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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Interpretation of Fracture Initiation Points by In-Well Low-Frequency Distributed Acoustic Sensing in Horizontal Wells

Summary Low-frequency distributed acoustic sensing (LF-DAS) exploits the optical phase shift of Rayleigh backscatter in fiber-optic cables to obtain distributed measurements of changes in strain and temperature. Fiber-optic cables are often installed for multistage hydraulic fracture diagnostics in horizontal wells. LF-DAS in an untreated well provides far-field strain measurements, while offset wells are hydraulically fractured. Such a configuration is called crosswell LF-DAS sensing. Crosswell LF-DAS measurements have proved useful in diagnosing fracture hits, fracture azimuth, planarity, cluster efficiency, fracture propagation rates, and the dynamic distance to the fracture front. In contrast, in-well LF-DAS is conducted on the actively fractured well. Due to cool fracture fluid being injected at high injection rates, the strain component of the LF-DAS response is largely obscured by temperature changes. In permanent fiber-optic cable installations, distributed temperature sensing (DTS) is often conducted simultaneously with LF-DAS. An opportunity exists to decouple the temperature and strain components of LF-DAS sensors to observe strain changes on in-well LF-DAS. The LF-DAS response is modeled as linearly dependent on strain and temperature changes. Theoretical LF-DAS temperature and strain sensitivity coefficients are derived based on the changes to the index of refraction and length of the fiber. Using the DTS measurements, temperature changes are computed, smoothed, filtered, and compared to the LF-DAS response. Crossplots of the in-well LF-DAS measurements and temperature changes from DTS measurements far from the actively fractured region are used to validate the theoretical sensitivity coefficients. Uncertainty in the temperature component of the LF-DAS response is quantified. The difficulty in corresponding the different spatial and temporal resolutions of the DTS and LF-DAS measurements is overcome by comparing the responses over a moving temporal and spatial window. If the LF-DAS response at the center of the window agrees with the DTS response within uncertainty, the measurement is filtered out. After filtering, the remaining nonzero in-well LF-DAS measurements are due to changes in strain. The data are then visualized in waterfall plots. The results indicate that the theoretical and observed strain and temperature coefficients agree within 10%. After the temperature component of the in-well LF-DAS response is extracted, the remaining nonzero measurements are located primarily within the actively treated region. Locations with peaks in the strain response are interpreted to indicate fracture initiation points. These fracture initiation points are compared with in-well DTS and high-frequency DAS noise measurements across multiple stages to better understand fracture initiation along the horizontal well.

Engineering↗
DOE OSTI2022

New insights into Mn 2+ and Mg 2+ inhibition of calcite growth

Impurity ion and isotope partitioning into carbonate minerals provide a window into the molecular processes occurring at the fluid-mineral interface during crystal growth. Here, we employ calcium isotope fractionation together with process-based modeling to elucidate the mechanisms by which two divalent cations with starkly contrasting compatibility, magnesium and manganese, inhibit calcite growth and incorporate into the mineral lattice. Calcite growth inhibition by Mg 2+ is log-linear and K Mg is on the order of 0.02–0.03 throughout the range of {Mg 2+ }/{Ca 2+ } studied here (0.01–2.6). Mn 2+ exhibits much stronger log-linear growth rate inhibition at low Mn 2+ concentrations (fluid {Mn 2+ }/{Ca 2+ } = 0.001–0.02). Mn 2+ is readily incorporated into the calcite lattice to form a calcite-rhodochrosite solid solution, with large partition coefficients (K Mn 4.6–15.6) inversely correlated to growth rate. For both Mn 2+ and Mg 2+ , calcium isotope fractionation is found to be invariant with {Me 2+ }/{Ca 2+ } despite more than an order of magnitude decline in growth rate. This invariant Δ 44/40 Ca suggests that the presence of Mn 2 + or Mg 2+ does not significantly change the relative rates of Ca 2+ attachment and detachment at kink sites during growth, indicative of a dominantly kink blocking inhibition mechanism. Because the partitioning behavior dictates that Mn 2+ must attach to the surface significantly faster than Ca 2+ , attachment of Mn 2+ is likely to be as a non-monomer species such as an ion pair or possibly a larger polynuclear cluster. We propose that calcite growth rate inhibition by Mn is determined by the kinetics of carbonate attachment at Mn-occupied kink sites, potentially due to slow re-orientation kinetics of carbonate ions that have formed an inner-sphere complex with Mn 2+ at the surface but must reorient to incorporate into the lattice. We demonstrate that patterns in Mg 2+ partitioning and inhibition behavior are broadly consistent with growth inhibition driven by slow Mg 2+ -aquo complex dehydration relative to Ca 2+ but argue that this mechanism likely represents one endmember scenario, seen in Mg-calcite growth at low supersaturations and net precipitation rates. During growth at faster net precipitation rates, some portion of Mg 2+ is likely incorporated as a partially hydrated or otherwise complexed species, but calcite growth remains significantly inhibited by the kinetics of CO 3 2- attachment at Mg 2+ kink sites. These findings suggest a hybrid classical/nonclassical growth mechanism whereby Ca 2+ incorporates largely as a free ion at kink sites while Mn 2+ and some portion of Mg 2+ are incorporated via non-monomer attachment. This pattern may be generalizable; trace constituent cations with aquo-complex desolvation rates significantly slower than the mineral growth rate preferentially incorporate as a non-monomer species during otherwise classical crystal growth.

58 GEOSCIENCES↗
DOE OSTI2024

Chemomechanics in alloy phase stability

We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to include an explicit dependence on homogeneous strain in addition to site occupation variables that track the degree of chemical ordering. The method is applied to the Si-Ge binary alloy and is used to calculate free energies that describe phase stability under arbitrary epitaxial constraints. We find that while the incoherent phase diagram (in which coexisting phases are not affected by coherency constraints) hosts a miscibility gap, coherent phase equilibrium predicts ordering and negative enthalpies of mixing. Instead of chemical instability, the chemomechanical free energy exhibits instabilities along directions that couple the composition of the alloy with a volumetric strain order parameter. Furthermore, this has fundamental implications for phase field models of spinodal decomposition as it indicates the importance of gradient energy coefficients that couple gradients in composition with gradients in strain.

Materials Science↗
DOE OSTI2021

Repetitively pulsed nanosecond discharge plasma decay in propane–oxygen gas mixture in the presence of a heating electric field

Plasma decay in the afterglow of a repetitively pulsed nanosecond discharge in a stoichiometric propane–oxygen mixture was experimentally investigated when a weak heating DC electric field was applied and in its absence. The discharge was ignited at room gas temperature and a pressure of 1–2 Torr and was characterized by low specific energy inputs (<0.004 eV per molecule in one pulse). Using microwave interferometry, the temporal evolution of the electron density during plasma decay was studied, and the effective recombination coefficients were obtained from data processing. It was shown that the rate of plasma decay behaved in a non-monotonic manner with increasing degree of propane oxidation; at first the decay rate grew, then passed through a maximum, fell and saturated in the limit of a large (~2000) number of pulses. In this limit, the effect of the heating DC electric field on the plasma decay decreased with approaching chemical equilibrium. Numerical simulation of the observed effects was performed for low and high oxidation degrees of propane taking into account changes in the composition of positive ions in the plasma. Good agreement was obtained between measurements and calculations of the electron density during plasma decay in these cases. Here it was shown that the formation of cluster ions in the discharge afterglow plays a fundamental role. The plasma decay was controlled by electron recombination with hydrocarbon cluster ion at low oxidation degree of propane and with water cluster (hydrated) ions at high oxidation degree. A hypothesis was proposed to explain the observed nonmonotonic behavior of the plasma decay rate with an increase in the propane oxidation in the discharge, based on the formation of hydrated hydrocarbon ions C x H y + (H 2 O) k at moderate oxidation degrees.

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

From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes

Electrolyte anions are pivotal for lithium battery performance, yet their fundamental electronic structural properties are not well understood. In this work, we employ a combination of negative-ion photoelectron spectroscopy (NIPES), ab initio calculations, and molecular dynamics (MD) simulations to investigate the electronic structures of three representative electrolyte anions. This multiscale approach enables us to elucidate how their intrinsic electronic properties govern anion–solvent interactions in gas-phase clusters, as well as lithium-ion (Li + ) solvation structures and ion transport behavior in the condensed phase. NIPES reveals that difluoro(oxalato)borate (DFOB – ), bis(fluorosulfonyl)imide (FSI – ), and bis(oxalato)borate (BOB – ) all exhibit high electron binding energies, with vertical/adiabatic detachment energies increasing from DFOB – (6.09/5.70 eV) to FSI – (6.80/6.10 eV) to BOB – (6.82/6.40 eV), correlating with enhanced oxidation stability. Ab initio calculations reveal that DFOB – /FSI – –solvent complexes bind Li + ∼ 10 kcal/mol stronger than BOB – series, aligning with the strength of a Li + –anion model. DFOB – exhibits pronounced charge localization on both oxygen and fluorine atoms, enabling their involvement in Li + coordination. In contrast, fluorine atoms in FSI – are largely electron-depleted and remain excluded from direct Li + binding. MD simulations further demonstrate that LiDFOB and LiFSI systems exhibit Li + diffusion coefficients three and five times higher than those of LiBOB across four common solvents. Notably, LiFSI salt in acetonitrile (AN) exhibits the fastest Li + diffusion among 12 electrolyte systems, highlighting the synergistic effect of FSI – and AN in promoting ion mobility. In conclusion, these findings provide a molecular-level understanding of the critical roles of anion and its microsolvation in optimizing Li + diffusion dynamics, once again emphasizing the positioning of FSI – and DFOB – as prime candidates for next-generation electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2022

Measurement and QCD analysis of double-differential inclusive jet cross sections in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A measurement of the inclusive jet production in proton-proton collisions at the LHC at $ \sqrt{s} $ = 13 TeV is presented. The double-differential cross sections are measured as a function of the jet transverse momentum p$_{T}$ and the absolute jet rapidity |y|. The anti-k$_{T}$ clustering algorithm is used with distance parameter of 0.4 (0.7) in a phase space region with jet p$_{T}$ from 97 GeV up to 3.1 TeV and |y| < 2.0. Data collected with the CMS detector are used, corresponding to an integrated luminosity of 36.3 fb$^{-1}$ (33.5 fb$^{-1}$). The measurement is used in a comprehensive QCD analysis at next-to-next-to-leading order, which results in significant improvement in the accuracy of the parton distributions in the proton. Simultaneously, the value of the strong coupling constant at the Z boson mass is extracted as α$_{S}$(m$_{Z}$) = 0.1170±0.0019. For the first time, these data are used in a standard model effective field theory analysis at next-to-leading order, where parton distributions and the QCD parameters are extracted simultaneously with imposed constraints on the Wilson coefficient c$_{1}$ of 4-quark contact interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Molecular-level insights into structure and dynamics in ionic liquids and polymer gel electrolytes

We report designing new electrolytes requires a better understanding of the correlation between their transport properties and their molecular structure. In this work, we present a detailed study of ionic liquids and polymer gel electrolytes probing their structure and dynamics by nuclear magnetic resonance (NMR) spectroscopy. In particular, ammonium- and phosphonium-based ionic liquids (ILs) are combined with different LiTFSI concentrations, and then with different ratios of poly(methylmethacrylate) polymer. The temperature dependence of self-diffusion coefficients of mobile species, D Li+ , D TFSI- and D P4441+ or D N4441+ , measured by pulsed field gradient (PFG) NMR spectroscopy obeys the Arrhenius equation. Diffusivity of [P4441][TFSI] ILs is found to be greater than those of the [N4441][TFSI] ILs in both liquid and gel electrolytes. Solid state NMR experiments including 13 C and 19 F MAS, 13 C{ 19 F}, 13 C{ 1 H} CPMAS probe the local structure and molecular-level interactions between ions and polymer in gel electrolytes, particularly for samples with higher PMMA content (≥25 wt%). Finally, the fast field cycling relaxometry has been used to unveil the rotational and translational dynamics of P4441 + or N4441 + and TFSI - by measuring 1 H and 19 F R 1 relaxation rate profiles at different temperatures. A comprehensive NMR analysis including relaxation studies at low magnetic field provides decisive new insights regarding the formation of ionic clusters and the interaction of ions with the polymer chain in the case of the gel electrolytes.

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

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

First test of the consistency relation for the large-scale structure using the anisotropic three-point correlation function of BOSS DR12 galaxies

ABSTRACT We present, for the first time, an observational test of the consistency relation for the large-scale structure (LSS) of the Universe through a joint analysis of the anisotropic two- and three-point correlation functions (2PCF and 3PCF) of galaxies. We parameterize the breakdown of the LSS consistency relation in the squeezed limit by Es, which represents the ratio of the coefficients of the shift terms in the second-order density and velocity fluctuations. Es ≠ 1 is a sufficient condition under which the LSS consistency relation is violated. A novel aspect of this work is that we constrain Es by obtaining information about the non-linear velocity field from the quadrupole component of the 3PCF without taking the squeezed limit. Using the galaxy catalogues in the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, we obtain $E_{\rm s} = -0.92_{-3.26}^{+3.13}$, indicating that there is no violation of the LSS consistency relation in our analysis within the statistical errors. Our parameterization is general enough that our constraint can be applied to a wide range of theories, such as multicomponent fluids, modified gravity theories, and their associated galaxy bias effects. Our analysis opens a new observational window to test the fundamental physics using the anisotropic higher-order correlation functions of galaxy clustering.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2022

Dynamics of deuterium retention and desorption from plasma-facing materials in fusion reactor-relevant conditions

Hydrogen isotopes retention and desorption during and after discharges in fusion devices are still not well understood due to the complex device conditions and limitations of in-situ diagnostics and measurements. Here, we simulated well-diagnosed recent experiments at the DIII-D facility to benchmark our ITMC-DYN integrated package of modeling deuterium diffusion, retention, and desorption during and after D discharge irradiation. Modeling results were compared with detail experimental data of D desorption fluxes for various irradiation conditions. We predicted the temporal evolution of free and trapped D distribution in tungsten (W) plasma-facing material (PFM). Effects of key parameters namely diffusion coefficient, recombination rate, trapping energies against different defect types, were examined in these simulations. Existing experimental data of these parameters in literature varies significantly which makes it harder to identify key mechanisms and physics responsible for hydrogen isotope retention and desorption. The purpose of this work is to accurately simulate recent well-diagnosed reactor experiments given the uncertainties in such parameters and identify mechanisms responsible for the retention and desorption. We implemented the best identified diffusion, recombination, and trapping parameters in ITMC-DYN package that integrate both various collisional and thermal processes. We predicted, for example, that sample cooling between discharges in DIII-D operations can significantly affect the spatial distribution of trapped D in W under reactor irradiation conditions. Correct prediction of desorption spectra from samples irradiated during 10 DIII-D discharges showed that up to 35% of D can be retained in high binding energy defects such as vacancy clusters or voids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Theoretical study of the CO 2 –O 2 van der Waals complex: potential energy surface and applications

A four-dimensional-potential energy surface (4D-PES) of the atmospherically relevant carbon dioxide–oxygen molecule (CO 2 –O 2 ) van der Waals complex is mapped using the ab initio explicitly correlated coupled cluster method with single, double, and perturbative triple excitations (UCCSD(T)-F12b), and extrapolation to the complete basis set (CBS) limit using the cc-pVTZ-F12/cc-pVQZ-F12 bases and the l –3 formula. An analytic representation of the 4D-PES was fitted using the method of interpolating moving least squares (IMLS). These calculations predict that the most stable configuration of CO 2 –O 2 complex corresponds to a planar slipped-parallel structure with a binding energy of V ~ –243 cm –1 . Another isomer is found on the PES, corresponding to a non-planar cross-shaped structure, with V ~ –218 cm –1 . The transition structure connecting the two minima is found at V ~ –211 cm –1 . We also performed comparisons with some CO 2 –X van der Waals complexes. Moreover, we provide a SAPT analysis of this molecular system. Then, we discuss the complexation induced shifts of CO 2 and O 2 . Afterwards, this new 4D-PES is employed to compute the second virial coefficient including temperature dependence. A comparison between quantities obtained in our calculations and those from experiments found close agreement attesting to the high quality of the PES and to the importance of considering a full description of the anisotropic potential for the derivation of thermophysical properties of CO 2 –O 2 mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning

Abstract Estimates of soil organic carbon (SOC) stocks are essential for many environmental applications. However, significant inconsistencies exist in SOC stock estimates for the U.S. across current SOC maps. We propose a framework that combines unsupervised multivariate geographic clustering (MGC) and supervised Random Forests regression, improving SOC maps by capturing heterogeneous relationships with SOC drivers. We first used MGC to divide the U.S. into 20 SOC regions based on the similarity of covariates (soil biogeochemical, bioclimatic, biological, and physiographic variables). Subsequently, separate Random Forests models were trained for each SOC region, utilizing environmental covariates and SOC observations. Our estimated SOC stocks for the U.S. (52.6 ± 3.2 Pg for 0–30 cm and 108.3 ± 8.2 Pg for 0–100 cm depth) were within the range estimated by existing products like Harmonized World Soil Database, HWSD (46.7 Pg for 0–30 cm and 90.7 Pg for 0–100 cm depth) and SoilGrids 2.0 (45.7 Pg for 0–30 cm and 133.0 Pg for 0–100 cm depth). However, independent validation with soil profile data from the National Ecological Observatory Network showed that our approach ( R 2 = 0.51) outperformed the estimates obtained from Harmonized World Soil Database ( R 2 = 0.23) and SoilGrids 2.0 ( R 2 = 0.39) for the topsoil (0–30 cm). Uncertainty analysis (e.g., low representativeness and high coefficients of variation) identified regions requiring more measurements, such as Alaska and the deserts of the U.S. Southwest. Our approach effectively captures the heterogeneous relationships between widely available predictors and the current SOC baseline across regions, offering reliable SOC estimates at 1 km resolution for benchmarking Earth system models.

58 GEOSCIENCES↗
DOE OSTI2025

Unsteady Land-Sea Breeze Circulations in the Presence of a Synoptic Pressure Forcing

Unsteady land-sea breezes (LSBs) that result from time-varying surface temperature contrasts Δθ(t) are explored in the presence of a constant synoptic pressure forcing, M g , oriented from sea to land (α = 0°) or land to sea (α = 180°). Large eddy simulations reveal the development of four distinctive regimes, depending on the joint interaction between M g , α, and Δθ(t) in modulating the fine-scale dynamics. Time lags, computed as the shifts that maximize correlation coefficients of the velocity between the unsteady and the corresponding steady scenarios at Δθ = Δθ max , are found to be significant and to extend 2 hr longer for α = 0° compared to α = 180°. These diurnal dynamics result in nonequilibrium conditions that are significantly affected by the flow history, and that behave differently over the two patches for the different α’s. Turbulence is found to be out of equilibrium with the mean flow, and the mean itself is found to be out of equilibrium with the thermal forcing. The sea surface heat flux is consistently more sensitive than its land counterpart to the time-varying external forcing Δθ(t), and more so for synoptic forcing from land to sea (α = 180°). Hence, although the land reaches equilibrium faster, the sea patch is found to exert a stronger control on the turbulence-mean flow equilibrium response. Finally, the vertical velocity profile at the shore and shore-normal velocity transects at the first grid level are shown to encode the multiscale regimes of the LSBs evolution and can thus be used to identify these regimes using k-means clustering.

58 GEOSCIENCES↗
DOE OSTI2022

Impact of Ion–Ion Correlated Motion on Salt Transport in Solvated Ion Exchange Membranes

The influence of dynamical ion-ion correlations and ion pairing on salt transport in ion exchange membranes remain poorly understood. In this study, we use the framework of Onsager transport coefficients within atomistic molecular dynamics sim- ulations to study the impact of ion-ion correlated motion on salt transport in hydrated polystyrene sulfonate membranes and compare with the results from aqueous salt so- lutions. At sufficiently high salt concentrations, cation-anion dynamical correlations exert a significant influence on both salt diffusivities and conductivities. Anion-anion distinct correlations, arising from the imbalance between the concentration of free (mo- bile) cations and anions, and the retarding effect of the fixed charge groups on cations, proves to be an additional important feature for polymer membranes. Furthermore, our results demonstrate that dynamical correlations should become an important consideration in experimental measurements of salt diffusivities and conductivities for non-dilute salt solutions in polymer membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

DESI luminous red galaxy samples for cross-correlations

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2–3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. Here, we also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗