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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Acoustic Emissions Sensing for Tracing Carbon Dioxide Movement in Caprock of a Carbon Capture Utilizations and Storage System (CCUS) (Final Technical Report)

The overall objective of this research project was to develop a non-invasive acoustic-emission (AE)-based technology that can accurately predict the location and movement of CO 2 through a confining layer in a carbon capture, utilization, and storage (CCUS) system. Specifically, the aim was to explore the feasibility of using the Haines jumps AEs as a passive method to track movement of CO 2 in reservoirs used for CCUS applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Remaining Useful Strength (RUS) Prediction of SiCf-SiCm Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remaining useful life (RUL) of machinery systems or batteries, no research has been reported on the remaining useful strength (RUS) prediction of silicon carbide fiber reinforced silicon carbide matrix (SiCf-SiCm) materials with pivotal role in its potential usage as a structural material in nuclear reactors and turbine engines. Knowledge of its degradation process is of the utmost importance to the manufacturers. For this purpose, two approaches based on the machine-learning techniques of random-forest (RF) and convolutional neural network (CNN) are proposed to predict the RUS of SiCf-SiCm using only acoustic emission (AE) signals generated during the material’s stress applying process. Experimental results show that the CNN models achieved better predictive performance than the RF models but the latter with expert-engineered features achieves better prediction for AE signals in the early stage of degradation. Additionally, our results demonstrate that both models can correctly predict the SiCf-SiCm RUS as evaluated by our robust testing method from which the best average root mean square error (RMSE) and Pearson correlation coefficient of 3.55 ksi units and 0.85 were obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cloning and Characterization of Aedes aegypti Trypsin Modulating Oostatic Factor (TMOF) Gut Receptor

Trypsin Modulating Oostatic Factor (TMOF) receptor was solubilized from the guts of female Ae. Aegypti and cross linked to His6-TMOF and purified by Ni affinity chromatography. SDS PAGE identified two protein bands (45 and 61 kDa). The bands were cut digested and analyzed using MS/MS identifying a protein sequence (1306 amino acids) in the genome of Ae. aegypti. The mRNA of the receptor was extracted, the cDNA sequenced and cloned into pTAC-MAT-2. E. coli SbmA− was transformed with the recombinant plasmid and the receptor was expressed in the inner membrane of the bacterial cell. The binding kinetics of TMOF-FITC was then followed showing that the cloned receptor exhibits high affinity to TMOF (KD = 113.7 ± 18 nM ± SEM and Bmax = 28.7 ± 1.8 pmol ± SEM). Incubation of TMOF-FITC with E. coli cells that express the receptor show that the receptor binds TMOF and imports it into the bacterial cells, indicating that in mosquitoes the receptor imports TMOF into the gut epithelial cells. A 3D modeling of the receptor indicates that the receptor has ATP binding sites and TMOF transport into recombinant E. coli cells is inhibited with ATPase inhibitors Na Arsenate and Na Azide.

Borovsky, Dov↗
DOE OSTI2023

Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Alfven eigenmodes and fast ion transport in negative triangularity DIII-D plasmas

The first energetic particle experiments in negative triangularity tokamak plasmas have been carried out on DIII-D. Alfvén eigenmode (AE) activity and associated fast ion transport comparable to that in positive triangularity is observed during the current ramp portion of all plasmas with early beam heating indicating negative triangularity does not confer a special advantage with respect to AE induced transport. In these discharges, a range of mode activity driven by the sub-Alfvénic (Vbeam/VA < 0.5) 80 kV neutral beams is found including beta induced Alfvén acoustic eigenmodes, beta induced Alfvén eigenmodes, reversed shear Alfvén eigenmodes (RSAEs) and toroidicity induced Alfvén eigenmodes (TAEs). Mode intermittency and possibly chirping appears to be more common than comparable positive triangularity and/or oval discharges but overall, the unstable spectra and mode amplitudes observed on magnetics, CO2 interferometry, and electron cyclotron emission in a set of matched positive and negative triangularity cases at moderate beam power is similar. Large levels of Alfvén eigenmode induced fast ion transport are found in both positive and negative triangularity with up to 70% central fast ion pressure deficits relative to classical predictions early during the current ramp phase for discharges with 3 MW injected 80 kV neutral beam power. The deficit in both cases is reduced toward zero as the current penetrates and eventually reaches classical levels during current flattop with qmin ≈ 1. Fast ion transport in negative triangularity plasmas measured using a beam modulation technique show very similar levels to those measured in oval plasmas over the range of tested beam powers (Pbeam ≈ 2–7 MW). This similarity is found despite quite different unstable spectra in the highest beam power case where a mixture of coherent and quasi-coherent modes in the TAE frequency range are observed in negative triangularity and a spectrum of more typical narrowband TAEs and RSAEs is observed for the oval plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Outlier classification using autoencoders: application for fluctuation driven flows in fusion plasmas

Understanding the statistics of fluctuation driven flows in the boundary layer of magnetically confined plasmas is desired to accurately model the lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a novel diagnostic that uniquely allow us to sample the plasma parameters on a time scale shorter than the characteristic time scale of their fluctuations. Sudden large-amplitude fluctuations in the plasma degrade the precision and accuracy of the plasma parameters reported by MLPs for cases in which the probe bias range is of insufficient amplitude. While some data samples can readily be classified as valid and invalid, we find that such a classification may be ambiguous for up to 40% of data sampled for the plasma parameters and bias voltages considered in this study. In this contribution, we employ an autoencoder (AE) to learn a low-dimensional representation of valid data samples. By definition, the coordinates in this space are the features that mostly characterize valid data. Ambiguous data samples are classified in this space using standard classifiers for vectorial data. In this way, we avoid defining complicated threshold rules to identify outliers, which require strong assumptions and introduce biases in the analysis. By removing the outliers that are identified in the latent low-dimensional space of the AE, we find that the average conductive and convective radial heat fluxes are between approximately 5% and 15% lower as when removing outliers identified by threshold values. For contributions to the radial heat flux due to triple correlations, the difference is up to 40%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Morphological and chemical characteristics of oxide scales formed on δ-Phase plutonium metal alloys I: 3.5 at% ga

Focused ion-beam scanning electron microscopy (FIB-SEM) and three-dimensional (3D) microscopy were applied to characterize the subsurface morphological features of oxide scales formed on an ~3.5 at.% Ga plutonium (Pu) metal alloy. Using the FIB-SEM technique, a number of morphological features formed in the interior of the oxide scale from Pu metal's environmental exposure were observed and identified. Here, Auger electron spectroscopy (AES) was utilized to characterize the cross-sectional composition and chemistry of the oxide scale. The oxide scale formed during inert storage and operational environments has a characteristic internal scale structure that includes a relatively dense oxide layer with some lateral and transverse cracking. Generally, after subsequent exposure to dry air environment, the oxide scale retained most of the original structural and chemical characteristics. However, after aging in a moist air environment, while the oxide scale was found to maintain the chemical characteristics of the source oxide, the scale was found to be on average thinner and without the previously observed internal microcracking, likely the result of spallation of the source scale during exposure to the new environment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Morphological and chemical characteristics of oxide scales formed on δ-phase plutonium metal alloys II: 2.0 at% Ga

The focused ion-beam scanning electron microscopy (FIB-SEM) and three-dimensional (3D) microscopy were applied to characterize the subsurface morphological features of oxide scales formed on an ~2.0 at. % Ga plutonium (Pu) metal alloy. Using the FIB-SEM technique, a number of morphological features formed in the interior of the oxide scale from Pu metal’s environmental exposure were observed and identified. Auger electron spectroscopy (AES) was utilized to characterize the cross-sectional composition and chemistry of the oxide scale. The oxide scale formed during inert storage and operational environments was found to be highly variable in thickness and morphology, presenting some regions with a thin (<400 nm), dense oxide layer and others with a thick (>2 µm) scale with substantial lateral cracking. After subsequent exposure to dry air environment, the oxide scale became thicker (~4 µm) and slightly more porous. The changes following aging in a moist air environment were observed to be more severe, with the formation of a highly porous internal structure containing significant lateral and transverse cracking. In comparison to the scale formed on an ~3.5 at. % Ga-Pu metal alloy, the oxide morphology of the lower gallium alloy investigated here exhibited greater variation in thickness and a noteworthy dependence on the presence of water vapor, particularly in terms of the internal porosity formed during growth of the oxide.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-Driven Day-Ahead PV Estimation Using Autoencoder-LSTM and Persistence Model

Inherent variability in photovoltaic (PV) and associated impacts on power systems is a challenging problem for both the PV owners and the grid operators. Existing statistical and machine learning algorithms typically work well for weather conditions similar to historical data. Furthermore, uncertain weather conditions pose a great challenge to the estimation accuracy of the estimation models. With the enhanced integration of intelligent electronic devices and the realization of associated automation in the power grid, renewable energy data is becoming more accessible, which can be utilized by deep learning models and improve the PV power generation estimation accuracy. In this paper, a hybrid deep learning model driven by external weather data is proposed to do day-ahead PV output forecasting at 15-minute-interval. The proposed model is motivated by the recent advancement of Long-Short-Term-Memory (LSTM) networks and AutoEncoder (AE), which estimates uncertainties in sequence while making the prediction for complex weather conditions. Meanwhile, the persistence model (PM) is used to predict continuous sunny weather conditions. The forecasting result is validated with data from multiple locations

42 ENGINEERING↗
DOE OSTI2022

Directional Cooling-Induced Fracturing: Directional Cooling Data Under True-Triaxial Stress State

Data includes Directional Cooling-Induced Fracturing (DCIF) testing data using westerly granite blocks. This submission includes data from two samples of westerly granite, lab sample 7 and 8. Files contain stress, temperature and acoustic emission data acquired during polyaxial, laboratory testing of westerly granite blocks for each sample. FILES: .tradb -- files containing acoustic emission waveforms; sqlite3 database .pridb -- files containing basic acoustic emission information (no waveforms); sqlite3 database .geom -- geometry of the AE sensor network (ASCII)

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

A Transformational Graduate Program: Mines and NREL Join Forces To Shape the Future of Energy

Developing secure, resilient, and adaptive energy infrastructure that fosters economic growth while reducing environmental impact is among the most pressing challenges—and greatest opportunities—of our time. It will require the next generation of thought leaders to capably and creatively guide this vital energy sector transition. Through a new interdisciplinary graduate program, Colorado School of Mines (Mines) and the National Renewable Energy Laboratory (NREL) are cultivating the rich opportunity landscape needed to develop these future innovators. The Mines/NREL Advanced Energy Systems (AES) degree program prepares researchers at the doctoral level and energy professionals at the master’s level to address the full complexity of tomorrow's infrastructure, economic, and environmental challenges. The combination of a thriving cleantech market in Colorado, world-class resources and researchers at NREL, and rigorous educational and technical programs at Mines create a truly one-of-a-kind opportunity for advancing fields related to energy systems. These links can uniquely equip top-caliber students to become the scientists and engineers at the forefront of our global energy economy transformation.

Advanced Energy Systems↗
DOE OSTI2024

Underlying Roles of Polyol Additives in Promoting CO2 Capture in PEI/Silica Adsorbents

Solid-supported amines having low molecular weight branched poly(ethylenimine) (PEI) physically impregnated into porous solid supports are promising adsorbents for CO2 capture. Co-impregnating short-chain poly(ethylene glycol) (PEG) together with PEI alters the performance of the adsorbent, delivering improved amine efficiency (AE, mol CO2 sorbed / mol N) and faster CO2 uptake rates. To uncover the physical basis for this improved gas capture performance, we probed the distribution and mobility of the polymers in the pores via small angle neutron scattering (SANS), solid-state NMR, and molecular dynamic (MD) simulation studies. SANS and MD simulations reveal that PEG displaces wall-bound PEI, making amines more accessible for CO2 sorption. Solid-state NMR and MD simulation suggest intercalation of PEG into PEI domains, separating PEI domains and reducing amine-amine interactions, providing potential PEG-rich and amine-poor interfacial domains that bind CO2 weakly via physisorption while providing facile pathways for CO2 diffusion. Contrary to a prior literature hypothesis, no evidence is obtained for PEG facilitating PEI mobility in solid supports. Instead, the data suggest that PEG chains coordinate to PEI, form larger bodies with reduced mobility compared to PEI alone. We also demonstrate promising CO2 uptake and desorption kinetics at varied temperatures, given by favorable amine distribution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Influence of Protection Layers on Thermal Stability of Nitride Thin Films

Nitrides are commonly studied for their properties relevant to numerous coating applications, and have been recently used to synthesize newly predicted materials in thin film form. However, thermodynamic stability of such nitride materials is difficult to experimentally evaluate, due to limited thermal budget of thin films. Here we show that thermal stability of nitride films can be extended using protection layers. Specifically, we find that zirconium nitride (ZrN) thin films are stable up to at least 1200°C annealing temperature in N2 atmosphere, if aluminum nitride (AlN) diffusion barriers and capping layers are used. X-ray diffraction (XRD) measurements show the expected thermodynamically stable rocksalt structure of ZrN, and scanning electron microscopy (SEM) confirms compact microstructure of these ZrN films. Without such protection layers, transient bixbyite Zr2ON2 phase and high-temperature ZrSi2 phase are observed after annealing by XRD, SEM, and auger electron spectroscopy (AES), due to side reaction with native surface oxide (ZrOx) and substrate (Si) respectively. These results demonstrate that protection layers are beneficial to increase the thermal budget of nitride thin films, for evaluating thermodynamic stability of new nitride materials, for capturing transient metastable phases during crystallization, and for using functional nitride coatings in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

GeoSoilEnviroCARS (Sector 13) at the Advanced Photon Source: a comprehensive synchrotron radiation facility for Earth science research at ambient and extreme conditions

GeoSoilEnviroCARS (GSECARS) is a comprehensive analytical laboratory for Earth and environmental science research using X-ray beams from the Advanced Photon Source, Argonne National Laboratory. State-of-the-art instruments are available for (1) high-pressure/high- or low-temperature diffraction, total scattering, and spectroscopy (Brillouin, Raman, and VIS-IR) using the laser heated diamond anvil cell (DAC); (2) high-pressure/high-temperature diffraction, scattering, and imaging as well as acoustic emission (AE) and ultrasonics using the large-volume press (LVP); (3) powder, single crystal, and surface/interface diffraction; (4) X-ray absorption fine structure spectroscopy; (5) X-ray fluorescence microprobe analysis; and (6) microtomography. As shown here, experiments are facilitated by senior level staff who collaborate on all aspects of the analytical work including experiment design, sample preparation, data collection, data interpretation, and publication preparation. Both technical and scientific synergies occur as a result of the intimate association of the various techniques and scientists experienced in the applications of synchrotron radiation to Earth, environmental, and planetary science problems. The facility includes state-of-the-art instrumentation designed and built in-house, including custom X-ray optics, online and offline laser-based systems, specialized sample environments and positioning systems, as well as pixel-array and multi-crystal energy dispersive X-ray detectors, which are available to be shared among the experimental stations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Investigation of GaAs surface treatments for ZnSe growth by molecular beam epitaxy without a buffer layer

Atomically clean and smooth surfaces are critical prerequisite for the epitaxial regrowth of dissimilar semiconductors. Using ZnSe/GaAs as a model system, epitaxial regrowth without a buffer layer after thermal cleaning with various As-fluxes, atomic Ga flux, and atomic hydrogen treatments to the GaAs substrates and the surfaces were investigated in this work via in-situ Auger electron spectroscopy (AES). The ZnSe epilayers grown on the pre-treated GaAs surfaces without a buffer layer were characterized by X-ray diffraction (XRD), photoluminescence (PL) and atomic force microscopy (AFM) to evaluate the effectiveness of the surface treatment methods. It was found that a high quality ZnSe layer can be achieved by atomic hydrogen surface treatment at 300°C without requiring GaAs buffer layer growth, which reveals a path for epitaxy growth avoiding high temperature treatments.

42 ENGINEERING↗
DOE OSTI2023

Separation of rare earth element radioisotopes by reverse-phase high-speed counter-current chromatography

Analytical scale purification of rare earth element (REE) radioisotopes is typically accomplished using cation-exchange resins (e.g. AG 50W-X8) and high-performance liquid chromatography (HPLC). Despite the variety of improvements made since the development of this separation process in the 1950s, nearest neighbor separations remain a challenge, as does the issue of irreversible sample adsorption. Herein, we report a study that evaluates the potential of high-speed counter-current chromatography (HSCCC) as an alternative method for purifying REE elements, with specific reference to separations of fission product REE of interest to nuclear forensics. Complementary HSCCC REE separation experiments, one spiked with radiotracer and REE fission product activity, allowed for in depth analysis of resulting fractions from both an elemental (inductively coupled plasma atomic emission spectroscopy, ICP-AES) and radiological (gamma-ray spectrometry, beta counting) purity perspective. The highly reproducible nature of separation profiles generated from HSCCC instruments was leveraged to simplify work-up of samples containing radioisotopes. Subsequent radioanalytical evaluation revealed minimal carryover of Eu into neighboring Sm and Tb fractions (as indicated by presence of 150Eu), and trace contamination of the Tb fraction with Y (as indicated by presence of 91Y). Subtle differences in stationary phase retention across the two columns were reflected in significant variations in decontamination factors of duplicate parallel separations. Furthermore, these differences paired with obtained distribution of radioisotopes provided valuable insights into future improvements. Collectively, this study represents a significant step forward in development of HSCCC technology for task specific REE radioisotope purification.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Parabolic oxidation kinetics of a plutonium alloy at room temperature

Auger electron spectroscopy (AES) was used to characterize the oxide scale formed on an ~0.5 wt. % Ga plutonium metal alloy. Analysis of changes to the characteristic Auger transitions for Pu and O during sputter depth profiles were used in combination with previously measured sputter yields to determine the thickness of the oxide scale and provide insight into its chemistry. From this data, the parabolic kinetics for the Pu-Ga alloy were determined as a function of relative humidity, RH = 14–92%, and oxygen partial pressure, p(O 2 ) = 31–157 Torr, at 25°C. For each relative humidity investigated, the parabolic rate constant was found to be independent of oxygen partial pressure. Furthermore, power-law fits to the relative humidity effect on the rate constant was found to have a power of n = 1.265, indicating the diffusion species which rate-limits the reaction isn’t molecular water, which subsequent dissociates at the oxide-metal interface, or hydroxyl from dissociation at the gas-surface interface.

36 MATERIALS SCIENCE↗