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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Thunderstorms With the Greatest Lightning Densities on Earth

The most intense thunderstorms on Earth were surveyed using the comprehensive meteorological instrumentation on the Tropical Rainfall Measuring Mission (TRMM) satellite. Expansive land-based Mesoscale Convective Systems (MCSs) were consistently identified among the Earth's most intense thunderstorms, with their organization into many convective cells spanning a large areal extent permitting exceptional overall flash rates for these storms. In this study, we identify a new class of extreme thunderstorm. Lightning-dense thunderstorms are relatively compact convective storms whose concentrated lightning activity hinders our ability to accurately measure their flash rates. The top storms have a flash rate of one flash spanning many seconds, as there is insufficient separation to distinguish one flash from another. While any particularly active convective cell could be capable of producing high lightning densities, we find that thunderstorms with the greatest lightning densities on Earth are found in maritime thunderstorms that have not been appreciated in prior work due to the inaccurate flash rate measurements. These storms that are mostly found throughout the Gulf of Mexico and east of South Africa (among other coastal and oceanic regions) have measured TRMM proxies for convective intensity that rival the top MCS thunderstorms, but their horizontal and vertical dimensions are small by comparison. Thus, the necessary microphysical elements for electrification processes are more highly concentrated, enabling the observed extreme lightning densities.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

GEO Sounding Using Microwave Instruments

There are several microwave instruments in low Earth orbit (LEO) that are used for atmospheric temperature and humidity sounding in conjunction with companion IR sounders as well as by themselves. These instruments have achieved a certain degree of maturity and undergoing a redesign to minimize their size, mass, and power from the previous generation instruments. An example of these instruments is the AMSU-A series, now flying on POES and AQUA spacecraft with the IR sounders HIRS and AIRS. These older microwave instruments are going to be replaced by the ATMS instruments that will fly on NPP and NPOESS satellites with the CrIS sounder. A number of techniques learned from the ATMS project in instrument hardware design and data processing are directly applicable to a similar microwave sounder on a geosynchronous platform. These techniques can significantly simplify the design of a Geostationary orbit (GEO) microwave instrument, avoiding costly development and minimizing the risk of not being able to meet the scientific requirements. In fact, some of the 'enabling' technology, such as the use of MMIC microwave components (which is the basis for the ATMS' much reduced volume) can be directly applied to a GEO sounder. The benefits of microwave sounders are well known; for example, they penetrate non-precipitating cloud cover and allow for use of colocated IR observations in up to 80% cloud cover. The key advantages of a microwave instrument in GEO will be the ability to provide high temporal resolution as well as uniform spatial resolution and extend the utility of a colocated advanced IR sounder to cases in which partial cloud cover exists. A footprint of the order of 100 km by 100 km resolution with hemispherical coverage within one hour can be easily achieved for sounding channels in the 50 to 59 GHz range. A GEO microwave sounder will also allow mesoscale sampling of select regions.

Shiue, James↗
DOE OSTI2023

Revisiting Interior Water Mass Responses to Surface Forcing Changes and the Subsequent Effects on Overturning in the Southern Ocean

Abstract Two coupled climate models, differing primarily in horizontal resolution and treatment of mesoscale eddies, were used to assess the impact of perturbations in wind stress and Antarctic ice sheet (AIS) melting on the Southern Ocean meridional overturning circulation (SO MOC), which plays an important role in global climate regulation. The largest impact is found in the SO MOC lower limb, associated with the formation of Antarctic Bottom Water (AABW), which in both models is enhanced by wind and weakened by AIS meltwater perturbations. Even though both models under the AIS melting perturbation show similar AABW transport reductions of 4–5 Sv (50%–60%), the volume deflation of AABW south of 30°S is four times greater in the higher resolution simulation (−20 vs. −5 Sv). Water mass transformation (WMT) analysis reveals that surface‐forced dense water formation on the Antarctic shelf is absent in the higher resolution and reduced by half in the lower resolution model in response to the increased AIS melting. However, the decline of the AABW volume (and its inter‐model difference) far exceeds the surface‐forced WMT changes alone, which indicates that the divergent model responses arise from interactions between changes in surface forcing and interior mixing processes. This model divergence demonstrates an important source of uncertainty in climate modeling, and indicates that accurate shelf processes together with scenarios accounting for AIS melting are necessary for robust projections of the deep ocean's response to anthropogenic forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

What Drives Upper-Ocean Temperature Variability in Coupled Climate Models and Observations?

Abstract A key question in climate modeling is to what extent sea surface temperature and upper-ocean heat content are driven passively by air–sea heat fluxes, as opposed to forcing by ocean dynamics. This paper investigates the question using a climate model at different resolutions, and observations, for monthly variability. At the grid scale in a high-resolution climate model with resolved mesoscale ocean eddies, ocean dynamics (i.e., ocean heat flux convergence) dominates upper 50 m heat content variability over most of the globe. For deeper depths of integration to 400 m, the heat content variability at the grid scale is almost totally controlled by ocean heat flux convergence. However, a strong dependence on spatial scale is found—for the upper 50 m of ocean, after smoothing the data to around 7°, air–sea heat fluxes, augmented by Ekman heat transports, dominate. For deeper depths of integration to 400 m, the transition scale becomes larger and is above 10° in western boundary currents. Comparison of climate model results with observations show that the small-scale influence of ocean intrinsic variability is well captured by the high-resolution model but is missing from a comparable model with parameterized ocean-eddy effects. In the deep tropics, ocean dynamics dominates in all cases and all scales. In the subtropical gyres at large scales, air–sea heat fluxes play the biggest role. In the midlatitudes, at large scales >10°, atmosphere-driven air–sea heat fluxes and Ekman heat transport variability are the dominant processes except in the western boundary currents for the 400 m heat content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗
DOE OSTI2024

Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields

Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.

36 MATERIALS SCIENCE↗
NASA NTRS2021

The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity is an ESA initiative originally meant to support and widen the uptake of Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Starting in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data, supporting studies on enhanced validation and scientific process over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: gathering all the data required to exploit satellite sea surface salinity data, systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. The Salinity Pi-MEP is becoming a reference hub for the validation of satellite sea surface salinity missions by providing valuable information on satellite products (SMOS, Aquarius, SMAP), an extensive in situ database (e.g., Argo, thermosalinographs, moorings, drifters) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc.). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools (automatic, user-driven) of the platform are described in detail in this paper. Several dedicated scientific case studies involving satellite SSS data are also systematically monitored by the platform, including major river plumes, mesoscale signatures in boundary currents, high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific. Since 2019, a partnership in the Salinity Pi-MEP project has been agreed between ESA and NASA to enlarge focus to encompass the entire set of satellite salinity sensors. The two agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from the SPURS campaigns

ocean↗
DOE OSTI2019

How lasing happens in CsPbBr 3 perovskite nanowires

Lead halide perovskites are emerging as an excellent material platform for optoelectronic processes. There have been extensive discussions on lasing, polariton formation, and nonlinear processes in this material system, but the underlying mechanism remains unknown. Here we probe lasing from CsPbBr 3 perovskite nanowires with picosecond (ps) time resolution and show that lasing originates from stimulated emission of an electron-hole plasma. We observe an anomalous blue-shifting of the lasing gain profile with time up to 25 ps, and assign this as a signature for lasing involving plasmon emission. The time domain view provides an ultra-sensitive probe of many-body physics which was obscured in previous time-integrated measurements of lasing from lead halide perovskite nanowires.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Evaluating the grain-scale deformation behavior of a single-phase FCC high entropy alloy using synchrotron high energy diffraction microscopy

We report although the deformation behavior of high-entropy alloys (HEAs) has been extensively studied at the macroscale, many important properties have yet to be explored for these alloys at the microscale, thus hampering accurate prediction of damage and failure processes. Synchrotron high-energy diffraction microscopy (HEDM) and fast-Fourier transform-based crystal plasticity modeling was conducted to investigate the three-dimensional (3D) grain-resolved micromechanical response for approximately 1,900 constituent grains within a single-phase FCC HEA up to 1% applied strain. The evolution of grain-resolved elastic strains, lattice reorientations, and maximum resolved shear stresses (mRSS) were evaluated to quantify elastic, yield, and fully plastic behavior. Overall, the initial critical resolved shear stress (CRSS), determined via in situ HEDM and companion modeling, was found to be > 20% higher than estimated using the classical polycrystalline Taylor factor (M = 3.06). However, a descriptive parameter based on the average grain-resolved Taylor factor ($\overline{M}$) was found to show excellent agreement with plastic yielding behavior observed within HEDM datasets. Noticeable deviations in HEDM lattice reorientations compared to both EVP-FFT simulations and classical predictions for FCC polycrystals were discovered, highlighting the complexity in correlating local lattice reorientations, Taylor, and Schmid factors with plastic response for this material at the grain-scale. Therefore, it is anticipated that the overall trends and parameter identification of 3D grain-resolved properties in this study can serve as an important foundation for continued mesoscale investigation on both well-established and newly developed Cantor-like HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

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.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Coarse, Intermediate and High Resolution Numerical Simulations of the Transition of a Tropical Wave Critical Layer to a Tropical Storm

Recent work has hypothesized that tropical cyclones in the deep Atlantic and eastern Pacific basins develop from within the cyclonic Kelvin cat's eye of a tropical easterly wave critical layer located equatorward of the easterly jet axis. The cyclonic critical layer is thought to be important to tropical cyclogenesis because its cat's eye provides (i) a region of cyclonic vorticity and weak deformation by the resolved flow, (ii) containment of moisture entrained by the developing flow and/or lofted by deep convection therein, (iii) confinement of mesoscale vortex aggregation, (iv) a predominantly convective type of heating profile, and (v) maintenance or enhancement of the parent wave until the developing proto-vortex becomes a self-sustaining entity and emerges from the wave as a tropical depression. This genesis sequence and the overarching framework for describing how such hybrid wave-vortex structures become tropical depressions/storms is likened to the development of a marsupial infant in its mother's pouch, and for this reason has been dubbed the "marsupial paradigm". Here we conduct the first multi-scale test of the marsupial paradigm in an idealized setting by revisiting the Kurihara and Tuleya problem examining the transformation of an easterly wave-like disturbance into a tropical storm vortex using the WRF model. An analysis of the evolving winds, equivalent potential temperature, and relative vertical vorticity is presented from coarse (28 km), intermediate (9 km) and high resolution (3.1 km) simulations. The results are found to support key elements of the marsupial paradigm by demonstrating the existence of rotationally dominant region with minimal strain/shear deformation near the center of the critical layer pouch that contains strong cyclonic vorticity and high saturation fraction. This localized region within the pouch serves as the "attractor" for an upscale "bottom up" development process while the wave pouch and proto-vortex move together.

Montgomery, M. T.↗
NASA NTRS2012

A FIRE-ACE/SHEBA Case Study of Mixed-Phase Arctic Boundary Layer Clouds: Entrainment Rate Limitations on Rapid Primary Ice Nucleation Processes

Observations of long-lived mixed-phase Arctic boundary layer clouds on 7 May 1998 during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)Arctic Cloud Experiment (ACE)Surface Heat Budget of the Arctic Ocean (SHEBA) campaign provide a unique opportunity to test understanding of cloud ice formation. Under the microphysically simple conditions observed (apparently negligible ice aggregation, sublimation, and multiplication), the only expected source of new ice crystals is activation of heterogeneous ice nuclei (IN) and the only sink is sedimentation. Large-eddy simulations with size-resolved microphysics are initialized with IN number concentration N(sub IN) measured above cloud top, but details of IN activation behavior are unknown. If activated rapidly (in deposition, condensation, or immersion modes), as commonly assumed, IN are depleted from the well-mixed boundary layer within minutes. Quasi-equilibrium ice number concentration N(sub i) is then limited to a small fraction of overlying N(sub IN) that is determined by the cloud-top entrainment rate w(sub e) divided by the number-weighted ice fall speed at the surface v(sub f). Because w(sub c)< 1 cm/s and v(sub f)> 10 cm/s, N(sub i)/N(sub IN)<< 1. Such conditions may be common for this cloud type, which has implications for modeling IN diagnostically, interpreting measurements, and quantifying sensitivity to increasing N(sub IN) (when w(sub e)/v(sub f)< 1, entrainment rate limitations serve to buffer cloud system response). To reproduce observed ice crystal size distributions and cloud radar reflectivities with rapidly consumed IN in this case, the measured above-cloud N(sub IN) must be multiplied by approximately 30. However, results are sensitive to assumed ice crystal properties not constrained by measurements. In addition, simulations do not reproduce the pronounced mesoscale heterogeneity in radar reflectivity that is observed.

Fridlin, Ann↗
DOE OSTI2024

Assessment of Storm-Associated Precipitation and Its Extremes Using Observational Data Sets and Climate Model Short-Range Hindcasts

Heavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio-economic loss. Here, in this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short-range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short-range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm-associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon-based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy-precipitating storms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Molecular-scale Understanding of Selective Oxidative Transformations of Alcohols Promoted by Au and Au-based Alloys

This project developed a molecular-scale mechanistic framework for complex selective oxidation of alcohols and amines on O-covered Au and Ag-Au alloys that guides the design of selective and energy efficient processes. Our work has led to the discovery of new classes of reactions. We have also bridged a wide range of pressures and materials complexity by demonstrating catalytic activity using nanoporous Au catalysts. The selective oxidation of alcohols with each other and with other reactants, such as CO or amines, were focused on in this work because it is a key technology for large-scale chemical synthesis. Theory and experiment were combined to understand selective oxidation reactions on Au. Significant accomplishments are: (i) development of molecular-scale mechanisms for selective alcohol oxidation over Au surfaces; (ii) discovery of two new classes of reactions on O/Au—amide synthesis from amines and aldehydes and carbonylation of alcohols; and, (iii) demonstration that the mechanisms derived from our fundamental work predict the conditions for efficient catalysis using nanoporous Au catalysts under flow conditions at atmospheric pressure. This work has made an unprecedented connection between fundamental surface science studies and their implementation under catalytic conditions. This research fits squarely in the DOE-BES mission articulated in several BES Basic Research Needs (BRN) reports. “Catalysis for Energy” emphasizes the need to fabricate, design, characterize, and assemble new structures, including nanoscale alloys, and to understand and model their chemical behavior for energy-related applications. Our studies of nanoporous materials also exploit unique mesoscale phenomena to address complex energy-related issues (http://www.meso2012.com/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

WIND Toolkit Long-Term Ensemble Dataset

WIND Toolkit Long-term Ensemble Dataset (WTK-LED), an updated version of the meteorological WIND Toolkit, is a meteorological dataset providing high-resolution time series, including interannual variability and model uncertainty of wind speed at every modeling grid point to indicate ranges of possible wind speeds. The data were produced using the Weather Research and Forecasting Model (WRF). The vertical grid used in WTK-LED includes many vertical layers in the atmospheric boundary layer to provide information of atmospheric quantities across the rotor layer of utility scale and distributed wind turbines. The WTK-LED includes: (1) Numerical simulations of wind speed and other meteorological variables covering the contiguous United States (CONUS) and Alaska, with high-resolution (5-minute [min], 2-kilometer [km]) data for 3 years (2018-2020): WTK-LED CONUS, WTK-LED Alaska. (2) Climate simulations from Argonne National Laboratory covering North America, including Alaska, Canada, and most of Mexico and the Caribbean islands. These simulations complement the new WTK-LED to offer a 4-km, hourly dataset covering 20 years (2001-2020): WTK-LED Climate. (3) Specific long-term, high-resolution offshore simulations have been conducted separately for the U.S. coasts, Hawaii, and the Great Lakes, leading to the 2023 National Offshore Wind dataset: NOW-23. The data for Hawaii include land-based data and are part of WTK-LED Hawaii. Because the accuracy of simulations from a mesoscale model, such as WRF, varies depending on the location and weather situation, and can reach up to several m/s for wind speed, we provide simulated wind speed uncertainty estimates to the community to be used in conjunction with the deterministic model simulations. This dataset was developed to satisfy a wide group of stakeholders across various wind energy disciplines, including but not limited to stakeholders in the distributed and utility scale wind industry, the new emerging airborne wind energy field, grid integration, power systems modeling, environmental modeling, and researchers in academia, and to close some of the gaps that current public datasets have. Based on our validation results to date, we suggest use cases and applications for each dataset of the WTK-LED as shown in "WTK-LED Use Cases" resource below.

Array↗
DOE OSTI2022

Electrophoretic Deposition of Platinum Nanoparticles using Ethanol-Water Mixtures Significantly Reduces Neural Electrode Impedance

We report platinum electrodes are critical components in many biomedical devices, an important example being implantable neural stimulation or recording electrodes. However, upon implantation, scar tissue forms around the electrode surface, causing unwanted deterioration of the electrical contact. We demonstrate that sub-monolayer coatings of platinum nanoparticles (PtNPs) applied to 3D neural electrodes by electrophoretic deposition (EPD) can enhance the electrode's active surface area and significantly lower its impedance. In this work we use ethanol-water mixtures as the EPD solvent, in contrast to our previous studies carried out in water. We show that EPD coating in 30 vol.% ethanol improves the device's electrochemical performance. Computational mesoscale multiparticle simulations were for the first time applied to PtNP-on-Pt EPD, revealing correlations between ethanol concentration, electrochemical properties, and coating homogeneity. Thereto, this optimum ethanol concentration (30 vol.%) balances two opposing trends: (i) the addition of ethanol reduces water splitting and gas bubble formation, which benefits surface coverage, and (ii) increased viscosity and reduced permittivity occur at high ethanol concentrations, which impair the coating quality and favoring clustering. A seven-fold increase in active surface area and significantly reduced in vitro impedance of the nano-modified neural stimulation electrode surfaces highlight the influence of ethanol-water mixtures in PtNP EPD.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Amphiphile Organization in Organic Solutions: An Alternative Explanation for Small-Angle X-ray Scattering Features in Malonamide/Alkane Mixtures

In this work, the role of different intermolecular interactions in the aggregation of amphiphiles in an organic solvent is studied for systems of relevance to liquid-liquid extraction (LLE), a chemical process used to selectively recover metals from complex mixtures. Of specific interest is the role, or lack thereof, of hydrogen bonding, which is often assumed to be a main driver of the organic phase structural organization that has been linked to separation efficacy. Toward that end, a series of malonamide extractants in n-dodecane have been studied in the absence of any extracted aqueous solutes, including water. The series of extractants includes N,N'-dimethyl-N,N'-dibutyltetradecylmalonamide (DMDBTDMA), two of its homologs, and N,N'-dimethyl-N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). This simplified model LLE system enables systematic investigation of the role of dipole-dipole and alkyl tail steric interactions in amphiphile aggregation. Small-angle X-ray scattering (SAXS) profiles computed from molecular dynamics trajectories are in good agreement with experimental SAXS data. Molecular dynamics simulations show that malonamide aggregation results from dipole-driven self-association and lacks characteristic aggregate sizes. Mid-q correlation peaks in the SAXS profiles emerge at high concentration for each malonamide. In those densely packed solutions, the correlation peaks are observed to result from alkyl tail-induced spacing between electron-rich polar head groups, with peak positions determined by the different alkyl tail lengths present in the malonamide molecule. This explanation of the SAXS correlation peaks contrasts with the prevailing literature, which attributes mesoscale features observed in small-angle scattering to the formation of microemulsions. Instead, this work finds that these features are present in the absence of water or any reverse micellar organization of the malonamides. As such, molecular-scale malonamide self-association and packing, rather than microemulsion-based colloidal-scale descriptions, is a more appropriate framework for these LLE systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗