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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Assessing Impacts on Pressure Stabilization and Leasing Acreage for CO 2 Storage Utilizing Oil Migration Concepts

Favorable geological storage for CO 2 has long been pictured as large anticlines with thick sandstones, similar to oil reservoirs in the petroleum system. Unlike oil, however, stored CO 2 does not need to be recoverable, which raises the possibility of using dissolution and residual trapping to augment the capacity of buoyant traps and tap more of the bulk rock volume. The work presented builds on that idea, asking the following question: If we inject CO 2 down to a syncline – analogous to the carrier bed in the petroleum system – how would this injection mechanism impact storage capacity and plume shape, migration, and stabilization? To address this question, we built a reservoir model, based on seismic interpretation of Middle Miocene strata, offshore Galveston, Texas. 3-D seismic and well logs were used to characterize key intervals. Reservoirs chosen for modeling are progradational-aggradational sands with mud intercalation. They have a higher degree of heterogeneity than the more conventional reservoirs commonly targeted for CO 2 storage. Modeling investigated how far the CO 2 plume would migrate under two scenarios: (1) injecting CO 2 at the base of the salt withdrawal basin (syncline scenario) and (2) injecting CO 2 at the base of the structural closure, similar to a common injection well location for EOR purposes (base scenario). For each scenario, we separately simulated injection of 30 MT of CO 2 and 60 MT of CO 2 continuously for 30 years and observe the plume and pressure evolution for 100 years after the injection stops. The simulation shows that injecting the CO 2 into a syncline limits the vertical migration of CO 2 , thus making synclinal injection more secure. In the syncline scenario, the geological layer around the injection point is more heterogeneous than the layer in the base scenario; thus, the CO 2 tends to migrate laterally. Additionally, in the syncline scenario, the plume does not even reach the upper part of the anticline, allowing us to safely store an additional amount of CO 2 into the reservoir. Furthermore, the simulation also shows that in the syncline scenario, the times needed for the reservoir to reach its stabilized pressure after the end of injections are faster. To summarize, CO 2 injection at the base of a syncline could provide additional storage, increase the safety of the project from the limited vertical plume migration, and expedite plume stabilization, which could result in the decrease of monitoring frequency as the project runs, thus lowering the operating cost of the project in the long run.

58 GEOSCIENCES↗
DOE OSTI2023

Complete lowest order radiative corrections in semi-inclusive scattering of polarized particles

For this work, the lowest order radiative corrections to the cross section and asymmetries measured in experiments on semi-inclusive deep inelastic scattering of polarized particles were calculated. Both exact and leading log expressions were presented and discussed for the total correction that include the contributions from the processes of i) real photon emission with semi-inclusive processes, ii) loop diagrams, and iii) real photon emission with exclusive processes. Radiative corrections to the Sivers and Collins asymmetries in $\pi^+$ electroproduction were studied numerically within the kinematical conditions of modern experimental environments at Jefferson Laboratory (JLab). The Wandzura-Wilczek approximation for the semi-inclusive structure functions and MAID2007 parameterization for the six amplitudes of exclusive processes were used in numeric analyses. The results show that i) radiative effects can generate a correction comparable to the size of Sivers and Collins asymmetries at the Born level, ii) there is good agreement between the exact and leading-order corrections, iii) external functions (that is, other than the Sivers and Collins functions in the respective asymmetries) can generate a contribution to the radiative correction up to 20%, and iv) there exists a strong dependence of the radiative correction on the models for semi-inclusive and exclusive structure functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Insights into Prismatic Loop Formation in Irradiated Fe–Cr Alloys from Hypothesis-Driven Active Learning and Causal Analysis

Neutron and electron irradiation experimental studies conducted on body-centered cubic Fe and Fe–Cr alloys have established two prismatic dislocation loop populations, which have Burgers vectors of either a/2$\langle$111$\rangle$ or a$\langle$100$\rangle$. Here, the loop formation depends on factors such as dose (D), dose rate (D rt ), temperature (T), chromium content (Cr%), and other alloying elements. Hence, it is important to understand how irradiation-induced dislocation loops evolve conditional upon the loop characteristics, such as loop density (DD), average loop size d̅, and irradiation parameters (D, D rt , T, and irradiation type), which is still an active area of research. To understand these complex structure–property relationships, machine learning (ML) is employed in a three-step approach. This includes imputing missing data with a k-nearest neighbor, generating functionalized features, and assessing feature importance with random forest classification and regression. Physics-based features are incorporated in a hypothesis-driven active learning scheme to overcome data unavailability challenges. Insights obtained from ML models (i) to categorize dislocation loop types, show the highest correlation with d̅; (ii) Log(DD), obtained through mathematical formulations involving D, Cr%, d̅, and T (e.g., Log(DD) ~ D + exp(-Cr%) + 1/d̅ and log(DD) ~ D + exp(-Cr%) + 1/T). Hypothesis-driven active learning is able to predict Log(DD) in which the experimental date is not known. Causal models verify cause–effect relationships for dislocation loop classification and irradiation factors in FeCr alloys.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Persistent, “Mysterious” Seismoacoustic Signals Reported in Oklahoma State during 2019

Here, we report on the source of seismoacoustic pulses that were observed across the state of Oklahoma (OK) during summer of 2019, and the subject of national media coverage and speculation. Seismic network data collected across four U.S. states and interviews with witnesses to the pulse’s effect on residential structures demonstrate that they were triggered by routine ammunition disposal operations conducted by McAlester Army Ammunition Plant (McAAP). During these operations, conventional explosives destroy obsolete munitions stored in pits through a controlled sequence of electronically timed shots that occur over tens of minutes. Despite noise-abatement efforts that reduce coupling of acoustic energy with air, some lower frequency, subaudible (infrasonic) sound radiates from these shots as discrete pulses. We use nine months of blast log documents, seismic network records, analyst picks, and physical modeling to demonstrate that seismic stations as far as 640 km from McAAP sample these pulses, which record seasonal patterns in stratospheric and tropospheric winds, as well as the dynamic formation of waveguides and shadow zones. Digital short-term average to long-term average detectors that we augment with dynamic thresholds and time-binning operations identify these pulses with a fair probability, when compared with visual observations. Our analyses thereby provide estimates of observation rates for both partial and full sequences of these pulses, as well as single shots. We suggest that disposal operations can exploit existing, composite seismic networks to predict where residents are likely to witness blasting. Crucially, our data also show that dense seismic networks can record multiscale atmospheric processes in the absence of infrasound arrays.

58 GEOSCIENCES↗
DOE OSTI2023

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗
DOE OSTI2020

A Search for FeH in Hot-Jupiter Atmospheres with High-dispersion Spectroscopy

Most of the molecules detected thus far in exoplanet atmospheres, such as water and CO, are present for a large range of pressures and temperatures. In contrast, metal hydrides exist in much more specific regimes of parameter space, and so can be used as probes of atmospheric conditions. Iron hydride (FeH) is a dominant source of opacity in low-mass stars and brown dwarfs, and evidence for its existence in exoplanets has recently been observed at low resolution. We performed a systematic search of archival CARMENES near-infrared data for signatures of FeH during transits of 12 exoplanets. These planets span a large range of equilibrium temperatures (600 ≲ T eq ≲ 4000 K) and surface gravities (2.5 ≲ logg ≲ 3.5). We did not find a statistically significant FeH signal in any of the atmospheres, but obtained potential low-confidence signals (signal-to-noise ratio ~ 3) in two planets, WASP-33b and MASCARA-2b. Previous modeling of exoplanet atmospheres indicate that the highest volume mixing ratios (VMRs) of 10 -7 to 10 -9 are expected for temperatures between 1800 and 3000 K and log g≳3. The two planets for which we find low-confidence signals are in the regime where strong FeH absorption is expected. We performed injection and recovery tests for each planet and determined that FeH would be detected in every planet for VMRs &NestedGreaterGreater;10 -6 , and could be detected in some planets for VMRs as low as 10 -9.5 . Additional observations are necessary to conclusively detect FeH and assess its role in the temperature structures of hot-Jupiter atmospheres.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Linking Stream Chemistry to Subsurface Redox Architecture

As drinking-water scarcity grows worldwide, we need to improve predictions of the quantity and quality of our water resources. An overarching problem for model improvement is that we do not know the geological structure of aquifers in sufficient detail. In this work, we demonstrate that mineral-water reactions imprint structure in the subsurface that impacts the flow and transport of some chemical species. Specifically, pyrite, a ubiquitous mineral, commonly oxidizes and depletes in the upper layers of the weathering profile in most humid watersheds, only remaining at depths of meters. We hypothesize that variations in concentrations (C) of pyrite-derived sulfate released into rivers as a function of discharge (q) reflect the rate-limiting step and depth of pyrite-oxidizing layers. We found that log C - log q behaviors thus differ in small and large watersheds in the Susquehanna River Basin as well as in selected watersheds in the Western United States. Although coal mining changes pyrite oxidation from closed to open system with respect to O 2 , patterns in stream chemistry as a function of discharge are consistent with deep and shallow pyrite oxidation zones in small and large watersheds respectively. Therefore, understanding the subsurface patterns of mineral reactions and how they affect the architecture of aquifers will elucidate patterns of changing river chemistry and our ability to manage water resources in the future under accelerated land use and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coherent gluon radiation: beyond leading-log accuracy

Abstract Results are presented for the medium-induced, soft coherent radiation spectrum for all 2 → 2 partonic channels in QCD, at leading-order inα s but beyond leading logarithmic accuracy. The general formula is valid in the full kinematic range of the underlying process, and reduces to previous results in special cases. The soft gluon radiation spectrum is expressed in terms of thecolor density matrixspecific to each channel, quantifying the entanglement between the color components of the 2 → 2 production amplitude. Beyond the leading logarithm, the spectrum depends explicitly on the off-diagonal elements of this matrix, owing to the soft gluon’s ability to probe the internal color structure of the parton pair.

Physics↗
DOE OSTI2020

From the inner to outer Milky Way: a photometric sample of 2.6 million red clump stars

ABSTRACT Large pristine samples of red clump stars are highly sought after given that they are standard candles and give precise distances even at large distances. However, it is difficult to cleanly select red clumps stars because they can have the same Teff and log g as red giant branch stars. Recently, it was shown that the asteroseismic parameters, $\rm {\Delta }$P and $\rm {\Delta \nu }$, which are used to accurately select red clump stars, can be derived from spectra using the change in the surface carbon to nitrogen ratio ([C/N]) caused by mixing during the red giant branch. This change in [C/N] can also impact the spectral energy distribution. In this study, we predict the $\rm {\Delta }$P, $\rm {\Delta \nu }$, Teff, and log g using 2MASS, AllWISE, Gaia, and Pan-STARRS data in order to select a clean sample of red clump stars. We achieve a contamination rate of ∼20 per cent, equivalent to what is achieved when selecting from Teff and log g derived from low-resolution spectra. Finally, we present two red clump samples. One sample has a contamination rate of ∼20 per cent and ∼405 000 red clump stars. The other has a contamination of ∼33 per cent and ∼2.6 million red clump stars that includes ∼75 000 stars at distances >10 kpc. For |b| > 30 deg, we find ∼15 000 stars with contamination rate of ∼9 per cent. The scientific potential of this catalogue for studying the structure and formation history of the Galaxy is vast, given that it includes millions of precise distances to stars in the inner bulge and distant halo where astrometric distances are imprecise.

Lucey, Madeline↗
DOE OSTI2026

The solubility of ErPO 4 and Er speciation in hydrothermal fluids at varying pH and salinity between 350 and 450 °C

The rare earth elements (REE) are important for the green-energy transition and can be incorporated into the REE phosphates, such as xenotime-(Y), which also hosts heavy REE (Tb– Lu). Xenotime-(Y) is a common accessory mineral in metamorphic rocks and a range of mineral deposits where it controls the mobility of heavy REE, however, the impact of high temperature aqueous fluids on the behavior of heavy REE is largely unknown. Thermodynamic modeling can be utilized as a tool to predict the mobility of REE in hydrothermal aqueous fluids, but must be supported by accurate experimental data. Here, we measured the solubility of endmember synthetic xenotime-structured ErPO4 in NaCl-HCl-NaOH-bearing aqueous solutions at 350 °C and water vapor saturation pressure, at 400 and at 450 °C and 500 bar using batch-type Inconel reactors. Erbium speciation was investigated as a function of pH from 2.8 to 8, where Er chloride species are predominant at acidic conditions (pH <3) and Er hydroxyl complexes are predominant at near- neutral to alkaline conditions (pH >3). At pH 7–9, the measured ErPO 4 solubility (-9.8 to -7.5 log m Er ) is up to 2.5 orders of magnitude lower than thermodynamic predictions (-9.4 to -6.7 log m Er ) using existing thermodynamic databases. At pH 2–3, the predicted ErPO 4 solubility is ~0.5 orders of magnitude higher at 350 °C and ~1 order of magnitude lower at 450 °C compared to experimentally measured Er concentrations. The thermodynamic properties of aqueous Er species were therefore revised in this study. The partial molal Gibbs energy of formation (Δ f G 0 T,P ) for aqueous Er hydroxyl and chloride species are optimized using GEMSFITS and the logarithmic formation constants (logβ n ( Cl,OH) ) were derived at each experimental temperature and pressure. The updated thermodynamic properties for Er hydroxyl species (Er(OH) +2 , Er(OH) 2 + , and Er(OH) 3 0 ) show that their stability shifts to more acidic conditions at and below 400 °C. The Er chloride species (ErCl +2 and ErCl 2 + ) show increased stability compared to Er hydroxyl species at temperatures of 450 °C and 0.01 mol/kg NaCl. The updated thermodynamic properties are implemented into the GEM-Selektor modeling package to investigate the mobility of Er in saline hydrothermal fluids in equilibrium with alkaline rocks. Importantly, the updated properties for Er hydroxyl species result in low Er solubility at rock equilibrated pH conditions due to an expanded hydroxyl predominance zone, but lower aqueous complex stability overall, whereas previous models suggest greater stability for aqueous Er species. Furthermore, ErPO 4 solubility increases with decreasing temperature due to the deprotonation of HCl, which increases the acidity of hydrothermal fluids and the availability of Cl - to complex with the REE. These simulations highlight how fluid-rock reaction and temperature affect the mobility of REE in hydrothermal ore-forming systems.

58 GEOSCIENCES↗
DOE OSTI2021

A Butterfly-Accelerated Volume Integral Equation Solver for Broad Permittivity and Large-Scale Electromagnetic Analysis

In this work, a butterfly-accelerated volume integral equation (VIE) solver is proposed for fast and accurate electromagnetic (EM) analysis of scattering from heterogeneous objects. The proposed solver leverages the hierarchical off-diagonal butterfly (HOD-BF) scheme to construct the system matrix and obtain its approximate inverse, used as a preconditioner. Complexity analysis and numerical experiments validate the O(N log 2 N) construction cost of the HOD-BF-compressed system matrix and O(N log 1.5 N) inversion cost for the preconditioner, where N is the number of unknowns in the high-frequency EM scattering problem. For many practical scenarios, the proposed VIE solver requires less memory and computational time to construct the system matrix and obtain its approximate inverse compared to a H matrix-accelerated VIE solver. The accuracy and efficiency of the proposed solver have been demonstrated via its application to the EM analysis of large-scale canonical and real-world structures comprising of broad permittivity values and involving millions of unknowns.

42 ENGINEERING↗
DOE OSTI2023

Reining in Radium for Nuclear Medicine: Extra-Large Chelator Development for an Extra-Large Ion

Targeted α therapy (TAT) of soft-tissue cancers using the α particle-emitting radionuclide 223 Ra holds great potential because of its favorable nuclear properties, adequate availability, and established clinical use for treating metastatic prostate cancer of the bone. Despite these advantages, the use of 223 Ra has been largely overshadowed by other α emitters due to its challenging chelation chemistry. A key criterion that needs to be met for a radionuclide to be used in TAT is its stable attachment to a targeting vector via a bifunctional chelator. The low charge density of Ra 2+ arising from its large ionic radius weakens its electrostatic binding interactions with chelators, leading to insufficient complex stability in vivo. In this study, we synthesized and evaluated macropa-XL as a novel chelator for 223 Ra. It bears a large 21-crown-7 macrocyclic core and two picolinate pendent groups, which we hypothesized would effectively saturate the large coordination sphere of the Ra 2+ ion. The structural chemistry of macropa-XL was first established with the nonradioactive Ba 2+ ion using X-ray diffraction and X-ray absorption spectroscopy, which revealed the formation of an 11-coordinate complex in a rare anti pendent-arm configuration. Subsequently, the stability constant of the [Ra(macropa-XL)] complex was determined via competitive cation exchange with 223 Ra and 224 Ra radiotracers and compared with that of macropa, the current state-of-the-art chelator for Ra 2+ . A moderate log K ML value of 8.12 was measured for [Ra(macropa-XL)], which is approximately 1.5 log K units lower than the stability constant of [Ra(macropa)]. This relative decrease in Ra 2+ complex stability for macropa-XL versus macropa was further probed using density functional theory calculations. Additionally, macropa-XL was radiolabeled with 223 Ra, and the kinetic stability of the resulting complex was evaluated in human serum. Furthermore, although macropa-XL could effectively bind 223 Ra under mild conditions, the complex appeared to be unstable to transchelation. Collectively, this study sheds additional light on the chelation chemistry of the exotic Ra 2+ ion and contributes to the small, but growing, number of chelator development efforts for 223 Ra-based TAT.

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

Quantum Multiple Eigenvalue Gaussian filtered Search: an efficient and versatile quantum phase estimation method

Quantum phase estimation is one of the most powerful quantum primitives. This work proposes a new approach for the problem of multiple eigenvalue estimation: Quantum Multiple Eigenvalue Gaussian filtered Search (QMEGS). QMEGS leverages the Hadamard test circuit structure and only requires simple classical postprocessing. QMEGS is the first algorithm to simultaneously satisfy the following two properties: (1) It can achieve the Heisenberg-limited scaling without relying on any spectral gap assumption. (2) With a positive energy gap and additional assumptions on the initial state, QMEGS can estimate all dominant eigenvalues to ϵ accuracy utilizing a significantly reduced circuit depth compared to the standard quantum phase estimation algorithm. In the most favorable scenario, the maximal runtime can be reduced to as low as log(1/ϵ). This implies that QMEGS serves as an efficient and versatile approach, achieving the best-known results for both gapped and gapless systems. Numerical results validate the efficiency of our proposed algorithm in various regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Lattice Boltzmann simulation of the dissolution of slag in alkaline solution using real-shape particles

Highlights: • A dissolution numerical model was proposed to capture the real dissolution kinetics of slag in alkaline solution. • The log forward dissolution rate of Si was described as a function of NBO/T and solution pH. • A threshold solid volume fraction of 0.688 was found for a voxel in 3D, 63.8% larger than that for a pixel in 2D. • The proposed dissolution numerical model provides a reliable alternative to study the dissolution kinetics of slag. A dissolution numerical model was proposed in this study to capture the real dissolution kinetics of slag in alkaline solution. It consists of three modules, i.e. (i) simulation of the initial particle parking structure of slag in alkaline solution using real-shape particles of slag, (ii) simulation of the chemical reactions between slag and solution based on the transition state theory, and (iii) simulation of the physical transport of aqueous ions using the lattice Boltzmann method. This dissolution numerical model was verified using experimental results, showing reasonable accuracy. After verification, the dissolution numerical model was implemented to study the influences of temperature and particle shape using a proper recipe of slag in alkaline solution. This recipe was designed to avoid solid phase precipitation or gel formation via thermodynamic analysis. The simulation results showed faster dissolution kinetics of slag when using higher temperatures and more irregular particle shapes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Utah FORGE: Well 16B(78)-32 Drill Core Fracture Analysis Images and Data

This dataset contains drilling core data from well 16B(78)-32, including PDF documents with flattened core images annotated by feature type and core interval, as well as spreadsheets detailing feature morphologies by depth, planar feature measurements, and planar feature orientations rotated to in situ conditions. Core was recovered from three intervals, one per stimulation stage, in the crystalline rocks affected by the stimulation of well 16A(78)-32. Seven core runs were conducted, yielding 135.8 feet of recovered core. Features in the core were categorized into planar fractures, semi-planar fractures, unbroken mineralized fractures, rough fractures, curviplanar fractures, concave-convex surfaces, and planar compositional features such as mylonite or dike-like structures. Planar features were measured while the core was positioned horizontally, with the core axis aligned to a downhole azimuth of 42 degrees. Planar core measurements from stimulations 2 and 3 that could be confidently correlated with FMI data were rotated to in situ orientations. This was done by rotating the planes along vertical and horizontal axes to match the azimuth and inclination data recorded in the directional survey of well 16B(78)-32, as well as applying an axial rotation to resemble the fracture orientations observed in the FMI log at corresponding depths. Coherent sets of planar fracture measurements were made by aligning the core within each 3-foot section of the dissected core barrel, and between adjacent 3-foot sections within a core run by matching rock fabrics, saw cuts and/or tool marks. Where coherent fracture measurements could not be made within a core run, data sets are denoted by a subscript (i.e. 2-Ta and 2-Tb both come from tangent core run number 2).

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Jackson, L., Johnson, M.B., Latrach, A., Grimes, D., Martinez, C., and Mclaughlin, J.F., 2024, Multidisciplinary geotechnical data collection, curation, and analysis for conformity with the regulatory framework for geologic carbon storage in Wyoming, USA: Geological Society of America Abstracts with Programs. Vol. 56, No. 5, 2024, doi: 10.1130/abs/2024AM-405024

Title: Multidisciplinary Geotechnical Data Collection, Curation, and Analysis for Conformity with the Regulatory Framework for Geologic Carbon Storage in Wyoming, USA. Text: Construction and operation of wells for geologic sequestration of carbon dioxide necessitate that they are permitted under the Environmental Protection Agency’s Underground Injection Control Class VI requirements. Class VI wells conform to stringent requirements to ensure long-term safety and integrity of the storage site and the protection of Underground Sources of Drinking Water. Entities pursuing Class VI permitting must provide comprehensive geologic site characterization, including regional geologic structure and stratigraphy, aquifer information, reservoir and confining unit geomechanical properties, geochemical analyses, assessment of trapping capacity and mechanisms, and a variety of other of multidisciplinary geotechnical data. The Wyoming Class VI Site Characterization Database Project is focused on developing a geologic site characterization database of geotechnical information, which has been compiled and verified from established, public databases/entities and scientific literature to expedite Class VI permitting in Sweetwater County within the Greater Green River Basin of southern Wyoming. The preliminary suite of compiled data from 14,000 wells includes 8,000 wells with logs and 7,250 wells with formation tops, ~70 wells with core data (e.g., X-Ray diffraction, petrographic, and petrophysical data), ~2,500 water analyses, ~740 seismic events data, and ~520 bottom-hole temperature measurements. Future work on—and stemming from—this project will include new core analyses, calculation and interpolation of subsurface temperature gradients, mechanical earth models, geochemical simulations, storage capacity estimation, stratigraphic column generation and correlation, and construction of subsurface maps. Finally, this work will help to inspire and facilitate subsurface data compilation and curation beyond Sweetwater County, Wyoming.

42 ENGINEERING↗
DOE OSTI2020

Stochastically Realized Observables for Excitonic Molecular Aggregates

In this work, we show that a stochastic approach enables calculations of the optical properties of large 2-dimensional and nanotubular excitonic molecular aggregates. Previous studies of such systems relied on numerically diagonalizing the dense and disordered Frenkel Hamiltonian, which scales approximately as $\mathcal{O}$($N$ 3 ) for $N$ dye molecules. Our approach scales much more efficiently as $\mathcal{O}$($N$ log($N$)), enabling quick study of systems with a million of coupled molecules on the micrometer size scale. We calculate several important experimental observables, including the optical absorption spectrum and density of states, and develop a stochastic formalism for the participation ratio. Quantitative agreement with traditional matrix diagonalization methods is demonstrated for both small- and intermediate-size systems. The stochastic methodology enables the study of the effects of spatial-correlation in site energies on the optical signatures of large 2D aggregates. Our results demonstrate that stochastic methods present a path forward for screening structural parameters and validating experiments and theoretical predictions in large excitonic aggregates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗