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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Elucidating the Influence of Metal Surface Composition on Organic Adsorbate Binding Using Active Particle Dynamics

The adsorption strengths of organic compounds on metal surfaces are sensitive to the metal composition, and they play a central role in many catalytic reactions, helping to control the coverage of the reactant and altering the overall reaction rate. While adsorption energies are straightforward to measure and calculate in vacuum and gas-phase environments, adsorption energetics can be dramatically altered by the presence of solvent in liquid-phase reactions. However, the effects of metal composition on binding strengths in a liquid environment are less well understood, primarily due to the difficulty of accurate in situ measurements of organic binding on metal surfaces in the liquid phase. Here, we utilize the motion of active particles in water to probe the adsorption energies of an organic adsorbate (furfural) on a range of metal surfaces (pure Pd, pure Pt, and four PdAu alloy compositions) to elucidate the effect of metal composition. Janus particles with catalytic caps of particular metal compositions all exhibited active motion resulting from consumption of H 2 O 2 ; adsorbate binding was inferred through the decrease in the velocity of active motion and was modeled by a Langmuir adsorption isotherm. The measured adsorption affinities were used to extract the adsorption enthalpy of furfural on the different metals. The Pd surface was found to bind furfural more strongly than the Pt surface by some 10 kJ/mol. Furthermore, the adsorption of furfural on the alloys was found to increase monotonically in magnitude with Pd content. As a result, the data reported herein aid the development of accurate understanding of organic adsorption in the presence of solvent and the role of the metal surface in tuning adsorption strengths to optimize catalytic processes in the liquid phase.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaling of Turbulence and Microphysics in a Convection–Cloud Chamber of Varying Height

Abstract The convection–cloud chamber enables measurement of aerosol and cloud microphysics, as well as their interactions, within a turbulent environment under steady‐state conditions. Increasing the size of a convection–cloud chamber, while holding the imposed temperature difference constant, leads to increased Rayleigh, Reynolds and Nusselt numbers. Large–eddy simulation coupled with a bin microphysics model allows the influence of increased velocity, time, and spatial scales on cloud microphysical properties to be explored. Simulations of a convection–cloud chamber, with fixed aspect ratio and increasing heights of H = 1, 2, 4, and (for dry conditions only) 8 m are performed. The key findings are: Velocity fluctuations scale as H 1/3 , consistent with the Deardorff expression for convective velocity, and implying that the turbulence correlation time scales as H 2/3 . Temperature and other scalar fluctuations scale as H −3/7 . Droplet size distributions from chambers of different sizes can be matched by adjusting the total aerosol injection rate as the horizontal cross‐sectional area (i.e., as H 2 for constant aspect ratio). Injection of aerosols at a point versus distributed throughout the volume makes no difference for polluted conditions, but can lead to cloud droplet size distribution broadening in clean conditions. Cloud droplet growth by collision and coalescence leads to a broader right tail of the distribution compared to condensation growth alone, and this tail increases in magnitude and extent monotonically as the increase of chamber height. These results also have implications for scaling within turbulent, cloudy mixed‐layers in the atmosphere, such as fog layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High-Resolution Near-Surface Imaging at the Basin Scale Using Dark Fiber and Distributed Acoustic Sensing: Toward Site Effect Estimation in Urban Environments

Near-surface seismic structure, particularly the shear wave velocity (V s ), can strongly affect local site response, and should be accurately estimated for ground motion prediction during seismic hazard assessment. The Imperial Valley (California), occupying the southern end of the Salton Trough, is a seismically active basin with thick surficial lacustrine sedimentary deposits. In this study, we utilize ambient noise records and local earthquake events for high-resolution near-surface characterization and site effect estimation with an unlit fiber-optic telecommunication infrastructure (dark fiber) in Imperial Valley by using the distributed acoustic sensing (DAS) technique. We apply ambient noise interferometry to retrieve coherent surface waves from DAS records, and evaluate performances of three different surface wave methods on DAS ambient noise dispersion imaging. We develop a quality control workflow to improve the dispersion measurement of noisy portions of the DAS data set by using a data selection strategy. Using the joint inversion of both the fundamental mode and higher overtones of Rayleigh waves, a high resolution two-dimensional (2D) V s structure down to 70 m depth is obtained. We successfully achieve an improved V s 30 (the time-averaged shear-wave velocity in the top 30 m) model with higher spatial-resolution and reliability compared to the existing community model for the area. We also explore the potential for utilizing DAS earthquake events for site amplification estimation. The preliminary results reveal a clear anti-correlation between the approximated site response and the V s 30 profile. In conclusion, our results indicate the potential utility of DAS deployed on dark fiber for near-surface characterization in appropriate contexts.

58 GEOSCIENCES↗
DOE OSTI2021

Holistic Numerical Calibration of the iMESA Electrostatic Analyzer

A drifted Maxwellian velocity distribution is the most common model used to interpret the data from low-energy charged-particle instruments onboard spacecraft that are used to investigate the ambient plasma environment in the low Earth orbit (LEO). An original method is presented for determining the flow parameters (density, temperature, and flow energy) of such a distribution from the output of the integrated miniaturized electrostatic analyzer, which has been successfully flown on several LEO missions. Rather than attempting to deconvolve from the on-orbit data the analyzer’s response to an ideal, monoenergetic input, numerical simulation is used to predict and parameterize the response of the device to an input distribution that includes an isotropic, non-zero temperature, yielding a straightforward method for extracting the flow parameters from the spacecraft data. The method is computationally simple enough to be incorporated into a robust algorithm suitable for rapid batch processing or real-time analysis of data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Caustic Neutralization and Precipitation of Acidic Dissolved Simulated Stainless Steel–Clad Plutonium and Plutonium/Uranium Nuclear Fuel

Simulated dissolved stainless steel (SS) clad Pu and Pu/U nuclear fuel in HNO 3 was neutralized to a free hydroxide (OH - ) concentration of 0.6 M. A thermal neutron poison, Gd, was added to the simulants at concentrations of either ~3 - 6 g/L or ~37 - 38 g/L. The supernate Pu concentration the day of neutralization ranged from 0.48 to 8.75 mg/L. The supernate Pu concentration of a simplified simulant neutralized to 0.6 M OH - above precipitated solids containing Pu was demonstrated to decrease over 18 days. A significant portion of precipitated Pu was found to be insoluble in 8 M HNO 3 at ambient temperature, but essentially quantitative Pu dissolution was achieved in 11.5 M HNO 3 /0.1 M KF at 100 °C. The difficulty in dissolving the Pu precipitate is believed to be due to the formation of refractory PuO 2 •xH 2 O during the neutralization process. Initial Gd concentrations of ~37 – 38 g/L were found to result in a greater Al precipitation when neutralized to 0.6 M OH - than initial Gd concentrations of ~3 – 6 g/L. Physical properties of the resultant slurries were measured and used to calculate limiting flowrates and slurry velocities by gravity only in transfer piping between the Savannah River Site’s H-Canyon Facility and the Concentration, Storage, and Transfer Facility (CSTF). These results were compared to calculated deposition velocities to predict if solids would settle during the transfer. The Newtonian model was found to be reasonable for each diluted slurry evaluated. Deposition velocities of Pu containing slurries are lower than nuclear fuel slurries primarily composed of U due to the high density of Pu solids. In conclusion, dilution of slurries reduces the margin between the slurry and deposition velocities due to the reduction in viscosity because higher viscous forces on the particles promote maintained suspension.

Actinide Neutralization↗
DOE OSTI2020

Observational constraints on the multiphase nature of outflows using large spectroscopic surveys at z ∼ 0

ABSTRACT Mass outflow rates and loading factors are typically used to infer the quenching potential of galactic-scale outflows. However, these generally rely on observations of a single gas phase that can severely underestimate the total ejected gas mass. To address this, we use observations of high mass (≥1010 M⊙), normal star-forming galaxies at z ∼ 0 from the MaNGA, xCOLD GASS, xGASS, and ALFALFA surveys and a stacking of Na d, Hα, CO(1–0), and H i 21 cm tracers with the aim of placing constraints on an average, total mass outflow rate, and loading factor. We find detections of outflows in both neutral and ionized gas tracers, with no detections in stacks of molecular or atomic gas emission. Modelling of the outflow components reveals velocities of |vNa d| = 131 km s−1 and |vHα| = 439 km s−1 and outflow rates of $\dot{M}_{\rm {Na\,\small{D}}}$ = 7.55 M⊙ yr−1 and $\dot{M}_{\text{H}\alpha }$ = 0.10 M⊙ yr−1 for neutral and ionized gas, respectively. Assuming a molecular/atomic outflow velocity of 200 km s−1, we derive upper limits of $\dot{M}_{\text{CO}}\lt 19.43$ M⊙ yr−1 and $\dot{M}_{\rm {H\,\small {I}}}\lt $ 26.72 M⊙ yr−1 for the molecular and atomic gas, respectively. Combining the detections and upper limits, we find average total outflow rates of $\dot{M}_{\text{tot}}\lesssim$27 M⊙ yr−1 and a loading factor of ηtot ≲ 6.39, with molecular gas likely contributing ≲72 per cent of the total mass outflow rate, and neutral and ionized gas contributing ∼28 and <1 per cent, respectively. Our results suggest that, to first order, a degree of quenching via ejective feedback could occur in normal galaxies when considering all gas phases, even in the absence of an active galactic nucleus.

Roberts-Borsani, G. W.↗
DOE OSTI2022

The phase and turbulent properties of Cattail

ABSTRACT A recent publication discovered one of the largest filamentary neutral hydrogen features dubbed Cattail from high-resolution Five-hundred-meter Aperture Spherical radio Telescope observations that might be a new galactic arm of the Milky Way. We evaluate the turbulent and phase properties of Cattail via the newly developed Velocity Decomposition Algorithm and Force Balancing Model. We discover that if there exists a phase transition, then Cattail is unlikely in the cold neutral media phase. We also show that the Cattail is two disjoint features in caustics space, suggesting that the Cattail has two different turbulent systems. We check the spectra of the individual system separated via VDA to confirm this argument. We do not exclude the existence of smaller scale cold media being embedded within this structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

SENSEI: A Search for Diurnal Modulation in Sub-GeV Dark Matter Scattering

Dark matter particles with sufficiently large interactions with ordinary matter can scatter in the Earth’s atmosphere and crust before reaching an underground detector. This Earth-shielding effect can induce a directional dependence in the dark matter flux, leading to a sidereal daily modulation in the signal rate. We perform a search for such a modulation using data from the SENSEI experiment, targeting MeV-scale dark matter. We achieve nearly an order-of-magnitude improvement in sensitivity over previous direct-detection bounds for dark-matter masses below ∼ 1 MeV , assuming the standard halo model with a Maxwell-Boltzmann velocity distribution, and restrict the amplitude of a general daily modulation signal to be below 6.8 e / g / d .

Bloch, Itay M. [UC, Berkeley; LBL, Berkeley]↗
DOE OSTI2020

Scaling Behavior of a Turbulent Kinetic Energy Closure Scheme for the Stably Stratified Atmosphere: A Steady-State Analysis

Abstract We present a turbulent kinetic energy (TKE) closure scheme for the stably stratified atmosphere in which the mixing lengths for momentum and heat are not parameterized in the same manner. The key difference is that, while the mixing length for heat tends toward the stability independent mixing length for momentum in neutrally stratified conditions, it tends toward one based on the Brunt–Väisälä time scale and square root of the TKE in the limit of large stability. This enables a unique steady-state solution for TKE to be obtained, which we demonstrate would otherwise be impossible if the mixing lengths were the same. Despite the model’s relative simplicity, it is shown to perform reasonably well with observational data from the 1999 Cooperative Atmosphere–Surface Exchange Study (CASES-99) using commonly employed model constants. Analyzing the scaling behavior of the nondimensional velocity and potential temperature gradients, or of the stability (correction) functions, reveals that for large stability the present model scales in the same manner as the first-order operational scheme of Viterbo et al. Alternatively, it appears as a blend of two cases of the TKE closure scheme of Baas et al. Critically, because a unique steady-state TKE can be obtained, the present model avoids the nonphysical behavior identified in one of the cases of Baas et al.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Data and scripts associated with a manuscript on residence time distribution simulation in two 10-kilometer long river sections

This data package is associated with the publication “On the Transferability of Residence Time Distributions in Two 10-km Long River Sections with Similar Hydromorphic Units” submitted to the Journal of Hydrology (Bao et al. 2024).Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface, along with their residence time distributions (RTDs) in the subsurface, is crucial for managing water quality and ecosystem health in dynamic river corridors. However, directly simulating high-spatial resolution HEFs and RTDs can be a time-consuming process, particularly for watershed-scale modeling. Efficient surrogate models that link RTDs to hydromorphic units (HUs) may serve as alternatives for simulating RTDs in large-scale models. One common concern with these surrogate models, however, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this, we evaluated the HEFs and the resulting RTD-HU relationships for two 10-kilometer-long river corridors along the Columbia River, using a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework that we previously developed. Applying this framework to the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. This data package includes the model inputs files and the simulation results data. This data package contains 10 folders. The modeling simulation results data are in the folders 100H_pt_data and 300area_pt_data, for the study domain Hanford 100H and 300 area respectively. The remaining eight folders contain the scripts and data to generate the manuscript figures. The file-level metadata file (Bao_2024_Residence_Time_Distribution _flmd.csv) includes a list of all files contained in this data package and descriptions for each. The data dictionary file (Bao_2024_Residence_Time_Distribution _dd.csv) includes column header definitions and units of all tabular files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating the feasibility of tidal energy extraction at non-operational gas platforms and effects of sedimentation and sea ice in Cook Inlet (Abstract)

Littoral Power Systems (LPS) has been granted a FERC preliminary permit for the Upper Cook Inlet Tidal Energy Project in an area that includes existing non-producing natural gas platforms. LPS is working to understand the feasibility of a 2 MW tidal energy project and is considering multiple technologies, the viability of using the platforms to support deployment and operation of the technologies, as well as the environmental conditions that will interact with tidal energy devices. The proposed TEAMER work will conduct a modeling study to understand 1) current velocity and turbulence; 2) the distribution of sea ice trajectories around the platform; and 3) the likelihood of seabed erosion and deposition through an analysis of shear stress in the seabed near the platforms. The results of this work will contribute to determining the feasibility of the site for tidal energy development.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Theoretical Analysis of Fractional Viscoelastic Flow in Circular Pipes: Parametric Study

Pipe flow is one of the most commonly used models to describe fluid dynamics. The concept of fractional derivative has been recently found very useful and much more accurate in predicting dynamics of viscoelastic fluids compared with classic models. In this paper, we capitalize on our previous study and consider space-time dynamics of flow velocity and stress for fractional Maxwell, Zener, and Burgers models. We demonstrate that the behavior of these quantities becomes much more complex (compared to integer-order classical models) when adjusting fractional order and elastic parameters. We investigate mutual influence of fractional orders and consider their limiting value combinations. Finally, we show that the models developed can be reduced to classical ones when appropriate fractional orders are set.

Gritsenko, Dmitry (ORCID:0000000248181512)↗
DOE OSTI2021

Weather on Other Worlds. V. The Three Most Rapidly Rotating Ultra-cool Dwarfs

We present the discovery of rapid photometric variability in three ultra-cool dwarfs from long-duration monitoring with the Spitzer Space Telescope. The T7, L3.5, and L8 dwarfs have the shortest photometric periods known to date: 1.080{sub −0.005}{sup +0.004} hr, 1.14{sub −0.01}{sup +0.03} hr, and 1.23{sub −0.01}{sup +0.01} hr, respectively. We confirm the rapid rotation through moderate-resolution infrared spectroscopy, which reveals projected rotational velocities between 79 and 104 km s{sup −1}. We compare the near-infrared spectra to photospheric models to determine the objects’ fundamental parameters and radial velocities. We find that the equatorial rotational velocities for all three objects are ≳100 km s{sup −1}. The three L and T dwarfs reported here are the most rapidly spinning and likely the most oblate field ultra-cool dwarfs known to date. Correspondingly, all three are excellent candidates for seeking auroral radio emission and net optical/infrared polarization. As of this writing, 78 L-, T-, and Y-dwarf rotation periods have now been measured. The clustering of the shortest rotation periods near 1 hr suggests that brown dwarfs are unlikely to spin much faster.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Emulating galaxy and peculiar velocity clustering on non-linear scales

We explore the potential of cross-correlating galaxies and peculiar velocities on non-linear scales to enhance cosmological constraints. Leveraging the ABACUSSUMMIT simulation suite and the halo occupation distribution (HOD) formalism, we trained emulator models to describe the non-linear clustering of galaxies and velocities in redshift space. Our analysis demonstrates that combining galaxy and peculiar velocity clustering provides tighter constraints on both HOD and cosmological parameters, particularly on σ8 and w0. We further applied our models to realistic mock catalogues, reproducing the expected density and peculiar velocity errors of type-Ia supernovae, Tully-Fisher and fundamental plane measurements for the combined ZTF and DESI measurements. While systematic biases arise in the HOD parameters, the cosmological constraints remain unbiased, yielding a 3.8% precision measurement on fσ 8 compared to 4.7% when using galaxy clustering alone. We demonstrate that while combining tracers with realistic velocity measurements still yields an improvement, the gains are diminished, highlighting the need for further efforts to reduce velocity measurement uncertainties and correct observational systematics on small scales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Evaluating the Trustworthiness of Explainable Artificial Intelligence (XAI) Methods Applied to Regression Predictions of Arctic Sea Ice Motion

Abstract Recent advances in explainable artificial intelligence (XAI) methods show promise for understanding predictions made by machine learning (ML) models. XAI explains how the input features are relevant or important for the model predictions. We train linear regression (LR) and convolutional neural network (CNN) models to make 1-day predictions of sea ice velocity in the Arctic from inputs of present-day wind velocity and previous-day ice velocity and concentration. We apply XAI methods to the CNN and compare explanations to variance explained by LR. We confirm the feasibility of using a novel XAI method [i.e., global layerwise relevance propagation (LRP)] to understand ML model predictions of sea ice motion by comparing it to established techniques. We investigate a suite of linear, perturbation-based, and propagation-based XAI methods in both local and global forms. Outputs from different explainability methods are generally consistent in showing that wind speed is the input feature with the highest contribution to ML predictions of ice motion, and we discuss inconsistencies in the spatial variability of the explanations. Additionally, we show that the CNN relies on both linear and nonlinear relationships between the inputs and uses nonlocal information to make predictions. LRP shows that wind speed over land is highly relevant for predicting ice motion offshore. This provides a framework to show how knowledge of environmental variables (i.e., wind) on land could be useful for predicting other properties (i.e., sea ice velocity) elsewhere. Significance Statement Explainable artificial intelligence (XAI) is useful for understanding predictions made by machine learning models. Our research establishes trustability in a novel implementation of an explainable AI method known as layerwise relevance propagation for Earth science applications. To do this, we provide a comparative evaluation of a suite of explainable AI methods applied to machine learning models that make 1-day predictions of Arctic sea ice velocity. We use explainable AI outputs to understand how the input features are used by the machine learning to predict ice motion. Additionally, we show that a convolutional neural network uses nonlinear and nonlocal information in making its predictions. We take advantage of the nonlocality to investigate the extent to which knowledge of wind on land is useful for predicting sea ice velocity elsewhere.

Hoffman, Lauren [Scripps Institution of Oceanograp↗
DOE OSTI2020

Evaluating Implementations of the Immersed Boundary Method in the Weather Research and Forecasting Model

The terrain-following coordinate system used by many atmospheric models can cause numerical instabilities due to discretization errors as resolved terrain slopes increase and the grid becomes highly skewed. The immersed boundary (IB) method, which does not require the grid to conform to the terrain, has been shown to alleviate these errors, and has been used successfully for high-resolution atmospheric simulations over steep terrain, including vertical building surfaces. Since many previous applications of IB methods to atmospheric models have used very fine grid resolution (5 m or less), the present study seeks to evaluate IB method performance over a range of grid resolutions and aspect ratios. Two classes of IB algorithms, velocity reconstruction and shear stress reconstruction, are tested within the common framework of the Weather Research and Forecasting (WRF) Model. Performance is evaluated in two test cases, one with flat terrain and the other with the topography of Askervein Hill, both under neutrally stratified conditions. WRF-IB results are compared to similarity theory, observations, and native WRF results. Despite sensitivity to the location at which the IB intersects the model grid, the velocity reconstruction IB method shows consistent performance when used with a hybrid RANS/LES surface scheme. The shear stress reconstruction IB method is not sensitive to the grid intersection, but is less consistent and near-surface velocity errors can occur at coarse resolutions. This study represents an initial investigation of IB method variability across grid resolutions in WRF. Future work will focus on improving IB method performance at intermediate to coarse resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Physical effects on compact high-velocity clouds in the circumgalactic medium

ABSTRACT We numerically investigate the evolution of compact high-velocity clouds (CHVCs) passing through a hot, tenuous gas representing the highly ionized circumgalactic medium (CGM) by applying the adaptive-mesh refinement code flash. The model clouds start from both hydrostatic and thermal equilibrium and are in pressure balance with the CGM. Here, we present 14 models, divided into two mass categories and two metallicities each and different velocities. We allow for self-gravity and thermal conduction or not. All models experience mass diffusion, radiative cooling, and external heating leading to dissociation and ionization. Our main findings are (1) self-gravity stabilizes clouds against Rayleigh–Taylor instability, which is disrupted within 10 sound-crossing times without; (2) clouds can develop Jeans-instable regions internally even though they are initially below Jeans mass; (3) all clouds lose mass by ram pressure and Kelvin–Helmholtz instability; (4) thermal conduction substantially lowers mass-loss rates, by this, extending the clouds’ lifetimes, particularly, more than doubling the lifetime of low-mass clouds; (5) thermal conduction leads to continuous, filamentary stripping, while the removed gas is heated up quickly and mixes efficiently with the ambient CGM; (6) without thermal conduction the removed gas consists of dense, cool, clumpy fragments; (7) thermal conduction might prevent CHVCs from forming stars; and (8) clouds decelerated by means of drag from the ambient CGM form head-tail shapes and collapse after they reach velocities characteristic for intermediate-velocity clouds. Conclusively, only sophisticated modelling of CHVCs as non-homogeneous and non-isothermal clouds with thermal conduction and self-gravity explains observed morphologies and naturally leads to the suppression of star formation.

Sander, Bastian↗