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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Aerothermodynamic design feasibility of a generic planetary aerocapture/aeromaneuver vehicle

Lifting aerodynamic configurations have been screened and selected for a generic planetary aerocapture/aeromaneuver vehicle where a common configuration will be utilized for missions to any of several planets including Mars, Saturn and Uranus. Hypersonic convective and radiative heat transfer to these vehicles was estimated based on a combination of three-dimensional inviscid and viscous flow field solutions and from engineering correlations developed for the numerous complete convective and radiative heat transfer evaluations in CO2 and H2-He mixtures from the Pioneer Venus and Galileo programs. Thermal protection materials have been selected and sized. It is recommended that the thermal protection system be designed for each specific mission, thus maximizing the deliverable payload. Aerothermodynamic technology needs of this generic aerocapture concept are identified.

Florence, D. E.↗
DOE OSTI2016

Lecture Notes on Criticality Safety Validation Using MCNP & Whisper

Training classes for nuclear criticality safety, MCNP documentation. The need for, and problems surrounding, validation of computer codes and data area considered first. Then some background for MCNP & Whisper is given--best practices for Monte Carlo criticality calculations, neutron spectra, S(α,β) thermal neutron scattering data, nuclear data sensitivities, covariance data, and correlation coefficients. Whisper is computational software designed to assist the nuclear criticality safety analyst with validation studies with the Monte Carlo radiation transport package MCNP. Whisper's methodology (benchmark selection – C k 's, weights; extreme value theory – bias, bias uncertainty; MOS for nuclear data uncertainty – GLLS) and usage are discussed.

42 ENGINEERING↗
DOE OSTI2015

SU-E-J-124: 18F-FDG PET Imaging to Improve RT Treatment Outcome for Locally Advanced Lung Cancer

Purpose: To investigate spatial correlation between high uptake regions of pre- and 10-days-post therapy{sup 1} {sup 8}F-FDG PET in recurrent lung cancer and to evaluate the feasibility of dose escalation boosting only regions with high FDG uptake identified on baseline PET. Methods: Nineteen patients with stages II– IV inoperable lung cancer were selected. Volumes of interest (VOI) on pre-therapy FDG-PET were defined using an isocontour at ≥50% of SUVmax. VOI of pre- and post-therapy PET images were correlated for the extent of overlap. A highly optimized IMRT plan to 60 Gy prescribed to PTV defined on the planning CT was designed using clinical dose constraints for the organs at risk. A boost of 18 Gy was prescribed to the VOI defined on baseline PET. A composite plan of the total 78 Gy was compared with the base 60 Gy plan. Increases in dose to the lungs, spinal cord and heart were evaluated. IMRT boost plan was compared with proton RT and SBRT boost plans. Results: Overlap fraction of baseline PET VOI with the VOI on 10 days-post therapy PET was 0.8 (95% CI: 0.7 – 0.9). Using baseline VOI as a boosting volume, dose could be escalated to 78 Gy for 15 patients without compromising the dose constraints. For 4 patients, the dose limiting factors were V20Gy and Dmean for the total lung, and Dmax for the spinal cord. An increase of the dose to OARs correlated significantly with the relative size of the boost volume. Conclusion: VOI defined on baseline 18F-FDG PET by the SUVmax-≥50% isocontour may be a biological target volume for escalated radiation dose. Dose escalation to this volume may provide improved tumor control without breaching predefined dose constraints for OARs. The best treatment outcome may be achieved with proton RT for large targets and with SBRT for small targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Effect of Mixed-Solvent Environments on the Selectivity of Acid-Catalyzed Dehydration Reactions

The composition of the liquid phase can alter the rates of individual reaction steps and thus alter the selectivity of acid-catalyzed reactions, but these solvent effects are difficult to anticipate for design purposes. Herein, we report the kinetics and selectivity of Brønsted acid-catalyzed 1,2-propanediol dehydration in pure water and in aqueous mixtures of the polar aprotic cosolvents γ-valerolactone, 1,4-dioxane, tetrahydrofuran, N-methyl-2-pyrrolidone, tetramethylene sulfoxide, and dimethyl sulfoxide at 433 K. We find that the major product of 1,2-propanediol dehydration is propanal in most mixed-solvent environments with selectivities between 1 and 68 mol %. In contrast, 1,2-propanediol dehydration in aqueous mixtures of dimethyl sulfoxide affords acetone as the major product with up to 48% selectivity with minimal propanal formation. We use classical molecular dynamics simulations to probe these solvent effects by computing the difference between the solvation free energies of 1,2-propanediol and propanal in aqueous mixtures of polar aprotic cosolvents and in pure water. We find that the difference in the solvation free energies is correlated with the rates of propanal formation in all mixed-solvent environments, indicating that the solvent-mediated stabilization of the product state relative to the reactant state translates to increased selectivity toward the same product. Similar agreement between simulated solvation free energies and experimental reaction rates/selectivities is established for the acid-catalyzed dehydration of cis- and trans-1,2-cyclohexanediol and 1,3-cyclohexanediol. Finally, analysis of the solvation environment around 1,2-propanediol shows that dimethyl sulfoxide uniquely competes against water to solvate reactive hydroxyl groups, which causes a change in reaction mechanism in this solvent system that leads to the formation of acetone rather than propanal. Here, these results represent a step toward the computationally efficient screening of solvent systems for acid-catalyzed, liquid-phase processes.

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

Estimating carrying capacity for juvenile salmon using quantile random forest models

Abstract Establishing robust methods and metrics to evaluate habitat quality is critical for the recovery of endangered Pacific salmonids ( Oncorhynchus spp.). A variety of modeling approaches are used for status and trend monitoring of anadromous species throughout the Pacific Northwest, USA, but current methods may fail to capture the complex relationship between fish and habitat and are often limited in predictive power beyond specific watersheds. Further, the focus on species distribution and abundance is not easily manipulated to predict carrying capacity and traditional stock‐recruitment analyses are reliant on long‐term data which are not always available. In this study, we developed a quantile random forest model to provide estimates of habitat carrying capacity for Chinook salmon ( O. tshawytscha ) parr during the summer months, at both the site and watershed scale. Quantile random forest models allow for the consideration of noisy data, correlated variables, and non‐linear relationships: common features in fish–habitat datasets. We leveraged Columbia Habitat Monitoring Program data to select habitat co‐variates and predict capacity at those sites. We also identified a set of globally available attributes to extrapolate capacity estimate predictions throughout wadeable streams within the Columbia River basin. Total capacity estimates for watersheds closely matched estimates from alternative fish productivity models. Carrying capacity estimates based on quantile random forest models, like those presented here, provide managers a framework to guide the identification, prioritization, and development of habitat rehabilitation actions to recover salmon populations.

See, Kevin E.↗
DOE OSTI2018

High‐fidelity detection of crop biomass quantitative trait loci from low‐cost imaging in the field

Abstract Field‐based, rapid, and nondestructive techniques for assessing plant productivity are needed to accelerate the discovery of genotype‐to‐phenotype relationships in next‐generation biomass grass crops. The use of hemispherical imaging and light attenuation modeling was evaluated against destructive harvest measures with respect to their ability to accurately capture phenotypic and genotypic relationships in a field‐grown grass crop. Plant area index ( PAI ) estimated from below‐canopy hemispherical images, as well as a suite of thirteen traits assessed by manual destructive harvests, were measured in a Setaria recombinant inbred line mapping population segregating for aboveground productivity and architecture. A significant correlation was observed between PAI and biomass production across the population at maturity ( r 2 = .60), as well as for select diverse genotypes sampled repeatedly over the growing season ( r 2 = .79). Twenty‐seven quantitative trait loci ( QTL ) were detected for manually collected traits associated with biomass production. Of these, twenty‐one were found in four clusters of colocalized QTL . Analysis of image‐based estimates of PAI successfully identified all four QTL hot spots for biomass production. QTL for PAI had greater overlap with those detected for traits associated with biomass production than with those for plant architecture and biomass partitioning. Hemispherical imaging is an affordable and scalable method, which demonstrates how high‐throughput phenotyping can identify QTL related to biomass production of field trials in place of destructive harvests that are labor, time, and material intensive.

09 BIOMASS FUELS↗
DOE OSTI2020

A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.

42 ENGINEERING↗
DOE OSTI2018

Microstructure, precipitates and hardness of selectively laser melted AlSi10Mg alloy before and after heat treatment

Highlights: • Microstructural characterization of SLM AlSi10Mg alloy and comparison with cast and powder AlSi10Mg • Effect of solution heat treatment and aging on the hardness change of SLM AlSi10Mg alloy • Evolution of strengthening precipitates and Fe-rich intermetallics in SLM AlSi10Mg during heat treatment - Abstract: The microstructure and precipitates within selectively laser melted (SLM) AlSi10Mg alloys in the as-built state and after T6 heat treatment were examined and correlated to the hardness evolution. The as-built alloy exhibited columnar patterns perpendicular to the build-direction and fish-scale pattern along the build-direction originating from the melt pool. The microstructure consisted of fine Al cells and eutectic structure with up to 4 μm in size. Tiny needle-like Si particles with highly faulted structure were identified within the Al cells and formed semi-coherent interface with the matrix. Nanoscale Si particles and π-Al{sub 8}Si{sub 6}Mg{sub 3}Fe phase were observed to segregate along the cell and grain boundary. Solution heat treatment (SHT) at 520 °C resulted in the dissolution of Al cellular microstructure. Precipitation and coarsening of the Si particles occurred, while the aspect ratio of Si particles remained nearly constant. The π-Al{sub 8}Si{sub 6}Mg{sub 3}Fe phase decomposed into plate-shaped β-Al{sub 5}SiFe. The artificial aging (AA) at 160 °C did not alter the microstructure but led to the formation of metastable Mg{sub 2}Si precipitates. The GP zones and β″ were identified through transmission electron microscopy after AA of 6 h, and β″ existed up to AA of 24 h. The hardness decreased after SHT due to the coarsening of the microstructure and reduced solid solution hardening. Hardness reached maximum magnitude after AA of 6–10 h due to the precipitation hardening, and remained relatively unchanged up to AA of 24 h. Microstructure and/or hardness of gas atomized powders and bulk cast AlSi10Mg alloys were also examined as references.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Analysis of the transport properties of thermally rearranged (TR) polymers and polymers of intrinsic microporosity (PIM) relative to upper bound performance

A critical analysis comparing the diffusion selectivity, solubility selectivity, diffusivity, and solubility coefficients of thermally rearranged (TR) polymers and polymers of intrinsic microporosity (PIM), two types of polymers which consistently perform at or beyond the polymer upper bound for certain gas pairs (O 2 /N 2 and CO 2 /CH 4 ), is reported in this paper. Although most polymers in these two classes exhibit transport properties in the range of typical glassy polymers, several variants offer exceptional performance. The diffusivity selectivity for O 2 /N 2 and CO 2 /CH 4 for TR polymers and PIM lies outside the range of the glassy polymer database. The solubility coefficients for O 2 are at the upper end of the range of both TR and PIM polymers, as is also the case for CO 2 solubility coefficients for PIM polymers. The O 2 /N 2 and CO 2 /CH 4 solubility selectivities for both PIM and TR polymers are in the range of typical glassy polymers. Thus, unique separation values for these polymers are a manifestation of maximizing diffusivity selectivity combined with very high gas solubility. Additionally, the previously determined diffusion gas kinetic diameters, d g , were found to correlate best with diffusion coefficients of PIM and TR polymers and serve to better analyze transport properties of upper bound materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

DNA Templated Metal Nanoclusters: From Emergent Properties to Unique Applications

Metal nanoclusters containing a few to several hundred atoms with sizes ranging from sub-nanometer to ~2 nm occupy an intermediate size regime that bridges larger plasmonic nanoparticles and smaller metal complexes. With strong quantum confinement, metal nanoclusters exhibit molecule-like properties. This paper focuses on noble metal nanoclusters that are synthesized within a single stranded DNA template. Compared to other ligand protected metal nanoclusters, DNA-templated metal nanoclusters manifest intriguing physical and chemical properties that are heavily influenced by the design of DNA templates. For example, DNA-templated silver nanoclusters can show bright fluorescence, tunable emission colors, and enhanced stability by tuning the sequence of the encapsulating DNA template. DNA-templated gold nanoclusters can also serve as excellent cocatalysts, which are integratable with other biocatalysts such as enzymes. In this Account, DNA-templated silver and gold nanoclusters are selected as paradigm systems to showcase their emergent properties and unique applications. We first discuss the DNA-templated silver nanoclusters with a focus on the creation of a complementary palette of emission colors, which has potential applications for multiplex assays. The importance of the DNA template toward enhanced stability of silver nanoclusters is also demonstrated. We then introduce a special class of activable fluorescence probes that are based on the fluorescence turn-on phenomena of DNA-templated silver nanoclusters, which are named nanocluster beacons (NCBs). NCBs have distinct advantages over molecular beacons for nucleic acid detection, and their emission mechanisms are also discussed in detail. We then discuss a universal method of creating novel DNA–silver nanocluster aptamers for protein detection with high specificity. The remainder of the Account is devoted to the DNA-templated gold nanoclusters. We demonstrate that DNA–gold nanoclusters can serve as enhancers for enzymatic reduction of oxygen, which is one of the most important reactions in biofuel cells. Although DNA-templated metal nanoclusters are still in their infancy, we anticipate they will emerge as a new type of functional nanomaterial with wide applications in biology and energy science. Future research will focus on the synthesis of size selected DNA–metal nanoclusters with atomic monodispersity, structural determination of different sized DNA–metal nanoclusters, and establishment of structure–property correlations. Some long-standing mysteries, such as the origin of fluorescence and mechanism for emission color tunability, constitute the central questions regarding the photophysical properties of DNA–metal nanoclusters. On the application side, more studies are required to understand the interaction between nanocluster and biological systems. In the foreseeable future, one can expect that new biosensors, catalysts, and functional devices will be invented based on the intriguing properties of well-designed DNA–metal nanoclusters and their composites. Altogether, DNA–metal nanoclusters can add additional spotlights into the highly vibrant field of ligand protected, quantum sized metal nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Revisiting Competing Paths in Electrochemical CO 2 Reduction on Copper via Embedded Correlated Wavefunction Theory

We re-evaluate two key steps in the mechanism of CO 2 reduction on copper at a higher level of theory capable of correcting inherent errors in density functional theory (DFT) approximations, namely, embedded correlated wavefunction (ECW) theory. Here, we consider the CO reduction step on Cu(111), which is critical to understanding reaction selectivity. Here, we optimize embedding potentials at the periodic plane-wave DFT level using density functional embedding theory (DFET). All possible adsorption sites (adsites) for each adsorbate then are screened with ECW theory at the catalytically active site to refine the local electronic structure. Unsurprisingly, DFT and ECW theory predict different adsite preferences, largely because of DFT’s inability to properly situate the CO 2π* level. Differing preferred adsites suggest that different reaction pathways could emerge from DFT versus ECW theory. Starting from these preferred ECW theory adsites, we then obtain reaction pathways at the plane-wave DFT level using the climbing-image nudged elastic band method to determine minimum energy paths. Thereafter, we perform ECW calculations at the catalytically active site to correct the energetics at each interpolated structure (image) along the reaction pathways. Via this approach, we confirm that the first step in CO reduction via hydrogen transfer on Cu(111) is to form hydroxymethylidyne (*COH) instead of formyl (*CHO). Although the prediction to preferentially form *COH is consistent with that of DFT, the two theories predict quite different structural and mechanistic behaviors, suggesting that verification is needed for other parts of the mechanism of CO 2 reduction, which is the subject of ongoing work.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Bichromatic moiré superlattices for tunable quadrupolar trions and correlated states

Moiré superlattices in transition metal dichalcogenide heterostructures provide a platform to engineer many-body interactions. Here, we realize a bichromatic moiré superlattice in an asymmetric WSe2/WS2/WSe2 heterotrilayer by combining R- and H-stacked bilayers with mismatched moiré wavelengths. This structure hosts fermionic quadrupolar moiré trions—interlayer excitons bound to an opposite-layer hole—with vanishing dipole moments. These trions arise from hybridized moiré potentials enabling multiple excitonic orbitals with tunable interlayer coupling, allowing control of excitonic and electronic ground states. We show that an out-of-plane electric field could effectively reshape moiré excitons and interlayer-intralayer electron correlations, driving a transition from interlayer to intralayer Mott states with enhanced Coulomb repulsion. The asymmetric stacking further enriches excitonic selection rules, broadening opportunities for spin-photon engineering. Our results demonstrate bichromatic moiré superlattices as a reconfigurable platform for emergent quantum states, where quadrupolar moiré trion emission may enable coherent and entangled quantum light manipulation.

Chen, Mingfeng [Washington University in St. Louis↗
DOE OSTI2025

Multireference diffusion Monte Carlo reaches 2D materials

Abstract Quantum confinement in 2D materials strongly enhances electronic correlation effects. Therefore, predicting the properties of these unique materials, with both a high level of accuracy and computational efficiency, without relying on adjustable parameters or functionals, remains an outstanding theoretical challenge. The majority of theoretical studies are based on the approximations of density functional theory (DFT). The reliability of DFT predictions are heavily dependent on the choice of an approximated exchange-correlation functional. Here, we estimate the magnitude of impact of correlation on the total energy for the quintessential 2D material, graphene, by performing and comparing state-of-the-art selected CI and quantum Monte Carlo extrapolated calculations for a single unit cell at the$$\Gamma$$point. We demonstrate that Self-Healing Diffusion Monte Carlo (SHDMC) obtains a very compact, but high-quality wavefunction for this system that lacks the strong basis set dependence displayed by state of the art quantum chemistry methods. The SHDMC wavefunction is of higher quality compared to that obtained from sCI, in the same orbital basis, while being$$\sim$$ 1000 times smaller in terms of determinant count compared to sCI. We also demonstrate that extrapolating SHDMC results to the infinite determinant limit compares extremely well with complete basis set extrapolated sCI. Our work paves the way for future validation of SHDMC applied to challenging 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2016

Clustering properties of g -selected galaxies at z ~ 0.8

In current and future large redshift surveys, as the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) or the Dark Energy Spectroscopic Instrument (DESI), we will use emission-line galaxies (ELGs) to probe cosmological models by mapping the large-scale structure of the Universe in the redshift range 0.6 < z < 1.7. We explore the halo-galaxy connection, with current data and by measuring three clustering properties of g-selected ELGs as matter tracers in the redshift range 0.6 < z < 1: (i) the redshift-space two-point correlation function using spectroscopic redshifts from the BOSS ELG sample and VIPERS; (ii) the angular two-point correlation function on the footprint of the CFHT-LS; (iii) the galaxy-galaxy lensing signal around the ELGs using the CFHTLenS. Furthermore, we interpret these observations by mapping them on to the latest high-resolution MultiDark Planck N-body simulation, using a novel (Sub)Halo-Abundance Matching technique that accounts for the ELG incompleteness. ELGs at z ~ 0.8 live in haloes of (1 ± 0.5) × 10 12 h -1 M⊙ and 22.5 ± 2.5 per cent of them are satellites belonging to a larger halo. The halo occupation distribution of ELGs indicates that we are sampling the galaxies in which stars form in the most efficient way, according to their stellar-to-halo mass ratio.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Rehabilitation of the Perdew-Burke-Ernzerhof generalized gradient approximation for layered materials

The structural and energetic properties of layered materials present a challenge to density functional theory with common semilocal approximations to the exchange-correlation energy. By combining the most widely used semilocal generalized gradient approximation (GGA), the Perdew-Burke-Ernzerhof (PBE) one, with the revised Vydrov–van Voorhis nonlocal correlation functional (rVV10), both excellent structural and energetic properties of 28 layered materials have been recovered with a judicious parameter selection. We term the resulting functional PBE+rVV10L, with the “L” indicating that it is for layered materials. Such a combination is not new, and only involves refitting a single global parameter. However, the resulting high accuracy suggests such a dispersion-corrected PBE for many aspects of theoretical studies on layered materials. For comparison, we also present the results for PBE+rVV10 where the parameter is determined by 22 interaction energies between molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2019

On the Design of Sinuous Antennas for UWB Radar Applications

We present that sinuous antennas are capable of producing ultra-wideband radiation with polarization diversity. This capability makes the sinuous antenna an attractive candidate for UWB polarimetric radar applications. Additionally, the ability of the sinuous antenna to be implemented as a planar structure makes it a good fit for close in sensing applications such as ground penetrating radar. However, recent literature has shown the sinuous antenna to suffer from resonances which degrade performance. Such resonances produce late time ringing which is particularly troubling for pulsed close in sensing applications. The resonances occur in two forms: log-periodic resonances on the arms, and a resonance due to the sharp ends left by the outer truncation. A detailed investigation as to the correlation between the log-periodic resonances and the sinuous antenna design parameters indicates the resonances may be mitigated by selecting appropriate design parameters. Additionally, a novel truncation method is proposed to remove the sharp end resonance. Both simulation and measured results are provided to support the developed sinuous antenna design guidance.

42 ENGINEERING↗
DOE OSTI2022

Perspectives on UV and x-ray photoelectron spectroscopy

Atomic photoionization using electron spectroscopy was one of the scientific topics in which Professor David A. Shirley excelled and established a research legacy. We discuss selected highlights of atomic photoionization research done by the Shirley group beginning in the 1970s. Our main topics are electron correlation satellites, photoelectron angular distributions with tunable synchrotron radiation, and developments of theory. We also discuss examples of more recent research that extends the earlier work, including double K-shell photoionization, nondipole interactions, and the pervasive role of interchannel coupling. Furthermore, we conclude with examples of current experimental and theoretical research.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton–proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV. Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb –1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗