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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Probing fractional statistics in quantum simulators of spin liquid Hamiltonians

Recent advances in programmable quantum devices brought to the fore the intriguing possibility of using them to realise and investigate topological quantum spin liquid phases. This new and exciting direction brings about important research questions on how to probe and determine the presence of such exotic, highly entangled phases in a noisy quantum environment. One of the most promising tools is investigating the behaviour of the topological excitations, and in particular their fractional statistics. In this work we put forward a generic route to achieve this, and we illustrate it in the specific case of \mathbb{Z}_2 ℤ 2 topological spin liquids implemented with the aid of combinatorial gauge symmetry. We design a convenient architecture to study signatures of fractional statistics via quasiparticle interferometry, and we assess its robustness to diagonal and off-diagonal disorder, as well as to dephasing - effects that are generally pervasive in current quantum programmable devices. Interestingly, when turned on its head, our scheme provides a remarkably clear test of the “quantumness” of these devices, with robust signatures that crucially hinge on quantum coherence and quantum interference effects, and cannot be mimicked by classical stochastic processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

General Quantum Field Theory of Flavor Mixing and Oscillations

We review the canonical transformation in quantum physics known as the Bogoliubov transformation and present its application to the general theory of quantum field mixing and oscillations with an arbitrary number of mixed particles with either boson or fermion statistics. The mixing relations for quantum states are derived directly from the definition of mixing for quantum fields and the unitary inequivalence of the Fock space of energy and flavor eigenstates is shown by a straightforward algebraic method. The time dynamics of the interacting fields is then explicitly solved and the flavor oscillation formulas are derived in a unified general formulation with emphasis on antiparticle content and effect introduced by nontrivial flavor vacuum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A critical assessment of solutions to the galaxy diversity problem

Galactic rotation curves exhibit a diverse range of inner slopes. Observational data indicates that explaining this diversity may require a mechanism that correlates a galaxy's surface brightness with the central-most region of its dark matter halo. Here, in this work, we compare several concrete models that capture the relevant physics required to explain the galaxy diversity problem. We focus specifically on a Self-Interacting Dark Matter (SIDM) model with an isothermal core and two Cold Dark Matter (CDM) models with/without baryonic feedback. In contrast to the CDM case, the SIDM model can lead to the formation of an isothermal core in the halo, and is also mostly insensitive to baryonic feedback processes, which act on longer time-scales. Using rotation curves from 90 galaxies in the Spitzer Photometry & Accurate Rotation Curves (SPARC) catalog, we perform a comprehensive model comparison that addresses issues of statistical methodology from prior works. The best-fit halo models that we recover are consistent with standard CDM concentration-mass and abundance matching relations. We find that both the SIDM and feedback-affected CDM models are better than a CDM model with no feedback in explaining the rotation curves of low and high surface brightness galaxies in the sample. However, when compared to each other, there is no strong statistical preference for either the SIDM or the feedback-affected CDM halo model as the source of galaxy diversity in the SPARC catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

ARETE: Accurate Error Assessment via Machine Learning-Guided Dynamic-Timing Analysis

Nanometer circuits are increasingly prone to timing errors, escalating the need for fault injection frameworks to accurately evaluate their impact on applications. Here in this paper, we propose ARETE, a novel cross-layer, fault-injection framework that combines dynamic-binary instrumentation with machine learning-guided dynamic-timing analysis. ARETE enables accurate fault-injection into any application by estimating the location of the injecting errors via dynamic-timing analysis. To accelerate fault-injection, we develop a novel, data-aware, machine learning-based mechanism that dynamically pre-selects the error-prone instructions and limits the application of the costly dynamic-timing analysis only to them. To evaluate ARETE's accuracy, our fully automated toolflow is configured to support fault-injection based on detailed post-layout gate-level simulations as well as via existing workload-agnostic error models. Our results for various workloads, including an autonomous-driving library, show that the location and time of injected errors performed by ARETE, is 89.9% consistent with fault-injection based on full gate-level simulation. On average, ARETE executes 84.6x faster than gate-level simulation and at a cost of 3.4% loss in the program output quality estimation. When compared to the existing statistical fault-injection tools that are based on workload-agnostic error models, ARETE improves the accuracy of fault-injection rate and output quality estimation by 143.9% and 40.4% on average, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Application of entropy and signal energy for ultrasound-based classification of three-dimensional printed polyetherketoneketone components

This paper describes a preliminary method for the classification of annealed and unannealed polyetherketoneketone (PEKK) components manufactured using a material extrusion three-dimensional (3D) printing process. PEKK is representative of a class of high-performance thermoplastics that are increasingly employed as feedstocks for use in 3D printing. PEKK components may be used continuously at elevated temperatures, are chemically resistant, and able to withstand large mechanical loads. These properties render PEKK suitable as a metal component replacement in aerospace applications, high-temperature industrial applications, and surgical implants. The structure of PEKK is semi-crystalline with the specific crystallinity correlating to the final properties during application, making determination of this property crucial. This study compares three different signal processing techniques intended to distinguish annealed (high crystallinity) from unannealed (low crystallinity) components using backscattered ultrasound. The first is energy-based and is unable to detect annealing. The second two are based on different entropies of the backscattered signal: a limiting form of Renyi's entropy and a limiting form of joint entropy. The joint entropy values for the annealed and unannealed specimens fall into two non-overlapping intervals and have a statistical separation of two standard deviations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2022

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality

Background: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions.Objectives: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables.Methods: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping.Results: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients.Conclusions: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Chemical Heterogeneity in PAN/LLZTO Composite Electrolytes by Synchrotron Imaging

Solid polymer/ceramic composite electrolytes are promising for batteries due to their attractive thermal stability and mechanical properties. Chemical heterogeneity in solid composite electrolytes, such as the inhomogeneity in the ceramic phase and salt distribution at the polymer/ceramic interface, is critical to the performance of solid composite electrolytes. However, such heterogeneity has not been well understood yet. In this work, we use Synchrotron-based X-ray fluorescence imaging (XRF) and Transmission X-ray Microscope (TXM) to image nanoscale chemical heterogeneity in polyacrylamide/Li 7+x La 3 Zr 2–x Ta x O 12 (LLZTO) composite electrolytes and investigate the effects of lithium salt, salt concentration, and plasticizer. We find that LLZTO particles show strong inter- and intra-particles chemical heterogeneities, and the off-stoichiometry of Zr in an LLZTO particle is unlikely to be only balanced by Ta substitution. Moreover, statistical analysis suggests that LiI tends to accumulate at the ceramic/polymer interface at a low concentration of 5 wt%, but no such tendency was observed in samples with 10 wt% LiI. However, composite electrolytes with LiTFSI show interfacial accumulation at both 5 wt% and 10 wt%. Furthermore, this report provides insight into element distributions in solid composite electrolytes, and we hope further researches can shed light on the connections between chemical heterogeneity and ionic transport pathway inside.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On the Quantum Mechanics of Entropic Forces

It was conjectured 30 years ago that gravity could arise from the entropic rearrangement of information. We offer a set of microscopic quantum models which realize this idea in detail. In particular, we suggest a simple mechanism by which Newton’s law of gravity arises from extremization of the free energy of a collection of qubits or oscillators, rather than from the exchange of virtual quanta of a fundamental field. We give both a local and a nonlocal version of the construction and show how to distinguish a range of these entropic models from ordinary perturbative quantum gravity using existing observations and near-term experiments.

quantum fluctuations↗
DOE OSTI2022

Changes in Aerosols, Meteorology, and Radiation in the Southeastern U.S. Warming Hole Region during 2000 to 2019

Abstract Surface air temperatures in the southeastern United States that did not change from the climatological mean from 1900 to 2000 have increased since the year 2000. Analyzed herein are factors modulating the surface air temperatures in the region for a 20-yr period (2000–19) using space- and surface-based observations, and output from a reanalysis model. The 20-yr period is segregated into two decades, 2000–09 and 2010–19, corresponding to different tropospheric chemical regimes. Changes in seasonal and decadal averages are examined. The later decade experienced higher average surface air temperatures with significant warming during summer and fall seasons. Decadal and seasonal averages of cloud properties, column water vapor, rain rates, and top-of-atmosphere outgoing longwave radiation did not exhibit statistically significant differences between the two decades. The region experienced strong warm and moist advection during the winter months and very weak advection during the summer months. The later decade exhibited higher low-level moisture advection during the winter months than the earlier decade with insignificant changes in the temperature advection between the two decades. The later decade had significantly lower aerosol dry and liquid water mass during all seasons, along with lower aerosol optical depth, higher single scattering albedo, and lower top-of-the-atmosphere outgoing shortwave radiation during cloud-free conditions in the summer season. Collectively, these results suggest that changes in the aerosol direct radiative forcing are responsible for warming during summer months that experience weak advection and highlight seasonal differences in the temperature controlling mechanisms in the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2024

Structural basis for intermodular communication in assembly-line polyketide biosynthesis

Assembly-line polyketide synthases (PKSs) are modular multi-enzyme systems with considerable potential for genetic reprogramming. Understanding how they selectively transport biosynthetic intermediates along a defined sequence of active sites could be harnessed to rationally alter PKS product structures. Here, to investigate functional interactions between PKS catalytic and substrate acyl carrier protein (ACP) domains, we employed a bifunctional reagent to crosslink transient domain–domain interfaces of a prototypical assembly line, the 6-deoxyerythronolide B synthase, and resolved their structures by single-particle cryogenic electron microscopy (cryo-EM). Together with statistical per-particle image analysis of cryo-EM data, we uncovered interactions between ketosynthase (KS) and ACP domains that discriminate between intra-modular and inter-modular communication while reinforcing the relevance of conformational asymmetry during the catalytic cycle. Our findings provide a foundation for the structure-based design of hybrid PKSs comprising biosynthetic modules from different naturally occurring assembly lines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Gaia–Kepler Stellar Properties Catalog. II. Planet Radius Demographics as a Function of Stellar Mass and Age

Studies of exoplanet demographics require large samples and precise constraints on exoplanet host stars. Using the homogeneous Kepler stellar properties derived using the Gaia Data Release 2 by Berger et al., we recompute Kepler planet radii and incident fluxes and investigate their distributions with stellar mass and age. We measure the stellar mass dependence of the planet radius valley to be dlogR{sub p}/dlogM{sub ⋆} = 0.26{sub −0.16}{sup +0.21}, consistent with the slope predicted by a planet mass dependence on stellar mass (0.24–0.35) and core-powered mass loss (0.33). We also find the first evidence of a stellar age dependence of the planet populations straddling the radius valley. Specifically, we determine that the fraction of super-Earths (1–1.8 R{sub ⊕}) to sub-Neptunes (1.8–3.5 R{sub ⊕}) increases from 0.61 ± 0.09 at young ages (<1 Gyr) to 1.00 ± 0.10 at old ages (>1 Gyr), consistent with the prediction by core-powered mass loss that the mechanism shaping the radius valley operates over Gyr timescales. Additionally, we find a tentative decrease in the radii of relatively cool (F {sub p} < 150 F{sub ⊕}) sub-Neptunes over Gyr timescales, which suggests that these planets may possess H/He envelopes instead of higher mean molecular weight atmospheres. We confirm the existence of planets within the hot sub-Neptunian “desert” (2.2 R {sub ⊕} < R {sub p} < 3.8 R{sub ⊕}, F {sub p} > 650 F{sub ⊕}) and show that these planets are preferentially orbiting more evolved stars compared to other planets at similar incident fluxes. In addition, we identify candidates for cool (F {sub p} < 20 F{sub ⊕}) inflated Jupiters, present a revised list of habitable zone candidates, and find that the ages of single and multiple transiting planet systems are statistically indistinguishable.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A direct numerical simulation of Jet A flame kernel quenching

The safe operation of aeronautical engines requires an understanding of flame ignition, propagation and extinction. In this study, direct numerical simulations are performed using a 29 species reduced chemical mechanism for jet fuel surrogate Jet A to understand the flame quenching process. Here, initially laminar spherical flames of varying sizes and equivalence ratios are subject to an identical periodic domain of decaying and isotropic high intensity turbulence with a turbulent Reynolds number of 2400. All cases become quenched, except for the larger kernel with lower Karlovitz number. An analysis of the flame structure shows broadened preheat zone, flame shortening on the product side, differential species diffusion and partial fuel pyrolysis in the fresh mixture. Two extinction mechanisms are identified arising from flame shortening and high flame stretch. Flame shortening occurs due to turbulence-chemistry interactions that resemble the flame–flame interaction in a laminar counterflow reactant-to-reactant configuration, which contorts and breaks up the ignition kernel. Flame stretch is a local effect that attenuates the heat release rate and causes the flame to retreat towards the product mixtures, similar to what has been observed for reactant-to-product laminar counterflow flames. Chemical explosive mode analysis was also performed to quantify the flame structure and local combustion mode. The diffusion–reaction balance in pinched-off flame islands favors extinction of these smaller structures, while auto-ignition modes are observed within the flame kernel after fresh mixture is engulfed and preheated in the product kernel. Statistics of the density-weighted displacement speed conditional on local combustion mode indicates strong correlation between the local extinction mode and negative displacement speed. The local balance between diffusion and reaction ultimately determines the propensity for local extinction in both laminar and turbulent flames, the extent of which has an impact on global flame propagation.

42 ENGINEERING↗
DOE OSTI2021

Observations of Density Cavities and Associated Warm Ion Flux Enhancements in the Inner Magnetosphere

We present a statistical study of density cavities observed in the inner magnetosphere by the Van Allen Probes during four one-month periods: February 2013, July 2013, January 2014, and June 2014. These periods were chosen to allow the survey of all magnetic local times. We find that density cavities are a recurrent feature of the density profiles of in situ measurements in the inner magnetosphere. We further investigate the correlation between the density cavities and the enhancement of fluxes of warm ions with energies of 10–100 eV. The results show that warm ion flux enhancements associated with the density cavities were observed more frequently for H + , then for He + and the least frequently for O + . The occurrences of the associated flux enhancements were increased when considering only the cavities inside the plasmasphere. Possible mechanisms responsible for the observed warm ion flux enhancements and the role of density cavities on these ion flux enhancements are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Analysis of the nonlinear propagation of incoherent pulses

The nonlinear propagation of incoherent optical pulses is studied using a normalized nonlinear Schrödinger equation and statistical analysis, demonstrating various regimes that depend on the field’s coherence time and intensity. The quantification of the resulting intensity statistics using probability density functions shows that, in the absence of spatial effects, nonlinear propagation leads to an increase in the likelihood of high intensities in a medium with negative dispersion, and a decrease in a medium with positive dispersion. In the latter regime, nonlinear spatial self-focusing originating from a spatial perturbation can be mitigated, depending on the coherence time and amplitude of the perturbation. These results are benchmarked against the Bespalov–Talanov analysis applied to strictly monochromatic pulses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Power spectrum and form factor in random diagonal matrices and integrable billiards

Triggered by a controversy surrounding a universal behavior of the power spectrum in quantum systems exhibiting regular classical dynamics, we focus on a model of random diagonal matrices (RDM), often associated with the Poisson spectral universality class, and examine how the power spectrum and the form factor get affected by two-sided truncations of RDM spectra. Having developed a nonperturbative description of both statistics, we perform their detailed asymptotic analysis to demonstrate explicitly how a traditional assumption (lying at the heart of the controversy) – that the power spectrum is merely determined by the spectral form factor – breaks down for truncated spectra. This observation has important consequences as we further argue that bounded quantum systems with integrable classical dynamics are described by heavily truncated rather than complete RDM spectra. High-precision numerical simulations of semicircular and irrational rectangular billiards lend independent support to these conclusions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Publishing statistical models: Getting the most out of particle physics experiments

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗