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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints (SHEBO) v1.0

SHEBO (surrogate optimization of problems with hidden constraints and expensive black-box objectives) is an efficient optimization algorithm that employs surrogate models to solve computationally expensive black-box simulation optimization problems that have hidden constraints. Hidden constraints are encountered when the objective function evaluation does not return a value for a parameter vector. These constraints are often encountered in optimization problems in which the objective function is computed by a black-box simulation code. SHEBO uses a combination of local and global search strategies together with an evaluability prediction function and a dynamically adjusted evaluability threshold to iteratively select new sample points.

Mueller, Juliane↗
DOE OSTI2021

Jet fragmentation transverse momentum distributions in pp and p-Pb collisions at $ \sqrt{s}$, $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV

Jet fragmentation transverse momentum ( j T ) distributions are measured in proton-proton (pp) and proton-lead (p-Pb) collisions at s NN = 5 . 02 TeV with the ALICE experiment at the LHC. Jets are reconstructed with the ALICE tracking detectors and electromagnetic calorimeter using the anti- k T algorithm with resolution parameter R = 0 . 4 in the pseudorapidity range |η| < 0 . 25. The j T values are calculated for charged particles inside a fixed cone with a radius R = 0 . 4 around the reconstructed jet axis. The measured j T distributions are compared with a variety of parton-shower models. Herwig and P ythia 8 based models describe the data well for the higher j T region, while they underestimate the lower j T region. The j T distributions are further characterised by fitting them with a function composed of an inverse gamma function for higher j T values (called the “wide component”), related to the perturbative component of the fragmentation process, and with a Gaussian for lower j T values (called the “narrow component”), predominantly connected to the hadronisation process. The width of the Gaussian has only a weak dependence on jet transverse momentum, while that of the inverse gamma function increases with increasing jet transverse momentum. For the narrow component, the measured trends are successfully described by all models except for Herwig. For the wide component, Herwig and PYTHIA 8 based models slightly underestimate the data for the higher jet transverse momentum region. These measurements set constraints on models of jet fragmentation and hadronisation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

High Dielectric Constant Semiconducting Poly(3-alkylthiophene)s from Side Chain Modification with Polar Sulfinyl and Sulfonyl Groups

In this paper, there is growing interest in designing and developing high dielectric constant (ε r ) organic semiconductors because they have the potential to further enhance device performance by promoting exciton dissociation, reducing bimolecular charge carrier recombination, and potentially enhancing charge carrier mobility via charge screening. In this study, a new class of semiconducting polymers with high ε r , i.e., sulfinylated and sulfonylated poly(3-alkylthiophene)s (P3ATs), were synthesized. Because of efficient rotation of highly polar methylsulfinyl and methylsulfonyl side groups (i.e., orientational polarization), high ε r values were achieved for these functionalized P3ATs based on an accurate capacitance measurement using a gold/semiconducting polymer/SiO 2 /n-doped Si configuration. For example, the ε r at megahertz and room temperature increased from 3.75 for the regioregular poly(3-hexylthiophene) (P3HT) to 7.4 for the sulfinylated and 8.1–9.3 for sulfonylated P3AT polymers. These values are among the highest ε r reported for conjugated polymers so far. Grazing-incident wide-angle X-ray diffraction results showed that these polar groups decreased the crystallinity for the polythiophene backbones and interfered with the π–π stacking in the crystalline structure. Consequently, their optical properties, including UV–vis absorption and fluorescence, changed in thin films. From this study, the sulfinylated polymer may be promising to provide a balance between high ε r and preserving favorable polythiophene π–π stacking structure for device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Simple model to investigate jet quenching and correlated errors for centrality-dependent nuclear modification factors in relativistic heavy-ion collisions

Here, we apply Bayesian techniques to compare a simple, empirical model for jet quenching in heavy-ion collisions to centrality-dependent jet R AA measured by ATLAS for Pb + Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV. We find that the R AA values for central collisions are adequately described with a model for the mean p T -dependent jet energy loss using only two parameters. This model is extended by incorporating two-dimensional initial geometry information from TRENTo and compared to centrality-dependent R AA values. We find that the results are sensitive to the value of the jet-quenching formation time, τ ƒ , and that the optimal value of τ ƒ varies with the assumed path-length dependence of the energy loss. We construct a covariance error matrix for the data from the p T -dependent contributions to the ATLAS systematic errors and perform Bayesian calibrations for several different assumptions for the systematic error correlations. We show that the most-probable functions and $χ^2_d$ values are sensitive to assumptions made when fitting to correlated errors. This work demonstrates the utility of a simple model that can quickly demonstrate the constraining power of jet-quenching observables with corresponding uncertainties and guide future studies using more sophisticated models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Measurement of R = σ L / σ T and the separated longitudinal and transverse structure functions in the nucleon-resonance region

Here we report on a detailed study of longitudinal strength in the nucleon resonance region, presenting new results from inclusive electron-proton cross sections measured at Jefferson Lab Hall C in the four-momentum transfer range 0.2 < Q 2 < 5.5 GeV 2 . The data have been used to accurately perform over 170 Rosenbluth-type longitudinal/transverse separations. The precision R = $\sigma_{L} /\sigma _{T}$ data are presented here, along with the first separate values of the inelastic structure functions F 1 and F L in this regime. The resonance longitudinal component is found to be significant. With the new data, quark-hadron duality is observed above Q 2 = 1 GeV 2 in the separated structure functions independently.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Predicting boron coordination in multicomponent borate and borosilicate glasses using analytical models and machine learning

Accurate prediction of boron coordination in multicomponent glasses is critical in glass science and technology as it strongly affects the properties of borate and borosilicate glasses. We have collected a dataset containing 657 glasses from literature with boron coordination values and developed models using analytical functions based on the well accepted Dell, Xiao and Bray model. Good prediction of boron coordination with a R 2 value higher than 0.8 was obtained. The large variation of boron coordination from experiments, originated from sample preparations and characterizations, led to difficulties in obtaining models with better prediction performance. Various machine learning (ML) algorithms were evaluated and slightly better prediction performance was observed; however, interpretation of the ML models is less straight forward. In conclusion, this study developed various models capable of providing quantitative boron coordination predictions, providing insights into its structural roles in multi-component glasses, and suggesting fruitful areas for future research.

36 MATERIALS SCIENCE↗
DOE OSTI2020

UQ Toolkit v 2.0

The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Loève expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).

Safta, Cosmin↗
DOE OSTI2023

Structural and thermodynamic effects of hydration in Na-zeolite A (LTA) from low-temperature heat capacity

Zeolite A (Linde Type A; LTA) is an industrially important porous mineral that has recently been shown to exhibit framework flexibility upon changes in hydration level. Here, to investigate the flexibility transition from a thermodynamic perspective, we have performed heat capacity measurements on sodium zeolite A at seven incremental hydration levels ranging from zero to equilibrium with ambient air. Excess low-frequency vibrations beyond the predictions of the Debye model are found in all samples, and the frequency of these vibrations increases as a function of hydration level. This suggests that an increase in hydration causes a decrease in at least one type of framework flexibility for sodium zeolite A. In addition, a subtle excess heat capacity contribution from 150 to 280 K is observed only for low and intermediate hydration levels, which may arise from a transformation tied to framework flexibility previously observed in zeolite A via gas absorption calorimetry. Values of the standard thermodynamic functions C p,m °, Δ 0 T S m °, Δ 0 T H m °, and Φ m ° are also reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The effect of self-interaction error on electrostatic dipoles calculated using density functional theory

Spurious electron self-interaction in density functional approximations (DFAs) can lead to inaccurate predictions of charge transfer in heteronuclear molecules that manifest as errors in calculated electrostatic dipoles. Here we show the magnitude of these errors on dipoles computed for a diverse set of 47 molecules taken from the recent benchmark study of Hait and Head-Gordon. We compare results of Perdew-Wang local spin density approximation (PW92), Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA), and strongly constrained and appropriatedly normed (SCAN) meta-GGA dipole calculations, along with those of their respective self-interaction-corrected (SIC) counterparts, to reference values from accurate wave function-based methods. The SIC calculations were carried out using the Fermi-Löwdin orbital (FLO-SIC) approach. We find that correcting for self-interaction generally increases the degree of charge transfer, thereby increasing the size of calculated dipole moments. The FLO-SIC-PW92 and FLO-SIC-PBE dipoles are in better agreement with reference values than their uncorrected DFA counterparts, particularly for strongly ionic molecules where significant improvement is seen. Applying FLO-SIC to SCAN does not improve dipole values overall. In addition, we show that removing self-interaction improves the description of the dipole for stretched-bond geometries and recovers the physically correct separated atom limit of zero dipole. Finally, we find that the best agreement between the FLO-SIC-DFA and reference dipoles occurs when the molecular geometries are optimized using the FLO-SIC-DFA.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

In-depth understanding of molecular mechanisms of aldehyde toxicity to engineer robust Saccharomyces cerevisiae

Aldehydes are ubiquitous electrophilic compounds that ferment microorganisms including Saccharomyces cerevisiae encounter during the fermentation processes to produce food, fuels, chemicals, and pharmaceuticals. Aldehydes pose severe toxicity to the growth and metabolism of the S. cerevisiae through a variety of toxic molecular mechanisms, predominantly via damaging macromolecules and hampering the production of targeted compounds. Compounds with aldehyde functional groups are far more toxic to S. cerevisiae than all other functional classes, and toxic potency depends on physicochemical characteristics of aldehydes. The yeast synthetic biology community established a design–build–test–learn framework to develop S. cerevisiae cell factories to valorize the sustainable and renewable biomass, including the lignin-derived substrates. However, thermochemically pretreated biomass-derived substrate streams contain diverse aldehydes (e.g., glycolaldehyde and furfural), and biological conversions routes of lignocellulosic compounds consist of toxic aldehyde intermediates (e.g., formaldehyde and methylglyoxal), and some of the high-value targeted products have aldehyde functional group (e.g., vanillin and benzaldehyde). Numerous studies comprehensively characterized both single and additive effects of aldehyde toxicity via systems biology investigations, and novel molecular approaches have been discovered to overcome the aldehyde toxicity. Based on those novel approaches, researchers successfully developed synthetic yeast cell factories to convert lignocellulosic substrates to valuable products, including aldehyde compounds. Here, we highlight the salient relationship of physicochemical charac- teristics and molecular toxicity of aldehydes, the molecular detoxification and macromolecules protection mechanisms of aldehydes, and the advances of engineering robust S. cerevisiae against complex mixtures of aldehyde inhibitors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

UV background fluctuations and three-point correlations in the large-scale clustering of the Lyman α forest

Using the Lyman α (Lyα) Mass Association Scheme, we make theoretical predictions for the three-dimensional three-point correlation function (3PCF) of the Lyα forest at redshift z = 2.3. We bootstrap results from the (100 h -1 Mpc) 3 Horizon hydrodynamic simulation to a (1 h -1 Gpc) 3 N -body simulation, considering both a uniform ultraviolet background (UVB) and a fluctuating UVB sourced by quasars with a comoving n q ≈ 10 -5 h 3 Mpc -3 placed either in massive haloes or randomly. On scales of 10–30 h -1 Mpc, the flux 3PCF displays hierarchical scaling with the square of the two-point correlation function (2PCF), but with an unusual value of Q ≡ ζ 123 /(ξ 12 ξ 13 + ξ 12 ξ 23 + ξ 13 ξ 23 ) ≈ -4.5 that reflects the low bias of the Lyα forest and the anticorrelation between mass density and transmitted flux. For halo-based quasars and an ionizing photon mean free path of λ = 300 h -1 Mpc comoving, UVB fluctuations moderately depress the 2PCF and 3PCF, with cancelling effects on Q . For λ = 100 or 50 h -1 Mpc, UVB fluctuations substantially boost the 2PCF and 3PCF on large scales, shifting the hierarchical ratio to Q ≈ -3. We scale our simulation results to derive rough estimate of the detectability of the 3PCF in current and future observational data sets for the redshift range z = 2.1–2.6. At r = 10 and 20 h -1 Mpc, we predict a signal-to-noise ratio (SNR) of ~9 and ~7, respectively, for both Baryon Oscillation Spectroscopic Survey (BOSS) and extended BOSS (eBOSS), and ~37 and ~25 for Dark Energy Spectroscopic Instrument (DESI). At r = 40 h -1 Mpc the predicted SNR is lower by a factor of ~3–5. Measuring the flux 3PCF would provide a novel test of the conventional paradigm of the Lyα forest and help separate the contributions of UVB fluctuations and density fluctuations to Lyα forest clustering, thereby solidifying its foundation as a tool of precision cosmology.

Astronomy & Astrophysics↗
DOE OSTI2022

The low-temperature heat capacity and thermodynamic properties of greigite (Fe 3 S 4 )

Heat capacity measurements provide important insights into the energetic, thermodynamic, and magnetic properties of materials. Herein we report the heat capacity of greigite (Fe 3 S 4 ) from 1.8 to 300 K. Greigite is a magnetic spinel mineral and through a ferromagnetic magnon term, C fsw = B fsw T 3/2 , ferrimagnetic ordering is observed in the low-temperature heat capacity. Using a set of theoretical fits of the experimental data, we calculate the thermodynamic functions, including the standard entropy ($Δ_{0}^{T}$S m °). Greigite is important in iron sulfide formation and reaction pathways in environmental, ore-forming, and technological settings and previous work has measured enthalpies $ΔH_{r}°$ of formation and decomposition to neighboring phases. In this work, the stability of greigite relative to the elements is demonstrated with a negative Gibbs energy ($ΔG_{r}°$) of formation and the stability relative to decomposition products of pyrrhotite (FeS 1.092 ) and pyrite (FeS 2 ) is demonstrated with a positive Gibbs energy ($ΔG_{r}°$) of decomposition. Values of the standard thermodynamic functions C p,m °, $Δ_{0}^{T}$S m °, $Δ_{0}^{T}$H m °, and Φ m ° are tabulated.

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

Heat capacity and thermodynamic functions of transition metal ion (Cu 2+ , Fe 2+ , Mn 2+ ) exchanged, partially dehydrated zeolite $\mathrm{A}$ ($\mathrm{LTA}$)

Here we have measured the heat capacity from 1.8 to 300 K of partially dehydrated zeolite A (LTA), fully exchanged with Cu 2+ , Fe 2+ , and Mn 2+ ions. The samples have a broad excess heat capacity contribution centered around 4 K, which we attribute to local electric fields splitting the magnetic moments of the cations. The excess heat capacity is modelled using a sum of several Schottky anomalies. From these models, we conclude that the cations in the Cu 2+ zeolite reside in at least four distinct coordination environments, and that some of the coordination environments in all three zeolites are highly asymmetric. We also report theoretical fits of the heat capacity data, and values of the standard thermodynamic functions C P,m , Δ 0K T S m ° , Δ 0K T H m ° , and Φ m ° at smooth temperatures. The standard molar entropies at 298.15 K are 71.8 J·K -1 ·mol -1 for Cu-zeolite A (Cu 0.22 Al 0.49 Si 0.51 O 2 1.04 H 2 O), 71.1 J·K -1 ·mol -1 for Fe-zeolite A (Na 0.01 Fe 0.23 Al 0.50 Si 0.51 O 2 ∙0.77 H 2 O), and 66.0 J·K -1 ·mol -1 for Mn-zeolite A (Mn 0.26 Al 0.49 Si 0.50 O 2 ∙0.53 H 2 O).

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

Island influences on plant functional traits and trait–trait associations across species‐ and community‐scales

The island rule predicts gigantism or dwarfism in body size of island species relative to their mainland counterparts. However, whether other functional traits shift and whether trait–trait associations on islands differ between species and community levels remains unclear. We measured 13 carbon- and water-related functional traits in 37 shared tree species across 35 eastern Chinese islands and 66 nearby mainland plots. We examined species-level trait value shifts and associations under the island rule and compared trait associations between species and communities. Most size-related, wood-anatomical, and hydraulic traits shifted on islands, with large values decreasing and small values increasing; yet, their associations remained stable, aligning with the global trait spectrum and trait–trait coevolution. This stability, despite trait value shifts, suggests evolutionary integration of functional strategies. By contrast, island community-scale trait associations diverged from shared species-level patterns and sometimes reversed, such as positive relationships between wood density and resource-acquisitive traits. Community-level trait associations were stronger on islands, likely reflecting constrained environmental filtering and migration limitation. These contrasting patterns suggest that dominant species can restructure trait associations at the community level, with implications for ecosystem functioning and carbon storage, thereby advancing understanding of plant trait strategies in island systems.

Archipelagos↗
DOE OSTI2022

The QCD Adler Function and the Muon g − 2 Anomaly from Renormalons

We describe the Adler function in Quantum Chromodynamics using a transseries representation within a resurgent framework. The approach is based on a Borel-Ecalle resummation of the infrared renormalons combined with an effective running for the strong coupling. The new approach is flexible enough to give values in agreement with the current Adler function determinations. We then apply our finding to the muon’s anomalous magnetic moment studying the possibility of saturating, solely in terms of the vacuum polarization function, the current discrepancy between the best Standard Model value for the muon’s anomalous magnetic moment and the experimental value obtained by the most recent muon g−2 collaboration. The latter shows that the Adler function’s new representation can also be consistent with recent lattice determinations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

An Integrated Platform for Wind Plant Operations: From Atmosphere to Electrons to the Grid

Under the Atmosphere to Electrons to Grid project (A2e2g), the National Renewable Energy Laboratory (NREL) is developing an optimization platform for wind plant operations. The platform merges forecasting tools with aerodynamic and economic models in order to identify optimal operating schedules and controller functions that will maximize a wind plant's value streams for energy and other grid services. In this presentation, we will describe functionalities of the platform. We will also discuss the implications the use of the platform might have for understanding and valuing the capabilities of wind resources for power system operations.

A2E2G↗