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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Connectivity between Static Field and Continuous Wave Field Effects on Excitation-Induced H 2 Activation

Due to the tremendous applications of the plasmon resonance excitation process, such as improvements in catalytic efficiency due to plasmonic enhancement and/or hot-electron processes, understanding the mechanism behind these processes has become a popular topic in recent years. In this work, we focus on unraveling the mechanism of excitation-induced H 2 activation using a simplified triangular Au 6 /Ag 6 cluster to investigate the effects of the electric field on electron redistribution and bond activation. We applied both static and continuous wave fields to investigate how these fields affect the systems. Geometrical changes (such as bond lengthening), molecular orbital reordering (affecting the relative energies of orbitals corresponding to hot-electron and charge-transfer excited states), and electronic charge redistribution between the cluster and the adsorbate occur upon application of a static electric field. To study H 2 activation, we apply Ehrenfest dynamics with real-time time-dependent density functional theory and examine how different excitation frequencies and polarizations affect bond activation. Moreover, electron-only dynamics are examined with real-time time-dependent density functional theory, and the time-dependent variations in the orbital populations and electronic transitions provide information about the excitation and relaxation processes of hot electrons with applied electric fields. Here, the static field results represent structures that can be accessed during the evolution of the systems when applying continuous wave fields. Through these studies, the effects of static and continuous wave field effects on plasmon-induced H 2 activation can be understood.

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

Photoluminescence Switching in Quantum Dots Connected with Carboxylic Acid and Thiocarboxylic Acid End-Group Diarylethene Molecules

We contrast the switching of photoluminescence (PL) of PbS quantum dots (QDs) cross-linked with photochromic diarylethene molecules with different end groups, 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] ( 1C ) and 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenethiocarboxylic acid] ( 2T ). Our results show that the QDs cross-linked with the carboxylic acid end group molecules ( 1C ) exhibit a greater amount of switching in photoluminescence intensity compared to QDs cross-linked with the thiocarboxylic acid end group ( 2T ). We also demonstrate that regardless of the molecule used, greater switching amounts are observed for smaller quantum dots. Varying these parameters allows for the fabrication of photoswitches with tunable PL change. We relate these observations to the differences in the HOMO energy levels between the QDs and the photochromic molecules. Our findings demonstrate how the size of the QDs and the energy levels of the linker ligands influences the charge tunneling rate and thus the PL switching performance in tunneling-based photoswitches.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Characterizing Hydrated Polymers via Dielectric Relaxation Spectroscopy: Connecting Relative Permittivity, State of Water, and Salt Transport Properties of Sulfonated Polysulfones

Sulfonated polysulfone is a promising membrane material for separation and energy generation processes that rely on membranes to control the rates of small-molecule (e.g., water and ions) transport. The interactions among water molecules, ions, and the sulfonate groups in these polymers play a key role in controlling these rates of transport, but much remains unknown about these fundamental interactions in sulfonated polymers. In this study, we used dielectric relaxation spectroscopy to characterize water molecule dynamics in sulfonated polysulfone and Nafion. We found that the charged sulfonate groups contribute to a restriction of water molecule dynamics (i.e., a reduction in the characteristic time scale of dipolar motions) in a manner that is governed by the concentration and nature (i.e., conjugate base strength) of the sulfonate group. Additionally, we develop strategies to use these data to aid in modeling ion transport in sulfonated polysulfone. These results may be useful to guide engineering strategies for polymeric membranes.

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

Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole–dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. In conclusion, this study enables the ability to predict the structure–property relations for PAN and analogues with sustainable ab initio accuracy across scales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Operando Surface-Enhanced Infrared Spectroscopy Connects Interfacial Dynamics with Reaction Kinetics During Electrochemical CO 2 Reduction on Copper

The reaction microenvironment plays a key role in dictating the selectivity of electrochemical CO 2 reduction. However, understanding the chemical nature of this microenvironment under operating conditions remains a substantial challenge. For this study, we employed attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) in operando for simultaneous measurements of reaction kinetics and concentrations of reactants and intermediates at the reaction interface, all under controlled mass transport conditions. These operando measurements enable direct correlations between the reaction microenvironment, mass transport, and kinetics for a Cu electrocatalyst, such as higher local concentrations of CO 2 under faster mass transport corresponding to higher rates of CO 2 reduction. We observed that faster mass transport decreased the *CO coverage at less negative potentials (-0.6 V RHE ) and increased the *CO coverage at more negative potentials (-1.1 V RHE ). We developed a transport-coupled kinetic model that captures these spectroscopic observations and provides insight into the processes controlling interfacial concentrations of reactants and intermediates, aiding future efforts toward tailoring reaction microenvironments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Connections Between Mean North Pacific Circulation and Western US Precipitation Extremes in a Warming Climate

Abstract Extreme precipitation has widespread impacts over the western US (WUS), which are expected to be exacerbated in the future given thermodynamically driven increases in atmospheric moisture and shifts in atmospheric circulation patterns. However, internal climate variability complicates how these factors affect future projections of precipitation changes. In this study, we investigate late 21st‐century changes in mean‐state responses over the North Pacific Ocean and associated WUS precipitation extremes using the Multi‐Model Large Ensemble Archive, which is a recent and valuable resource to disentangle the effects of model structural differences from internal variability. We found that inter‐model differences in precipitation extremes over the WUS are large: from south to north (here, from California to Washington), models show different levels of increases for both the frequency and intensity of heavy precipitation. In general, the Pacific Northwest sees a more consistent signal than California. We show that wet‐season mean circulation influences extreme precipitation, by using a decomposition of the relative contributions of thermodynamic (atmospheric humidity) and dynamic (large‐scale circulation) driven changes. The thermodynamic contribution dominates, however, the dynamic contribution varies with latitude and differs substantially between model ensembles. Inter‐model differences affect the spread in not only the magnitude, but also the sign of the dynamic contribution. This implies that mean circulation changes contribute to uncertainty in quantifying the regional structure of concentrated moisture flux and future extreme events. This result highlights the need to more accurately constrain projected North Pacific coupled circulation changes to narrow the spread in projections of future precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Role of Regional Connections in Planning for Future Power System Operations Under Climate Extremes

Identifying the sensitivity of future power systems to climate extremes must consider the concurrent effects of changing climate and evolving power systems. We investigated the sensitivity of a Western U.S. power system to isolated and combined heat and drought when it has low (5%) and moderate (31%) variable renewable energy shares, representing historic and future systems. We used an electricity operational model combined with a model of historically extreme drought (for hydropower and freshwater-reliant thermoelectric generators) over the Western U.S. and a synthetic, regionally extreme heat event in Southern California (for thermoelectric generators and electricity load). We found that the drought has the highest impact on summertime production cost (+10% to +12%), while temperature-based deratings have minimal effect (at most +1%). The Southern California heat wave scenario impacting load increases summertime regional net imports to Southern California by 10-14%, while the drought decreases them by 6-12%. Combined heat and drought conditions have a moderate effect on imports to Southern California (-2%) in the historic system and a stronger effect (+8%) in the future system. Southern California dependence on other regions decreases in the summertime with the moderate increase in variable renewable energy (-34% imports), but hourly peak regional imports are maintained under those infrastructure changes. By combining synthetic and historically driven conditions to test two infrastructures, we consolidate the importance of considering compounded heat wave and drought in planning studies and suggest that region-to-region energy transfers during peak periods are key to optimal operations under climate extremes.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Ice Nucleating Particle Connections to Regional Argentinian Land Surface Emissions and Weather During the Cloud, Aerosol, and Complex Terrain Interactions Experiment

Abstract Here, we present a multi‐season study of ice‐nucleating particles (INPs) active via the immersion freezing mechanism, which took place in north‐central Argentina, a worldwide hotspot for mesoscale convective storms. INPs were measured untreated, after heating to 95°C, and after hydrogen peroxide digestion. No seasonal cycle of INP concentrations was observed. Heat labile INPs, which we define as “biological” herein, dominated the population active at −5 to −20°C, while non‐heat‐labile organic INPs (decomposed by peroxide) dominated at lower temperatures, from −20 to −28°C. Inorganic INPs (remaining after peroxide digestion), were minor contributors to the overall INP activity. Biological INP concentration active around −12°C peaked during rain events and under high relative humidity, reflecting emission mechanisms independent of the background aerosol concentration. The ratio of non‐heat‐labile organic and inorganic INPs was generally constant, suggesting they originated from the same source, presumably from regional arable topsoil based on air mass histories. Single particle mass spectrometry showed that soil particles aerosolized from a regionally common agricultural topsoil contained known mineral INP sources (K‐feldspar and illite) as well as a significant organic component. The INP activity observed in this study correlates well with agricultural soil INP activities from this and other regions of the world, suggesting that the observed INP spectra might be typical of many arable landscapes. These results demonstrate the strong influence of regional continental landscapes, emitting INPs of types that are not yet well represented in global models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Weather Systems Connecting Modes of Climate Variability to Regional Hydroclimate Extremes

Abstract Weather system clustering provides a high‐level summary of regional meteorological conditions. Most quantitative clustering schemes focus on precipitation alone, which does not sufficiently describe the meteorological conditions driving hydroclimate variability. This study presents the Weather Anomaly Clustering (WAC‐hydro), which extends the existing capability of predicting weather systems to predicting hydroclimate variability. Focusing on both precipitation and temperature predictions, WAC‐hydro identifies 12 clusters of daily weather anomaly modes in the US Pacific Northwest Puget Sound region during 1981–2020. The influence of El Niño‐Southern Oscillation and Madden‐Julian Oscillation on regional precipitation can be well approximated by their modulation on the weather clusters. Within each weather cluster, local factors such as topography only play a secondary role in the hydrologic variability. The weather clusters highlight two types of flood‐inducing regional weather conditions, one causing floods by inducing positive precipitation anomalies and the other causing floods through combined precipitation and temperature‐induced rain‐on‐snow effect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.

60 APPLIED LIFE SCIENCES↗