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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 OSTI2020

Exploring the Role of Inorganic and Organic Interfaces on CO 2 and CH 4 Partitioning: Case Study of Silica, Illite, Calcite, and Kerogen Nanopores on Gas Adsorption and Nanoscale Transport Behaviors

The adsorption, partitioning, and diffusion of CO 2 and CH 4 in organic–inorganic pores composed of kerogen with silica, illite, or calcite are studied using density functional theory and classical molecular dynamics simulations. The adsorption and partitioning behavior of CO 2 and CH 4 molecules is found to be a function of chemistry of the solid interface, pore size, and surface area. CO 2 molecules are preferentially adsorbed compared to CH 4 molecules on silica, illite, calcite, and kerogen surfaces due to significant contributions of electrostatic interactions with the atoms of the associated surfaces. CO 2 and CH 4 molecules display higher adsorption energy on calcite and silica compared to those on illite and kerogen because of enhanced interactions with the positively charged calcium ions on the calcite surface and the hydroxyl group (-OH) on the silica surface. Enhanced internal nanopores and the availability of adsorption active sites in illite and kerogen matrices aid in higher partitioning of the gas molecules into these pores. CO 2 has a significant influence on the clustering and swelling of kerogen fragments compared to CH 4 . Higher CO 2 adsorption on inorganic and kerogen surfaces results in lower overall self-diffusivities compared to CH 4 . This study illustrates surface and pore size controls on the adsorption, partitioning, and self-diffusivities of CO 2 and CH 4 at conditions relevant for subsurface energy applications. The chemistry of the surfaces along with the availability of internal pores and active adsorption sites influences the adsorption behavior of gases. Our results suggest that CO 2 stored in depleted gas reservoirs may preferentially inhabit nanoconfined pores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

The stability of ground ice in the equatorial region of Mars

The lifetime of an unreplenished layer of ground ice lying within 30 deg of the Martian equator was examined within the context of the existing data base on Martian regolith and climate. Data on the partial pressure of H2O in the Martian atmosphere and the range of mean annual temperatures indicated the ground ice would be restricted to latitudes poleward of 40 deg. However, the ground ice near the poles may be a relic from early Martian geologic times held in place by a thin layer of regolith. Consideration of twelve model pore size distributions, similar to silt- and clay-type earth soils, was combined with a parallel pore model of gaseous diffusion to calculate the flux of H2O molecules escaping from the subsurface ground ice layer. Martian equatorial ground ice was found to be influenced by the soil structure, the magnitude of the geothermal gradient, the climatic desorption of CO2 from the regolith. It is concluded that equatorial ground ice is present on Mars only if a process of replenishment is active.

Clifford, S. M.↗
DOE OSTI2021

SMART Perovskite Growth: Enabling a Larger Range of Process Conditions

Cost-effective, high-throughput industrial applications of metal-halide perovskites require a highly tolerant method (i.e., wide process window) that produces high-quality materials with a short annealing time. Here, we introduce a Seed Modulation for ARTificially controlled nucleation (SMART) process that enables rapid fabrication of high-quality perovskite films under a wide set of initial input parameters. Additionally, we characterized the thin-film evolution from the perspective of crystallinity, surface potential, diffusivity, surface carrier dynamics, and interfacial recombination. We find that surface and subsurface defects primarily determine the performance of materials and devices. By modulating the seeds for perovskite nucleation, we were able to improve the overall crystallization. We achieved a >20% power conversion efficiency using only a 5 min annealing step, and we found that the annealing window is widened such that differing initial conditions achieve similar quality. Furthermore, we demonstrated reproducibility and performance improvement in larger-area perovskite cells by incorporating the SMART process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Atomic layer deposition of nanofilms on porous polymer substrates: Strategies for success

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Short communication: Cosmogenic noble gas depletion in soils by wildfire heating

Measurements of cosmic-ray-produced beryllium-10, neon-21, and helium-3 in quartz in a soil profile from a forested landscape in the Oregon Coast Range show that the cosmogenic noble gases 21 Ne and 3 He are depleted relative to 10Be in the shallow subsurface. The noble gases are mobile in mineral grains via thermally activated diffusion and 10 Be is not, implying that noble gas depletion is the result of surface heating by wildfires and subsequent mixing of partially degassed quartz downward into the soil. Cosmogenic noble gas depletion by wildfire heating of soils is a potential means of estimating wildfire intensity and/or frequency over pre-observational timescales.

58 GEOSCIENCES↗
DOE OSTI2022

Classification of computed thermal tomography images with deep learning convolutional neural network

Thermal tomography (TT) is a computational method for the reconstruction of depth profile of the internal material defects from Pulsed Infrared Thermography (PIT) nondestructive evaluation. Here, the PIT method consists of recording material surface temperature transients with a fast frame infrared camera, following thermal pulse deposition on the material surface with a flashlamp and heat diffusion into material bulk. TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of the subsurface internal defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to the heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify the size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. The performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shapes imported from scanning electron microscopy images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on the TT images of elliptical defects is capable of classifying the shape and orientation of irregular defects.

42 ENGINEERING↗
DOE OSTI2023

Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Columnar and subsurface silicide growth with novel molecular beam epitaxy techniques

We have found novel growth modes for epitaxial CoSi2 at high temperatures coupled with Si-rich flux ratios or low deposition rates. In the first of these modes, codeposition of metal and Si at 600-800 C with excess Si leads to the formation of epitaxial silicide columns surrounded by single-crystal Si. During the initial stages of the deposition, the excess Si grows homoepitaxially in between the silicide, which forms islands, so that the lateral growth of the islands is confined. Once a template layer is established by this process, columns of silicide form as a result of selective epitaxy of silicide on silicide and Si on Si. This growth process allows nanometer control over silicide particles in three dimensions. In the second of these modes, a columnar silicide seed layer is used as a template to nucleate subsurface growth of CoSi2. With a 100 nm Si layer covering CoSi2 seeds, Co deposited at 800C and 0.01 nm/s diffuses down to grow on the buried seeds rather than nucleating surface silicide islands. For thicker Si caps or higher deposition rates, the surface concentration of Co exceeds the critical concentration for nucleation of islands, preventing this subsurface growth mode from occurring. Using this technique, single-crystal layers of CoSi2 buried under single-crystal Si caps have been grown.

Fathauer, R. W.↗
DOE OSTI2024

RAIS Portsmouth Background Values

The Portsmouth Background Values (https://rais.ornl.gov/tools/ports_background.html) are from a Soil Background Report for the Portsmouth Gaseous Diffusion Plant, which sought to develop a comprehensive soil dataset using surface and subsurface soil samples. The Portsmouth background dataset on the RAIS also includes background concentrations for groundwater.

Dolislager, Fred [Oak Ridge National Laboratory (O↗
NASA NTRS1992

Subsurface emissions from Mercury - VLA radio observations at 2 and 6 centimeters

Radio observations of Mercury made with the VLA; once in 1986, and on two dates in February of 1988 are presented. These observations are the first to spatially map both hot regions associated with the theoretical hot poles. These 'hot poles' are separated by 180 deg and are a result of the unusual diurnal heating from Mercury's 3/2 spin-orbit resonance and eccentric orbit. The highest resolution data maps areas of the planet as small as 330 km. Maps of total intensity, brightness temperature, polarized intensity, fractional polarization, depolarization, and spectral index are included. It is found that the subsurface thermal emissions from Mercury are characteristic of blackbody reradiation from the solar insolation over a diurnal cycle. These observations to produce full-disk thermophysical models are used. The one-dimensional, time-dependent heat-diffusion equation for all observed disk elements at each epoch in order to constrain thermophsyical parameters and properties of the subsurface material are solved. Using typical lunar values for several of the parameters, it is possible to reproduce the temperature morphology and most of the observed temperature values. It is found that the best-fit models require a substantial contribution of the heat transport in the subsurface to be radiative in nature. The primary difficulty in the models is in predicting the observed temperature differences as a function of frequency.

Ledlow, Michael J.↗
DOE OSTI2020

Challenges in simulating ground interacting nuclear explosions

This paper summarizes recent above-ground nuclear explosion simulations as part of a broader effort to better characterize conditions within a fireball that may influence the chemical evolution of bomb materials and other materials entrained from the local explosion environment. A critical component of this work is validation against historic footage of atmospheric testing, requiring that we understand how the frequency-dependent sensitivity of the utilized film footage influences data captured in such images. We focus first on the early physics of a nuclear explosion in the atmosphere before discussing some of the technical challenges we seek to capture in late-time models that include more complex emplacement conditions and subsurface features. We discuss required physics packages (compressible hydrodynamics, radiation transport, as well as necessary ancillary tables such as equations of state (EOS) and opacities). Additionally, we note reasonable “shortcuts” one may make and their limitations, e.g., using ideal gas EOS, replacing spectrally resolved radiation with spectrally averaged radiation, and exchanging deterministic transport with diffusion. We then discuss an approach to achieving an equilibrated initial stress state for problems where buoyancy and subsurface lithostatic stress are important. Our methodology is presented in the context of LLNL’s ALE3D multiphysics code but may readily be implemented in other codes. In this paper, we start with a description of the challenges of NUDET simulations, followed by a presentation of the simulated intensity (flux) as it would appear on an analysis of the Dixie test. We then progressively introduce additional complexity in subsequent sections (near-surface burst and gravity initialization) before concluding.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Distinguishing Surface and Bulk Reactivity: Concentration-Dependent Kinetics of Iodide Oxidation by Ozone in Microdroplets

Iodine oxidation reactions play an important role in environmental, biological, and industrial contexts. The multiphase reaction between aqueous iodide and ozone is of particular interest due to its prevalence in the marine atmosphere and unique reactivity at the air–water interface. Here, we explore the concentration dependence of the I – + O 3 reaction in levitated microdroplets under both acidic and basic conditions. To interpret the experimental kinetics, molecular simulations are used to benchmark a kinetic model, which enables insight into the reactivity of the interface, the nanometer-scale subsurface region, and the bulk interior of the droplet. For all experiments, a kinetic description of gas- and liquid-phase diffusion is critical to interpreting the results. We find that the surface dominates the iodide oxidation kinetics under concentrated and acidic conditions, with the reactive uptake coefficient approaching an upper limit of 10 –2 at pH 3. In contrast, reactions in the subsurface dominate under more dilute and alkaline conditions, with inhibition of the surface reaction at pH 12 and an uptake coefficient that is 10× smaller. In conclusion, the origin of a changing surface mechanism with pH is explored and compared to previous ozone-dependent measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantifying the Impact of Electric Fields on the Local Structure and Migration of Potassium Ions at the Orthoclase (001) Surface

Developing an understanding of the response of mineral/water interfaces to applied electric fields is central to detecting and interpreting signatures of interfacial processes in the subsurface. Here we focus density functional theory calculations on understanding K + cation binding and diffusion across the (001) surface of orthoclase feldspar under various applied electric fields with and without surface hydration. The calculations reveal how water ligands labilize surface K + cations for diffusion while also increasing their sensitivity to electric field effects on the binding energy at different surface sites. The calculations also show how the direction and strength of the electric field systematically affect surface cation mobility, sorption, and hydration behavior. Specifically, electric fields directed toward the surface increase the potassium binding energies, facilitate K + diffusion across multiple binding sites, and increase the propensity of surface K + ions to lose their hydration shells. Furthermore, the findings help fill a major knowledge gap into the impact of electric fields on mineral/water interface structure and dynamics more generally, featuring in this case a commonly found type of feldspar involved in a multitude of atmospheric and geochemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anisotropic thermal diffusivity and conductivity in SiC/SiC tubes studied by infrared imaging and X-ray computed tomography

Traditional flash diffusivity evaluation of thermal diffusivity/conductivity of composite tubes require machining of specimens. For a thin-wall tube, this method can only be used to obtain through-thickness transport property. A novel method to evaluate anisotropic thermal diffusivity in a composite tube has been developed. Braided SiC/SiC composite tubes were subjected to a xenon flash heating pulse. A high-speed, high-sensitivity infrared camera was used to measure surface temperature changes as a function of time and nondestructively detect subsurface defects/damages, such as macroscopic pores. Standard reference material (Pyroceram 9606) and curved SiC/SiC composite tube specimens were used to validate thermal diffusivity obtained from infrared imaging. Unlike the traditional method, there is no need prepare special specimens, and thermal diffusivity values in three orientations are obtained after a single flash. A finite element analysis model based on x-ray computed tomography scans was developed to simulate the heat transfer. In conclusion, this technique is significant in assessing thermal conductivity and inspecting the health of ceramic tubes during and after service.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Detecting Volcanic Co2 Emissions Hidden in Tropical Volcanic Forests Using Fixed-Wing sUAS

CO2 emissions are among the earliest indicators of subsurface state change and reactivation of volcanic systems and these deep signals reflect in faint diffuse emissions variations on volcanic flanks. Monitoring vast areas of rainforests covering tropical volcanoes is challenging, and space-borne sensors like OCO-2 are not sensitive enough. Fortunately, trees exposed to mild enhancements of CO2 may experience fertilization and build excess CO2 into excess biomass (Cawse-Nicholson, et al. 2018, Biogeosciences). They also process excess CO2 through photosynthesis, measurable by fluorescence (Bogue et al., 2019, Biogeosciences). Furthermore, spaceborne remote sensing instruments have demonstrated increasing NDVI months to years before eruptions, unexplained by other factors (e.g., Houlie et al. 2006, EPSL; Seiler et al. 2017, PLoS One). By providing a means to map large areas of above-canopy CO2 variations over tropical rainforest on the flanks of actively degassing volcanoes, we enable to interpret the signals plants provide in response to excess CO2 with airborne and spaceborne hyperspectral remote sensing methods, including a possible future Surface Biology and Geology (SBG) NASA satellite mission.As a critical step to mature and test this concept, we deployed small unmanned aerial systems (sUAS) using a fixed-wing sUAS designed for autonomous operations and long endurance in extreme environments, without causing significant disturbance of the sampled air. We integrated an in-situ sensor to record the CO2 enhancement field above the forest canopy. Test flight results on the flanks of Turrialba volcano in Costa Rica above forest canopies covering known moderate gas seeps demonstrate the sUAS-borne detection and mapping capabilities of above-canopy elevated CO2 gradients. The strong detection capabilities and high detector signal stability resulted from key system design elements including RF shielding, mechanical stabilization, and calibration procedures. This highly robust system is readily applied for diffuse volcanic CO2 emission studies on active volcanoes covered by dense vegetation.

Volcanic↗
NASA NTRS2000

Atmospheric energy for subsurface life on Mars?

The location and density of biologically useful energy sources on Mars will limit the biomass, spatial distribution, and organism size of any biota. Subsurface Martian organisms could be supplied with a large energy flux from the oxidation of photochemically produced atmospheric H(2) and CO diffusing into the regolith. However, surface abundance measurements of these gases demonstrate that no more than a few percent of this available flux is actually being consumed, suggesting that biological activity driven by atmospheric H(2) and CO is limited in the top few hundred meters of the subsurface. This is significant because the available but unused energy is extremely large: for organisms at 30-m depth, it is 2,000 times previous estimates of hydrothermal and chemical weathering energy and far exceeds the energy derivable from other atmospheric gases. This also implies that the apparent scarcity of life on Mars is not attributable to lack of energy. Instead, the availability of liquid water may be a more important factor limiting biological activity because the photochemical energy flux can only penetrate to 100- to 1,000-m depth, where most H(2)O is probably frozen. Because both atmospheric and Viking lander soil data provide little evidence for biological activity, the detection of short-lived trace gases will probably be a better indicator of any extant Martian life.

NASA Center JPL↗
DOE OSTI2025

Corrosion of 316 L stainless steel under the natural circulation of molten NaCl-MgCl 2 salt

The corrosion behavior of 316 L stainless steel (SS) was studied via the natural circulation of molten eutectic NaCl-MgCl 2 salt through a microloop. The post-corrosion tested 316 L SS microloop sections were characterized with microscopy techniques to determine the microstructural and microchemical changes that occurred at the alloy/salt interface. It was found that 316 L SS showed heterogeneous dissolution at the hot-leg, whereas deposition of corrosion products occurred at the cold-leg. For the first time, experimentally obtained molten salt flow-induced corrosion of 316 L SS results were combined with computational thermodynamic-kinetic models to validate the dissolution and deposition in terms of elemental compositional changes at the alloy/salt interface. The thermodynamic-kinetic modeling predicted that the heterogeneous dissolution of Cr and Fe from the hot-leg section of 316 L SS persisted throughout the salt circulation. The model also estimated that, despite Cr deposition starting earlier than Fe, the total redeposition of Fe is expected to be significantly greater than that of Cr over the circulation of salt. Furthermore, the modeling accurately predicted the subsurface enrichment of Mo which is attributed to the reduced Cr activity and the relatively higher diffusion rate of Mo within the alloy matrix. Here, the agreement between modeling and experimental results confirms that Fe chlorides dissolve at the hot-leg and subsequently deposit at the cold-leg due to activity changes driven by the thermal gradient. By contrast, Cr was not detected in the cold-leg deposits, which is attributed to its weaker temperature dependence on activity, limiting its redeposition under these conditions.

36 - MATERIALS SCIENCE↗