S-MODE Saildrone
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
These data are collected by NASA as part of the Sub-Mesoscale Ocean Dynamics Experiment (https://espo.nasa.gov/s-mode), providing observations of submesoscale (1-10 km) processes.
The behavior of highly concentrated electrolytes departs radically from the dilute-solution theory, yet the molecular origin of this transformation remains unresolved. Here, we identify the conformational isomerization of molecular ions as a decisive, previously unrecognized control parameter governing structure and transport in crowded aqueous electrolytes. Across a series of fluorosulfonimide anions, we show that increasing concentration drives a collective shift from extended transoid to compact cisoid conformers, revealed by small-angle X-ray scattering, vibrational spectroscopy, pulsed-field gradient NMR, and molecular dynamics simulations. This conformational transition triggers a collapse of the hydrogen-bonded water network and the emergence of densely packed ionic domains with confined water, producing a qualitative change in Li+ transport from solvent-mediated diffusion to network-confined hopping. Anion size and asymmetry systematically tune the onset of this transition, demonstrating that molecular geometry dictates mesoscale organization and dynamics in the ion-rich regime. Our results establish ion conformation, not merely composition or coordination, as a fundamental thermodynamic variable in concentrated solutions, providing a chemical framework that unifies solvation structure and transport in water-in-salt electrolytes and suggesting new principles for designing dense ionic media.
The development of a microjoule-class pulsed Doppler lidar and deployment of this compact system on mobile platforms such as aircraft, ships, or trucks have opened a new opportunity to characterize the dynamics of complex mesoscale wind flows. The PickUp-based Mobile Atmospheric Sounder (PUMAS) truck-based lidar system was recently used during the American Wake Experiment (AWAKEN) to assess the general structure of boundary layer (BL) wind and turbulence around wind turbines in central Oklahoma. Wind speed profiles averaged over PUMAS transects influenced by the operating turbines (waked flow) show a 1–2 m s −1 reduction compared to mean undisturbed (free flow) wind speed profiles. Spatial variability in wind speed was observed in time–height cross-sections at different distances from turbines. The wind speeds were about 9–12 m s −1 at 6 km distance compared to 5–7 m s −1 at the transects near the turbines. The PUMAS dataset from AWAKEN demonstrated the capability of the mobile Doppler lidar system to document spatial variability in wind flows at different distances from wind turbines and obtain quantitative estimates of wind speed reduction in the waked flow. The high-frequency, simultaneous measurements of the horizontal and vertical winds provide a new approach for characterizing dynamic processes critical for wind farm wake analyses.
Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.
Marine stratocumulus clouds play a central role in Earth's climate system by reflecting incoming solar radiation and exerting a strong cooling effect. Their organization into open and closed mesoscale cellular morphologies can be thought of as an example of bistable dynamics driven by aerosol–cloud interactions and mesoscale processes. From the perspective of non-equilibrium thermodynamics, these structures are an example of a far-from-equilibrium open system that continuously produces and exports entropy. While entropy production has been studied in idealized deep convective systems, it has not yet been quantified for shallow clouds. Here, we compute and decompose the internal entropy production of open- and closed-cell stratocumulus using an ensemble of large-eddy simulations. We show that the overall entropy production of stratocumulus is low, reflecting the limited vertical extent and corresponding reduced ability to utilize the energy fluxes at the system's boundaries. Moist processes dominate the overall irreversibility, which, combined with their low entropy production, leads to a mechanical efficiency about an order of magnitude smaller than in deep convective systems. Although the dominant irreversible processes differ between open- and closed-cell regimes, the distributions of total entropy production largely overlap across the ensemble, limiting the ability to distinguish the dynamics of individual cases based solely on total entropy production.
Hydrogels are three-dimensional networks of hydrophilic polymers often used as a simplified model of hydrated biological materials, from cartilaginous joints to the ocular tear film. However, the lubrication mechanisms of hydrogels remain poorly understood, partly due to their complex polymeric structure, which creates blurred interfaces during sliding that are challenging to study experimentally. In this study, we employ dissipative particle dynamics (DPD) to investigate the frictional behavior of a polymeric hydrogel network sliding against a solid wall in an explicit viscous solvent. This computational approach enables us to model hydrodynamic interactions and mesoscale polymer dynamics, capturing key aspects of hydrogel friction. Our simulations reveal that hydrogel friction is governed by the interplay between polymer relaxation and viscous shear, characterized by the Weissenberg number (Wi). At low Wi, friction coefficient remain nearly constant, dominated by polymer relaxation. However, at higher Wi, friction is dominated by viscous drag within a near-wall solvent layer, leading to a linear increase in friction coefficient with Wi. Furthermore, our results demonstrate an inverse relationship between the friction coefficient and the applied normal load, consistent with experimental observations. This work provides new insights into the fundamental tribological properties of hydrogels, shedding light on the micromechanics of hydrogel friction. Improving our understanding of hydrogel structure and dynamics under friction advances our knowledge of the mechanisms regulating biological lubrication in health and disease.
Abstract Midlatitude SSTs forced by mesoscale oceanic processes can affect the large-scale atmosphere, pointing to the ocean’s crucial role outside the tropics. Previous studies have shown oceanic mesoscale processes’ effect on global and regional climate variability. This study quantifies the local contribution of ocean dynamics to mixed-layer temperature across the globe by directly estimating the ocean heat flux divergence resolved by state-of-the-art ocean reanalysis, eddy-resolving, and eddy-parameterized versions of two U.S. national climate models and indirectly from air–sea flux satellite-based estimates. Our results show that the eddy-resolving climate simulations resolve mixed-layer temperature variances that are larger and closer to those inferred from observations than both their eddy-parameterized counterparts and ECCO over much of the extratropics. The observations and the eddy-resolving models indicate a more significant role of ocean dynamics in the mixed-layer temperature variability than the surface fluxes over most extratropics compared to their eddy-parameterized versions. A frequency domain analysis shows that the better-resolved ocean mesoscale and thermal gradients enhance the variance over a time scale from 2 months to 30 years. Results show agreement in the ocean’s contribution among satellite-based estimates, ocean reanalysis products, and ocean eddy-resolving simulations. At the same time, differences emerge for ECCO and the eddy-parameterized models, suggesting that surface fluxes account for a larger fraction of the mixed-layer temperature variability in most of the extratropics.
Mesoscale convective systems (MCS) and low-pressure systems (LPS) are both strongly associated with precipitation across the regions where they occur, particularly within global monsoon systems; however, their co-occurrence and its relationship to precipitation have not been systematically examined. Here, we use LPS and MCS trackers to detect compound MCS and LPS events in five monsoon regions and assess the association of this co-occurrence with anomalies of winds, precipitation, and other atmospheric variables. Additionally, we investigate the spatial distribution of precipitating MCS and LPS events. Our results show that most (∼60%) MCS and LPS co-occurrences are located in the lower latitudes, where they contribute up to 40% of annual precipitation. We find that compound events generally produce more extreme precipitation than MCS-only or LPS-only events. Furthermore, our assessment of the synoptic and mesoscale composites reveals that the underlying dynamics of compound events exhibit anomalously positive convective available potential energy and an anomalously low-pressure within the location of the event. In terms of the synoptic environment of the features, the compound MCS and LPS events are associated with inverted troughs in three out of five monsoon locations assessed.
This paper describes the atmospheric component of the US Department of Energy's Energy Exascale Earth System Model (E3SM) version 3. Significant updates have been made to the atmospheric physics compared to earlier versions. Specifically, interactive gas chemistry has been implemented, along with improved representations of aerosols and dust emissions. A new stratiform cloud microphysics scheme more physically treats ice processes and aerosol‐cloud interactions. The deep convection parameterization has been largely improved with sophisticated microphysics for convective clouds, making model convection sensitive to large‐scale dynamics, and incorporating the dynamical and physical effects of organized mesoscale convection. Improvements in aerosol wet removal processes and parameter re‐tuning of key aerosol and cloud processes have improved model aerosol radiative forcing. The model's vertical resolution has increased from 72 to 80 layers with the extra eight layers added in the lower stratosphere to better simulate the Quasi‐Biennial Oscillation. These improvements have enhanced E3SM's capability to couple aerosol, chemistry, and biogeochemistry and reduced some long‐standing biases in simulating tropical variability. Compared to its predecessors, the model shows a much stronger signal for the Madden‐Julian Oscillation, Kelvin waves, mixed Rossby‐gravity waves, and eastward inertia‐gravity waves. Aerosol radiative forcing has been considerably reduced and is now better aligned with community best estimates, leading to significantly improved skill in simulating historical temperature records. Its simulated mean‐state climate is largely comparable to E3SMv2, but with some notable degradation in shortwave cloud radiative effect, precipitable water, and surface wind stress, which will be addressed in future updates.
Project Goal and Objective. The demand for energy and for an upgraded energy infrastructure has steadily grown, as have the needs for energy independence and alternatives to our reliance on petroleum. Hydrogen is considered the most viable fuels for wide-scale implementation in the near future as it is less-polluting, non-toxic, and has more stored energy than petroleum. It is envisioned that hydrogen can eventually become the prime energy carrier, integrating the transportation, grid, and chemical sectors in a way that improves resiliency, diversifies feedstocks, and affords new economic opportunities. A key remaining challenge is the development materials with enhanced gravimetric and volumetric hydrogen storage capacities that offer a higher performance than compressed gas. These materials would eliminate the need for large-scale compression, thereby dramatically reducing the footprint and cost of gas storage. The high gravimetric and volumetric hydrogen capacities of complex hydrides has prompted an intensive investigation of the potential of this class of materials as hydrogen storage media over the past 25 years. Among the many complex hydrides that have been explored, magnesium borohydride, Mg(BH 4 ) 2 , has been found to possess the best combination of practical thermodynamic properties. These include a gravimetric H 2 density of 14.9 wt% H 2 and thermodynamics for the dehydrogenation of Mg(BH 4 ) 2 to MgB 2 (equation 1) (ΔH° = 39 kJ/mol H 2 , ΔS = 112 J/K mol H 2 ) which lie in the narrow window required Mg(BH 4 ) 2 $\Leftrightarrow$ MgB 2 + 4 H 2 (1) for reversibility under moderate pressure and temperature. However, overcoming the extremely slow kinetics of the reversible release of hydrogen by this material in the solid state is a daunting challenge. At temperatures greater than 400 °C, the borohydride releases up to 14 wt% hydrogen giving MgB 2 . We discovered that the direct re-hydrogenation of MgB 2 to Mg(BH 4 ) 2 can be accomplished under 950 bar H 2 at 400 °C. While this demonstrated that complete reversibility can be achieved, the conditions employed are far too extreme for commercial hydrogen storage applications. More recently, we found through US DOE funded research projects (EERE HyMARC and HySCOR), that hydrogen cycling, can be accomplish at much milder conditions upon modification of the borohydride or boride. Guided by these discoveries these discoveries, the objective of this research project was to obtain key information that will enable the development of a model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 . The ultimate goal of our efforts is to attain a model of this transformation that can be utilized to accelerate development further advanced materials. This project directly follows on discoveries that were made over the course of a US DOE, EERE HyMARC project that was focused on improvement of the hydrogen cycling kinetics of modified MgB 2 . We found that that mechanical milling with graphene results the desired, pronounced kinetic enhancement. The dramatic lowering of the conditions required for the hydrogenation of MgB 2 is a significant step towards overcoming its chemical inertness allowing its development as a practical onboard hydrogen storage material. However, the exact nature of the modification(s) of MgB 2 that is responsible for its activation towards hydrogenation is completely unknown. This situation is not unique, as efforts to develop hydrogen storage materials typically have a narrow focus rather than a comprehensive approach that takes atomic level bonding and structure; molecular dynamics; long range, nano- and mesoscale-structure and their interconnection all into account. The goal of this project was the development of a comprehensive, multi-scale computational model of reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 that can be utilized for development of higher performance versions of the modified material. Development of the model requires determination of: 1) the bulk, nano-scale, and meso-scale structural changes occurring at elevated pressure following mechano-chemical modification of MgB 2 ; 2) the reaction pathway of the reversible hydrogenation of MgB 2 to Mg(BH 4 ) 2 ; 3) the effect of elevated pressure and mechano-chemical modification on the chemical reaction pathways; 4) the interactions at solid-gas interfaces; and particle surfaces; and 5) the kinetics and thermodynamic parameters associated with each step of the hydrogenation reaction pathway. This investigation required advanced techniques as preliminary, standard XRD, 11 B NMR, and FTIR analysis showed no signs of material modification. In order to gain this level of understanding of modified MgB 2 , required the teaming of a diverse group of experts and state-of-the art experimental capabilities at the University of Hawaii at Manoa (UHM) and collaborating National Laboratories: Craig Jensen , Department of Chemistry (PI and Project Director), solid state, solution, and high pressure NMR spectroscopy; solid-state synthesis; and high pressure hydrogenation (collaboration with SNL); Godwin Severa , Hawaii Natural Energy Institute (co-PI) calorimetry; infrared and Raman spectroscopy (collaboration with NREL); Dera , high pressure X-ray diffraction including in situ experiments (collaboration with ANL); Hope Ishii , Hawaii Institute of Geophysics electron microscopy investigations (collaboration with LBNL); and Joe Brown , Mechanical Engineering , material electronic structure and electric field effects.
This study investigates the role of geometrically necessary dislocations (GNDs) and microstructure on void nucleation and growth in wrought and additively manufactured (AM) tantalum subjected to high-strain rate loading. Multi-modal 3D data was collected using TriBeam tomography to calculate GND densities and their spatial relationship to voids. A microstructural comparison between the wrought and AM samples identified distinct void shapes and locations, with intragranular voids and more spherical voids frequently observed in the AM dataset. Results indicate that voids preferentially form at both high-angle grain boundaries and low-angle subgrain boundaries, the latter of which are frequently observed in the AM material. Through a radial distribution analysis of all voids in the datasets, significant GND localization to near-void-surface regions was observed in both samples. 3D crystal plasticity simulations were employed to extend the experimental observations, revealing higher void growth rates in [111] oriented grains when compared to [001] grains. The simulations also suggest that GNDs can be generated as part of the void growth process, with more GND accumulation for growth in a [111] grain than a [001] grain. These findings provide valuable insights into the links between nanoscale void nucleation, mesoscale void growth, and microstructural effects in dynamically loaded tantalum.
The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport.
A new continuum-based mesoscale modeling approach for shock-induced chemical reactions (SICRs) in Ni+Al multilayers is demonstrated in Sandia’s shock physics hydrocode, CTH. The approach utilizes Arrhenius-type kinetics and artificial thermal conduction. Our work builds upon previous efforts to parameterize equations of state for Ni x Al y [J. Appl. Phys. 137, 075102 (2025)], as well as simulations of inert shocks in realistic 2D microstructures [J. Appl. Phys. 137, 225301 (2025)]. To calibrate the reaction kinetics, pairs of the reaction coordinate, R′, vs time are extracted from the molecular dynamics (MD) literature. Here, the MD-informed kinetics are used to simulate the dynamic evolution of pressure and temperature in 2D mesoscale simulations. Overall, the MD-informed kinetics obtained for planar interfaces are too slow, as initial reaction is not observed on a nanosecond time scale. Even with quasi-periodic shock focusing leading to the formation of so-called “hot-spots,” the hot spots are unable to grow and coalesce using the fitted Arrhenius rate constants. However, by increasing the rate constants by two orders of magnitude, SICRs are observed at a shock pressure near 30 GPa, which is supported by experiments. Consequently, these mesoscale simulations suggest that unresolved shear-based mechanical mixing might possibly account for the discrepancies in kinetic rates, with shock-generated intense perturbations, interfacial vortical flows, and elevated temperatures serving as favorable reaction conditions. Future work will calibrate a shear-dependent reaction rate from the MD simulations with realistic interfaces that are wavy, diffuse, and disordered.
Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.
Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.
Complex, multicomponent liquids with hierarchical structure and phase transitions are encountered in many natural and industrial processes, including in chemical separations. One notable example is aggregation and organic phase splitting in liquid–liquid extraction (LLE) of metal ions. While these two phenomena that have long been closely associated, a mechanistic link between mesoscale structure and the capacity-limiting organic phase splitting remains elusive due to complexity of these systems. Here, in this study, we combine small-angle X-ray scattering (SAXS), X-ray photon correlation spectroscopy (XPCS), and molecular dynamics simulation to reveal a comprehensive picture of structure at the nano- and mesoscale in these complex solutions. For the representative case of rare earth extraction from an acidic aqueous phase by a malonamide extractant in dodecane, we investigate a wide range of process-relevant extractant and acid concentrations to provide a complete picture of how aggregation depends on composition. We decompose organic phase structure from SAXS into two contributions, which together can capture the scattering at all compositions: composition fluctuations described by the Ornstein–Zernike equation at low wavenumber Q, and nanostructure modeled by a “pre-peak” at intermediate Q. The former contains information about the thermodynamics of demixing, while the latter reflects nanoscopic self-assembly of the extractant and extracted solutes. While fluctuations have typically not been considered in the literature, we find they in fact dominate the total structure for nearly all practical conditions. As only the fluctuations have a strong temperature response, we confirm this attribution with temperature-dependent SAXS measurements, including for extracted europium nitrate complexes. SAXS and XPCS measurements near the critical point find static and dynamic scaling consistent with theory. Overall, this new paradigm for understanding LLE organic phases connects composition, nanoscale, and mesoscale structuring to phase behavior, providing both a comprehensive picture of solution structure and a quantitative link between aggregation and third phase formation.