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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Threshold progressions in covering and packing contexts

Here, using standard methods (due to Janson, Stein–Chen, and Talagrand) from probabilistic combinatorics, we explore the following general theme: As one progresses from each member of a family of objects $\mathcal{A}$ being “covered” by at most one object in a random collection $\mathcal{C}$, to being covered at most λ times, to being covered at least once, to being covered at least λ times, a hierarchy of thresholds emerge. We will use examples from extremal set theory, combinatorics, and additive number theory to see how these results vary according to the context, and level of dependence introduced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Induced and non-induced poset saturation problems

A subfamily G ⊆ F ⊆ 2 [ n ] of sets is a non-induced (weak) copy of a poset P in F if there exists a bijection i : P → G such that p ≤ P q implies i ( p ) ⊆ i ( q ) . In the case where in addition p ≤ P q holds if and only if i ( p ) ⊆ i ( q ) , then is an induced (strong) copy of P in G . We consider the minimum number sat ( n , P ) [resp. sat ⁎ ( n , P ) ] of sets that a family F ⊆ 2 [ n ] can have without containing a non-induced [induced] copy of P and being maximal with respect to this property, i.e., the addition of any G ∈ 2 [ n ] ∖ F creates a non-induced [induced] copy of P.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Analyzing the Free States of one Quantum Resource Theory as Resource States of Another

In the context of quantum resource theories (QRTs), free states are defined as those that can be obtained at no cost under a certain restricted set of conditions. However, when taking a free state from one QRT and evaluating it through the optics of another QRT, it might well turn out that the state is now extremely resourceful. Such realization has recently prompted numerous works characterizing states across several QRTs. Here, in this work, we contribute to this body of knowledge by analyzing the resourcefulness in free states for—and across witnesses of—the QRTs of multipartite entanglement, fermionic non-Gaussianity, imaginarity, realness, spin coherence, Clifford non-stabilizerness, $S_n$-equivariance, and non-uniform entanglement. We provide rigorous theoretical results as well as present numerical studies that showcase the rich and complex behavior that arises in this type of cross-examination.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

New H2O–H2O collisional rate coefficients for cometary applications

ABSTRACT We re-introduce a semiclassical methodology based on theories developed for the determination of broadening coefficients. We show that this simple and extremely fast methodology provides results that are in good agreement with results obtained using the more sophisticate MQCT approach. This semiclassical methodology could be an alternative approach which allows to provide large sets of collisional data for very complex molecular systems. It saves time both on the determination of potential energy surfaces and on the collisional dynamical calculations. In addition, this paper provides more complete sets of rotational de-excitation cross-sections and rate coefficients of H2O perturbed by a thermal average of water molecules. Those data can be used in the radiative transfer modelling of cometary atmospheres.

Boursier, C.↗
DOE OSTI2025

From Existing and New Nuclear and Astrophysical Constraints to Stringent Limits on the Equation of State of Neutron-Rich Dense Matter

Through continuous progress in nuclear theory and experiment and an increasing number of neutron-star (NS) observations, a multitude of information about the equation of state (EOS) for matter at extreme densities is available. To constrain the EOS across its entire density range, this information needs to be combined consistently. However, the impact and model dependency of individual observations vary. Given their growing number, assessing the various methods is crucial to compare the respective effects on the EOS and discover potential biases. For this purpose, we present a broad compendium of different constraints and apply them individually to a large set of EOS candidates within a Bayesian framework. Specifically, we explore different ways of how chiral effective field theory and perturbative quantum chromodynamics can be used to place a likelihood on EOS candidates. We also investigate the impact of nuclear experimental constraints, as well as different radio and x-ray observations of NS masses and radii. This is augmented by reanalyses of the existing data from binary neutron star coalescences, in particular of GW170817, with improved models for the tidal waveform and kilonova light curves, which we also utilize to construct a tight upper limit of 2.39 M ⊙ on the TOV mass based on GW170817’s remnant. Our diverse set of constraints is eventually combined to obtain stringent limits on NS properties. We organize the combination in a way to distinguish between constraints where the systematic uncertainties are deemed small and those that rely on less conservative assumptions. For the former, we find the radius of the canonical 1.4 M ⊙ neutron star to be R 1.4 = 12.2 6 − 0.91 + 0.80 km and the TOV mass at M TOV = 2.2 5 − 0.22 + 0.42 M ⊙ (95% credibility). Including all the presented constraints yields R 1.4 = 12.2 0 − 0.48 + 0.50 km and M TOV = 2.3 0 − 0.20 + 0.07 M ⊙ . When comparing these limits to individual data points, we find that the quoted radius of HESS J1731-347 displays noticeable tension with other constraints. Constraining microphysical properties of the EOS proves more challenging. For instance, the symmetry energy slope is restricted to L sym = 48 − 25 + 21 MeV , where this constraint is mainly dominated by our reanalysis of the PREX-II and CREX experiment. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Conformal bootstrap deformations

We explore the space of extremal functionals in the conformal bootstrap. By recasting the bootstrap problem as a set of non-linear equations parameterized by the CFT data, we find an efficient algorithm for converging to the extremal solution corresponding to the boundary of allowed regions in the parameter space of CFTs. Furthermore, by deforming these solutions, we demonstrate that certain solutions corresponding to known theories are continuously connected. Employing these methods, we will explore the space of non-unitary CFTs in the context of modular as well as correlation function bootstrap. In two dimensions, we show that the extremal solution corresponding to the Ising model is connected to that of the Yang-Lee minimal model. By deforming this solution to three dimensions, we provide evidence that the CFT data obtained in this way is compatible with the E-expansion for a non-unitary theory

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Estimation of the Surface Fluxes for Heat and Momentum in Unstable Conditions with Machine Learning and Similarity Approaches for the LAFE Data Set

Abstract Measurements of three flux towers operated during the land atmosphere feedback experiment (LAFE) are used to investigate relationships between surface fluxes and variables of the land–atmosphere system. We study these relations by means of two machine learning (ML) techniques: multilayer perceptrons (MLP) and extreme gradient boosting (XGB). We compare their flux derivation performance with Monin–Obukhov similarity theory (MOST) and a similarity relationship using the bulk Richardson number (BRN). The ML approaches outperform MOST and BRN. Best agreement with the observations is achieved for the friction velocity. For the sensible heat flux and even more so for the latent heat flux, MOST and BRN deviate from the observations while MLP and XGB yield more accurate predictions. Using MOST and BRN for latent heat flux, the root mean square errors (RMSE) are 107 Wm $$^{-2}$$ - 2 and 121 Wm $$^{-2}$$ - 2 , respectively, as well as the intercepts of the regression lines are $$\approx 110$$ ≈ 110 Wm $$^{-2}$$ - 2 . For the ML methods, the RMSEs reduce to 31 Wm $$^{-2}$$ - 2 for MLP and 33 Wm $$^{-2}$$ - 2 for XGB as well as the intercepts to just 4 Wm $$^{-2}$$ - 2 for MLP and $$-1$$ - 1 Wm $$^{-2}$$ - 2 for XGB with slopes of the regression lines close to 1, respectively. These results indicate significant deficiencies of MOST and BRN, particularly for the derivation of the latent heat flux. In fact, in contrast to the established theories, feature importance weighting demonstrates that the ML methods base their improved derivations on net radiation, the incoming and outgoing shortwave radiations, the air temperature gradient, and the available water contents, but not on the water vapor gradient. The results imply that further studies of surface fluxes and other turbulent variables with ML techniques provide great promise for deriving advanced flux parameterizations and their implementation in land–atmosphere system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SNEWPY: A Data Pipeline from Supernova Simulations to Neutrino Signals

Current neutrino detectors will observe hundreds to thousands of neutrinos from a Galactic supernovae, and future detectors will increase this yield by an order of magnitude or more. With such a data set comes the potential for a huge increase in our understanding of the explosions of massive stars, nuclear physics under extreme conditions, and the properties of the neutrino. However, there is currently a large gap between supernova simulations and the corresponding signals in neutrino detectors, which will make any comparison between theory and observation very difficult. SNEWPY is an open-source software package which bridges this gap. The SNEWPY code can interface with supernova simulation data to generate from the model either a time series of neutrino spectral fluences at Earth, or the total time-integrated spectral fluence. Data from several hundred simulations of core-collapse, thermonuclear, and pair-instability supernovae is included in the package. This output may then be used by an event generator such as sntools or an event rate calculator such as SNOwGLoBES. Additional routines in the SNEWPY package automate the processing of the generated data through the SNOwGLoBES software and collate its output into the observable channels of each detector. In this paper we describe the contents of the package, the physics behind SNEWPY, the organization of the code, and provide examples of how to make use of its capabilities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

SNEWPY: A Data Pipeline from Supernova Simulations to Neutrino Signals

Current neutrino detectors will observe hundreds to thousands of neutrinos from Galactic supernovae, and future detectors will increase this yield by an order of magnitude or more. With such a data set comes the potential for a huge increase in our understanding of the explosions of massive stars, nuclear physics under extreme conditions, and the properties of the neutrino. However, there is currently a large gap between supernova simulations and the corresponding signals in neutrino detectors, which will make any comparison between theory and observation very difficult. SNEWPY is an open-source software package that bridges this gap. The SNEWPY code can interface with supernova simulation data to generate from the model either a time series of neutrino spectral fluences at Earth, or the total time-integrated spectral fluence. Data from several hundred simulations of core-collapse, thermonuclear, and pair-instability supernovae is included in the package. This output may then be used by an event generator such as sntools or an event rate calculator such as the SuperNova Observatories with General Long Baseline Experiment Simulator (SNOwGLoBES). Additional routines in the SNEWPY package automate the processing of the generated data through the SNOwGLoBES software and collate its output into the observable channels of each detector. In this paper we describe the contents of the package, the physics behind SNEWPY, the organization of the code, and provide examples of how to make use of its capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstrata

Abstract Microstrata are the non-extremal analogues of superstrata: they are smooth, non-extremal (non-BPS) solitonic solutions to IIB supergravity whose deep-throat limits approximate black holes. Using perturbation theory and numerical methods, we construct families of solutions using a consistent truncation to three-dimensional supergravity. The most general families presented here involve two continuous parameters, or amplitudes, and four quantized parameters that set the angular momenta and energy levels. Our solutions are asymptotic to the vacuum of the D1-D5 system: AdS 3 ×S 3 × 𝕋 4 . Using holography, we show that the they are dual to multi-particle states in the D1-D5 CFT involving a large number of mutually non-BPS supergravitons and we determine the anomalous dimensions of these states from the binding energies in supergravity. These binding energies are uniformly negative and depend non-linearly on the amplitudes of the states. In one family of solutions, smoothness restricts some of the fields to lie on a special locus of the parameter space. Using precision holography we show that this special locus can be identified with the multi-particle states constructed via the standard OPE of the single-particle constituents. Our numerical analysis shows that microstrata are robust at large amplitudes and the solutions can be obtained to very high precision.

Physics↗
DOE OSTI2023

Interplay between Facets and Defects during the Dissociative and Molecular Adsorption of Water on Metal Oxide Surfaces

Both surface terminations and defects play a central role in determining how water interacts with metal oxides, thereby setting important properties of the interface that govern reactivity such as the type and distribution of hydroxyl groups. However, the interconnections between facets and defects remain poorly understood, limiting the usefulness of conventional notions such as that hydroxylation is controlled by metal cation exposure at the surface. Here, using hematite (α-Fe 2 O 3 ) as a model system, we show how oxygen vacancies overwhelm surface cation-dependent hydroxylation behavior. Synchrotron-based ambient-pressure X-ray photoelectron spectroscopy was used to monitor the adsorption of molecular water and its dissociation to form hydroxyl groups in situ on (001), (012), or (104) facet-engineered hematite nanoparticles. Supported by density functional theory calculations of the respective surface energies and oxygen vacancy formation energies, the findings show how oxygen vacancies are more prone to form on higher energy facets and induce surface hydroxylation at extremely low relative humidity values of 5 x10 - 5 %. Further, when these vacancies are eliminated, the extent of surface hydroxylation across the facets is as expected from the areal density of exposed iron cations at the surface. These findings help answer fundamental questions about the nature of reducible metal oxide-water interfaces in natural and technological settings and lay the groundwork for rational design of improved oxide-based catalysts.

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

Deep-freeze graph training for latent learning

Scientific and engineering advances are primarily driven by multi-tier conceptual constructs and conditional theoretical frameworks. The theories allow predictions of hypothetical system responses, given a set of approximate conditions (ranges of applicability) imposed on latent parameters that cannot be measured directly. Learning to estimate the latent variables (Latent Learning) helps to pinpoint the anticipated range-edge anomalies and improves the confidence in interpretation, interpolation and extrapolation of limited experimental data. Due to high dimensionality and extreme non-linearity of the materials science problems, very large datasets are typically required for conventional data-driven model development. The vital experimental data collection, particularly on microstructural phases, is very challenging, which makes it difficult to compile a high-quality database. Incorporation of the domain knowledge into the computational graph structure, initialization and optimization processes presents a viable mechanism for developing accurate models, with limited datasets. Furthermore, this study successfully utilized the approach to build the Deep Freeze Graph (DeepFreG) by mapping known causality relationships and by digitizing empirical domain knowledge for Latent Learning (LL), with specific applications in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Many-body reactive force field development for carbon condensation in C/O systems under extreme conditions

In this paper, we describe the development of a reactive force field for C/O systems under extreme temperatures and pressures, based on the many-body Chebyshev Interaction Model for Efficient Simulation (ChIMES). The resulting model, which targets carbon condensation under thermodynamic conditions of 6500 K and 2.5 g cm –3 , affords a balance between model accuracy, complexity, and training set generation expense. We show that the model recovers much of the accuracy of density functional theory for the prediction of structure, dynamics, and chemistry when applied to dissociative condensed phase systems at 1:1 and 1:2 C:O ratios, as well as molten carbon. Our C/O modeling approach exhibits a 104 increase in efficiency for the same system size (i.e., 128 atoms) and a linear system size scalability over standard quantum molecular dynamics methods, allowing the simulation of significantly larger systems than previously possible. We find that the model captures the condensed-phase reaction-coupled formation of carbon clusters implied by recent experiments, and that this process is susceptible to strong finite size effects. Overall, we find the present ChIMES model to be well suited for studying chemical processes and cluster formation at pressures and temperatures typical of shock waves. We expect that the present C/O modeling paradigm can serve as a template for the development of a broader high pressure–high temperature force-field for condensed phase chemistry in organic materials.

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

Simulations of Attosecond Metallization in Quartz and Diamond Probed with Inner-Shell Transient Absorption Spectroscopy

When dielectrics are hit with intense infrared (IR) laser pulses, transient metalization can occur. The initial attosecond dynamics behind this metallization are not entirely understood. Therefore, simulations are needed to understand this process and to help interpret experimental observations of it, such as with attosecond transient absorption (ATA). In this paper, we present first-principles simulations of ATA based on bulk-mimicking clusters and real-time time-dependent density functional theory (RT-TDDFT), with Koopmans-tuned range-separated hybrid functionals and Gaussian basis sets. Our method gives good agreement with the experiment for the breakdown threshold in silica and diamond. This breakdown voltage corresponds to a Keldysh parameter of approximately one and thus involves a transition to a regime where the dynamics are driven by tunneling. Pumping at an amplitude just below this value causes a mixture of multiphoton and tunneling excitations across the band gap to occur. The computed extreme ultraviolet and X-ray attosecond transient spectra also agree well with the experiment and show a decrease in optical density due to the transient population of the conduction band from the IR field. First-principles approaches such as this are valuable for interpreting the complicated modulations in a spectrum and for guiding future attosecond experiments on solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Bootstrapping 2d ϕ 4 theory with Hamiltonian truncation data

We combine the methods of Hamiltonian Truncation and the recently proposed generalisation of the S-matrix bootstrap that includes local operators to determine the two-particle scattering amplitude and the two-particle form factor of the stress tensor at s > 0 in the 2d Φ 4 theory. We use the form factor of the stress tensor at s ≤ 0 and its spectral density computed using Lightcone Conformal Truncation (LCT), and inject them into the generalized S-matrix bootstrap set-up. The obtained results for the scattering amplitude and the form factor are fully reliable only in the elastic regime. We independently construct the “pure” S-matrix bootstrap bounds (bootstrap without including matrix elements of local operators), and find that the sinh-Gordon model and its analytic continuation the “staircase model” saturate these bounds. Surprisingly, the Φ 4 two-particle scattering amplitude also very nearly saturates these bounds, and moreover is extremely close to that of the sinh-Gordon/staircase model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Universality in logarithmic temperature corrections to near-extremal rotating black hole thermodynamics in various dimensions

The low-temperature thermodynamics of near-extremal rotating black holes has recently been revisited to incorporate one-loop contributions that are dominant in this regime. We discuss these quantum corrections to the gravitational path integral for asymptotically Anti de-Sitter black holes in four and five dimensions. In four dimensions we explicitly consider Kerr-AdS 4 , Kerr-Newman-AdS 4 and the rotating black hole in $\mathcal{N}$ = 4 gauged supergravity with two scalars and two electric charges turned on. In five dimensions we explicitly address the asymptotically flat Myers-Perry black hole and the Kerr-AdS5 black hole. In every case we find that tensor modes contribute $\frac{3}{2}$logT Hawking to the low-temperature thermodynamics. We identify the root cause of this universality in two facts: (i) the universal presence of a SL(2, $\mathbb{R}$) subgroup of isometries in the near-horizon geometry and (ii) a set of cancellations in the Lichnerowicz operator. We show that these two conditions hold for near-extremal black holes in asymptotically flat and asymptotically AdS spacetimes of various dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗