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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 325 records · Page 18

Transportability of exogenous microbial community correlates with interwell connectivity in deep aquifers

Subsurface resource engineering operations often utilize continuous injection of externally-sourced water into geological reservoirs for formation pressure maintenance, resource recovery or energy/waste storage. Such injected water generally contains naturally occurring microbes. Little is known, however, about how the injectate microbes transport through geological media as a community, how such transportability is affected by injector-producer connectivity, and whether such knowledge can be utilized for flowpath characterization. In this study, we analyzed daily-to-weekly timeseries microbial community data from the injected- and produced-fluids of a ten-month flow test at a deep, well-characterized engineered aquifer. We found that the injectate microbial community was distinct from the indigenous community at the amplicon sequence variant (ASV) level, and that the transportability of injectate community towards a given producer, quantified by an “nASV-Overlap” metric we propose, had strong and significant positive correlation with known injector-producer connectivities at our site. This suggests that the better the connectivity, the higher the probability for more injectate species to flow through the interwell region and arrive at a producer. Because interwell connectivity is an important yet usually unknown parameter in subsurface resource engineering, such correlation in turn points to nASV-Overlap as a useful indicator of interwell connectivity for aquifer characterization and long-term monitoring. Based on our findings, an nASV-Overlap-based microbial tracing approach was developed for characterizing and monitoring the relative connectivities across multiple producers with a given injector. A side-by-side comparison between the new nASV-Overlap approach and traditional artificial tracer methods is presented, and their respective strengths and limitations are discussed.

Deep biosphere↗

Pre- and post-coppice production and biomass chemistry of eastern cottonwood and hybrid poplars in the southeastern US

Sustainably grown feedstocks for bioenergy and bioproducts are important tools to fight climate change, provide ecosystem services, and sequester carbon. Populus species including hybrid poplars have been utilized around the world, and in the southeastern US native eastern cottonwood (P. deltoides) is often favored due to its resistance to stem cankers. However, P. deltoides has historically been grown in single stem production and its relative performance in short rotation coppice production, prevalent in Europe, is not well documented. Therefore, this study's goals were to evaluate eastern cottonwood (D × D) and hybrid poplar (P. deltoides × P. maximowiczii (D × M) and P. deltoides × P. trichocarpa (D × T) taxa) productivity under a two-year establishment and two-year coppice cycle, analyze biomass chemistry properties, identify drivers of productivity, and select clones suited for marginal vs. optimal sites. We found that D × M and D × D grew best in both establishment and coppice rotation with production increasing after coppice. Taxa and clones exhibited few differences in select biomass chemistry properties despite differences in growth rate and stem size. Across years and sites, production was correlated with the soil's carbon to nitrogen ratio, percentage of sand, and shrink-swell potential of the soil. A D × M clone ‘9709’ tended to perform better than other tested clones on marginal sites and had the highest survival rate after four years. Overall, this research suggests that Populus species can be grown in coppice rotation in the southeastern US with the potential for hybrid poplars to be successful on certain sites in the region although longer term studies are necessary to confirm these results.

54 ENVIRONMENTAL SCIENCES↗

Microstructure, stored energy, and stability of H/He-filled nanocavities in low temperature irradiated Inconel 718

The microstructure, trapped transmutation gases, stored energy, and mechanical behavior of samples from an irradiated Inconel 718 proton beam window were characterized using transmission electron microcopy, thermal desorption spectrometry (TDS), differential scanning calorimetry (DSC), and tensile testing. In the as-irradiated condition the microstructure contained a high number density of 1–3 nm gas-filled nanocavities. Emissions of trapped gases, H and He, during TDS correlated with peaks of the energy release curves from DSC examinations, which suggest these gases were likely stored in highly stable defect traps. The stored energy from radiation damage saturated at doses of a few dpa and did not increase with increasing radiation dose, but the amount of stored H and He increased with increasing dose. Effects of post-irradiation annealing were studied as well. After exposure to 700 °C, the nanocavities grew only slightly to 2–4 nm in diameter, but after exposure to 900 °C, the cavities grew to 10–20 nm in diameter and electron energy-loss spectroscopy showed these cavities contained a core of He surrounded by a shell of H. Further, this study demonstrated that the irradiation defect structures containing H and He were remarkably stable during irradiation and after exposure up to 700 °C. The effect of the irradiation temperature, defect mobility, and interaction of H, He, and irradiation defects on mechanical behavior provides insight into the processes responsible for the unusual recovery in ductility with increasing radiation dose observed in Inconel 718 after high energy proton and spallation neutron irradiation.

36 MATERIALS SCIENCE↗

Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide

Abstract While yearly budgets of CO 2 flux (F c ) and evapotranspiration (ET) above vegetation can be readily obtained from eddy‐covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely on analysis of conventional high frequency eddy‐covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large‐eddy simulations, which are used to replicate eddy‐covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO 2 and water vapor. In addition, best performances for all partitioning methods were found when all four flux components are non‐negligible, and measurements are collected close to the canopy top. Methods relying on the water‐use efficiency (W) perform better whenWis known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO 2 and water vapor can be used to infer the reliability of differentWparameterizations.

Environmental Sciences & Ecology↗

Probing primordial power spectrum and non-Gaussianities with fast radio bursts

We use the precision measurements of the arrivaltime differences of the same fast radio burst (FRB) source along multiple sightlines to measure the primordial power spectrum and Non-Gaussianities. The anticipated experiment requires a sightline separation of 100 AU, achieved by sending three or more radio telescopes to the outer solar system.The Shapiro time delays, measured relatively between different telescopes, are sensitive to the gradient field of the gravitational potential between different sightlines. Since the arrival time difference is independent of when the transient signal is emitted from the source, every measurement of the detected FRB source can be correlated. With enough FRB sources discovered, we can map the gravitational potential across the sky. We further calculate the two-point and three-point correlation function of the arrival time difference between telescopes for different FRB sources in the sky. If 10$^{4}$ FRBs were to be detected, our results suggest that this technique can test the inflationary scale-invariant power spectrum down to ∼ 10$^{3}$ Mpc$^{-1}$ and primordial Non-Gaussianities at a level of f$_{NL}$ ∼ 1.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Microscopic understanding of the effects of impurities in low RRR SRF cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

43 PARTICLE ACCELERATORS↗

Microscopic Understanding of the Effects of Impurities in Low RRR SRF Cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Microscopic Understanding of the Effects of Impurities in Low RRR SRF Cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K.↗

Microscopic understanding of the effects of impurities in low RRR SRF cavities

The SRF community has shown that introducing certain impurities into high-purity niobium can improve quality factors and accelerating gradients. We question why some impurities improve RF performance while others hinder it. The purpose of this study is to characterize the impurities of niobium coupons with a low residual resistance ratio (RRR) and correlate these impurities with the RF performance of low RRR cavities so that the mechanism of impurity-based improvements can be better understood and improved upon. The combination of RF testing, temperature mapping, frequency vs temperature analysis, and materials studies reveals a microscopic picture of why low RRR cavities experience low BCS resistance behavior more prominently than their high RRR counterparts. We evaluate how differences in the mean free path, grain structure, and impurity profile affect RF performance. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K.↗

In‐situ Analysis of Paste Properties in Resonant Acoustic Mixers for Quality Monitoring

Formulation control is key to achieving consistent target properties of energetic materials, as feedstock variations and slight deviations in the ratios of different ingredients can have major effects on final product properties, particularly in dense pastes with high particle loading >65 vol.%. In large‐scale operations, it is imperative to either correct or remove batches of material that perform outside baseline property specifications as early as possible to avoid unnecessary processing of suboptimal material. Quality monitoring is the practice of measuring material properties during processing using process analytical technologies as opposed to only testing the properties of the final product; it is a key principle in the quality‐by‐design frameworks used for designing formulations and manufacturing processes. Herein, a process analytical technology method for correlating material properties of dense pastes directly after mixing in a Resonant Acoustic Mixer to motor data is developed and used to detect differences in the particle content of dense paste formulations. This method was also capable of detecting variations in powder feedstock properties, such as particle packing efficiency, and is sensitive enough to detect changes of 2 wt.% in the total solids content of the formulation. The techniques presented herein show excellent promise for use as a process analytical technology capable of quantifying formulation effects on material movement modes during resonant acoustic mixing.

Materials science↗

Observation and Modeling of Dynamic Fracture Behaviors of Battery Cell Under Impact Loading Using Enhanced Representative Volume Element Concept

The burgeoning electric automobile industry has increased interest in battery safety. Battery cells experience significant mechanical stress during operation, including the impact of accidents and vibrations from driving. The potential for thermal runaway reactions in battery cells raises safety concerns. Although numerous researchers have defined the dynamic behavior of battery cells and proposed numerical models to describe it, few studies have focused on the high-strain rate mechanical impact phase correlated with the onset of fracture. In this study, we describe the dynamic behavior of pouch battery cells and propose a modeling method to study their mechanical failure under impact situations. Impact tests are conducted at various velocities and heights. To overcome numerical issues commonly encountered under rapid deformation scenarios, a new finite element model is developed based on the representative volume element model. The proposed approach efficiently simulates continuous crack propagation and brittleness behavior during impact by permitting the individual behavior of the cell components. Therefore, engineers can reliably design safer electric vehicle battery cells by measuring the properties of the cell components.

ENERGY STORAGE↗

DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman alpha forest

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-α(Lyα) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over 420 000 Lyα forest spectra and their correlation with the spatial distribution of more than 700 000 quasars. An essential facet of this work is the development of a new analysis methodology on a blinded dataset. We conducted rigorous tests using synthetic data to ensure the reliability of our methodology and findings before unblinding. Additionally, we conducted multiple data splits to assess the consistency of the results and scrutinized various analysis approaches to confirm their robustness. For a given value of the sound horizon (r d ), we measure the expansion at z eff = 2.33 with 2% precision, H(z eff ) = (239.2 ± 4.8) (147.09 Mpc /r d ) km/s/Mpc. Similarly, we present a 2.4% measurement of the transverse comoving distance to the same redshift, DM(z eff ) = (5.84 ± 0.14) (r d /147.09 Mpc) Gpc. Together with other DESI BAO measurements at lower redshifts, these results are used in a companion paper to constrain cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

In-Situ and Ex-Situ Studies on the Morphology Changes of Polymer Pipeline Materials for Use in Hydrogen Gas Environments

The US natural gas infrastructure is a national asset that could be used to deliver hydrogen and hydrogen blends of natural gas as a pathway to reduce carbon emissions. The distribution system comprises nearly 50% plastic pipe composed of medium- and high-density polyethylene materials (MDPE and HDPE). While these materials perform adequately for natural gas, research on their hydrogen compatibility is essential to understand if any immediate and long-term risks are associated with hydrogen addition. The Blended Gas CRADA, a HyBlend project, has established a comprehensive test method for evaluating MDPE and HDPE of various plastic resin compositions of pipeline material in pure hydrogen and 20% hydrogen/80% methane blends. Both in-situ and ex-situ measurements were performed to capture hydrogen-induced changes in the polyethylene material's crystalline, amorphous and their interphase regions. We investigated MDPE and HDPE pipeline materials made from different polymer resin systems to evaluate the effects of hydrogen gas. The materials were characterized by their density, diffusion coefficient, free volume ratio, and degree of crystallinity. Various advanced characterization methods, including in situ NMR, ex situ XRD, ex situ DSC, and ex situ TDA, were used to analyze the effects of changes in crystalline, amorphous, and interphase regions due to gas exposure. Time-dependent post-decompression quasi-static tensile tests were conducted to explore the effects of gas exposure time on the mechanical behavior of the pipe materials. This work will highlight the time sensitivities during and after gas exposure. The correlation between gas-induced polyethylene morphology changes and the associated material performance will be addressed for the intended applications. These studies will show that polyethylene resin composition and material exposure are important factors when considering whether hydrogen gas affects pipeline materials positively or negatively.

Simmons, Kevin L.↗

Heart Shape to Fracture Distance: Characterizing Hydraulic Fracture Propagation before Hits

Estimating the distance from the hydraulic fracture tip to the monitor well can be useful for fracture characterization, well spacing optimization, and preventing parent-child well interference. A heart-shaped signal is referred to as the extensional precursor of a fracture hit recorded by crosswell strain measurements and can serve as a vital tool for such estimation. This study incorporates the 3D displacement discontinuity method (DDM) to understand the impact of fracture geometry and monitor well offset on the heart-shaped signal’s characteristics. Results from numerical simulation and analytical solutions reveal a strong linear correlation between the spatial extent of the heart-shaped signal and the fracture tip distance. This relationship was further developed to predict tip distance using field data from the Hydraulic Fracture Test Site 2 (HFTS2). A reasonable approximation result from field data further validates the methodology. In addition, it is worth noting that the estimation accuracy depends on the ratio between fracture dimension and tip distance. The findings of this study offer a novel approach for real-time monitoring and characterizing hydraulic fracture propagation, which can be further used for well spacing optimization in unconventional and enhanced geothermal system reservoir development, as well as caprock integrity monitoring for carbon sequestration projects.

58 GEOSCIENCES↗

Carbon Capture through Membranes - Leveraging Multiphysics Modeling, Dimensional Analysis and Machine Learning to Scale up and Optimize Devices and Processes for Decarbonization

We study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow (DFfeed). Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

Modeling and Scaling up of Membrane Modules Leveraging Dimensional Analysis

In the current analysis, we study the separation performance using membrane modules through dimensional analysis (DA). We formulate the main process equations to identify relevant dimensionless numbers inherent in the physics. In particular, we identify that the critical step in the separation process is mass transfer through the selective layer. Remarkably, the dimensionless feed flow (DFfeed) emerges as a crucial factor in describing this process. Not only does DFfeed directly appear in the governing equations, but it also holds a physical significance associated with the time scales for the mass transfer across the feed side and through the selective layer. Regarding the output performance variables, we consider the recovery, stage cut, productivity and purity. In this context, we profit from experimental data and CFD simulations to evaluate the separation performance of the modules when varying the input flowrate, the scale of the module, and the CO2 permeance. These datasets enable us to establish correlations between performance metrics and the dimensionless feed flow. Using simple power functions of DFfeed, we obtain R2 coefficients exceeding 0.99, indicating the accuracy of the correlations built in the present work. In the future, we wish to use DA to understand key transport mechanisms, predict and control module performance, and challenge the universality of these findings by testing various gas separations across different membrane modules beyond our case study.

Pedrozo, Hector A.↗

Degradation science: Integrating modeling and experiments to predict localized corrosion processes (Annual Progress Report)

Additively manufactured (AM) eutectic high-entropy alloys (EHEAs), such as nano-lamellar AlCoCrFeNi 2.1 , have excellent strength, ductility, and wear resistance even at elevated temperatures, but their corrosion behavior in aggressive acids at different length scales remain poorly understood. This work investigates the corrosion behavior of laser powder bed–fused (L-PBF) AlCoCrFeNi 2.1 as a function of annealing temperatures, probing degradation mechanisms from nanoscopic to macroscopic length scales. The alloy is dual phase consisting of a ductile FCC L1 2 phase and a high-strength BCC B2 phase. Rapid solidification during L-PBF produces a far-from-equilibrium nano-lamellar structure with nearly homogeneous elemental distribution, which tends to evolve upon annealing toward Cr/Co/Fe-enriched FCC and Al/Ni-enriched B2. Three conditions were studied: as-printed, 600 °C/5 h, and 1000 °C/1 h, over which B2 lamellae coarsen, lamellar spacing increases, and elemental segregation becomes more prominent. Microstructure and chemistry were characterized by scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS), while in-situ electrochemical atomic force microscopy (EC-AFM) was used to link early (<5 h) local dissolution to microstructure after exposure in sulfuric acid. EC-AFM highlights preferential dissolution of the BCC/B2 phase where the surrounding matrix is Cr-depleted and directly quantifies the dissolution rates within individual phases, tracks the transition from early nano-scale attack to partial repassivation, to correlate height differences with current and impedance responses. To monitor longer-term behavior (up to 96 h), ex-situ AFM, SEM, and confocal imaging were combined with conventional bulk electrochemical tests, bridging nanoscale observations to micro/meso-scale damage morphologies. At the meso-scale, the deepest dissolution channels align with the build-direction lamellae and melt-pool boundaries, indicating that printing directionality guides the propagation of these localized corrosion sites. Annealing modifies corrosion by restructuring BCC/FCC phase fractions, lamellar spacing, and Cr/Al segregation, thereby changing the cathode/anode ratio and passive film stability. The results clarify how as-printed and annealed nano-lamellar architectures differ in their susceptibility to selective dissolution; how elemental segregation competes with residual stresses along the build direction. With these insights, future work will use CALPHAD-guided alloy modification to stabilize higher Cr contents in the B2 phase while retaining a dominant FCC+B2/BCC microstructure, with the goal of designing mechanically robust, corrosion-resistant EHEAs for safety-critical applications to leverage the LLNL’s broader national and global security mission.

36 MATERIALS SCIENCE↗

Radio Frequency Transients Correlated with Electron Flux Measured On-Board the STP-Sat6

We analyzed transient electromagnetic signatures, referred to as spacecraft environment discharges (SEDs) or on-board discharges (OBDs), and the in-situ particle environment simultaneously measured by the Radio Frequency Sensor (RFS) and the Space and Atmospheric Burst Reporting System Z-plasma spectrometer (SABRS-ZPS), respectively. These sensors are on-board the U.S. Department of Defense Space Test Program Satellite 6 (STP-Sat6) in geostationary orbit. Radio frequency signatures of SEDs on STP-Sat6 have relatively high peak amplitudes; they often caused amplitude-saturation in the so-called high band (120–140 MHz frequency range) of the RFS likely due to the proximity of their source to the RFS’s dipole antennas. We examined the occurrence rate of SEDs reported by the RFS and its temporal relationship to electron flux in the 7.9–12.2 keV range. Peaks in SED count rates were time-correlated with peaks in electron flux. The electron-flux peaks appeared to lead the SED count rate peaks by 24–45 min for the 7.9–12.2 keV energies. This indicates that incidence of electrons at this relatively low-energy range likely resulted in ramping up of the charging of the spacecraft leading to periods of high occurrence rates of discharges in and around the spacecraft.

54 ENVIRONMENTAL SCIENCES↗