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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Durable and High-Performance SOECs Based on Proton Conductors for Hydrogen Production

Proton-conducting solid oxide electrolysis cells (P-SOECs) are a promising technology for cost-effective and efficient production of green hydrogen. Breakthroughs in materials development, optimization of cell structure, and achievement of high performance and durability are essential to significantly increase the commercial competitiveness of these technologies. The main objective of this project is to gain scientific knowledge for the rational design, fabrication, and demonstration of a robust, highly efficient, and low-cost SOEC technology based on a proton-conducting electrolyte membrane for hydrogen production. We focused on better understanding the degradation mechanisms of proton-conducting electrolytes, air electrodes, and catalyst materials under electrolysis mode to develop an effective strategy for rationalizing new materials that are vital for enhancing cell performance and durability. The scope includes enhancing the performance and durability of the electrolyte and electrode materials under realistic operating conditions, developing highly active and robust catalysts to minimize electrode losses while improving tolerance to contaminant poisoning, revealing the mechanism of enhanced activity and stability of the catalyst, and understanding the underlying degradation mechanisms. In addition, various characterization techniques were employed to gain a fundamental understanding of the materials’ behavior and their impact on cell performance, providing vital information to guide materials discovery and cell design. After defect chemistry engineering, the optimized donor and acceptor co-doped electrolytes BaMo/W 0.03 Ce 0.71 Yb 0.26 O 3-δ (BM/W03) showed substantially improved chemical stability against high concentrations of CO 2 and H 2 O compared to the state-of-the-art electrolyte (BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ , BZCYYb1711) while maintaining comparable ionic conductivity and ionic transference number. To bypass the inherent trade-off between conductivity and chemical stability, we fabricated a bi-layer electrolyte composed of BZCYYb1711 coated with a highly-stable thin layer of BaHf 0.83 Yb 0.17 O 3-δ (BHYb). This bi-layer electrolyte displayed excellent chemical stability against high concentration CO 2 ; there was no detectable formation of BaCO 3 after exposure to 97% CO 2 (with 3% H 2 O) at 500 °C for 1000 hours and the rate of degradation in resistance was about 0.4% per 1,000 hours (kh). In contrast, the same BZCYYb1711 electrolyte without a BHYb coating degraded significantly under the same testing conditions; the degradation rate was increased to 5.1%/kh. In addition, a triple conducting air electrode Ba 0.9 Pr 0.1 Hf 0.1 Y0.1Co 0.8 O 3-δ (BPHYC) was developed by heavily doping transition metal ions into a proton-conducting material. This air electrode material, composed of 3 distinct phases, exhibits superior electrocatalytic activity due to the synergistic effect from the three component phases. Moreover, an active and durable catalyst, La 2 Ni 0.5 Fe 0.5 O 4+δ (LNF), was developed, showing excellent catalytic activity and contaminant tolerance, with a degradation rate of only 0.49%/kh when exposed to high concentrations of steam and Cr. Finally, single cells were constructed from the best electrolytes, electrodes, and catalyst coatings developed in this project. These cells demonstrated superior high current density at a given cell voltage, high roundtrip efficiency, and remarkable durability (up to 1000 hours of operation).

08 HYDROGEN↗
DOE OSTI2024

Water Resource Assessment In The New Mexico Permian Basin: BLM 2023 Assessment Report

The Permian Basin is the highest producing oil field in the United States and is comprised of three component basins including; the Midland Basin, Delaware Basin and the Marfa Basin. This report describes the work conducted by Sandia National Laboratories (SNL) for the Bureau of Land Management (BLM) to investigate the occurrence of usable water (quality, and depth to water) in the Delaware Sub-basin of the Permian Basin. High Production Areas (HPAs) were identified for the region based on Reasonable Foreseeable Development Scenario (RFD) published by New Mexico Tech University. HPAs were established based on potential for future development of oil reserves. The study was initiated by the BLM-Carlsbad Field Office (CFO) based on concerns that special protections for groundwater in these HPAs may be warranted. A combination of analysis of existing data and field work to collect new data for analysis were used to complete the investigation objectives. This study summarizes the most recent analyses in an ongoing project and builds on previously completed work as listed in Table 1. Advancements in directional drilling and well completion technologies have resulted in an exponential growth in the use of hydraulic fracturing for oil and gas extraction in the Permian Basin. Within the New Mexico portion of the Delaware Sub-basin, water demand to complete each hydraulically fractured well is estimated to average 7.3 acre-feet (2.4 million gallons), resulting in 30 billion barrels of water over the life of the plan or 1.5 billion barrels per year. This rising demand is creating concern for the regions ability to provide the necessary water in a manner that fulfills BLM’s role of protecting human health and the environment while sustainably meeting the needs of various water users in the region. This report documents water-level and water chemistry baselines to aid the BLM in understanding the regional water supply dynamics under various management, policy, and growth scenarios and to pre-emptively identify risks to water sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

MatCal Users Guide: Release 1.3.0

Any continuum mechanics model will require three components: (1) a discretized geometry of the boundary value problem being studied, (2) the partial differential equations to be solved, and (3) the initial conditions and boundary conditions for the problem. To describe material behavior in these computational models, material models contribute to (2) the underlying equations and, occasionally, to (3) the initial conditions for the simulation. These material models can exhibit a mathematical form that is empirically based, based on first principles, or developed from both empirical observations and known physics. In general, these models are meant to represent a class of materials with well understood behavior. As a result, material models have parameters that must be tuned or calibrated so that the model response matches characterization data available for the specific material it is intended to represent when used to simulate a specific system. For simple models, such as isotropic, linear elastic materials in solid mechanics, this calibration process can be a simple analytical calculation directly extracting the parameters from experimental measurements. For complex models that have many inputs and require many characterization datasets to adequately identify the material behavior, the model calibration process can require an inverse problem approach where an optimization is performed to tune the model parameters to the available data.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Teleseismic Network Association with GENIE

In this report we investigate adapting the Graph Neural Interpretation Engine (GENIE), an associator developed for three-component dense monitoring networks, to regional to teleseismic association using a sparse network of array stations. We expand GENIE’s input features to include first-P detection time, azimuth, and slowness estimates. Additionally, we include a probability of detection (PDET) term which measures a station’s likelihood of detecting an event. To assess each feature’s relative importance, we train four models, each using an increasing set of node features and find that the PDET models perform the best. We define two measures of event complexity which demonstrate that all GENIE model versions perform better than the standard backprojection stack.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Catalytic Activity of TiO 2 Toward a Multicomponent Reaction Depends on its Morphology, Mechanoactivation and Presence of Visible Light

Aims: Test the hypothesis that the catalytic activity of TiO2 nanoparticles towards a liquidphase or mechanoactivated multicomponent reaction can be tuned by visible light and the shape of nanoparticles. Background: Catalytic multicomponent reactions have been proven to be excellent synthetic approaches to a series of biologically relevant compounds including 2-amino-4H-benzo[b]pyrans. However, the potential photocatalytic activity and structural diversity of nanostructured catalysts remained underutilized in the design of new catalytic systems. Objective: Harness the photocatalytic potential and diverse morphology of TiO2 particles as catalysts for the liquid phase and mechanoactivated multicomponent organic reactions. Results: Catalytic activity of TiO2 nanoparticles towards multicomponent synthesis of 2-amino-4Hbenzo[ b]pyrans is increased by visible light. The nanorod-shaped TiO2 nanoparticles have shown substantially higher catalytic activity towards mechanoactivated multicomponent synthesis of 2- amino-4H-benzo[b]pyrans than their spherically-shaped counterparts. Conclusion: : An efficient methodology for the synthesis of 2-amino-4H-benzo[b]pyrans under ambient light condition has been developed using TiO2 nanorods (high aspect ratio anatase nanocrystals) as photocatalyst. This simple method furnished the corresponding terahydrobenzopyrans in high yields via three component reaction of aldehyde, malononitrile, and dimidone under solvent free reaction conditions at room temperature. The reaction takes 8-10 min at room temperature under ambient light condition and the catalyst can be reused multiple times. Utilization of light and the nanorod morphology of the catalyst through mechanoactivation has been applied for the -first time to the synthetic technique of multicomponent reactions. The synthetic procedures for 2-amino-4Hbenzo[ b]pyrans have been improved.

Thirumeni, Subramanian↗
DOE OSTI2020

State-Constrained Grid-Forming Inverter Control for Robust Operation of AC Microgrids

The control of grid-forming inverters has become an important problem to achieve high efficiency, reliability, and resilience of the future power grid. The distributed control that utilizes a sparse communication network has been proposed for AC microgrids, in which each DG only has access to the information of a small number of its neighboring DGs, reducing the computational complexity and improving the resiliency to faults and unknown parameters. However, these approaches have not provided a clear analysis of the coupling between active/reactive power injections and the voltage magnitude/frequency or a distributed updating law with a solid theoretical foundation. Additionally, in the existing approaches, tracking the references from the secondary control may violate operational constraints.

Xu, Ying↗
DOE OSTI2026

Seismic Observations of the OSIRIS-REx Sample Return Capsule Reentry: Deployment, Signal Characteristics, and Wavefield Phenomenology

Controlled spacecraft reentries from interplanetary trajectories provide rare, well-characterized hypersonic sources for advancing seismoacoustic observation techniques. Here we present seismic observations of the OSIRIS-REx sample return capsule (SRC) reentry on 24 September 2023, recorded by 16 three-component nodal seismometers deployed near Eureka, Nevada, at ground distances of 7–20 km from the capsule trajectory. Air-to-ground coupled signals are detected at all stations, exhibiting impulsive onsets consistent with ballistic shock arrivals from the descending Mach cone. We characterize the seismic wavefield through signal amplitude, period, waveform cross-correlation, and array processing. Signal periods decrease systematically with increasing distance from the trajectory within the airport array, indicating that higher-frequency content becomes more prominent at greater offsets, opposite to expectations from geometric spreading and atmospheric absorption. Seismic array processing identifies frequency-dependent back-azimuth variations whose origin remains unresolved; possible contributing factors include source geometry, scattering by fine-scale layered structure in the stratosphere, and near-surface effects. These observations document a spatially complex seismic wavefield from a well-characterized hypersonic line source and provide constraints for future modeling of atmospheric propagation and air-to-ground coupling.

OSIRIS-REx↗
DOE OSTI2023

Simultaneous Measurements of Noncommuting Observables: Positive Transformations and Instrumental Lie Groups

We formulate a general program for describing and analyzing continuous, differential weak, simultaneous measurements of noncommuting observables, which focuses on describing the measuring instrument autonomously, without states. The Kraus operators of such measuring processes are time-ordered products of fundamental differential positive transformations, which generate nonunitary transformation groups that we call instrumental Lie groups. The temporal evolution of the instrument is equivalent to the diffusion of a Kraus-operator distribution function, defined relative to the invariant measure of the instrumental Lie group. This diffusion can be analyzed using Wiener path integration, stochastic differential equations, or a Fokker-Planck-Kolmogorov equation. This way of considering instrument evolution we call the Instrument Manifold Program. We relate the Instrument Manifold Program to state-based stochastic master equations. We then explain how the Instrument Manifold Program can be used to describe instrument evolution in terms of a universal cover that we call the universal instrumental Lie group, which is independent not just of states, but also of Hilbert space. The universal instrument is generically infinite dimensional, in which case the instrument’s evolution is chaotic. Special simultaneous measurements have a finite-dimensional universal instrument, in which case the instrument is considered principal, and it can be analyzed within the differential geometry of the universal instrumental Lie group. Principal instruments belong at the foundation of quantum mechanics. We consider the three most fundamental examples: measurement of a single observable, position and momentum, and the three components of angular momentum. As these measurements are performed continuously, they converge to strong simultaneous measurements. For a single observable, this results in the standard decay of coherence between inequivalent irreducible representations. For the latter two cases, it leads to a collapse within each irreducible representation onto the classical or spherical phase space, with the phase space located at the boundary of these instrumental Lie groups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Constraints on the Physical Properties of GW190814 through Simulations Based on DECam Follow-up Observations by the Dark Energy Survey

On 2019 August 14, the LIGO and Virgo Collaborations detected gravitational waves from a black hole and a 2.6 solar mass compact object, possibly the first neutron star–black hole merger. In search of an optical counterpart, the Dark Energy Survey (DES) obtained deep imaging of the entire 90% confidence level localization area with Blanco/DECam 0, 1, 2, 3, 6, and 16 nights after the merger. Objects with varying brightness were detected by the DES Pipeline, and we systematically reduced the candidate counterparts through catalog matching, light-curve properties, host-galaxy photometric redshifts, Southern Astrophysical Research spectroscopic follow-up observations, and machine-learning-based photometric classification. All candidates were rejected as counterparts to the merger. To quantify the sensitivity of our search, we applied our selection criteria to full light-curve simulations of supernovae and kilonovae as they would appear in the DECam observations. Because the source class of the merger was uncertain, we utilized an agnostic, three-component kilonova model based on tidally disrupted neutron star (NS) ejecta properties to quantify our detection efficiency of a counterpart if the merger included an NS. We find that, if a kilonova occurred during this merger, configurations where the ejected matter is greater than 0.07 solar masses, has lanthanide abundance less than 10 -8.56 , and has a velocity between 0.18c and 0.21c are disfavored at the 2σ level. Furthermore, we estimate that our background reduction methods are capable of associating gravitational wave signals with a detected electromagnetic counterpart at the 4σ level in 95% of future follow-up observations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Phase Separation in Ultramassive White Dwarfs

We report ultramassive white dwarfs are extreme endpoints of stellar evolution. Recent findings, such as a missing multi-Gyr cooling delay for a number of ultramassive white dwarfs and a white dwarf with a quasi-Chandrasekhar mass, motivate a better understanding of their evolution. A key process still subject to important uncertainties is the crystallization of their dense cores, which are generally assumed to be constituted of 16 O, 20 Ne, and a mixture of several trace elements (most notably 23 Na and 24 Mg). In this work, we use our recently developed Clapeyron integration technique to compute accurate phase diagrams of three-component mixtures relevant to the modeling of O/Ne ultramassive white dwarfs. We show that, unlike the phase separation of 22 Ne impurities in C/O cores, the phase separation of 23 Na impurities in O/Ne white dwarfs cannot lead to the enrichment of their cores in 23 Na via a distillation process. This severely limits the prospect of transporting large quantities of 23 Na toward the center of the star, as needed in the white dwarf core-collapse mechanism recently proposed by Caiazzo et al. We also show that despite representing ≈10% of the ionic mixture, 23 Na and 24 Mg impurities only have a negligible impact on the O/Ne phase diagram, and the two-component O/Ne phase diagram can be safely used in white dwarf evolution codes. We provide analytic fits to our high-accuracy O/Ne phase diagram for implementation in white dwarf models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

GIGA-Lens: Fast Bayesian Inference for Strong Gravitational Lens Modeling

We present GIGA-Lens: a gradient-informed, GPU-accelerated Bayesian framework for modeling strong gravitational lensing systems, implemented in TensorFlow and JAX. The three components, optimization using multistart gradient descent, posterior covariance estimation with variational inference, and sampling via Hamiltonian Monte Carlo, all take advantage of gradient information through automatic differentiation and massive parallelization on graphics processing units (GPUs). We test our pipeline on a large set of simulated systems and demonstrate in detail its high level of performance. The average time to model a single system on four Nvidia A100 GPUs is 105 s. The robustness, speed, and scalability offered by this framework make it possible to model the large number of strong lenses found in current surveys and present a very promising prospect for the modeling of ${ \mathcal O }({10}^{5})$ lensing systems expected to be discovered in the era of the Vera C. Rubin Observatory, Euclid, and the Nancy Grace Roman Space Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling

We introduce a novel semi-supervised learning approach, named Teacher-Student Bayesian Optimization (TSBO ), integrating the teacher-student paradigm into BO to minimize expensive labeled data queries for the first time. TSBO incorporates a teacher model, an unlabeled data sampler, and a student model. The student is trained on unlabeled data locations generated by the sampler, with pseudo labels predicted by the teacher. The interplay between these three components implements a unique selective regularization to the teacher in the form of student feedback. This scheme enables the teacher to predict high-quality pseudo labels, enhancing the generalization of the GP surrogate model in the search space. To fully exploit TSBO , we propose two optimized unlabeled data samplers to construct effective student feedback that well aligns with the objective of Bayesian optimization. Furthermore, we quantify and leverage the uncertainty of the teacher-student model for the provision of reliable feedback to the teacher in the presence of risky pseudo-label predictions. TSBO demonstrates significantly improved sample-efficiency in several global optimization tasks under tight labeled data budgets. The implementation is available at https://github.com/reminiscenty/TSBO-Official.

Yin, Yuxuan↗
DOE OSTI2026

Point-scale organic-matter decomposition in streambeds is weakly associated with reach-scale respiration

Stream and river ecosystems play a central role in the movement and decomposition of particulate organic matter, serving as a conduit between terrestrial hillslopes and coastal environments. Microbial-catalyzed decomposition generates simpler organic molecules that fuel respiration, often in the sediments of these ecosystems. However, the degree of connection between sediment-associated respiration (ER??d) and organic-matter decomposition remains poorly understood. How that relationship compares to decomposition’s relationship with whole ecosystem (ERtot) and water column (ERwc) respiration is also not clear. We examined the link between particulate organic matter decomposition—using cellulose-based cotton strips as a standardized substrate—and all three components of respiration across 48 sites in the environmentally diverse Yakima River Basin (Washington State, USA). We hypothesized that decomposition within sediments would be most strongly related to ERsed, but decomposition rates were more closely associated with ERtot, with little connection to ERsed or ERwc. This suggests that particulate organic matter decomposition within stream/river sediments reflects integrated system respiration rather than processes confined to sediments or the water column alone. Further, across the basin, decomposition rates nearly spanned the previously reported global range for streams and rivers and were best explained by total dissolved nitrogen (TDN), sediment grain size, and aridity of the upstream drainage area. These results highlight the strong influence of land cover and basin-scale biophysical variation on sediment-associated decomposition processes and indicate that mechanistic models of organic matter decomposition in streams/rivers should account for coupled sediment–water–land interactions.

Stegen, James C. (ORCID:0000000191357424)↗
DOE OSTI2024

High resolution hydrologic routing with machine learning assisted waterbody classification

This software contains the code for a machine learning-based pipeline for creating persistent waterbody databases used in hydrologic routing. It consists of three components, 1) a PyTorch library (TorchWBType) for classifying/labeling arbitrary waterbodies into lakes and non-lakes, 2) a batch processing orchestrator (wbextractor) for delineating waterbodies from remote sensing imagery, and 3) graphing/analysis scripts for reproducing the plots in an associated journal article (LA-UR-24-22590).

Stachelek, Jemma↗
DOE OSTI2022

A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County

The dataset contains hourly Anthropogenic heat (AH) from buildings in Los Angeles County, based on weather data from 2018. The hourly AH is aggregated at three spatial resolutions: 450m x 450m grid, 12km x 12km grid, and census tract. The AH is broken down into three components: building envelope surface convection, heating, ventilation, and air conditioning (HVAC) system heat release, and zone exfiltration and exhaust air heat loss. The dataset is created with the physics-based EnergyPlus building energy models to calculate individual buildings' AH considering WRF-UCM simulated microclimate conditions. Please refer to the paper "A multi-scale time-series dataset of anthropogenic heat from buildings in Los Angeles County" for more information about the data generation workflow and the data validation procedure. The data set contains two folders: the "output_data" folder holds the simulation results (EP_output and EP_output_csv), building metadata (building_metadata.geojson and building_metadata.csv), aggregated heat emission and energy consumption time-series data (hourly_heat_energy), and geographical data (geo_data) associated with the GEOID referenced in heat and energy consumption data. The "input_data" folder contains the raw data used to generate files in the "output_data" folder as well as data sets used in the validation. The code repository (https://github.com/IMMM-SFA/xu_etal_2022_sdata) holds the processing scripts for data curation, validation, and visualization.

Energy↗
DOE OSTI2020

A Numerical Study on the Energy Performance of a Novel Furnace With Acidic Gas Trap Absorbers

Natural gas furnaces are widely used in US residential and commercial building markets. An important issue for natural gas furnaces is serious corrosion and fouling problems caused by acidic gas, such as SOx. An advanced adsorption technology based on acidic gas trap (AGT) absorbers offers the possibility to remove SOx acidic gas from natural gas furnaces with high efficiency and low cost, thereby enabling the development of condensing furnaces without the use of expensive corrosion resistant materials in the heat exchanger. A three-dimensional (3D) computational fluid dynamics (CFD) model has been developed to evaluate the heat transfer performance of a furnace with AGT absorbers and to compare it with a baseline conventional furnace without the AGT. Moreover, an axisymmetric model has been built focusing on the absorbing process in the AGT. The baseline conventional furnace used for the study is a commercial condensing furnace (Rheem 92% AFUE 84,000 BTU Multi-Position Gas Furnace). This furnace was completely disassembled, and the dimensions of each part were carefully measured and used to build a detailed CFD model. A model representing the new furnace, incorporating the AGT absorbers, was developed by adding the AGT system to the conventional furnace model. For the CFD analysis, a mixture model was employed to characterize the heat and mass transfer during the condensing process in the furnace while considering three components—air, water vapor and liquid water. Condensation takes place in the condensing heat exchanger, where water vapor changes phase to liquid water, and the latent heat is thus used in the furnace for useful heating. The simulation results characterize the energy performance of both the conventional furnace and the novel furnace with AGT absorbers, as well as the reactive processing in the AGT. These results provide insightful guidance for the development of the AGT absorber-based furnace from the perspective of its energy performance and will be used to further optimize this novel furnace design.

Laclair, Tim↗
DOE OSTI2021

Data Release Report for the Source Physics Experiment Phase II: Dry Alluvium Geology Experiments (DAG-1 through DAG-4), Nevada National Security Site

The Dry Alluvium Geology (DAG) project was Phase II of the Source Physics Experiment and consisted of a series of four chemical explosive tests conducted in the same source hole on the Nevada National Security Site. This hole is located at 37.1146°N and -116.0693°W, with a surface elevation of 1,285.2 meters (m) (4,216.5 feet [ft]) above sea level. The first test (DAG-1) was conducted on July 20, 2018, at 16:51:52.67838 Coordinated Universal Time (UTC). The explosive source for DAG-1 was nitromethane initiated by a small plastic-bonded explosive (PBX) charge, detonated at the depth of 385.0 m (1,263.2 ft) below ground surface. DAG-1 had a trinitrotoluene (TNT) equivalent yield of 0.908 metric tons (2,002 pounds [lbs]). DAG-2 was conducted on December 19, 2018, at 18:45:56.92115 UTC. This test was the largest in the series, with a TNT equivalent yield of 50.997 metric tons (112,429 lbs). The explosive source for DAG-2 was nitromethane initiated by a small PBX charge, detonated at the depth of 299.8 m (983.6 ft) below ground surface. DAG-3 was conducted on April 27, 2019, at 15:49:01.84183 UTC. The explosive source for this test was nitromethane initiated by a small PBX charge, detonated at the depth of 149.9 m (492.0 ft) below ground surface. DAG-3 had a TNT equivalent yield of 0.908 metric tons (2,002 lbs). The final DAG test (DAG-4) was conducted on June 22, 2019, at 21:06:19.87632 UTC. The explosive source for DAG-4 was nitromethane initiated by a small PBX charge, detonated at the depth of 51.6 m (169.3 ft) below ground surface. DAG-4 had a TNT equivalent yield of 10.357 metric tons (22,833 lbs). The four tests were recorded by an extensive set of instrumentation that included sensors both at near-field (less than 200 m) and far-field (200 m or greater) distances. The near-field instruments consisted of three-component (3C) accelerometers installed at various depths ranging from 51.6 to 385 m (169.3 to 1,263.1 ft) below ground surface in boreholes positioned around the source hole, and arrays of single-component and 3C accelerometers on the surface. The far-field network comprised a variety of seismic and acoustic sensors, including short-period geophones, broadband seismometers, and 3C accelerometers at distances of 200 m to 400 kilometers. In addition, the DAG-2, DAG-3, and DAG-4 explosions were recorded by a temporary array of 496 geophones arranged in a densely spaced grid pattern known as “Large N.” This report coincides with the release of these data for analysts and organizations that are not participants in this program. This report describes the four DAG tests and the various types of near-field, far-field, and other data that are available. Assembled data sets are accessible through: Incorporated Research Institutions for Seismology, Data Management Center 1408 NE 45th Street, Suite 201, Seattle, Washington 98105 USA. www.iris.washington.edu

58 GEOSCIENCES↗
DOE OSTI2023

Localized High-Concentration Electrolytes Get More Localized

Liquid electrolytes in batteries are typically treated as macroscopically homogeneous ionic transport media, despite having complex chemical composition and atomistic solvation structures, thus leaving a knowledge gap of microstructural characteristics. A promising electrolyte system design has recently been developed with the title of a localized high-concentration electrolyte (LHCE). These electrolytes are a summation of three components – a charge-carrying salt, a solvent that solvates the salt, and a diluent that is sparingly interactive with the salt in terms of ion solvation. This creates the perception of a high-concentration electrolyte (HCE) with high anion-cation interactions that supports a salt-derived, stable solid-electrolyte interphase, while an LHCE improves bulk electrolyte properties, such as ionic conductivity and viscosity, when compared to an HCE. Much trial by error design of this LHCE concept has been supported by simulations to confirm ionic interactions, cycling data to confirm cell stability, and post-mortem analysis to provide evidence of mechanisms. However, a systematic design to extend the capabilities of LHCEs is still to be desired. Here, we analyzed a specific LHCE mixture to dictate the best viable mixture that extends the localization of solvation structures while maintaining viable cell-level capabilities. We seek to observe and understand solvent-to-salt interactions that impact electrolyte performance. These interactions range from single-ion solvation, multidentate interactions (i.e., solvation-driven clustering), to more widespread network-level interactions. With the support of both experimental and computational analysis of different electrolyte features, we have begun a methodology of formulating the most ideal LHCE mixtures for improving the cyclability of high-capacity battery chemistries.

25 ENERGY STORAGE↗