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DOE OSTI2025

A15 phase Ta 3⁢ Sb thin films: Direct synthesis, charge transport, and spin-orbit torque

Ta 3 ⁢Sb is one of the A15 compounds that have been predicted to have giant spin Hall conductivities due to the gapped Dirac-like band crossings in their electronic structures. We use co-sputtering to directly synthesize thin films of Ta 3 ⁢Sb and identify a large window of Ta:Sb flux ratio that permits the formation of single-phase A15 structure. These sputtered films have an actual Ta:Sb atomic ratio of 4:1, as determined from Rutherford backscattering spectrometry. Their high resistivity, at the Mott-Ioffe-Regel limit, suggests that the electron mean free path is comparable to interatomic distances. From harmonic Hall and spin-torque ferromagnetic resonance measurements, the intrinsic spin Hall conductivity of thin film Ta 3 ⁢Sb is estimated to be in the range of −526 to −1230⁢(ℏ/𝑒)S/cm at 300 K, lower in magnitude than the predicted value of −1400⁢(ℏ/𝑒)S/cm . Here, first-principles calculations of the electronic structure show that the discrepancy is consistent with an increase of the Fermi level due to the nonideal stoichiometry needed to stabilize the A15 structure.

Density functional theory↗

NASA NTRS2016

Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM (sub 2.5).

Environmental Public Health↗

DOE OSTI2026

Degassing fluxes in a temperate hydropower reservoir predictable by deep‐water dissolved oxygen but highly sensitive to discharge variability

Hydropower reservoirs contribute to methane (CH 4 ) and carbon dioxide (CO 2 ) emissions, like all aquatic ecosystems. Unique to hydropower reservoirs are degassing emissions that occur when deep-water intakes move water with high CH 4 and CO 2 concentrations through turbines, leading to the release of these gases. However, few studies from hydropower reservoirs have measured seasonal variability and drivers of degassing fluxes, especially in temperate systems. We measured monthly degassing emissions in temperate Douglas Reservoir (Tennessee, USA) from 2023 to 2024. We found that degassing fluxes were highest in the summertime, and deep-water CH 4 and CO 2 concentrations were predictable by deep-water dissolved oxygen (DO) concentrations. Degassing emissions accounted for 37–62% of annually estimated CH 4 emissions, outweighing ebullitive emissions during summer months. We highlight the value of using DO data to estimate deep-water CH 4 and CO 2 concentrations and degassing fluxes at higher temporal resolution to improve annualization and extrapolation of reservoir degassing emissions at broader scales.

Pilla, Rachel M. [Oak Ridge National Laboratory (O↗

DOE OSTI2023

The highly exothermic hydrogen abstraction reaction H 2 Te + OH → H 2 O + TeH: comparison with analogous reactions for H 2 Se and H 2 S

The “gold standard” CCSD(T) method is adopted along with the correlation consistent basis sets up to aug-cc-pV5Z-PP to study the mechanism of the hydrogen abstraction reaction H 2 Te + OH. Here, the predicted geometries and vibrational frequencies for reactants and products are in good agreement with the available experimental results. With the ZPVE corrections, the transition state in the favorable pathway of this reaction energetically lies 1.2 kcal mol -1 below the reactants, which is lower than the analogous relative energies for the H 2 Se + OH reaction (-0.7 kcal mol -1 ), the H 2 S + OH reaction (+0.8 kcal mol -1 ) and the H 2 O + OH reaction (+9.0 kcal mol -1 ). Accordingly, the exothermic reaction energies for these related reactions are predicted to be 47.8 (H 2 Te), 37.7 (H 2 Se), 27.1 (H 2 S), and 0.0 (H 2 O) kcal mol -1 , respectively. Geometrically, the low-lying reactant complexes for H 2 Te + OH and H 2 Se + OH are two-center three-electron hemibonded structures, whereas those for H 2 S + OH and H 2 O + OH are hydrogen-bonded. With ZPVE and spin–orbit coupling corrections, the relative energies for the reactant complex, transition state, product complex, and the products for the H 2 Te + OH reaction are estimated to be -13.1, -1.0, -52.0, and -52.6 kcal mol -1 , respectively. Finally, twenty-eight DFT functionals have been tested systematically to assess their ability in describing the potential energy surface of the H 2 Te + OH reaction. The best of these functionals for the corresponding energetics are -9.9, -1.4, -46.4, and -45.4 kcal mol -1 (MPWB1K), or -13.1, -2.4, -57.1, and -54.6 kcal mol -1 (M06-2X), respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

A General Spatiotemporal Imputation Framework for Missing Sensor Data

Many applications from precision agriculture, environmental monitoring and transportation networks rely on data collected across space and time over a large geographic area. Missing data poses a significant challenge for any data-driven inference and control tasks. Data imputation or the estimation of missing data can help fill these gaps by utilizing inherent spatial relationships and temporal patterns. A variety of spatiotemporal imputation models have been developed to address missing data in spatiotemporal datasets. However, these classical methods rely on the assumption that the underlying data follows a smooth trend and fail to provide accurate estimates when there is a large number of missing points in the data. Even though there are machine learning driven tensor completion approaches such as convolutional neural network based tensor completion (CoSTCo) that capture the non-linear relationships in the dataset, the transductive nature makes the algorithm less scalable. Thus, existing approaches for estimating the missing information do not effectively capture all dimensions of the spatiotemporal data structure, resulting in erroneous predictions and poor performance. The main contributions of this paper are: (1) We propose a novel inductive framework (G-LSTM) for missing data imputation that integrates a graph neural network with LSTMs to effectively capture both spatial and temporal dependencies. (2) Experimental results on a traffic dataset demonstrate that the proposed GNN integrated with an LSTM framework achieves improved imputation and maintains steady performance even when there are extreme missing conditions in comparison with the state-of-the-art imputation framework (i.e, CoSTCo). (3) The simulation results on a traffic network show up to 69% reduction in mean absolute error and 61% reduction in root mean square error when compared to CoSTCo.

Tharzeen, Aabila↗

DOE OSTI2022

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1994

Interhemispheric asymmetry of the high-latitude ionospheric convection pattern

The assimilative mapping of ionospheric electrodynamics technique has been used to derive the large-scale high-latitude ionospheric convection patterns simultaneously in both northern and southern hemispheres during the period of January 27 to 29, 1992. When the interplanetary magnetic field (IMF) B(sub z) component is negative, the convection patterns in the southern hemisphere are basically the mirror images of those in the northern hemisphere. The total cross-polar cap potential drops in the two hemispheres are similar. When B(sub z) is positive and absolute value of B(sub y) greater than B(sub z), the convection configurations are mainly determined by B(sub y) and they may appear as normal 'two-cell' patterns in both hemispheres much as one would expect under southward IMF conditions. However, there is a significant difference in the cross-polar-cap potential drop between the two hemispheres, with the potential drop in the southern (summer) hemisphere over 50% larger than that in the northern (winter) hemisphere. As the ratio of absolute value of B(sub y)/B(sub z) decreases (less than one), the convection configuration in the two hemispheres may be significantly different, with reverse convection in the southern hemisphere and weak but disturbed convection in the northern hemisphere. By comparing the convection patterns with the corresponding spectrograms of precipitating particles, we interpret the convection patterns in terms of the concept of merging cells, lobe cells, and viscous cells. Estimates of the ' merging cell' potential drops, that is, the potential ascribed to the opening of the dayside field lines, are usually comparable between the two hemispheres, as they should be. The 'lobe cell' provides a potential between 8.5 and 26 kV and can differ greatly between hemispheres, as predicted. Lobe cells can be significant even for southward IMF, if absolute value of B(sub y) greater than the absolute value of B(sub z). To estimate the potential drop of the 'viscous cells,' we assume that the low-latitude boundary layer is on closed field lines. We find that this potential drop varies from case to case, with a typical value of 10 kV. If the source of these cells is truly a viscous interaction at the flank of the magnetopause, the process is likely spatially and temporally varying rather than steady state.

Lu, G.↗

NASA NTRS1996

X-29A Lateral-Directional Stability and Control Derivatives Extracted From High-Angle-of-Attack Flight Data

The lateral-directional stability and control derivatives of the X-29A number 2 are extracted from flight data over an angle-of-attack range of 4 degrees to 53 degrees using a parameter identification algorithm. The algorithm uses the linearized aircraft equations of motion and a maximum likelihood estimator in the presence of state and measurement noise. State noise is used to model the uncommanded forcing function caused by unsteady aerodynamics over the aircraft at angles of attack above 15 degrees. The results supported the flight-envelope-expansion phase of the X-29A number 2 by helping to update the aerodynamic mathematical model, to improve the real-time simulator, and to revise flight control system laws. Effects of the aircraft high gain flight control system on maneuver quality and the estimated derivatives are also discussed. The derivatives are plotted as functions of angle of attack and compared with the predicted aerodynamic database. Agreement between predicted and flight values is quite good for some derivatives such as the lateral force due to sideslip, the lateral force due to rudder deflection, and the rolling moment due to roll rate. The results also show significant differences in several important derivatives such as the rolling moment due to sideslip, the yawing moment due to sideslip, the yawing moment due to aileron deflection, and the yawing moment due to rudder deflection.

Iliff, Kenneth W.↗

NASA NTRS2003

Validation and Error Characterization for the Global Precipitation Measurement

The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration, assumption, or algorithm. The instrumentation and techniques of the Supersites will be discussed. The GPM core satellite, with its dual-frequency radar and conically scanning radiometer, will provide insight into precipitation drop-size distributions and potentially increased measurement capabilities of light rain and snowfall. The ground validation program will include instrumentation and techniques commensurate with these new measurement capabilities.

Bidwell, Steven W.↗

NASA NTRS2006

Current Sheet Evolution In The Aftermath Of A CME Event

We report on SOHO UVCS observations of the coronal restructuring following a coronal mass ejection (CME) on 2002 November 26, at the time of a SOHO-Ulysses quadrature campaign. Starting about 1.5 hr after a CME in the northwest quadrant, UVCS began taking spectra at 1.7 R, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 A line of [Fe XVIII], indicating temperatures above 6 x 10(exp 6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature versus time in the current sheet and estimate its density. At the time of the quadrature, Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by the Ulysses SWICS throughout the magnetic cloud associated with the CME, although its rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. The SOHO-Ulysses data set provided us with the unique opportunity of analyzing a current sheet structure from its lowest coronal levels out to its in situ properties. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗

NASA NTRSDate not supplied

Comparison of Entry Descent and Landing Aerodynamic Databases with Uncertainty Quantification Developed Using Machine Learning Techniques

When developing the aerodynamic databases for use in trajectory simulations, it is important to develop a system of metrics to qualify which aerodynamic models are best to use. Since aerodynamics are just one input into trajectory simulations, the results of these simulations do not reflect on the quality of the aerodynamic database used. This means that aerodynamic database comparisons must be done offline. While traditional metrics that focus on mean/nominal predictions are a good first step, more robust estimates of the prediction interval become important as more focused uncertainty models are developed. We explore the limitations of evaluating aerodynamic models based purely on nominal-centered response surfaces. Before elaborating and evaluating metrics based on distributed models, the value of evaluating prediction interval and confidence interval are discussed to conclude that prediction intervals are more relevant to the use of trajectory analysis. Several metrics to evaluate the prediction interval are introduced with a focus on the standard calibration metric. Finally, we compare candidate models using both mean and distributed metrics. A finalized candidate model developed using state of the art machine learning methods is compared to a baseline model developed using traditional aerodynamic database modeling techniques.

Aerodynamic Database↗

NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

The James Webb Space Telescope (JWST) is a NASA flagship mission launched on December 25, 2021. The early orbit phase was highlighted by three midcourse correction burns that were performed to maneuver the vehicle into a libration orbit at the second Sun-Earth-Moon (SEM) libration point (L2). During the coast to L2, the vehicle’s primary observatory and sunshield were deployed. Once the tennis-court-sized sunshield was unfurled and tensioned into place, the large area exposed to solar radiation pressure (SRP) dictated that the SRP force model would need to account for the vehicle’s geometry, reflective properties, and orientation relative to the Sun. Following the insertion of JWST into its L2 libration orbit on January 24, 2022, the commissioning phase for the vehicle’s observatory commenced along with the first cycle of routine station-keeping maneuvers. The NASA Goddard Space Flight Center’s Flight Dynamics Facility (FDF) provides navigation services for the JWST mission. The FDF serves as the prime or backup navigation operations center for more than 30 active missions spanning a wide array of flight regimes performing orbit determination, maneuver planning, trajectory optimization, and tracking data evaluation. Definitive orbit determination for JWST is performed by the FDF using an Extended Kalman Filter (EKF) to estimate the vehicle’s trajectory and reflective properties using Deep Space Network (DSN) TRK-2-34 tracking data and spacecraft attitude telemetry. For the purposes of orbit prediction and station-keeping maneuver targeting, the sensitivity of the SRP force to the vehicle’s orientation requires that predictive attitude information must be incorporated to generate accurate orbit predictions and maneuver plans. Predictive attitude plans are provided to the FDF by the JWST Spacecraft Operations Center (SOC). Short-term (28 day) orbit predictions are propagated using a Short Range Attitude Plan (SRAP) to model the vehicle’s future attitude states for up to a week. SRAP attitude data is highly reliable, as it reflects finalized planned attitude states that the vehicle will be commanded to attain during the ensuing week. A Long Range Attitude Plan (LRAP) can be implemented to model predicted attitude states beyond one week, but these predictions are tentative and subject to revision due to changes in science operations plans. Instead, a conservative approach of applying a Sun-Pointing Neutral (SPN) attitude configuration is utilized for long-term (2 year) orbit predictions where reliable planned attitude data is not available. SPN attitude mode aligns the net SRP force along the JWST-to-Sun vector where it becomes independent of the vehicle’s angle of rotation about this vector, defined as the Sun yaw. Given the dynamic instability of the libration orbit, station-keeping thrust must be applied in either the sunward or anti-sunward direction to balance the resulting orbit. The attitude constraints of the vehicle also impose limits on the available pointing directions for station-keeping thrusters. The thrusters cannot be aligned with the optimal pointing direction for sunward maneuvers, rendering sunward maneuvers to be significantly less fuel efficient than anti-sunward maneuvers. Consequently, station-keeping maneuvers must be targeted to balance the orbit while ensuring that the next maneuver will also be performed in the anti-sunward direction to optimize propellant usage. When targeting a station-keeping maneuver, the attitude and SRP modeling configuration which is applied to the predicted post-maneuver trajectory will dictate the direction of the subsequent station-keeping maneuver, assuming nominal propulsion system performance. If the predicted post-maneuver attitude states result in an SRP model which under-predicts the cumulative SRP impact on the post-maneuver orbit, a targeted anti-sunward maneuver will be larger than necessary and the next maneuver will need to be executed sunward in order to compensate. In contrast, an anti-sunward maneuver which is targeted using an SRP model which over-predicts the cumulative SRP impact will achieve station-keeping while ensuring that the next maneuver will likewise be performed anti-sunward. For this reason, station-keeping maneuvers are targeted while applying the SPN attitude mode, as this mode entails the largest possible SRP area cross-section and therefore a larger modeled cumulative SRP impact. This paper documents the NASA Goddard Space Flight Center’s FDF support for JWST on-orbit operations and the analysis projects undertaken utilizing the experiences and data accumulated throughout the first full year of routine science operations. The results of these analysis efforts have been used to implement improvements to orbit prediction accuracy and maneuver efficiency which have the potential to prolong the lifespan of JWST to continue to conduct ground-breaking infrared astronomy for decades to come.

Flight Dynamics↗

DOE OSTI2025

Leveraging interpolation models and error bounds for verifiable scientific machine learning

Effective verification and validation techniques for modern scientific machine learning workflows are challenging to devise. Statistical methods are abundant and easily deployed, but often rely on speculative assumptions about the data and methods involved. Error bounds for classical interpolation techniques can provide mathematically rigorous estimates of accuracy, but often are difficult or impractical to determine computationally. Here, in this work, we present a best-of-both-worlds approach to verifiable scientific machine learning by demonstrating that (1) multiple standard interpolation techniques have informative error bounds that can be computed or estimated efficiently; (2) comparative performance among distinct interpolants can aid in validation goals; (3) deploying interpolation methods on latent spaces generated by deep learning techniques enables some interpretability for black-box models. We present a detailed case study of our approach for predicting lift-drag ratios from airfoil images. Code developed for this work is available in a public Github repository.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Attitude determination of a high altitude balloon system. Part 2: Development of the parameter determination process

The attitude of the balloon system is determined as a function of time if: (a) a method for simulating the motion of the system is available, and (b) the initial state is known. The initial state is obtained by fitting the system motion (as measured by sensors) to the corresponding output predicted by the mathematical model. In the case of the LACATE experiment the sensors consisted of three orthogonally oriented rate gyros and a magnetometer all mounted on the research platform. The initial state was obtained by fitting the angular velocity components measured with the gyros to the corresponding values obtained from the solution of the math model. A block diagram illustrating the attitude determination process employed for the LACATE experiment is shown. The process consists of three essential parts; a process for simulating the balloon system, an instrumentation system for measuring the output, and a parameter estimation process for systematically and efficiently solving the initial state. Results are presented and discussed.

Nigro, N. J.↗

NASA NTRS1986

An economical semi-analytical orbit theory for micro-computer applications

An economical algorithm is presented for predicting the position of a satellite perturbed by drag and zonal harmonics J2 through J4. Simplicity being of the essence, drag is modeled as a secular decay rate in the semimajor axis (retarded motion) with the zonal perturbations modeled from a modified version of Brouwers formulas. The algorithm is developed as an alternative on-board orbit predictor; a back up propagator requiring low energy consumption; or a ground based propagator for microcomputer applications (e.g., at the foot of an antenna). An O(J2) secular retarded state partial matrix (matrizant) is also given to employ with state estimation. The theory has been implemented in BASIC on an inexpensive microcomputer, the program occupying under 8K bytes of memory. Simulated trajectory data and real tracking data are employed to illustrate the theory's ability to accurately accommodate oblateness and drag effects.

Gordon, R. A.↗

NASA NTRS2000

Constituent-Based Life Models Being Developed for SiC/SiC Composites

For the successful utilization of ceramic matrix composites (CMC) as hot-section components in advanced aeropropulsion engines, the CMC constituents will need to be tailored and optimized to meet all the critical property demands of each component. Under the High-Speed Research (HSR) and Advanced High-Temperature Engine Materials Technology (HITEMP) Programs, the NASA Glenn Research Center at Lewis Field initiated research to develop mechanistic models for key CMC thermostructural properties. These models would describe the effects of different constituent factors (composition, geometry, and volume fraction) and of potential application conditions (stress, time, temperature, and environment) on these properties. Particular focus was placed on both analytical and numerical modeling of state-of-the-art SiC/SiC composites where the primary load-bearing constituents are stoichiometric SiC fibers in a complex multiphase SiC matrix produced by chemical vapor infiltration and melt infiltration. Recent studies have resulted in computer-based numerical models for the elastic modulus, thermal expansion, and thermal conductivity properties of the SiC/SiC system. Additional studies have generated analytical and empirical models for the time dependence of composite rupture strength at temperatures above 2200 F (1200 C), where CMC's have an important thermostructural advantage over current nickel-based superalloys. These life models utilize thermal activation theory and fiber stress-rupture results measured at Glenn to generate Larson-Miller (L M) plots of fiber rupture strength versus q, a single time- and temperature-dependent parameter. Assuming a worse case in which the SiC matrix is cracked, rupture is then controlled by the time-dependent fracture characteristics of the fiber bundles bridging the matrix cracks. With this as the controlling mechanism, one can then use simple composite theory and the fiber L M plots to predict CMC rupture strength versus the q parameter. The dashed line shows the predicted rupture strength of a SiC/SiC composite that is reinforced by a state-of-the-art stoichiometric SiC fiber. For the q parameter, time is in hours and temperature in degrees kelvin. To generate these predictions, a two-dimensional 0 /90 composite with approximately 16 percent fiber in the applied stress direction and an air test environment were assumed. As such, it is possible to compare the model predictions against limited stress-rupture data for this CMC as shown by the data points. The good agreement confirms the rupture model at least for the selected CMC and test conditions. Thus for this particular SiC/SiC composite, one can estimate a 1000-hr rupture strength of approximately 12 ksi at 2400 F (T = 1588 K and q = 39 700 K). At lower CMC application stresses, the SiC matrix is typically uncracked, so both the fiber and matrix constituents share the composite load. In this case, CMC rupture is controlled by the constituent with the longest rupture time based on the creep rate of the composite. Measured Monkman-Grant plots of rupture time versus creep rate for the two SiC constituents have been used to develop CMC life models for this important application condition. NASA and DOD are currently using this information to establish application and material goals for more advanced CMC's that can be used at even higher temperatures.

DiCarlo, James A.↗

DOE OSTI2026

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗

DOE OSTI2022

A combined first principles study of the structural, magnetic, and phonon properties of monolayer CrI3

The first magnetic 2D material discovered, monolayer (ML) CrI3, is particularly fascinating due to its ground state ferromagnetism. However, because ML materials are difficult to probe experimentally, much remains unresolved about ML CrI3’s structural, electronic, and magnetic properties. Here, we leverage Density Functional Theory (DFT) and high-accuracy Diffusion Monte Carlo (DMC) simulations to predict lattice parameters, magnetic moments, and spin–phonon and spin–lattice coupling of ML CrI3. We exploit a recently developed surrogate Hessian DMC line search technique to determine CrI3’s ML geometry with DMC accuracy, yielding lattice parameters in good agreement with recently published STM measurements—an accomplishment given the ~10% variability in previous DFT-derived estimates depending upon the functional. Strikingly, we find that previous DFT predictions of ML CrI3’s magnetic spin moments are correct on average across a unit cell but miss critical local spatial fluctuations in the spin density revealed by more accurate DMC. DMC predicts that magnetic moments in ML CrI3 are 3.62 μB per chromium and -0.145 μB per iodine, both larger than previous DFT predictions. The large disparate moments together with the large spin–orbit coupling of CrI3’s I-p orbital suggest a ligand superexchange-dominated magnetic anisotropy in ML CrI3, corroborating recent observations of magnons in its 2D limit. We also find that ML CrI3 exhibits a substantial spin–phonon coupling of ~3.32 cm-1. Our work, thus, establishes many of ML CrI3’s key properties, while also continuing to demonstrate the pivotal role that DMC can assume in the study of magnetic and other 2D materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗