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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measurements of scattering and absorption properties of submillimeter bauxite and silica particles

Submillimeter solid particles have been considered as thermal storage media for concentrated solar power applications. Knowledge of the scattering and absorption properties of individual particles is crucial for modeling the radiative heat transfer of the particle bed. In this work, a laser scatterometer is used to measure the single-particle scattering properties at a wavelength of 635 nm by using two configurations: (1) a falling particle curtain and (2) a taped particle layer. Because a one-particle nominal thickness is formed with area fractions of 5-55% depending on the configuration, multiple scattering is minimized and hence the single scattering phase function, averaged over all illuminated particles, is directly measured. Bauxite-based ceramic particles that are strongly absorbing in the solar spectrum and silica particles that are nonabsorbing in the visible and near-infrared are investigated. The directional-hemispherical reflectance and transmittance of the taped particles are also measured to deduce the forward and backward scattering efficiency factors and the absorption efficiency factors. Only weak wavelength dependence is observed in the measured region from 380 nm to 1020 nm. Furthermore, the scattering phase functions of all bauxite-based particles with varying sizes and compositions are very similar and can be fitted to a Henyey-Greenstein phase function with an asymmetry factor g = -0.20. For the silica particles, forward scattering dominates and g = 0.45 yields the best fit. A Monte Carlo method is developed to model the particle scattering characteristics, and reasonable agreements between the modeling and experimental results are observed by introducing a specularity parameter.

42 ENGINEERING↗
DOE OSTI2020

Simulation of energy loss of fractionally charged particles using Geant4

Over the years several rare-event search experiments have shown increasing interest to search for Fractionally Charged Particles (FCPs) within the data acquired in those experiments. This, in turn, has required the need for a framework to calculate accurately the energy loss expected from FCPs as they pass through the detector material. We have developed Monte Carlo methods within Geant4 to simulate for the first time energy loss of FCPs through different physics processes. The program can be used to calculate energy deposition distributions, a major component of any FCP search analysis, as they interact with detector material. We discuss the implementation and validation of the energy loss of FCPs using a typical detector material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

SchrödingerNet: A Universal Neural Network Solver for the Schrödinger Equation

Recent advances in machine learning have facilitated numerically accurate solution of the electronic Schrödinger equation (SE) by integrating various neural network (NN)-based wave function ansatzes with variational Monte Carlo methods. Nevertheless, such NN-based methods are all based on the Born–Oppenheimer approximation (BOA) and require computationally expensive training for each nuclear configuration. In this work, we propose a novel NN architecture, SchrödingerNet, to solve the full electronic-nuclear SE by defining a loss function designed to equalize local energies across the system. This approach is based on a translationally, rotationally and permutationally symmetry-adapted total wave function ansatz that includes both nuclear and electronic coordinates. Furthermore, this strategy not only allows for an efficient and accurate generation of a continuous potential energy surface at any geometry within the well-sampled nuclear configuration space, but also incorporates non-BOA corrections, through a single training process. Comparison with benchmarks of atomic and small molecular systems demonstrates its accuracy and efficiency.

Chemical calculations↗
DOE OSTI2023

Local Chemical Clustering Enabled Ultrahigh Capacitive Energy Storage in Pb-Free Relaxors

Designing Pb-free relaxors with both a high capacitive energy density (W rec ) and high storage efficiency (η) remains a remarkable challenge for cutting-edge pulsed power technologies. Local compositional heterogeneity is crucial for achieving complex polar structure in solid solution relaxors, but its role in optimizing energy storage properties is often overlooked. Here, in this paper, we report that an exceptionally high W rec of 15.2 J cm –3 along with an ultrahigh η of 91% can be achieved through designing local chemical clustering in Bi 0.5 Na 0.5 TiO 3 –BaTiO 3 -based relaxors. A three-dimensional atomistic model derived from neutron/X-ray total scattering combined with reverse Monte Carlo method reveals the presence of subnanometer scale clustering of Bi, Na, and Ba, which host differentiated polar displacements, and confirming the prediction by density functional theory calculations. This leads to a polar state with small polar clusters and strong length and direction fluctuations in unit-cell polar vectors, thus manifesting improved high-field polarizability, steadily reduced hysteresis, and high breakdown strength macroscopically. The favorable polar structure features also result in a unique field-increased η, excellent stability, and superior discharge capacity. Our work demonstrates that the hidden local chemical order exerts a significant impact on the polarization characteristic of relaxors, and can be exploited for accessing superior energy storage performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Interaction-driven spontaneous ferromagnetic insulating states with odd Chern numbers

Motivated by recent experimental work on moiré systems in a strong magnetic field, we compute the compressibility as well as the spin correlations and Hofstadter spectrum of spinful electrons on a honeycomb lattice with Hubbard interactions using the determinantal quantum Monte Carlo method. While the interactions in general preserve quantum and anomalous Hall states, emergent features arise corresponding to an antiferromagnetic insulator at half-filling and other incompressible states following the Chern sequence ± (2N + 1). These odd integer Chern states exhibit strong ferromagnetic correlations and arise spontaneously without any external mechanism for breaking the spin-rotation symmetry. Analogs of these magnetic states should be observable in general interacting quantum Hall systems. In addition, the interacting Hofstadter spectrum is qualitatively similar to the experimental data at intermediate values of the on-site interaction.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Low-iridium stabilized ruthenium oxide anode catalyst for durable proton-exchange membrane water electrolysis

While mixing iridium (Ir) with ruthenium oxide (RuO 2 ) has proven to be an effective strategy for reducing Ir loading in anode catalysts for proton-exchange membrane (PEM) water electrolysers, achieving industrially relevant long-term stability typically requires an Ir-rich, Ru-lean combination. Here, in this study, by combining density functional theory with Metropolis Monte Carlo methods, we discovered that sufficient stabilization in the RuO 2 lattice could be achieved with less than 50 at.% of Ir, and that Ir in the first subsurface layer plays a critical role. By effectively dispersing Ir dopants within the RuO 2 lattice, we demonstrated an Ir:Ru atomic ratio of only 1:6 that exhibited exceptional stability for over 1,500 h of continuous water electrolysis at 2 A cm −2 . Our Ru 6 IrO x catalyst has the potential to reduce Ir loading by 80% compared with current commercial PEM water electrolysers, and its stability was further validated under industrial testing conditions in a 25-cm 2 PEM electrolyser.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Neuromorphic scaling advantages for energy-efficient random walk computations

Neuromorphic computing, which aims to replicate the computational structure and architecture of the brain in synthetic hardware, has typically focused on artificial intelligence applications. What is less explored is whether such brain-inspired hardware can provide value beyond cognitive tasks. Here we show that the high degree of parallelism and configurability of spiking neuromorphic architectures makes them well suited to implement random walks via discrete-time Markov chains. Overall, these random walks are useful in Monte Carlo methods, which represent a fundamental computational tool for solving a wide range of numerical computing tasks. Using IBM’s TrueNorth and Intel’s Loihi neuromorphic computing platforms, we show that our neuromorphic computing algorithm for generating random walk approximations of diffusion offers advantages in energy-efficient computation compared with conventional approaches. We also show that our neuromorphic computing algorithm can be extended to more sophisticated jump-diffusion processes that are useful in a range of applications, including financial economics, particle physics and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Neural-network quantum states for ultra-cold Fermi gases

Abstract Ultra-cold Fermi gases exhibit a rich array of quantum mechanical properties, including the transition from a fermionic superfluid Bardeen-Cooper-Schrieffer (BCS) state to a bosonic superfluid Bose-Einstein condensate (BEC). While these properties can be precisely probed experimentally, accurately describing them poses significant theoretical challenges due to strong pairing correlations and the non-perturbative nature of particle interactions. In this work, we introduce a Pfaffian-Jastrow neural-network quantum state featuring a message-passing architecture to efficiently capture pairing and backflow correlations. We benchmark our approach on existing Slater-Jastrow frameworks and state-of-the-art diffusion Monte Carlo methods, demonstrating a performance advantage and the scalability of our scheme. We show that transfer learning stabilizes the training process in the presence of strong, short-ranged interactions, and allows for an effective exploration of the BCS-BEC crossover region. Our findings highlight the potential of neural-network quantum states as a promising strategy for investigating ultra-cold Fermi gases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Cuboidal Liquid Crystal Phases Under Multiaxial Geometrical Frustration.

Cuboidal liquid crystal phases - the so-called blue phases - consist of a network of topological defects arranged into a cubic symmetry. They exhibit striking optical properties, including Bragg reflection in the visible range and fast response times. Confining surfaces can interfere with the packing of such a network, leading to structures that have not been explored before. In this work, a Landau-de Gennes free energy formalism for the tensor alignment field Q is used to investigate the behavior of chiral liquid crystals under non-isotropic confinement. The underlying free energy functional is solved by relying on a Monte Carlo method that facilitates efficient exploration of configuration space. The results of simulations are expressed in terms of phase diagrams as a function of chirality and temperature for three families of spheroids: oblate, spherical, and prolate. Upon deformation, blue phases adapt and transform to accommodate the geometrical constraints, thereby resulting in a wider range of thermal stability. For oblate spheroids, confinement interferes with the development of a full blue phase structure, resulting on a combination of half skyrmions. For prolate spheroids, the blue phases are hybridized and exhibit features of blue phases I and II. More generally, it is shown that mechanical deformation provides an effective means to control, manipulate and stabilize blue phases and cholesterics confined in tactoids.

Palacio-Betancur, Viviana↗
DOE OSTI2020

Surface diffusion manifestation in electrodeposition of metal anodes

Metal anode-based battery systems have been deemed indispensable towards energy storage renaissance engendering extensive research into strategies countering dendritic growth of metal electrodeposition. Fundamentally, the morphological evolution of a material is uniquely characterized by the heights of its self-diffusion barrier across multiple pathways. Herein, based on a coarse-grained kinetic Monte Carlo method, we derive insights into the nucleation and growth of metallic electrodeposits in liquid electrolytes, governed by surface self-diffusion characteristics cognizant of the diverse diffusion routes including terrace, away from step and interlayer pathways. We deconvolve the roles played by each of these surface diffusion mechanisms in conjunction with the electrochemical reaction rate on the deposition morphology regime (film vs. mossy vs. fractal). We identify interlayer diffusion as the predominant morphology-determining mechanism; dendrite-free deposition even at moderate current rates constrains this diffusion barrier to an upper limit. Additionally, we highlight subtle features amidst the realm of the morphological growth assortment that connect to the cell's electrochemical performance. Finally, we delineate morphological features of Li, Na, Mg and Al based on their respective surface diffusion barriers and applied overpotentials, and provide a baseline for the interpretation of experimental observations. This fundamental study sheds light on the mesoscale underpinnings of morphological variances in mono-valent and multi-valent metal electrodeposition.

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

Automating Bayesian inference and design to quantify acoustic particle levitation

Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. Furthermore, this work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.

42 ENGINEERING↗
DOE OSTI2023

VarIabiLity seLection of AstrophysIcal sources iN PTF (VILLAIN): I. Structure function fits to 71 million objects

Light-curve variability is well-suited to characterizing objects in surveys with high cadence and a long baseline. This is especially relevant in view of the large datasets to be produced by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We aim to determine variability parameters for objects in the Palomar Transient Factory (PTF) and explore differences between quasars (QSOs), stars, and galaxies. We relate variability and colour information in preparation for future surveys. We fit joint likelihoods to structure functions (SFs) of 71 million PTF light curves with a Markov chain Monte Carlo method. For each object, we assume a power-law SF and extract two parameters: the amplitude on timescales of one year, A, and a power-law index, γ. With these parameters and colours in the optical (Pan-STARRS1) and mid-infrared (WISE), we identify regions of parameter space dominated by different types of spectroscopically confirmed objects from SDSS. Candidate QSOs, stars, and galaxies are selected to show their parameter distributions. QSOs show high-amplitude variations in the R band, and the highest γ values. Galaxies have a broader range of amplitudes and their variability shows relatively little dependency on timescale. With variability and colours, we achieve a photometric selection purity of 99.3% for QSOs. Even though hard cuts in monochromatic variability alone are not as effective as seven-band magnitude cuts, variability is useful in characterizing object subclasses. Through variability, we also find QSOs that were erroneously classified as stars in the SDSS. We discuss perspectives and computational solutions in view of the upcoming LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Thermonuclear 28 P(p, γ ) 29 S reaction rate and astrophysical implication in ONe nova explosion

An accurate 28 P(p, γ) 29 S reaction rate is crucial to defining the nucleosynthesis products of explosive hydrogen burning in ONe novae. Using the recently released nuclear mass of 29 S, together with a shell model and a direct capture calculation, we reanalyzed the 28 P(p, γ) 29 S thermonuclear reaction rate and its astrophysical implication. We focus on improving the astrophysical rate for 28 P(p, γ) 29 S based on the newest nuclear mass data. Our goal is to explore the impact of the new rate and associated uncertainties on the nova nucleosynthesis. We evaluated this reaction rate via the sum of the isolated resonance contribution instead of the previously used Hauser-Feshbach statistical model. The corresponding rate uncertainty at different energies was derived using a Monte Carlo method. Nova nucleosynthesis is computed with the 1D hydrodynamic code SHIVA. The contribution from the capture on the first excited state at 105.64 keV in 28 P is taken into account for the first time. We find that the capture rate on the first excited state in 28 P is up to more than 12 times larger than the ground-state capture rate in the temperature region of 2.5 × 10 7 K to 4 × 10 8 K, resulting in the total 28 P(p, γ) 29 S reaction rate being enhanced by a factor of up to 1.4 at ~1 × 10 9 K. In addition, the rate uncertainty has been quantified for the first time. It is found that the new rate is smaller than the previous statistical model rates, but it still agrees with them within uncertainties for nova temperatures. The statistical model appears to be roughly valid for the rate estimation of this reaction in the nova nucleosynthesis scenario. Using the 1D hydrodynamic code SHIVA, we performed the nucleosynthesis calculations in a nova explosion to investigate the impact of the new rates of 28 P(p, γ) 29 S. Our calculations show that the nova abundance pattern is only marginally affected if we use our new rates with respect to the same simulations but statistical model rates. Finally, the isotopes whose abundance is most influenced by the present 28 P(p, γ) 29 S uncertainty are 28 Si, 33,34 S, 35,37 Cl, and 36 Ar, with relative abundance changes at the level of only 3% to 4%.

Astronomy & Astrophysics↗
DOE OSTI2024

Monte Carlo evaluation of the semiclassical multi-step direct reaction series

We show how the multi-step direct reaction series can be evaluated using Monte Carlo methods. Nucleon-nucleon collisions occur according to the random selection of a nucleon’s attenuation factor along its classical trajectory. The particles and hole excited in a collision are selected from a local Fermi distribution. We assume that the particles continue to propagate and possibly collide again before leaving the nucleus. We assume that holes collide in place, to possibly produce other particles and holes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Modeling DC electrical breakdown using a truncated emission spectrum for trapped radiation

Spontaneously emitted radiation from excited atoms can be of principle importance in certain modes of electrical breakdown, especially positive streamers and some regimes of Townsend breakdown. The electrostatic particle-in-cell code Aleph utilizes the direct simulation Monte Carlo method to compute radiation transport. When there is strong radiation trapping, this approach is limited in that it must resolve the timescale associated with self-absorption. This renders many cases computationally intractable as sub-femtosecond time steps can be required to compute solutions for phenomena that occur over nanoseconds or microseconds. For two specific cases which exhibit strong radiation trapping, we find that spontaneous emissions having a frequency near the line center are inactive in the breakdown process and can be neglected. This enables larger time steps and a computational speedup of up to two orders of magnitude is observed. Some considerations for determining the validity of making such an approximation for Townsend breakdown problems and positive ionization wave problems are presented.

Roberds, N. A.↗
DOE OSTI2021

Top-level physics requirements and simulated performance of the MRSt on the National Ignition Facility

The time-resolving Magnetic Recoil Spectrometer (MRSt) for the National Ignition Facility (NIF) has been identified by the US National Diagnostic Working Group as one of the transformational diagnostics that will reshape the way inertial confinement fusion (ICF) implosions are diagnosed. The MRSt will measure the time-resolved neutron spectrum of an implosion, from which the time-resolved ion temperature, areal density, and yield will be inferred. Top-level physics requirements for the MRSt were determined based on simulations of numerous ICF implosions with varying degrees of alpha heating, P2 asymmetry, and mix. Synthetic MRSt data were subsequently generated for different configurations using Monte–Carlo methods to determine its performance in relation to the requirements. The system was found to meet most requirements at current neutron yields at the NIF. This work was supported by the DOE and LLNL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Bandgap analysis and carrier localization in cation-disordered ZnGeN 2

The bandgap of ZnGeN 2 changes with the degree of cation site disorder and is sought in light emitting diodes for emission at green to amber wavelengths. By combining the perspectives of carrier localization and defect states, we analyze the impact of different degrees of disorder on electronic properties in ZnGeN 2 , addressing a gap in current studies, which largely focus on dilute or fully disordered systems. The present study demonstrates changes in the density of states and localization of carriers in ZnGeN 2 calculated using bandgap-corrected density functional theory and hybrid calculations on partially disordered supercells generated using the Monte Carlo method. We use localization and density of states to discuss the ill-defined nature of a bandgap in a disordered material and identify site disorder and its impact on the structure as a mechanism controlling electronic properties and potential device performance. Decreasing the order parameter results in a large reduction of the bandgap. The reduction in bandgap is due, in part, to isolated, localized states that form above the valence band continuum associated with nitrogen coordinated by more zinc than germanium. The prevalence of defect states in all but the perfectly ordered structure creates challenges for incorporating disordered ZnGeN 2 into optical devices, but the localization associated with these defects provides insight into the mechanisms of electron/hole recombination in the material.

36 MATERIALS SCIENCE↗