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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Geochemical and Microstructural Characterization of Shale Rock: A Workflow for Site Evaluation for Energy–Fluids Storage

Shales are a central component of petroleum systems, as source, seal, and unconventional reservoir rocks. Unlike traditional unconventional shale, a newly emerging Caney Shale play is regarded as an unconventional of unconventional shales (UUS), due to its high content of fine-grained materials, lower reservoir porosity, dominance of nanopores, and a scarcity of visible natural fractures. Other developed unconventional shales such as the Woodford and Barnett have larger average pore size, higher porosity, and extensive natural fractures at core scale that contribute to reservoir quality. In this work, the Caney Shale was cored in entirety to characterize its interbedded ductile and reservoir intervals and establish criteria for their recognition. Representative ductile and reservoir intervals known as D2 and R3, respectively, were selected for detailed analysis including variations in elemental composition, mineralogy, facies, and the presence of natural fractures at well and core scales using X-ray fluorescence, X-ray diffraction, and thin section and core description. Characteristics of microstructure and microgeochemistry at nano- and microscales are compared using field emission scanning electron microscopy with energy dispersive spectroscopy and lowpressure nitrogen adsorption isotherms with fractal dimension analysis. The ductile (detrital clay-rich) member D2 is characterized by higher concentrations of Ti and Al and lower Si, while the reservoir R3 (possibly biogenic silica-accumulated) is characterized by lower Ti and Al and higher Si. Eight mixed carbonate–siliciclastic facies are recognized, and R3 shows a higher heterogeneity of facies stacking and average fracture abundance than D2. Further, R3 shows a more microscopically heterogeneous fabric/texture of matrix and a higher microporosity than D2 that has a higher pore surface heterogeneity. A fundamental understanding of the compositional and microstructural characteristics of UUS and further ductile/reservoir intervals will allow for a better assessment of reservoir quality, more effective production of hydrocarbons, and optimized selection of safe caprocks in carbon sequestration and subsurface hydrogen storage.

58 GEOSCIENCES↗
DOE OSTI2023

A Graphical Model for Fusing Diverse Microbiome Data

This paper develops a Bayesian graphical model for fusing disparate types of count data. The motivating application is the study of bacterial communities from diverse high-dimensional features, in this case, transcripts, collected from different treatments. In such datasets, there are no explicit correspondences between the communities and each corresponds to different factors, making data fusion challenging. We introduce a flexible multinomial-Gaussian generative model for jointly modeling such count data. This latent variable model jointly characterizes the observed data through a common multivariate Gaussian latent space that parameterizes the set of multinomial probabilities of the transcriptome counts. The covariance matrix of the latent variables induces a covariance matrix of co-dependencies between all the transcripts, effectively fusing multiple data sources. We present a computationally scalable variational Expectation-Maximization (EM) algorithm for inferring the latent variables and the parameters of the model. Here, the inferred latent variables provide a common dimensionality reduction for visualizing the data and the inferred parameters provide a predictive posterior distribution. In addition to simulation studies that demonstrate the variational EM procedure, we apply our model to a bacterial microbiome dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Real time evolution for ultracompact Hamiltonian eigenstates on quantum hardware

In this work we present a detailed analysis of variational quantum phase estimation (VQPE), a method based on real-time evolution for ground and excited state estimation on near-term hardware. We derive the theoretical ground on which the approach stands, and demonstrate that it provides one of the most compact variational expansions to date for solving strongly correlated Hamiltonians. At the center of VQPE lies a set of equations, with a simple geometrical interpretation, which provides conditions for the time evolution grid in order to decouple eigenstates out of the set of time evolved expansion states, and connects the method to the classical filter diagonalization algorithm. Further, we introduce what we call the unitary formulation of VQPE, in which the number of matrix elements that need to be measured scales linearly with the number of expansion states, and we provide an analysis of the effects of noise which substantially improves previous considerations. The unitary formulation allows for a direct comparison to iterative phase estimation. Our results mark VQPE as both a natural and highly efficient quantum algorithm for ground and excited state calculations of general many-body systems. We demonstrate a hardware implementation of VQPE for the transverse field Ising model. Further, we illustrate its power on a paradigmatic example of strong correlation (Cr2 in the SVP basis set), and show that it is possible to reach chemical accuracy with as few as ~50 timesteps.

Klymko, Katherine↗
DOE OSTI2020

Landslide monitoring using seismic refraction tomography – The importance of incorporating topographic variations

Seismic refraction tomography provides images of the elastic properties of subsurface materials in landslide settings. Seismic velocities are sensitive to changes in moisture content, which is a triggering factor in the initiation of many landslides. However, the application of the method to long-term monitoring of landslides is rarely used, given the challenges in undertaking repeat surveys and in handling and minimizing the errors arising from processing time-lapse surveys. This work presents a simple method and workflow for producing a reliable time-series of inverted seismic velocity models. This method is tested using data acquired during a recent, novel, long-term seismic refraction monitoring campaign at an active landslide in the UK. Potential sources of error include those arising from inaccurate and inconsistent determination of first-arrival times, inaccurate receiver positioning, and selection of inappropriate inversion starting models. At our site, a comparative analysis of variations in seismic velocity to real-world variations in topography over time shows that topographic error alone can account for changes in seismic velocity of greater than ±10% in a significant proportion (23%) of the data acquired. The seismic velocity variations arising from real material property changes at the near-surface of the landslide, linked to other sources of environmental data, are demonstrated to be of a similar magnitude. Over the monitoring period we observe subtle variations in the bulk seismic velocity of the sliding layer that are demonstrably related to variations in moisture content. This highlights the need to incorporate accurate topographic information for each time-step in the monitoring time-series. The goal of the proposed workflow is to minimize the sources of potential errors, and to preserve the changes observed by real variations in the subsurface. Following the workflow produces spatially comparable, time-lapse velocity cross-sections formulated from disparate, discretely-acquired datasets. These practical steps aim to aid the use of the seismic refraction tomography method for the long-term monitoring of landslides prone to hydrological destabilization.

Whiteley, J. S.↗
DOE OSTI2022

Effect of inoculation with prion dilutions within the dynamic range of ELISA absorbance on prion incubation period

This study examines the effect of various infectious prion titers within the dynamic range as measured by ELISA on incubation period. We inoculated ovinized transgenic mice with seven decreasing dilutions of a fast-incubating scrapie strain. The highest inoculum group was a 20% w/v brain homogenate from a sheep with scrapie. The subsequent six inoculum dilutions ranged from the highest ELISA optical density reading of 4.000 to a dilution where scrapie prions were not detectable by ELISA. Multiple comparison analysis demonstrated variation in the incubation periods between some inoculum groups. Incubation periods were similar between inoculum groups unless their optical density differed by more than ≈2 units of absorbance. These data will inform the interpretation of future studies that compare incubation periods in experimentally inoculated animals for TSE research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Quantifying cover crop effects on soil health and productivity

The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of acetic acid exposure on metal contact degradation of different crystalline silicon solar cell technologies

Degradation due to acetic acid in photovoltaic (PV) modules has been a commonly observed phenomenon for both damp-heat exposure and outdoor operations. Acetic acid is a degradation byproduct of ethylene-vinyl acetate (EVA), a common module encapsulant. To address this issue, robust metallization pastes and cell technologies are being developed. However, it is important to assess how these technologies perform in an acetic acid environment and withstand degradation before they are implemented in the solar market. In this work, we investigate the impact of acetic acid exposure on four different cell groups: monofacial passivated emitter and rear contact (PERC) cells with advanced telluride-based front contact pastes, bifacial PERC cells with novel aluminum rear contact pastes, bifacial tunnel oxide passivated contacts (TOPCon) cells, and silicon heterojunction (SHJ) cells. These cells were exposed to acetic acid for different time increments. The recombination losses were characterized by Suns-VOC, and multi-variate regression analysis of intensity-dependent photoluminescence (PL) images with Griddler AI. Resistive losses were tracked with the transmission line method (TLM). Samples showing severe performance degradation were selected for further materials characterization to understand the root cause. Top-down and cross-sectional scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) were performed to investigate the change in materials properties. Our study shows that the front contacts of the bifacial TOPCon cells and monofacial PERC cells were significantly affected by acetic acid exposure. Here, the SHJ cells were found to be the most stable.

14 SOLAR ENERGY↗
DOE OSTI2020

CO 2 –Brine Contact Angle Measurements on Navajo, Nugget, Bentheimer, Bandera Brown, Berea, and Mt. Simon Sandstones

In this study, contact angles were measured for CO 2 bubbles on six different sandstones (Navajo, Nugget, Bentheimer, Bandera Brown, Berea, and Mt. Simon) that could potentially represent properties of CO 2 storage depositional environments. The impacts of pressure and temperature were studied by focusing on the CO 2 phase behavior in three different scenarios: gaseous, liquid, and supercritical conditions. Despite controlling the sample preparation and cleanliness, CO 2 -brine equilibration conditions, and pressure and temperature, there were inconsistencies in contact angle trends that could largely be attributed to natural sample heterogeneity resulting from localized variations in topography, surface roughness, and mineral composition across the surface. Despite these variations, the analysis of 298 measurements from this study showed that 81% of the contact angles were below 40° representing strongly water-wet to (moderately) water-wet behaviors. Also, 17.3% of the measurements were between 40° and 60° (weakly water-wet) and primarily belonged to small CO 2 bubbles (< 500 μm) that were heavily impacted by localized surface heterogeneity in natural sandstone samples. Additionally, only 1.7% of the measurements had angles greater than 60° and could be classified as CO 2 -wet behavior, but these measurements occurred on extremely small bubbles (100-200 μm) that were very dependent on localized surface heterogeneity. While some of the detailed physics of the CO 2 -brine-sandstone interface is still poorly understood, from an application standpoint, the sandstones of this study were best characterized as strongly water-wet to (moderately) water-wet.

03 NATURAL GAS↗
DOE OSTI2025

Analytical Model for the Higher Order Moments of Midlatitude Atmospheric Temperature Distributions

Observed distributions of atmospheric temperature are non-Gaussian. Therefore, moments beyond variance are necessary in determining the frequency of extreme temperature events. Here we propose a simple kinematic model for atmospheric mid-latitude temperature variability based on symmetric advection from a non-symmetric background temperature profile. We then use this model to derive analytical expressions for the higher order moments of temperature distributions. Our results show that nonzero skewness and kurtosis arise due to the nonlinearity of the time-mean meridional temperature profile. The analytical model matches an idealized Held-Suarez atmospheric model, indicating nonlinearity of time-mean temperature in latitude is the dominant contribution to nonzero skewness and kurtosis in synoptic temperature variations. Model analysis further shows decrease in higher order moments due to climate change come roughly equally from changes in mixing length and changes in the background temperature profiles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Stress Field Dynamics and Fault Slip Potential in the Paradox Basin

Abstract The Paradox Basin, straddling Utah, Colorado, Arizona, and New Mexico is characterized by an intricate amalgamation of evaporites and clastic layers and is dominated by prominent salt walls and related subsurface structures. Our research offers a new examination of the stress distribution across the basin, deriving from continuous and discrete stress measurements conducted in boreholes in the region and focal mechanism analysis, emphasizing variations over salt structures. Integrating Coulomb failure criteria with probabilistic methods, we assess potential fault movements resulting from fluid pressure alterations. Our approach provides a comprehensive understanding of the Paradox Basin's state of stress, showing a continuous change of the maximum horizontal stress orientation from N‐S at the Wasatch Fault Zone to WNW‐ESE in the northern part of the Paradox Basin and to WSW‐ENE in the southern part of the basin. Further East, into the Colorado Plateau and the Uncompahgre Uplift, the S H max orientation becomes E‐W. Decoding stress orientation dynamics has enabled critical insights into fault slip potential, especially in the basin's northern region. The salt wall faults are less likely to slip, and the Paradox Formation's evaporite and clastic rock sequence can serve as a potential low seismic risk target for carbon storage and hydrocarbon extraction.

Geochemistry & Geophysics↗
DOE OSTI2020

Expression profiling of MADS-box gene family revealed its role in vegetative development and stem ripening in S. spontaneum

Sugarcane is the most important sugar and biofuel crop. MADS-box genes encode transcription factors that are involved in developmental control and signal transduction in plants. Systematic analyses of MADS-box genes have been reported in many plant species, but its identification and characterization were not possible until a reference genome of autotetraploid wild type sugarcane specie, Saccharum spontaneum is available recently. We identified 182 MADS-box sequences in the S. spontaneum genome, which were annotated into 63 genes, including 6 (9.5%) genes with four alleles, 21 (33.3%) with three, 29 (46%) with two, 7 (11.1%) with one allele. Paralogs (tandem duplication and disperse duplicated) were also identified and characterized. These MADS-box genes were divided into two groups; Type-I (21 Mα, 4 Mβ, 4 Mγ) and Type-II (32 MIKCc, 2 MIKC*) through phylogenetic analysis with orthologs in Arabidopsis and sorghum. Structural diversity and distribution of motifs were studied in detail. Chromosomal localizations revealed that S. spontaneum MADS-box genes were randomly distributed across eight homologous chromosome groups. The expression profiles of these MADS-box genes were analyzed in leaves, roots, stem sections and after hormones treatment. Important alleles based on promoter analysis and expression variations were dissected. qRT-PCR analysis was performed to verify the expression pattern of pivotal S. spontaneum MADS-box genes and suggested that flower timing genes ( SOC1 and SVP ) may regulate vegetative development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stability of trapped solutions of a nonlinear Schrödinger equation with a nonlocal nonlinear self-interaction potential

This work focuses on the study of the stability of trapped soliton-like solutions of a (1 + 1)-dimensional nonlinear Schrödinger equation (NLSE) in a nonlocal, nonlinear, self-interaction potential of the form [|Ψ(x,t)| 2 +|Ψ(-x,t)| 2 ] κ where κ is an arbitrary nonlinearity parameter. Although the system with κ = 1 (i.e. fully integrable case) was first reported by Yang (2018 Phys. Rev. E 98 042202), here in the present work, we extend this model to the one in which κ is arbitrary. This allows us to compare the stability properties of the now trapped solutions to previously found solutions of the more usual NLSE with κ ≠ 1 which are moving soliton solutions. We show that there is a simple, one-component, nonlocal Lagrangian and corresponding action governing the dynamics of the system. Using a collective coordinate method derived from the action as well as assuming the validity of Derrick's theorem, we find that these trapped solutions are stable for 0 < κ < 2 and unstable when κ > 2. At the critical value of κ, i.e. κ = 2, the solution can either collapse or blowup linearly in time when q 0 = 0, where q 0 is the center of the initial density ρ(x, t = 0) = ψ*ψ of the solution. For q 0 ≠ 0 the displaced solution collapses. When κ > 2 initial small displacements from the origin also lead to collapse of the wave function. This phenomenon is not seen in the usual NLSE.

collective coordinates↗
DOE OSTI2024

Testing lepton flavor universality at future Z factories

As one of the hypothetical principles in the Standard Model (SM), lepton flavor universality (LFU) should be tested with a precision as high as possible such that the physics violating this principle can be fully examined. The run of a Z factory at a future e + e − collider, such as the Circular Electron-Positron Collider or Future Circular Collider (electron/positron), provides a great opportunity to perform this task because of the large statistics and high reconstruction efficiencies for b hadrons at the Z pole. In this paper, we present a systematic study on the LFU test in future Z factories. The goal is threefold. First, we study the sensitivities of measuring the LFU-violating observables of b → c τ ν , i.e., R J / ψ , R D s , R D s * , and R Λ c , where τ decays muonically. For this purpose, we develop the strategies for event reconstruction, based on the track information significantly. Second, we explore the sensitivity robustness against detector performance and its potential improvement with the message of event shape or beyond the b -hadron decays. A picture is drawn on the variation of analysis sensitivities with the detector tracking resolution and soft photon detectability, and the impact of Fox-Wolfram moments is studied on the measurement of relevant flavor events. Finally, we interpret the projected sensitivities in the SM effective field theory, by combining the LFU tests of b → c τ ν and the measurements of b → s τ + τ − and b → s ν ¯ ν . We show that the limits on the LFU-violating energy scale can be pushed up to ∼ O ( 10 ) TeV for ≲ O ( 1 ) Wilson coefficients at Tera- Z . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulated wildfire burned area over the CONUS during 2001-2020

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM). A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

Liu, Ye↗