam energies. The project now proceeds to the full engineering design and fabrication to be performed by Elytt Energy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Formation of ncl-Si in the Amorphous Matrix a-SiO{sub x}:H Located near the Anode and on the Cathode, Using a Time-Modulated DC Plasma with the (SiH{sub 4}–Ar–O{sub 2}) Gas Phase (C{sub O{sub 2}} = 21.5 mol %)

The formation of ncl-Si in the amorphous matrix a-SiO{sub x}:H using a time-modulated DC plasma at an elevated oxygen content of C{sub O{sub 2}} = 21.5 mol % in a gas mixture of (SiH{sub 4}–Ar–O{sub 2}) is investigated. Plasma modulation implies the repeated (n = 180) switching on (for t{sub on} = 5, 10, 15 s) and switching off (for t{sub off} = 5, 10, 15 s) of the magnet coil of the DC magnetron. The effect of self-induction is used to enhance the processes of SiH{sub 4} dissociation, the formation of Si nanoparticles, and the ionization of oxygen and ncl-Si flows towards the electrodes. The samples are located both on an electrically isolated substrate holder near the anode and on the cathode (beyond its erosion zone). These experiments show that the shape of the dependences of the photoluminescence intensity I{sub PL}{sup ncl−Si} on the wavelength Λ are identical for all pairs of samples on the anode and cathode. When the t{sub on} value is small (t{sub on} = 5 s), the difference in the sample location only slightly affects the infrared (IR) spectra. At longer times t{sub on} (≥10 s) and a short time t{sub off} (5 s), the amorphous matrix located on the cathode is enriched with oxygen (as compared with that near the anode). The optimal plasma-modulation parameters are found to be t{sub off}/t{sub on} = 5, 10, 15/10 and t{sub off}/t{sub on} = 5, 10/15; under these conditions, the amorphous matrix has a “perfect structure” and is transparent to radiation, and the I{sub PL}{sup ncl−Si} value is the largest in the range λ ≈ 0.75–0.9 μm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Parametric Modeling and Economic Analysis of a 2MW th 3-Stream sCO 2 Heat Exchanger

Here, this paper presents the design and cost optimization of a novel 2MW th 3-stream sCO2 plate-fin heat exchanger. This heat exchanger design is unique in that it uses reduced metal oxide particle-to-sCO2 heat exchanger for cost-effective energy storage applications. The design uses low velocity, laminar air as the re-oxidizing reactant to transfer the heat of the re-oxidizing reaction to a sCO2 power loop. The design of the heat exchanger is based on a 2-D, 3-fluid plate/fin heat transfer model. The model parameterizes the size, shape, and number of passages of the heat exchanger to calculate the temperature profile, pressure drop, and fluid velocities of all three fluids. Global heat exchanger parameters such as the effectiveness and total heat transferred to the sCO2 are then calculated for overall performance. Due to the value and increased use of sCO2 heat exchangers in power cycles, a cost model of the system based on the unique high temperature/high pressure operating conditions was created using quotes from reference projects and market analysis. These quoted air-to-sCO2 heat exchangers are then processed using multiple weighting factors pertinent to heat exchanger design, including heat exchanger type, maximum temperature, differential pressures, fluids, duty, and more. These factors are then used in an exponential function in order to generate a parameterized cost curve. The design and cost of the heat exchanger are then optimized using the SMPSO genetic algorithm in Python. The optimization objectives for the system are to maximize the overall system effectiveness, including an air recuperator for preheating, and to minimize unit costs. Additional constraints are added to the system for the sCO2 and air pressure drops, air velocity to reduce particle entrainment, and the length and volume of the heat exchanger.

Cost Model↗
DOE OSTI2019

Transmission EBSD (t-EBSD) as Tool to Investigate Nanostructures in Superconductors

The transmission electron backscatter diffraction (t-EBSD) technique has proven to be an indispensable tool for the analysis of microstructures of superconducting samples, both high-T{sub c} samples (YBa{sub 2}Cu{sub 3}O{sub y}, Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8}) as well as MgB{sub 2} or iron-based materials. The knowledge of the grain boundary properties (misorientation, length, width) is essential for the further optimization of sample performance. Any addition of secondary phase(s) to improve the flux pinning properties is required to be of nanometer dimensions, so the higher achievable resolution and the better imaging properties are important to obtain reasonably high image quality to enable automated orientation mapping. The orientation maps reveal not only the location and the shape of the inclusions within the superconducting matrix or at the grain boundaries but also their influence on the surrounding superconducting matrix, which also plays an important role in flux pinning. In the case of sintered MgB{sub 2} bulk samples, the demand for higher critical current densities leads to MgB{sub 2} grains in the 100-nm range, which is already difficult to be studied by means of conventional EBSD. Furthermore, t-EBSD is useful for the analysis of specific microstructures of unconventional superconductors like superconducting foams or superconducting nanowire networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Predicting the morphologies of γ' precipitates in cobalt-based superalloys

Cobalt-based alloys with γ/γ' microstructures have the potential to become the next generation of superalloys, but alloy compositions and processing steps must be optimized to improve coarsening, creep, and rafting behavior. While these behaviors are different than in nickel-based superalloys, alloy development can be accelerated by understanding the thermodynamic factors influencing microstructure evolution. In this work, we develop a phase field model informed by first-principles density functional theory and experimental data to predict the equilibrium shapes of Co-Al-W γ' precipitates. Three-dimensional simulations of single and multiple precipitates are performed to understand the effect of elastic and interfacial energy on coarsened and rafted microstructures; the elastic energy is dependent on the elastic stiffnesses, misfit strain, precipitate size, applied stress, and precipitate spatial distribution. We observe characteristic microstructures dependent on the type of applied stress that have the same γ' morphology and orientation seen in experiments, indicating that the elastic stresses arising from coherent γ/γ' interfaces are important for morphological evolution during creep. Here, the results also indicate that the narrow γ channels between γ' precipitates are energetically favored, and provide an explanation for the experimentally observed directional coarsening that occurs without any applied stress.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Constraints on OPF Surrogates for Learning Stable Local Volt/Var Controllers

We consider the problem of learning local Volt/Var controllers in distribution grids (DGs). Our approach starts from learning separable surrogates that take both local voltages and reactive powers as arguments and predict the reactive power setpoints that approximate optimal power flow (OPF) solutions. We propose an incremental control algorithm and identify two different sets of slope conditions on the local surrogates such that the network is collectively steered toward desired configurations asymptotically. Our results reveal the trade-offs between each set of conditions, with coupled voltage-power slope constraints allowing an arbitrary shape of surrogate functions but risking limitations on exploiting generation capabilities, and reactive power slope constraints taking full advantage of generation capabilities but constraining the shape of surrogate functions. AC power flow simulations on the IEEE 37-bus feeder illustrate their guaranteed stability properties and respective advantages in two DG scenarios.

asymptotic stability↗
DOE OSTI2025

Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing

In this paper, we propose a method to perform empirical analysis of the loss landscape of machine learning (ML) models. The method is applied to two ML models for scientific sensing, which necessitates quantization to be deployed and are subject to noise and perturbations due to experimental conditions. Our method allows assessing the robustness of ML models to such effects as a function of quantization precision and under different regularization techniques -- two crucial concerns that remained underexplored so far. By investigating the interplay between performance, efficiency, and robustness by means of loss landscape analysis, we both established a strong correlation between gently-shaped landscapes and robustness to input and weight perturbations and observed other intriguing and non-obvious phenomena. Our method allows a systematic exploration of such trade-offs a priori, i.e., without training and testing multiple models, leading to more efficient development workflows. This work also highlights the importance of incorporating robustness into the Pareto optimization of ML models, enabling more reliable and adaptive scientific sensing systems.

Baldi, Tommaso [Pisa, Scuola Normale Superiore]↗
DOE OSTI2017

Precision analysis of the photomultiplier response to ultra low signals

Here, a new computational model for the description of the photon detector response functions measured in conditions of low light is presented, together with examples of the observed photomultiplier signal amplitude distributions, successfully described using the parameterized model equation. In extension to the previously known approximations, the new model describes the underlying discrete statistical behavior of the photoelectron cascade multiplication processes in photon detectors with complex non-uniform gain structure of the first dynode. Important features of the model include the ability to represent the true single-photoelectron spectra from different photomultipliers with a variety of parameterized shapes, reflecting the variability in the design and in the individual parameters of the detectors. The new software tool is available for evaluation of the detectors’ performance, response, and efficiency parameters that may be used in various applications including the ultra low background experiments such as the searches for Dark Matter and rare decays, underground neutrino studies, optimizing operations of the Cherenkov light detectors, help in the detector selection procedures, and in the experiment simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Overbuilding & curtailment: The cost-effective enablers of firm PV generation

Current thinking considers that PV output curtailment is a last resort measure to be avoided. In this article, we argue that supply-shaping, achieved through proactive curtailment associated with PV oversupply, is actually critical to achieving intermittency mitigation and delivering firm PV generation at the lowest cost. We investigate the premium to transform a low-cost, but intermittent solar kWh into a firm, effectively dispatchable kWh. We show that a fundamental ingredient of minimizing this premium is to optimally overbuild and, as necessary and appropriate, curtail PV generation. Drawing on a case study in the State of Minnesota, we show that firm, high-penetration-ready PV generation could be achieved at a production cost at or below current conventional generation, especially when optimally coupled with wind generation. Here, we conclude with a recommendation that in order to achieve this lowest cost firm generation potential, proactive curtailment strategies should inform future transactional PV remuneration systems.

14 SOLAR ENERGY↗