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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
DOE OSTI2025

Ultrahigh-pressure crystallographic passage towards metallic hydrogen

The structural evolution of molecular hydrogen H 2 under multi-megabar compression and its relation to atomic metallic hydrogen is a key unsolved problem in condensed-matter physics. Although dozens of crystal structures have been proposed by theory, only one, the simple hexagonal-close-packed (hcp) structure of only spherical disordered H 2 , has been previously confirmed in experiments. Through advancing nano-focused synchrotron X-ray probes, here we report the observation of the transition from hcp H 2 to a post-hcp structure with a six-fold larger supercell at pressures above 212 GPa, indicating the change of spherical H 2 to various ordered configurations. Theoretical calculations based on our XRD results found a time-averaged structure model in the space group $P\bar{6}2c$ with alternating layers of spherically disordered H 2 and new graphene-like layers consisting of H 2 trimers (H 6 ) formed by the association of three H 2 molecules. Here, this supercell has not been reported by any previous theoretical study for the post-hcp phase, but is close to a number of theoretical models with mixed-layer structures. The evidence of a structural transition beyond hcp establishes the trend of H 2 molecular association towards polymerization at extreme pressures, giving clues about the nature of the molecular-to-atomic transition of metallic hydrogen. Considering the spectroscopic behaviours that show strong vibrational and bending peaks of H 2 up to 400 GPa, it would be prudent to speculate the continuation of hydrogen molecular polymerization up to its metallization.

Ji, Cheng [Center for High Pressure Science and Te↗
DOE OSTI2013

Climate change effects on agriculture: Economic responses to biophysical shocks

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

climate change adaptation model intercomparison in↗
DOE OSTI2019

Constraining spectroscopic factors near the r -process path using combined measurements: Kr 86 ( d , p ) 87 Kr

Background: Current nuclear structure models indicate that the shell structure near the valley of stability, with well-established shell closures at N=50, for example, changes in very neutron-rich nuclei far from stability. Single-particle properties of nuclei away from stability can be probed in single-neutron (d,p) transfer reactions with beams of rare isotopes. The interpretation of these data requires reaction theories with various effective interactions. Often, approximations made to the final bound-state potential introduce a large uncertainty in the extracted single-particle properties, in particular the spectroscopic factor. Purpose: Mitigate this uncertainty using a combined measurement method to constrain the shape of the bound-state potential and to reliably extract the spectroscopic factor. Methods: The 2 H( 86 Kr,p) 87 Kr reaction was measured at 33 MeV/u at the National Superconducting Cyclotron Laboratory (NSCL) as a test of the combined method. The reaction protons were detected with the Oak Ridge Rutgers University Barrel Array (ORRUBA) of position sensitive silicon strip detectors, the first implementation of ORRUBA coupled to the S800 spectrograph with fast beams at NSCL. Results: These measurements at 33 MeV/u are combined with previous studies of the 86 Kr(d,p) reaction at 5.5 MeV/u to demonstrate a successful case of the combined method to constrain the shape of the single-particle potential and deduce asymptotic normalization coefficients and spectroscopic factors. In particular, the single-particle asymptotic normalization coefficient for the ground state of 87 Kr was constrained to b d5/2 =6.46$^{+1.12}_{–0.57}$ fm –1/2 , and therefore the deduced spectroscopic factor is S=0.44$^{+0.09}_{–0.13}$ with uncertainties dominated by experimental statistics. Conclusions: By combining measurements at two very different beam energies, single-particle asymptotic normalization coefficients, at least for low angular momentum transfers, can be constrained. Thus, spectroscopic factors can be deduced with uncertainties dominated by experimental uncertainties, rather than limited knowledge of bound-state potential parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop–vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that, cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 g CO 2 eq l –1 ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus , however, emits only 21–36 g CO 2 eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. Furthermore, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop–specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles

Extreme temperature events can have considerable negative impacts on sectors such as health, agriculture, and transportation. Observational evidence indicates the severity and frequency of warm extremes are increasing over much of the United States, but there are sizeable challenges both in estimating extreme temperature changes and in quantifying the relevant associated uncertainties. This study provides a simple statistical framework using a block maxima approach to analyze the representation of warm temperature extremes in several recent global climate model ensembles. Uncertainties due to structural model differences, grid resolution, and internal variability are characterized and discussed. Results show that models and ensembles differ greatly in the representation of extreme temperature over the United States, and variability in tail events is dependent on time and anthropogenic warming, which can influence estimates of return periods and distribution parameter estimates using generalized extreme value (GEV) distributions. These effects can considerably influence the uncertainty of model hindcasts and projections of extremes. Several idealized regional applications are highlighted for evaluating ensemble skill and trends, based on quantile analysis and root-mean-square errors in the overall sample and the upper tail. The results are relevant to regional climate assessments that use global model outputs and that are sensitive to extreme warm temperature. Accompanying this manuscript is a simple toolkit using the R statistical programming language for characterizing extreme events in gridded datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Network Scale Travel Time Prediction using Deep Learning

In recent years, deep learning models have been receiving increased attention within the artificial intelligence (AI) community because of their high prediction accuracy. In this paper, two deep learning models, long short-term memory (LSTM) and convolutional neural network (CNN), are proposed to predict travel time in a road network. One major advantage of using deep learning for travel time prediction is that it can make accurate predictions for all the segments in the transportation network with a single model structure, instead of building customized models for each segment separately. The proposed models were evaluated on a transportation network in the City of Saint Louis, Missouri. The prediction results show that deep learning can provide accurate prediction for both congested and uncongested traffic conditions, and can successfully capture the traffic dynamics of unexpected incidents or special events. The study findings show that deep learning offers a promising approach to real-time prediction of travel times on a network scale.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Dark matter halo mass functions and density profiles from mass and energy cascade

Abstract Halo abundance and structure play a central role for modeling structure formation and evolution. Without relying on a spherical or ellipsoidal collapse model, we analytically derive the halo mass function and cuspy halo density (inner slope of −4/3) based on the mass and energy cascade theory in dark matter flow. The hierarchical halo structure formation leads to halo or particle random walk with a position-dependent waiting time $$\tau _g$$ τ g . First, the inverse mass cascade from small to large scales leads to the halo random walk in mass space with $$\tau _g\propto m_h^{-\lambda }$$ τ g ∝ m h - λ , where $$m_h$$ m h is the halo mass and $$\lambda$$ λ is a halo geometry parameter with predicted value of 2/3. The corresponding Fokker-Planck solution for halo random walk in mass space gives rise to the halo mass function with a power-law behavior on small scale and exponential decay on large scale. This can be further improved by considering two different $$\lambda$$ λ for haloes below and above a critical mass scale $$m_h^*$$ m h ∗ , i.e. a double- $$\lambda$$ λ halo mass function. Second, a double- $$\gamma$$ γ density profile can be derived based on the particle random walk in 3D space with a position-dependent waiting time $$\tau _g \propto \Phi (r)^{-1} \propto r^{-\gamma }$$ τ g ∝ Φ ( r ) - 1 ∝ r - γ , where $$\Phi$$ Φ is the gravitational potential and r is the particle distance to halo center. Theory predicts $$\gamma =2/3$$ γ = 2 / 3 that leads to a cuspy density profile with an inner slope of −4/3, consistent with the predicted scaling laws from energy cascade. The Press-Schechter mass function and Einasto density profile are just special cases of proposed models. The small scale permanence can be identified due to the scale-independent rate of mass and energy cascade, where density profiles of different halo masses and redshifts converge to the $$-4/3$$ - 4 / 3 scaling law ( $$\rho _h \propto r^{-4/3}$$ ρ h ∝ r - 4 / 3 ) on small scales. Theory predicts the halo number density scales with halo mass as $$\propto m_h^{-1.9}$$ ∝ m h - 1.9 , while the halo mass density scales as $$\propto m_h^{4/9}$$ ∝ m h 4 / 9 . Results were compared against the Illustris simulations. This new perspective provides a theory for nearly universal halo mass functions and density profiles.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

The verification and uncertainty quantification of surrogate models used for structural analysis

High fidelity modeling of complex systems can require large finite element models to capture the physics of interest. Typically these high-order models take an excessively long time to run. For important studies such as model validation and uncertainty quantification, where probabilistic measures of the response are required, a large number of simulations of the high fidelity model with different parameters are necessary. In addition, some environments, such as an extensive random vibration excitation, require a long simulation time to capture the entire event. A process that produces a highly efficient model from the original high order model is necessary to enable these analyses. These highly efficient models are referred to as surrogate models, for their purpose is to represent the main physics that is of importance, but decrease the computational burden. A critical aspect of any surrogate model is how faithfully the efficient model represents the original high-order model. This paper describes the process for verifying a surrogate model using response quantities of interest and quantifying the introduced uncertainties in the use of the surrogate model. This is done to help any analyst if they use any surrogate model; such has, Craig-Bampton Reduc tions, POD, etc.

Ross, Michael↗
DOE OSTI2020

What are the current limits on determination of protonation state using neutron macromolecular crystallography?

The rate of deposition of models determined by neutron diffraction, or a hybrid approach that combines X-ray and neutron diffraction, has increased in recent years. The benefit of neutron diffraction is that hydrogen atom (H) positions are detectable, allowing for the determination of protonation state and water molecule orientation. This study analyses all neutron models deposited in the Protein Data Bank to date, focusing on protonation state and properties of H (or deuterium, D) atoms as well as the details of water molecules. In particular, clashes and hydrogen bonds involving H or D atoms are investigated. As water molecules are typically the least reproducible part of a structural model, their positions in neutron models were compared to those in homologous high-resolution X-ray structures. For models determined by joint refinement against X-ray and neutron data, the water structure comparison was also carried out for models re-refined against the X-ray data alone. The homologues have generally fewer conserved water molecules where X-ray only was used and the positions of equivalent waters vary more than in the case of the hybrid X-ray model. As neutron diffraction data are generally less complete than X-ray data, the influence of neutron data completeness on nuclear density maps was also analyzed. Here, we observe and discuss systematic map quality deterioration as result of data incompleteness.

Hydrogen bond↗
DOE OSTI2014

Weak data do not make a free lunch, only a cheap meal

Refinement and analysis of four structures with various data resolution cutoffs suggests that at present there are no reliable criteria for judging the diffraction data resolution limit and the condition I/σ(I) = 2.0 is reasonable. However, extending the limit by about 0.2 Å beyond the resolution defined by this threshold does not deteriorate the quality of refined structures and in some cases may be beneficial. Four data sets were processed at resolutions significantly exceeding the criteria traditionally used for estimating the diffraction data resolution limit. The analysis of these data and the corresponding model-quality indicators suggests that the criteria of resolution limits widely adopted in the past may be somewhat conservative. Various parameters, such as R{sub merge} and I/σ(I), optical resolution and the correlation coefficients CC{sub 1/2} and CC*, can be used for judging the internal data quality, whereas the reliability factors R and R{sub free} as well as the maximum-likelihood target values and real-space map correlation coefficients can be used to estimate the agreement between the data and the refined model. However, none of these criteria provide a reliable estimate of the data resolution cutoff limit. The analysis suggests that extension of the maximum resolution by about 0.2 Å beyond the currently adopted limit where the I/σ(I) value drops to 2.0 does not degrade the quality of the refined structural models, but may sometimes be advantageous. Such an extension may be particularly beneficial for significantly anisotropic diffraction. Extension of the maximum resolution at the stage of data collection and structure refinement is cheap in terms of the required effort and is definitely more advisable than accepting a too conservative resolution cutoff, which is unfortunately quite frequent among the crystal structures deposited in the Protein Data Bank.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

Atomistic simulation and ab initio study of the defect structure of spinel-related Li{sub 0.5−0.5x}Mg{sub x}Fe{sub 2.5−0.5x}O{sub 4}

Graphical abstract: Unit cell of Li0{sub 5−0.5x}Mg{sub x}Fe{sub 2.5−0.5x}O{sub 4}, showing the lowest energy structure obtained using interatomic potential and DFT ab initio calculations. Large white spheres O{sup 2−}; small light grey spheres Mg{sup 2+} (evenly substituting of Li{sup +} and Fe{sup 3+} at octahedral sites); small dark grey spheres Fe{sup 3+}; small black spheres Li{sup +}. Display Omitted Highlights: ► Defect structure of Li{sub 0.5−0.5x}Mg{sub x}Fe{sub 2.5−x}O{sub 4} is studied with atomistic and DFT methods. ► 19 possible defect structure models with ∼60 defect configurations are investigated. ► The most favourable model found is when Mg{sup 2+} ions evenly replace Li{sup +} and octahedral Fe{sup 3+}. ► This defect structure decreases the magnetisation relative to that of Li{sub 0.5}Fe{sub 2.5}O{sub 4}. ► Experimentally-deduced models, at variance with the one obtained here, are discussed. -- Abstract: The position of magnesium ions in Mg{sup 2+}-doped lithium ferrite of the composition Li{sub 0.5−0.5x}Mg{sub x}Fe{sub 2.5−0.5x}O{sub 4}, which has been a matter of uncertainty among some experimentalists, is investigated using interatomic potential and ab initio DFT calculations. Among possible 19 defect structure models, some of which have been reported experimentally to be the most favorable, the lowest energy is found for Mg{sup 2+} ions evenly replacing Li{sup +} and Fe{sup 3+} ion on octahedral sites. This gives a decrease in magnetisation for the Mg{sup 2+}-doped ferrite relative to the un-doped lithium ferrite. The results suggest that some experimental observations of increased magnetisation of spinel lithium ferrite on Mg{sup 2+}-doping could be due to substitution of Mg{sup 2+} or Li{sup +} on tetrahedral sites at the high temperatures used in preparation of the solid and/or the presence of undetected defects in the initial precursors.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The crystal structure of a new calcium aluminate phase containing formate

A new calcium aluminate phase containing formate ions was synthesized and its crystal structure determined. This new phase is indicated as M-phase and was firstly observed in Portland cement pastes hydrated in presence of Ca-formate and in excess of water. The crystal structure of the M-phase was successfully solved in the R-3 space group of the trigonal system on the basis of synchrotron X-ray single crystal diffraction data. The structural model was confirmed by Rietveld refinement of the powder diffraction data acquired on the synthesized pure sample. The crystal structure of the M-phase is similar to that of ettringite, being characterized by columns of AlO{sub 6} octahedra alternating with groups of three edge-sharing CaO{sub 7} polyhedra. The formate ions (HCOO){sup −} share two oxygens with Ca polyhedra and are located in the interspace between the columns. The crystal structure of the M-phase testifies the strong interaction occurring between small organic molecules as formate and the calcium aluminate components of Portland cement.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Dynamic order reduction of thin-film deposition kinetics models: A reaction factorization approach

A set of numerical tools for the analysis and dynamic dimension reduction of chemical vapor and atomic layer deposition (ALD) surface reaction models is developed in this work. The approach is based on a two-step process where in the first, the chemical species surface balance dynamic equations are factored to effectively decouple the (nonlinear) reaction rates, a process that eliminates redundant dynamic modes and that identifies conserved quantities. If successful, the second phase is implemented to factor out redundant dynamic modes when species relatively minor in concentration are omitted; if unsuccessful, the technique points to potential model structural problems. An alumina ALD process is used for an example consisting of 19 reactions and 23 surface and gas-phase species. Using the approach developed, the model is reduced by nineteen modes to a four-dimensional dynamic system without any knowledge of the reaction rate values. Results are interpreted in the context of potential model validation studies.

42 ENGINEERING↗
DOE OSTI2014

Identification of a Novel Drug Lead That Inhibits HCV Infection and Cell-to-Cell Transmission by Targeting the HCV E2 Glycoprotein

We report that Hepatitis C Virus (HCV) infects 200 million individuals worldwide. Although several FDA approved drugs targeting the HCV serine protease and polymerase have shown promising results, there is a need for better drugs that are effective in treating a broader range of HCV genotypes and subtypes without being used in combination with interferon and/or ribavirin. Recently, two crystal structures of the core of the HCV E2 protein (E2c) have been determined, providing structural information that can now be used to target the E2 protein and develop drugs that disrupt the early stages of HCV infection by blocking E2’s interaction with different host factors. Using the E2c structure as a template, we have created a structural model of the E2 protein core (residues 421–645) that contains the three amino acid segments that are not present in either structure. Computational docking of a diverse library of 1,715 small molecules to this model led to the identification of a set of 34 ligands predicted to bind near conserved amino acid residues involved in the HCV E2: CD81 interaction. We used surface plasmon resonance detection to screen the ligand set for binding to recombinant E2 protein, and the best binders were subsequently tested to identify compounds that inhibit the infection of Huh-7 cells by HCV. One compound, 281816, blocked E2 binding to CD81 and inhibited HCV infection in a genotype-independent manner with IC50’s ranging from 2.2 µM to 4.6 µM. 281816 blocked the early and late steps of cell-free HCV entry and also abrogated the cell-to-cell transmission of HCV. Collectively the results obtained with this new structural model of E2c suggest the development of small molecule inhibitors such as 281816 that target E2 and disrupt its interaction with CD81 may provide a new paradigm for HCV treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Generalized thick strip modelling for vortex-induced vibration of long flexible cylinders

We propose a generalized strip modelling method that is computationally efficient for the VIV prediction of long flexible cylinders in three-dimensional incompressible flow. In order to overcome the shortcomings of conventional strip-theory-based 2D models, the fluid domain is divided into “thick” strips, which are sufficiently thick to locally resolve the small scale turbulence effects and three dimensionality of the flow around the cylinder. An attractive feature of the model is that we independently construct a three-dimensional scale resolving model for individual strips, which have local spanwise scale along the cylinder's axial direction and are only coupled through the structural model of the cylinder. Therefore, this approach is able to cover the full spectrum for fully resolved 3D modelling to 2D strip theory. The connection between these strips is achieved through the calculation of a tensioned beam equation, which is used to represent the dynamics of the flexible body. In the limit, however, a single “thick” strip would fill the full 3D domain. A parallel Fourier spectral/hp element method is employed to solve the 3D flow dynamics in the strip-domain, and then the VIV response prediction is achieved through the strip–structure interactions. Numerical tests on both laminar and turbulent flows as well as the comparison against the fully resolved DNS are presented to demonstrate the applicability of this approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

First-principle investigation of Jahn-Teller distortion and topological analysis of chemical bonds in LiNiO{sub 2}

First-principle GGA+U calculations were performed on the undistorted rhombohedral R3-bar m model, the collinear Jahn-Teller distorted monoclinic C2/m model, and six non-collinear Jahn-Teller distortion ordering models of LiNiO{sub 2}. The zigzag and C2/m models are found to be the most stable and the next most stable structural models, respectively. An energy gap appears for the C2/m and zigzag structures, whereas no energy gap appears for the R3-bar m structure. Topological analyses were performed on the R3-bar m, C2/m and zigzag models using the atoms-in-molecules theory and the electron localization function. The results show that the Ni-O interaction is the transit closed-shell interaction, in which the net electron transfer occurs from the Ni ion to the ligand O ions. The Ni-O bond possesses the {sigma} dative bond character and is polarized toward the O ions. In the distorted structures, the bonding electrons around the oxygen atom are strongly polarized toward the long Ni-O bond. - Graphical abstract: Isosurfaces of the difference charge density and the electron localization function for the zigzag structure of LiNiO{sub 2}. Highlights: > Using ELF and AIM, topological analyses were carried out on different structures. > The zigzag Jahn-Teller distortion ordering is the most stable structure. > Semiconductor gap emerges in the C2/m and zigzag structures. > The Ni-O bonds are dative bonds. > In the distorted structures, bond electrons accumulate in the long Ni-O bond basins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Beta decay rates of neutron-rich nuclei

Heavy element nucleosynthesis models involve various properties of thousands of nuclei in order to simulate the intricate details of the process. By necessity, as most of these nuclei cannot be studied in a controlled environment, these models must rely on the nuclear structure models for input. Of all the properties, the beta-decay half-lives are one of the most important ones due to their direct impact on the resulting abundance distributions. Currently, a single large-scale calculation is available based on a QRPA calculation with a schematic interaction on top of the Finite Range Droplet Model. In this study we present the results of a large-scale calculation based on the relativistic nuclear energy density functional, where both the allowed and the first-forbidden transitions are studied in more than 5000 neutron-rich nuclei.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗