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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 OSTI2020

Developing new alkaline ceramics as possible CO 2 chemisorbents at high temperatures: The lithium and sodium yttriates (LiYO 2 and NaYO 2 ) cases

In this work, lithium and sodium yttriates (LiYO 2 and NaYO 2 ) were synthesized, characterized and tested as possible carbon dioxide (CO 2 ) captors. All the experimental syntheses and analyses were supported by the theoretical thermodynamic calculations, showing that both ceramics would be able to chemisorb CO 2 in a wide temperature range. Therefore, both ceramics were prepared by solid-state reaction and structurally characterized. In fact, the structural characterization evidenced that sodium atoms are located in a octahedral close-packed structure, while lithium ions are not so packed. The lithium ions are, indeed, in a highly distorted tetrahedron, tending to square-planar coordination. Then, based on the theoretical and structural analysis, LiYO 2 and NaYO 2 samples were investigated for the CO 2 capture process through dynamic and isothermal thermogravimetric experiments. All these experiments showed that LiYO 2 has better CO 2 capture properties than NaYO 2 , which was further correlated with the crystal structures of each ceramic. Furthermore, both ceramics presented similar CO 2 capture efficiencies regardless of the CO 2 concentration. Finally, LiYO 2 sample was tested for cyclic CO 2 chemisorption-desorption processes. The obtained results showed that the CO 2 capture efficiency is maintained high at least through 10 cycles. Therefore, these alkaline yttriates seem to present interesting alternatives as high and moderate temperature CO 2 captors, applicable for post-combustion industrial capture processes.

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

Structural uncertainty assessment for fire-engulfed objects in crosswind: Establishing credibility for a multiphysics wall-modeled large-eddy simulation paradigm

A structural uncertainty validation study for a large-scale, fire-engulfed, elevated object subjected to crosswind is presented to establish the credibility of a high-fidelity, low-Mach, turbulent reacting flow wall-modeled large-eddy simulation (WMLES) approach that includes multiphysics coupling to participating media radiation and conjugate heat transfer. To establish that WMLES can accurately predict surface quantities including drag and pressure coefficient in the low-Mach crosswind regime, a foundational elevated isothermal cylinder validation case is presented at a similar gap-to-diameter ratio of 0.25, spanning the subcritical to supercritical drag regime (Re 𝐷 = 1.1 × 10 5 and 4.3 × 10 5 , respectively). Here, this study exercised both static and dynamic coefficient LES (Smagorinsky and 𝑘 sgs ) with both local and exchange-based velocity sampling. Results showcase that the drag crisis (or the sudden drop in drag coefficient at increased Re 𝐷 ) is well captured when using an exchange-based dynamic coefficient WMLES methodology, while noting lack of mesh convergence and overall drag and pressure coefficient predictively when using a static coefficient, local velocity sampling WMLES. For the 𝒪⁡(10) m JP-8 liquid pool fire crosswind validation study presented, two experimental crosswind configurations (2 m/s and 9.5 m/s) are showcased for a fire-engulfed mock fuselage roughly 4 m in diameter. Using the best model-form practices identified in the isothermal study, dynamic coefficient 𝑘 sgs exchange-based WMLES fire validation findings demonstrate accurate peak irradiation and skin temperature predictions as a function of crosswind magnitude. Excessive yaw in the low-crosswind fuselage configuration, consistent with experimental findings, captured a significant predicted asymmetry in flame attachment and heat flux toward the downwind cylindrical cap—indicative of axial vortex structures transporting the flame along the upper and lower fuselage leeward surface. All fire mesh resolution simulations captured the experimental finding that as crosswind increased, predicted flame shape and peak irradiation magnitude onto the fuselage transitioned from a windward to a leeward cylinder location due to the migration of the upper- to lower-shear fuel/air mixing layer thereby demonstrating the novelty, significance, and credibility of this high-fidelity WMLES reacting flow framework.

Domino, Stefan Paul [Sandia National Laboratories ↗
DOE OSTI2019

Spatio-temporal microbial community dynamics within soil aggregates

Soil microbial communities are highly spatially organized, shaped in part by the structure of soil itself. Understanding how spatially discrete microbial communities change across years and seasons in response to environmental factors, plant phenology and aggregate turnover, is key to understanding how varying management practices impact the ecology of soil microbial communities. We investigated both seasonal (within year) and annual (across sampling years) changes of discrete microbial communities in soil aggregate fractions, large macroaggregates (LM) and microaggregates (MICRO) in three different bioenergy management systems. We hypothesized that 1) seasonal changes due to plant phenology and aggregate turnover will be most pronounced within the MICRO aggregate soil microbial community; 2) inter-annual variability will lead to changes in microbial diversity across aggregate sizes and the magnitude of change will be mediated by management regime. We found that LM and MICRO aggregates have unique microbial communities within soil. MICRO aggregate microbial communities are more diverse and change more dynamically across the sampling season, peaking in diversity at peak plant growth and maximum biomass. The number of families indicative of specific MICRO aggregate habitats increases over the growing season for both bacteria (from 3 to 51) and fungi (from 8 to 14). The LM aggregates harbored less diverse, yet more stable, communities within a growing season. By contrast, between years the LM aggregates were the most responsive to inter-annual variability. Our study demonstrates the importance of including the spatio-temporal dynamics of soil microbes. We identified “hot spots” of microbial diversity within soil, with a greater diversity of microbes found under prairies, within the MICRO aggregates, and seasonally during peak plant biomass. Targeted analysis of the MICRO aggregates can contribute to deeper understanding of potential diversity and functioning of soil microbial communities for ecosystem maintenance as well as the response to climatic events and environmental change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Structural transition in sputter-deposited amorphous germanium films by aging at ambient temperature

The structure of amorphous Ge (a-Ge) films prepared by sputter-deposition and the effects of aging at ambient temperature and pressure were studied by pair-distribution-function (PDF) analysis from electron scattering and molecular dynamics simulations. The PDFs of the as-deposited and aged samples for 3–13 months showed that the major peaks for Ge-Ge bonds decrease in intensity and broaden with aging for up to 7 months. In the PDFs of a-Ge of molecular dynamics simulation obtained by quenching liquid at different rates, the major peak intensities of a slowly cooled model are higher than those of a rapidly cooled model. Analyses on short- and medium-range configurations show that the slowly cooled model includes a certain amount of medium-range ordered (MRO) clusters, while the rapidly cooled model includes liquid-like configurations rather than MRO clusters. The similarity between experimental and computational PDFs implies that as-deposited films are similar in structure to the slowly cooled model, whereas the fully aged films are similar to the rapidly cooled model. It is assumed that as they undergo room-temperature aging, the MRO clusters disintegrate and transform into liquid-like regions in the same matrix. This transition in local configurations is discussed in terms of instability and the non-equilibrium of nanoclusters produced by a vapor-deposition process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Snapshot transient absorption spectroscopy: toward in vivo investigations of nonphotochemical quenching mechanisms

Although the importance of nonphotochemical quenching (NPQ) on photosynthetic biomass production and crop yields is well established, the in vivo operation of the individual mechanisms contributing to overall NPQ is still a matter of controversy. In order to investigate the timescale and activation dynamics of specific quenching mechanisms, we have developed a technique called snapshot transient absorption (TA) spectroscopy, which can monitor molecular species involved in the quenching response with a time resolution of 30 s. Using intact thylakoid membrane samples, we show in this study how conventional TA kinetic and spectral analyses enable the determination of the appropriate wavelength and time delay for snapshot TA experiments. As an example, we show how the chlorophyll-carotenoid charge transfer and excitation energy transfer mechanisms can be monitored based on signals corresponding to the carotenoid (Car) radical cation and Car S1 excited state absorption, respectively. The use of snapshot TA spectroscopy together with the previously reported fluorescence lifetime snapshot technique provides valuable information such as the concurrent appearance of specific quenching species and overall quenching of excited Chl. Furthermore, we show that the snapshot TA technique can be successfully applied to completely intact photosynthetic organisms such as live cells of Nannochloropsis. This demonstrates that the snapshot TA technique is a valuable method for tracking the dynamics of intact samples that evolve over time, such as the photosynthetic system in response to high-light exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction

Purpose: Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction. Methods: SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects. Results: For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS. Conclusion: The analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Understanding the Mechanism of Dynamic Recrystallization During High-Temperature Deformation in Nb-1Zr-0.1C Alloy

In the present investigation, a systematic study of the evolution of microstructure and crystallographic texture during hot deformation of Nb-1Zr-0.1C was carried out in the temperature range 1773-1973 K (1500-1700 °C) at different strain rates of 0.001, 0.01 and 0.1 s{sup −1}. The aim was to examine the mechanisms of dynamic recovery and recrystallization in a high-temperature range. A detailed microstructural analysis of the deformed samples was performed using the electron backscatter diffraction technique to study the occurrence and nature of various dynamic restoration processes; the different regimes of dynamic recovery and recrystallization were identified. The orientations of the dynamically recrystallized grains were found to be (001) .

36 MATERIALS SCIENCE↗
DOE OSTI2017

X-ray CT characterization and fracture simulation of ASR damage of glass particles in alkaline solution and mortar

The alkali-silica reaction (ASR) damage in reactive aggregates affects the long-term durability of the concrete infrastructure. The generated ASR gel can expand by imbibing water from the pore solution and the resulting expansion pressure causes the aggregate fracture. This study aims to simulate the development of ASR damage in glass particles of two types of samples (glass in alkali solution and glass mortars). The dynamic micro X-ray CT technique was conducted to monitor the crack propagation in glass aggregates at different reaction stages (up to 64 hrs). The Boundary Element Method (BEM) and Displacement Discontinuity Method (DDM) were used to efficiently simulate the crack propagation within irregular glass particles under gel expansion pressures. The aggregate boundaries were built with the BEM elements and the initial cracks were meshed with the DDM elements. The estimated expansion pressure was applied to the initial crack surfaces. The discontinuous displacements and stresses were calculated along the crack path and crack tip. The mixed-mode Stress Intensity Factors (SIFs) were calculated based on plane stress conditions. The maximum circumferential stress criteria was used to simulate the propagation of cracks along a specific angle. The simulation results include the simulated crack path and the combined SIFs changing with the increments. With the estimate expansion pressure, the glass particle damages were simulated within conditions of alkali solution and confined motar samples. The predicted crack propagation path was compared with the X-ray CT imaging data. The comparison results demonstrate the DDM has the ability to predicting the ASR damage propagation inside aggregates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Discrete generative diffusion models without stochastic differential equations: A tensor network approach

Diffusion models (DMs) are a class of generative machine learning methods that sample a target distribution by transforming samples of a trivial (often Gaussian) distribution using a learned stochastic differential equation. In standard DMs, this is done by learning a “score function” that reverses the effect of adding diffusive noise to the distribution of interest. Here we consider the generalisation of DMs to lattice systems with discrete degrees of freedom, and where noise is added via Markov chain jump dynamics. We show how to use tensor networks (TNs) to efficiently define and sample such “discrete diffusion models” (DDMs) without explicitly having to solve a stochastic differential equation. We show the following: (i) by parametrising the data and evolution operators as TNs, the denoising dynamics can be represented exactly; (ii) the auto-regressive nature of TNs allows to generate samples efficiently and without bias; (iii) for sampling Boltzmann-like distributions, TNs allow to construct an efficient learning scheme that integrates well with Monte Carlo. We illustrate this approach to study the equilibrium of two models with non-trivial thermodynamics, the d = 1 constrained Fredkin chain and the d = 2 Ising model. Published by the American Physical Society 2025

Causer, Luke (ORCID:0000000194243473)↗
DOE OSTI2020

A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication

We report accurate estimation of cropping intensity (CI), an indicator of food production, is well aligned with the ongoing efforts to achieve sustainable development goals (SDGs) under diminishing natural resources. The advancement in satellite remote sensing provides unprecedented opportunities for capturing CI information in a spatially continuous manner. However, challenges remain due to the lack of generalizable algorithms for accurately and efficiently mapping global CI with a fine spatial resolution. In this study, we developed a 30-m planetary-scale CI mapping framework with the reconstructed time series of Normalized Difference Vegetation Index (NDVI) from multiple satellite images. Using a binary crop phenophase profile indicating growing and non-growing periods, we estimated pixel-by-pixel CI by enumerating the total number of valid cropping cycles during the study years. Based on the Google Earth Engine cloud computing platform, we implemented the framework to estimate CI during 2016–2018 in eight geographic regions across continents that are representative of global cropping system diversity. Comparison with PhenoCam network data in four cropland sites suggests that the proposed framework is capable of capturing the seasonal dynamics of cropping practices. Spatially, overall accuracies based on validation samples range from 80.0% to 98.9% across different regions worldwide. Regarding the CI classes, single cropping systems are associated with more robust and less biased estimations than multiple cropping systems. Finally, our CI estimates reveal high agreement with two widely used land surface phenology products, including Vegetation Index and Phenology V004 (VIP4) and Moderate Resolution Imaging Spectroradiometer Land Cover Dynamics (MCD12Q2), meanwhile providing much more spatial details. Due to its robustness, the developed CI framework can be potentially generalized to produce global fine resolution CI products for food security and other applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Electrical Properties of Intercalated Ag{sub x}MoSe{sub 2} Compounds in Constant and Alternating Fields

On intercalated Ag{sub x}MoSe{sub 2} samples, in addition to temperature measurements of the direct current electrical resistivity, measurements of the alternating current resistivity using the impedance spectroscopy technique are carried out in a wide frequency range and at different temperatures. The activation behavior of the d.c. conductivity, which increases with increasing silver content in the samples, is shown. The a.c. conductivity undergoes frequency dispersion, described by a “universal dynamic response” (UDR). It is shown that the relaxation processes during charge transfer in a variable field are accelerated with increasing silver content in the samples and with increasing temperature. The data obtained are analyzed using the models of the band and hopping conduction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Spin dynamics in linear magnetoelectric material Mn 3 Ta 2 O 8

We performed inelastic neutron scattering experiments on single crystal samples of a linear magnetoelectric material Mn 3 Ta 2 O 8 , which exhibits a collinear antiferromagnetic order, to reveal the spin dynamics. Numerous modes observed in the neutron spectra were reasonably reproduced by linear spin-wave theory on the basis of the spin Hamiltonian including eight Heisenberg interactions and an easy-plane type single-ion anisotropy. In conclusion, the presence of strong frustration was found in the identified spin Hamiltonian.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Stellar mass, not dynamical mass nor gravitational potential, drives the mass–metallicity relationship

The widely known relation between stellar mass and gas metallicity [mass–metallicity relation (MZR)] in galaxies is often ascribed to the higher capability of more massive systems to retain metals against the action of galactic outflows. In this scenario the stellar mass would simply be an indirect proxy of the dynamical mass or of the gravitational potential. We test this scenario by using a sample of more than 1000 star-forming galaxies from the MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) survey for which dynamical masses have been accurately determined. By using three different methods (average dispersion, partial correlation coefficients, and random forest), we unambiguously find that the gas metallicity depends primarily and fundamentally on the stellar mass. Once the dependence on stellar mass is taken into account, there is little or no dependence on either dynamical mass or gravitational potential (and, if anything, the metallicity dependence on the latter quantities is inverted). Our result indicates that the MZR is not caused by the retention of metals in more massive galaxies. The direct, fundamental dependence of metallicity on stellar mass suggests the much simpler scenario in which the MZR is just a consequence of the stellar mass being proportional to the integral of metals production in the galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dynamic in situ imaging of methane hydrate formation in coal media

Fast 3D X-ray imaging has proved to provide crucial insights into multi-phase dynamic processes in various geomaterials. In particular, many in situ imaging experiments have been made to study gas-hydrate formation in porous sandy samples. Such imaging is challenging for the methane gas-hydrate formation in coal samples because of the coal micro-porosity structure and lower X-ray contrast. Here we present results of the first dynamic in situ micro-computed tomography experiment of methane-hydrate formation in coal samples. Synchrotron phase-contrast tomography techniques allowed to achieve necessary contrast levels to separate all the materials of interest (gas, water, coal, and gas hydrate) in reconstructed images with high spatial and temporal resolution. The imaging results are compared to the ones from a similar tomographic experiment with sand samples. Methane-hydrate formation is accompanied by the water movements caused by cryogenic water suction that happens in sequences of short fast movements with longer equilibrium states in between. Only one type of the hydrate formation was observed in coal (growth as shells on grain boundaries) as opposed to three types in sand (shells, growth into gas pockets, and inside water volumes). In particular, this leads to a slower hydrateformation speed in coal. For the coal sample, we also observed water extraction from grains, and interpreted it as competitive sorption of methane. Lastly, we visualized the dynamic behavior of this water extraction via microchannels inside the coal grains, and performed nano-tomography imaging of these channels for a better understanding of this phenomenon.

58 GEOSCIENCES↗
DOE OSTI2017

Galaxy Cluster Mass Reconstruction Project – III. The impact of dynamical substructure on cluster mass estimates

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses is crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an ‘unrelaxed’ state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by ~ 10 percent at 10 14 and ≳ 20 percent for ≲ 10 13.5 . Finally, the use of cluster samples with different levels of substructure can therefore bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies.

79 ASTRONOMY AND ASTROPHYSICS↗