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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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249 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electrical monitoring of saline tracers to reveal subsurface flow pathways in a flat ditch-drained field

Time-lapse electrical resistivity imaging (ERI) combined with salt tracers can enhance our understanding of subsurface flow and transport in ditch-drained agroecosystems. In a nearly level field adjacent to a drainage ditch, we installed 192 electrodes in a 72-m2 plot along with five hydrometric stations to enable time-lapse ERI monitoring during storms. Immediately prior to a wintertime rainstorm, we applied 5 kg of KBr to a shallow trench located roughly 11 m upgradient from the ditch. Antecedent conditions prior to the storm were wet, assuring a hydrologically connected state that favored tracer dissolution and movement in the subsurface. We monitored the evolution of the tracer plume with ERI over a seven-day period. Four-dimensional (4D) delineation of precipitation and tracer transport using time-lapse ERI showed that the tracer plume moved preferentially downward through a discontinuity in the argillic horizon within the first 57 hrs. Over the following 79 hrs, the tracer plume exhibited steady, lateral movement towards the drainage ditch within a more permeable sandy horizon situated just below the argillic. A spatial moment analysis of logarithmic changes in conductivity in the sand layer revealed seepage velocities ranging from 0.0027 to 0.0482 m d-1; these values were positively correlated with hydraulic gradients, suggesting laminar flow processes typical of sandy aquifers. Increasing groundwater velocities with hydraulic gradients suggest that solute transfers from groundwater to ditch are likely to be faster in storms, especially during wet periods. Even so, predominantly slow lateral transport within the sandy horizon, even during storms, indicates that critical source areas of pollutant loss are likely within a few meters of the ditch.

Robinson, Judith L.↗
DOE OSTI2020

Experimental system for studying temperature gradient-driven fracture of oxide nuclear fuel out of reactor

Temperature gradients in ceramic light water reactor (LWR) uranium dioxide (UO 2 ) nuclear fuel pellets generate thermal stresses that cause fractures in the fuel beginning early in the life of fresh fuel. The combination of heating due to fission and forced convective cooling on the exterior of LWR fuel rods generates a temperature profile that is difficult to replicate outside the reactor environment. In the present study, a state-of-the-art experimental set-up using electrical heating to replicate fission heating was built and surrogate fuel materials such as ceria (CeO 2 ) were used to validate the system. Cracking experiments were conducted on these surrogates by inducing reactivity-initiated-accident (RIA) like temperature gradients in the pellets via induction and direct resistance heating. Induction heating was done using copper coils and molybdenum susceptors which heated the surrogates to a threshold temperature that is sufficiently high for the fuel material to conduct current. Thereafter, direct resistance heating was used by a D.C. power supply to introduce volumetric heating to replicate LWR operating conditions analogous to fission heating. The pellets were held against nickel electrodes and mounted on a boron nitride test-stand. All the tests were carried out in a stainless-steel vacuum chamber. Simultaneous real-time dual imaging of the surrogate pellet surface has been implemented using an optical and infrared camera system which will be mounted along axial and perpendicular directions to the pellet surface respectively. A beam-splitter was used to split the incoming radiation from the sample into two halves. While one of the beams is transmitted from the splitter through a bandpass filter to obtain optical images, the other beam is reflected from the splitter to the thermal camera to capture full field temperature gradients of the as fabricated pellet surface during crack initiation and propagation. In the current series of tests, a 2-color pyrometer was used for recording and comparing the surface and centerline temperatures of the surrogate pellets in lieu of the thermal camera. A LabVIEW data acquisition system has been set up for collecting useful data during experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling

Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

A computational pipeline to generate a synthetic dataset of metal ion sorption to oxides for AI/ML exploration

The charged mineral/electrolyte interfaces are ubiquitous in the surface and subsurface–including the surroundings of the geological disposal sites for radioactive waste. Therefore, understanding how ions interact with charged surfaces is critically important for predicting radionuclide mobility in the case of waste leakage. At present, the Surface Complexation Models (SCMs) are the most successful thermodynamic frameworks to describe ion retention by mineral surfaces. SCMs are interfacial speciation models that account for the effect of the electric field generated by charged surfaces on sorption equilibria. These models have been successfully used to analyze and interpret a broad range of experimental observations including potentiometric and electrokinetic titrations or spectroscopy. Unfortunately, many of the current procedures to solve and fit SCM to experimental data are not optimal, which leads to a non-transferable or non-unique description of interfacial electrostatics and consequently of the strength and extent of ion retention by mineral surfaces. Recent developments in Artificial Intelligence (AI) offer a new avenue to replace SCM solvers and fitting algorithms with trained AI surrogates. Unfortunately, there is a lack of a standardized dataset covering a wide range of SCM parameter values available for AI exploration and training–a gap filled by this study. Here, we described the computational pipeline to generate synthetic SCM data and discussed approaches to transform this dataset into AI-learnable input. First, we used this pipeline to generate a synthetic dataset of electrostatic properties for a broad range of the prototypical oxide/electrolyte interfaces. The next step is to extend this dataset to include complex radionuclide sorption and complexation, and finally, to provide trained AI architectures able to infer SCMs parameter values rapidly from experimental data. Here, we illustrated the AI-surrogate development using the ensemble learning algorithms, such as Random Forest and Gradient Boosting. These surrogate models allow a rapid prediction of the SCM model parameters, do not rely on an initial guess, and guarantee convergence in all cases.

Li, Chunhui↗
DOE OSTI2022

First-Principles Calculations of Thermoelectric Transport Properties of Quaternary and Ternary Bulk Chalcogenide Crystals

Chalcogenide crystals have a wide range of applications, especially as thermoelectric materials for energy conversion. Thermoelectric materials can be used to generate an electric current from a temperature gradient based on the Seebeck effect and based on the Peltier effect, and they can be used in cooling applications. Using first-principles calculations and semiclassical Boltzmann theory, we have computed the Seebeck coefficient, electrical conductivity, electronic thermal conductivity, power factor, and figure of merit of 30 chalcogenide crystals. A Quantum Espresso package is used to calculate the electronic properties and locate the Fermi level. The transport properties are then calculated using the BoltzTraP code. The 30 crystals are divided into two groups. The first group has four crystals with quaternary composition (A 2 BCQ 4 ) (A = Tl; B = Cd, Hg; C = Si, Ge, Sn; Q = S, Se, Te). The second group contains 26 crystals with the ternary composition (A’B’Q 2 ) (A’ = Ag, Cu, Au, Na; B’ = B, Al, Ga, In; Q = S, Se, Te). Among these 30 chalcogenide crystals, the results for 11 crystals: Tl 2 CdGeSe 4 , Tl 2 CdSnSe 4 , Tl 2 HgSiSe 4 , Tl 2 HgSnS 4 , AuBSe 2 , AuBTe 2 , AuAlTe 2 , AuGaTe 2 , AuInTe 2 , AgAlSe 2 , and AgAlTe 2 are revealed for the first time. In addition, temperature-dependent transport properties of pure and doped AgSbSe 2 and AgSbTe 2 crystals with dopant compositions of AgSb 0.94 Cd 0.06 Te 2 and AgSbTe 1.85 Se 0.15 were explored. These results provide an excellent database for bulk chalcogenides crucial for a wide range of potential applications in renewable energy fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Geomechanical and Hydrogeological Evaluation of a Shallow Hydraulic Fracture at the Devine Fracture Pilot Site, Medina County, Texas

UT-Austin’s Devine Fracture Pilot Site, 50 miles southwest of San Antonio, Texas, has been targeted for a comprehensive, multidisciplinary development of fracture diagnostic techniques that are cross-validated by ground-truth data acquisition near a recently created, 175-ft-deep, horizontal hydraulic fracture (Ahmadian et al. 2018 Demonstration of proof of concept of electromagnetic geophysical methods for high resolution illumination of induced fracture networks. In Proceedings of the SPE Hydraulic Fracturing Technology Conference and Exhibition, The Woodlands, Texas, USA, 23–25 January 2018. SPE-189858-MS.). To evaluate the fracture diagnostic methods at this site, we conducted injection tests with a predefined volumetric flow-rate profile, resembling a diagnostic fracture injection test on September 2020. Subsequently, we developed hydrogeological and geomechanical models based on flow-rate and bottomhole-pressure measurements. History-matching efforts using a simplified layer-cake hydrogeological model resulted in the field-scale formation permeability of 9.87 × 10 –15 m 2 (10 mD) and Darcy-scale fracture permeability. The analysis of the bottomhole pressure and injection-rate history showed that (1) the newly created horizontal fracture was closed adjacent to the injection well pre-injection and (2) the initial pump-pressure increase at a nominal volumetric injection rate led to near-well fracture reopening, fluid conductivity increase, and abrupt injection-rate increase. To overcome hydrogeological-model limitations of predicting fracture reopening throughout injection, we extended the modeling to a finite-element, poroelastic analysis of horizontal-fracture growth using a cohesive-zone model. Using this fracture-reopening model, we improved the history match of the transient-pressure response during the experiment by adjusting the hydromechanical properties. Furthermore, post-injection pressure transient analyses helped reduce uncertainty in the overburden-stress gradient, and the initial hydraulic-fracturing simulation verified the plausibility of achieving the surveyed propped fracture area.

02 PETROLEUM↗
DOE OSTI2024

Analytic Gradients for Equation-of-Motion Coupled Cluster with Single, Double, and Perturbative Triple Excitations

Understanding the process of molecular photoexcitation is crucial in various fields, including drug development, materials science, photovoltaics, and more. The electronic vertical excitation energy is a critical property, for example in determining the singlet-triplet gap of chromophores. However, a full understanding of excited-state processes requires additional explorations of the excited-state potential energy surface and electronic properties, which is greatly aided by the availability of analytic energy gradients. Owing to its robust high accuracy over a wide range of chemical problems, equation-of-motion coupled-cluster with single and double excitations (EOM-CCSD) is a powerful method for predicting excited state properties, and the implementation of analytic gradients of many EOM-CCSD (excitation energies, ionization potentials, electron attachment energies, etc.) along with numerous successful applications high- lights the flexibility of the method. In specific cases where a higher level of accuracy is needed or in more complex electronic structures, the inclusion of triple excitations becomes essential, for example, in the EOM-CCSD* approach of Saeh and Stanton. In this work, we derive and implement for the first time the analytic gradients of EOMEE-CCSD*, which also provides a template for analytic gradients of related ex- cited state methods with perturbative triple excitations. Here, the capabilities of analytic EOMEE-CCSD* gradients are illustrated by several representative examples.

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

Cryogenic thermal modeling of microwave high density signaling

Superconducting quantum computers require microwave control lines running from room temperature to the mixing chamber of a dilution refrigerator. Adding more lines without preliminary thermal modeling to make predictions risks overwhelming the cooling power at each thermal stage. In this paper, we investigate the thermal load of SC-086/50-SCN-CN semi-rigid coaxial cable, which is commonly used for the control and readout lines of a superconducting quantum computer, as we increase the number of lines to a quantum processor. We investigate the makeup of the coaxial cables, verify the materials and dimensions, and experimentally measure the total thermal conductivity of a single cable as a function of the temperature from cryogenic to room temperature values. We also measure the cryogenic DC electrical resistance of the inner conductor as a function of temperature, allowing for the calculation of active thermal loads due to Ohmic heating. Fitting this data produces a numerical thermal conductivity function used to calculate the static heat loads due to thermal transfer within the wires resulting from a temperature gradient. The resistivity data is used to calculate active heat loads, and we use these fits in a cryogenic model of a superconducting quantum processor in a typical Bluefors XLD1000-SL dilution refrigerator, investigating how the thermal load increases with processor sizes ranging from 100 to 225 qubits. We conclude that the theoretical upper limit of the described architecture is approximately 200 qubits. However, including an engineering margin in the cooling power and the available space for microwave readout circuitry at the mixing chamber, the practical limit is approximately 140 qubits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Microwave Heating-Induced Temperature Gradients in Liquid–Liquid Biphasic Systems

Microwaves (MWs) can enable the electrification and intensification of chemical manufacturing. They have been applied to various unit separations, such as drying, distillation, and extraction, entailing gas–liquid and solid–liquid systems. However, a limited quantitative understanding of MW-heated liquid–liquid biphasic systems related to extraction exists. This work measures the temporal and spatial temperature difference between an aqueous and an organic phase in batch and continuous microfluidic modes. We demonstrate permanent temperature differences between phases over 35 °C and spatiotemporal periodic and quasiperiodic oscillations modulated by the flow patterns. The temperature differences are primarily driven by the faster absorption rate of MW irradiation by the aqueous phase versus the slower heat transfer from the aqueous phase to the organic phase. These are amplified by low specific interfacial area and modifications of the electromagnetic field. We employ a multiphysics model to predict the temperature difference in a batch system. The model is in good agreement with the experiments. We demonstrate a strong effect of input power, dielectric properties of organic solvents, the volume of solvents, and the volume ratio between phases on the temperature difference. A simple analytical model describes the temperature difference and provides design principles. Furthermore, the combined approach offers new insights into the design and optimization of the MW-heated biphasic systems.

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

Synthesis of cobalt grown from Co-S eutectic in high magnetic fields

Samples of Co were grown directly in the ferromagnetic state under equilibrium conditions using a cobalt sulfide flux. Magnetic fields up to 9 T were applied during growth, and isolated Co products exhibit progressively elongated morphologies, from cubes to rectangular rods to needle-like tendrils with poorly-defined facets. The degree of elongation of the major axis was found to correlate with magnetic field direction, strength, and gradient. Two-dimensional X-ray diffraction data indicate some level of polycrystalline-like samples, and quantitative analyses (Le Bail and Rietveld) of the one-dimensional data confirm the presence of hcp and fcc phases. The magnetic responses indicate a partial alignment of the magnetic easy-axis of the hcp phase along the magnetic field present during growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Play Fairway Analysis: Structurally Controlled Geothermal Systems in the Eastern Great Basin Extensional Regime, Utah

A research team with membership from the University of Utah/Energy & Geoscience Institute, the University of Utah/Dept. of Geology & Geophysics, and the Utah Geological Survey, undertook a play fairway analysis (PFA) for geothermal resources in the Eastern Great Basin (EGB) extensional tectonic regime of western Utah. This is a high-priority region for geothermal exploration because active Basin and Range (B&R) extension with volcanism having a N-S strike is superimposed upon pre-existing E-W belts of plutonic rocks and large-scale structural lineaments. Cumulative heat flow along the N-S strike of the state totals approximately 5 GWt above background stable interior. Three electricity producing power plants currently exist with substantial potential for increase. Succinctly, our PFA approach aims to resolve potential sources of heat and permeability in the region, which are the two principal criteria for establishing a geothermal resource. An initial Phase 1 was carried out using only existing geoscientific data in the area. Criteria selected for focusing heat potential include direct heat flow measurements in boreholes, magnetotelluric (MT) low resistivity anomalies, fluid/gas geochemistry, and proximity to recent volcanic eruptions. Permeability is established through geological structures (fault density, critically stressed areas, seismicity, gravity), and MT low resistivity anomalies. In Phase II of this PFA project, additional geological, geophysical and geochemical data were acquired and analysis carried out primarily over promising composite common risk (CCR) areas initially identified in Phase I in order to focus prospectivity and prepare for drilling recommendations. These prospects are near the Twin Peaks rhyolite field, high heat flow areas north of the producing Cove Fort system, and geophysical structure beneath the Crater Knoll area off the northeast flank of the Mineral Mountains. Additional data included MT site fill-in, structural mapping and analysis using high-resolution imagery, gravity and on-ground mapping, Nodal 3C passive seismic collection, and passive 3He surveying. Heat source and permeability potential are again expressed in terms of their individual common risk segment (CRS) maps, with a color scheme using green for most favorable (low risk) and red for least favorable (high risk). Diverse data types are united through the technique of probability kriging, which establishes prospectivity thresholds for each data type and then computes probability of exceeding that threshold over the PFA area. Modified CRS and CCRS maps are compared to those of Phase I to highlight tighter prospectivity focus. In doing so, the prospectivity threshold for heat was increased significantly to narrow the targeting. In the final Phase III of this project where a recommended deep thermal gradient hole was sited, additional geophysical, geochemical and geological field collection and analysis was carried out to refine drill hole targeting. This includes prospect-scale MT, gravity, structure, passive seismic deployment (Cove Fort area), and detailed 3He isotope profiling. It was the recommendation of the DOE Technical Monitoring Team (TMT) that one or more holes be sited in the north-ern Cove Fort area where legacy TG gradient holes showed high cumulative heat flow. These were to be of moderate depth, 2000-3000 feet, to reach the geothermal fluid table expected to start in excess of 1000 feet depth. The drilling organization stipulated by the DOE/GTO was that of the USGS Research Drilling Program (RDP) centered in Las Vegas, NV. A detailed well plan, appended to this report, was developed principally by Dr. Ben Barker consulting to University of Utah, Dr. Steve Pye on the DOE TMT, Mr. Steven Crawford of the USGS-RDP, and the project PI Phil Wannamaker. However, temperature and possible H 2 S at the systems lead to cancellation of the drilling last-minute as this appeared outside the experience base of the USGS-RDP. We hope to have the opportunity to revisit the test drilling and expand the Play Fairway Analysis of this region at some point in the future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Generation of shear flows induced by AE / EPM in LHD plasma

The generation of shear flows (SFs) by Alfven Eigenmodes (AEs) and energetic particle modes (EPMs) have important effects on the operation of future nuclear fusion reactors, because SFs regulate the saturation of the AEs/EPMs, the transport of EPs and thermal plasma, as well as the formation of transport barriers among other consequences. The aim of this study is the analysis of SFs generation during the saturation phase of AEs and EPMs in LHD plasma. Experiments performed in the 23rd and 24th LHD experimental campaigns are dedicated to explore the destabilization of AEs/EPMs in discharges with different heating patterns, thermal plasma and magnetic field configurations. In particular, the shots 176490 and 179697 show the destabilization of MHD bursts and energetic-ion-driven resistive interchange modes (EIC), respectively. Charge exchange spectroscopy measurements in both discharges indicate that the generation of SFs by AE/EPM is uncorrelated with the perturbation induced by the neutral beam injector (NBI). Nonlinear simulations performed using the gyro-fluid code FAR3d show the generation of zonal structures, especially SFs, induced during the saturation phase of Toroidal Alfven Eigenmodes (TAEs) triggered in the MHD burst as well as by the 1/1 EIC in the bursting phase. The simulations indicate that SFs are caused by the radial electric fields powered by energy transfers from the unstable AE/EPM towards the thermal plasma. The strongest SFs are measured during the EIC bursting phase once the 1/1 EPM overlaps with nearby resonances at the plasma periphery. Likewise, the largest SFs during the MHD burst are observed once TAEs radially overlap in the inner-middle plasma region.

AE↗
DOE OSTI2025

The Effects of Morphology and Hydration on Anion Transport in Self-Assembled Nanoporous Membranes

Ordered nanoporous polymer membranes offer opportunities for systematically probing the mechanisms of ion transport under confinement and for realizing useful materials for electrochemical devices. Here, we examine the impact of morphology and ion hydration on the transport of hydroxide and bromide anions in nanostructured polymer membranes with 1 nm scale pores. We use aqueous lyotropic self-assembly of an amphiphilic monomer, with a polymerizable surfactant to create direct hexagonal (H I ) and gyroid mesophases. UV-induced cross-linking leads to the formation of nanoporous polymers with water continuous channels. The membranes are mechanically robust and chemically durable, resisting degradation during extended exposure to 1 M NaOH solutions. We use a combination of electrochemical impedance spectroscopy, pulsed-field gradient NMR spectroscopy, and molecular simulations to elucidate anion and water transport. The as-prepared hexagonal systems display higher conductivity and lower activation energies for both anions relative to the gyroid system. When compared at equivalent hydration, however, gyroid and hexagonal membranes show similar activation energies, with nearly identical conductivities at ambient temperatures. Both ionic conductivity and water diffusivity increase with increasing hydration. Here, the water uptake as a function of relative humidity for the hexagonal and gyroid mesophases ultimately dictates the water diffusion and magnitude of the ionic conductivity, with the hexagonal system showing overall higher capacity for hydration and thus faster ion transport. The durability of these materials under aggressive alkaline conditions and their relatively high hydroxide ion conductivity suggest that these nanostructured polymers could be of interest as membranes for alkaline fuel cells.

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

Influence of Ether-Functionalized Pyrrolidinium Ionic Liquids on Properties and Li + Cation Solvation in Solvate Ionic Liquids

Ionic liquids are tunable solvents composed entirely of ions that have properties desirable as electrolytes for lithium batteries such as non-flammability and a large electrochemical stability window. Solvate ionic liquids are a subclass of ionic liquids that consist of a glyme-based solvent and lithium salt in an equimolar ratio, where Li + cation-glyme solvation interactions result in ionic liquid-like properties. LiG4TFSi is a well-studied solvate ionic liquid consisting of equimolar amounts of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and tetraglyme (G4). In this work, pyrrolidinium ionic liquids with ether-functionalized side chains were synthesized containing either one ether (EO1) moiety or three ether (EO3) moieties and mixed with LiG4TFSI to form a new class of electrolyte mixtures. Their physical and transport properties, as well as ion solvation structures, were characterized by electrochemical, thermal, rheological, and spectroscopic measurements. The conductivity of the electrolyte mixture composed of EO1:LiTFSI:G4 in a 1:1:1 molar ratio is 2.54 mS/cm at 30 °C, compared to 1.53 mS/cm for LiG4TFSI, an increase of 67%. A significant decrease in the conductivity to 0.279 mS/cm is observed for the EO3:LiTFSI:G4 mixture in a 1:1:0.4 molar ratio. Pulsed-field gradient nuclear magnetic resonance (PFG-NMR) measurements revealed that the EO1 cation diffuses significantly faster than the EO3 cation in their respective mixtures. Liquid-state 13 C NMR experiments indicate that Li + cations preferentially coordinate with tetraglyme. Li + cations do not coordinate with the EO1 cation and only coordinate with EO3 ether side chains at lower concentrations of tetraglyme. We hypothesize that the oligoether EO3 cation competes with G4 and TFSI - for lithium cation solvation in G4 deficient compositions, leading to a largely adverse effect on the mass transport properties of the electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗