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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Topological analysis of X-ray CT data for the recognition and trending of subtle changes in microstructure under material aging

X-ray computed tomography (CT) is an established non-destructive tool for 3D imaging of multiphasic composites. Numerous applications of X-ray CT in medical diagnosis and materials characterization have been reported, many involving field-specific innovations in the imaging technology itself. Yet, quantitative summarization to link image features to properties of interest has been rare. Here we address this issue by employing state-of-the-art technics in scalar field topology for the summarization of X-ray CT images of an example biphasic system. By varying processing-parameters we create different microstructures, evolve them through accelerated thermal aging, CT-image them pre- and post-aged, and demonstrate the ability of our image summarization method to systematically track process- and age-related changes, which can often be very subtle. A novel aspect of the algorithm involves recognition over multiple resolution levels, which provides deeper insight into the pattern relationship between grain-like features and their neighbors. The method is general, adaptable to diverse image reconstruction methods and materials systems, and particularly useful in applications where practical constraints on the sample-size limits the reliable use of more complex models, e.g., convolutional neural networks.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Omics-guided metabolic pathway discovery in plants: Resources, approaches, and opportunities

Plants produce a vast array of metabolites, the biosynthetic routes of which remain largely undetermined. Genome-scale enzyme and pathway annotations and omics technologies have revolutionized research to decrypt plant metabolism and produced a growing list of functionally characterized metabolic genes and pathways. However, what is known is still a tiny fraction of the metabolic capacity harbored by plants. Here, in this work, we review plant enzyme and pathway annotation resources and cutting-edge omics approaches to guide discovery and characterization of plant metabolic pathways. We also discuss strategies for improving enzyme function prediction by integrating protein 3D structure information and single cell omics. This review aims to serve as a primer for plant biologists to leverage omics datasets to facilitate understanding and engineering plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Robust fluorescent calcium coordination polymers as Cu 2+ sensors with high sensitivity and fast response

A three-dimensional (3D) and highly fluorescent calcium-based coordination polymer (Ca-CP) has been synthesized and structurally characterized. Furthermore, built on a strongly fluorescent (FL) chromophore ligand, [Ca(H 2 tcbpe)(H 2 O) 2 ] (1) (H 4 tcbpe = 4',4''',4''''',4'''''''-(ethene-1,1,2,2-tetrayl)tetrakis(([1,1'-biphenyl]-4-carboxylic acid))) is highly luminescent. Photoluminescence (PL) studies indicate that 1 undergoes a bathochromic shift in emission energy from blue to green color upon outgassing or under mechanic force. Notably, 1 exhibits selective FL sensing for Cu 2+ ions with a detection limit (LOD) of 0.064 ppm, far below the U.S. WHO and EPA standard for drinking water. Detailed investigation of the sensing mechanism reveals that uncoordinated COO– groups in 1 play a major role in recognizing Cu 2+ ions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Nature and Scalings of Density Fluctuations of Compressible Magnetohydrodynamic Turbulence with Applications to the Solar Wind

Abstract The solar wind is a magnetized and turbulent plasma. Its turbulence is often dominated by Alfvénic fluctuations and often deemed as nearly incompressible far away from the Sun, as shown by in situ measurements near 1 au. However, for solar wind closer to the Sun, the plasma β decreases (often lower than unity) while the turbulent Mach number M t increases (can approach unity, e.g., transonic fluctuations). These conditions could produce significantly more compressible effects, characterized by enhanced density fluctuations, as seen by several space missions. In this paper, a series of 3D MHD simulations of turbulence are carried out to understand the properties of compressible turbulence, particularly the generation of density fluctuations. We find that, over a broad range of parameter space in plasma β , cross helicity, and polytropic index, the turbulent density fluctuations scale linearly as a function of M t , with the scaling coefficients showing weak dependence on parameters. Furthermore, through detailed spatiotemporal analysis, we show that the density fluctuations are dominated by low-frequency nonlinear structures, rather than compressible MHD eigenwaves. These results could be important for understanding how compressible turbulence contributes to solar wind heating near the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1999

An overview of vertebrate mineralization with emphasis on collagen-mineral interaction

The nucleation, growth, and development of mineral crystals through their interaction principally with collagen in normal bone and calcifying tendon have been elaborated by applying a number of different techniques for analysis of the inorganic and organic constituents of these tissues. The methods have included conventional and high voltage electron microscopy, electron diffraction, microscopic tomography and 3D image reconstruction, and atomic force microscopy. This summary presents results of these studies that have now characterized the size, shape, and aspects of the chemical nature of the crystals as well as their orientation, alignment, location, and distribution with respect to collagen. These data have provided the means for understanding more completely the formation and strength of the collagen-mineral composite present in most vertebrate calcifying tissues and, from that information, a basis for the adaptation of such tissues under mechanical constraints. In the context of the latter point, other data are given showing effects on collagen in bone cell cultures subjected to the unloading parameters of spaceflight. Implications of these results may be particularly relevant to explaining loss of bone by humans and other vertebrate animals during missions in space, during situations of extended fracture healing, long-term bedrest, physical immobilization, and related conditions. In a broader sense, the data speak to the response of bone and mineralized vertebrate tissues to changes in gravitational loading and applied mechanical forces in general.

Non-NASA Center↗

NASA NTRS2011

VESGEN Mapping of Bioactive Protection against Intestinal Inflammation: Application to Human Spaceflight and ISS Experiments

Challenges to successful space exploration and colonization include adverse physiological reactions to micro gravity and space radiation factors. Constant remodeling of the microvasculature is critical for tissue preservation, wound healing, and recovery after ischemia. Regulation of the vascular system in the intestine is particularly important to enable nutrient absorption while maintaining barrier function and mucosal defense against micro biota. Although tremendous progress has been made in understanding the molecular circuits regulating neovascularization, our knowledge of the adaptations of the vascular system to environmental challenges in the intestine remains incomplete. This is in part because of the lack of methods to observe and quantify the complex processes associated with vascular responses in vivo. Developed by GRC as a mature beta version, pre-release research software, VESsel GENeration Analysis (VESGEN) maps and quantifies the fractal-based complexity of vascular branching for novel insights into the cytokine, transgenic and therapeutic regulation of angiogenesis, lymphangiogenesis and microvascular remodeling. Here we demonstrate that VESGEN can be used to characterize the dynamic vascular responses to acute intestinal inflammation and mucosal recovery from in vivo confocal microscopic 3D image series. We induced transient intestinal inflammation in mice by DSS treatment and investigated whether the ability of the pro biotic yeast Saccharomyces boulardii (Sb) to protect against intestinal inflammation was due to regulation of vascular remodeling. A primary characteristic of inflammation is excessive neovascularization (angiogenesis) resulting in fragile vessels prone to bleeding. Morphological parameters for triplicate specimens revealed that Sb treatment greatly reduced the inflammatory response of vascular networks by an average of 78%. This resulted from Sb inhibition of vascular endothelial growth factor receptor signaling, a major angiogenesis signaling pathway. It needs to be determined whether pro biotic yeast represents a promising approach to GI protection in space. GRC performed only the VESGEN post-testing analysis.

Parsons-Wingerter, P. A.↗

NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.

Jaehyun Cho↗

NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

Jaehyun Cho↗

NASA NTRS2022

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI). Part III: Simulated Observables - The Return of the Spectrum

The TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI) is a community project that aims to quantify how differences in general circulation models (GCMs) could impact the climate prediction for TRAPPIST-le and, subsequently its atmospheric characterization in transit. Four GCMs have participated in THAI so far: ExoCAM, LMD-Generic, ROCKE-3D and the UM. This paper, focused on the simulated observations, is the third part of a trilogy, following the analysis of two land planet scenarios (part I) and two aquaplanet scenarios (part II). Here, we show a robust agreement between the simulated spectra and the number of transits estimated to detect the land planet atmospheres. For the cloudy aquaplanet ones, a 5-σ detection of CO2 could be achieved in about 10 transits if the atmosphere contains at least 1 bar of CO2. That number can vary by 41- 56% depending on the GCM used to predict the terminator profiles, principally due to differences in the cloud deck altitude, with ExoCAM and LMD-G producing higher clouds than ROCKE-3D and UM. Therefore, for the first time, this work provides "GCM uncertainty error bars" of ~ 50% that need to be considered in future analyses of transmission spectra. We also analyzed the inter-transit variability induced by weather patterns and changes of terminator cloudiness between transits. Its magnitude differs significantly between the GCMs but its impact on the transmission spectra is within the measurement uncertainties. THAI has demonstrated the importance of model intercomparison for exoplanets and also paved the way for a larger project to develop an intercomparison meta-framework, namely the Climates Using Interactive Suites of Intercomparisons Nested for Exoplanet Studies (CUISINES).

Exoplanet atmospheres↗

NASA NTRSDate not supplied

Additive Manufacturing and Working Fluid Characterization of Ceramic Heat Pipes

In this work, additively manufactured aluminum nitride (AlN) ceramic heat pipes are developed to improve spacecraft heat rejection capabilities beyond the current state-of-the-art metal systems. Printed AlN parts are characterized via SEM, EDS, X-ray diffraction, optical profilometry, thermal conductivity, and emissivity testing. AlN 3D-printed parts are also tested for compatibility with aluminum bromide, aluminum chloride, and iodine, among other proposed working fluids at 500-600 K in vacuum.

Thermal management↗

NASA NTRS2024

Metal Extraction from Trash via Trash-to-Gas Processing for Use in 3D Printing

This work synergized state-of-the-art trash-to-gas (TtG) and in-space manufacturing (ISM) technologies to successfully extract metals from astronaut waste items for use in 3D printing. This was accomplished by isolating pure aluminum (Al 1235) from astronaut multilayer food packaging via TtG processing, cleaning the extracted aluminum, and preparing it for compatibility with the bound metal deposition (BMD) 3D printing process. A suite of material analyses was performed on the extracted aluminum product to fully characterize the key properties linked to effective additive manufacturing, including particle size distribution, oxygen content quantitation, and elemental composition. Metal extraction from Lunar and Martian regolith has become a significant area of interest for the in-situ resource utilization (ISRU) community to produce metallic equipment for various mission scenarios. However, the extraction of metals from astronaut waste streams has yet to be investigated. This project demonstrated an end-to-end waste metallic reuse process which may garner considerable metal production that would otherwise be disposed of.

Ray Pitts↗

DOE OSTI2022

Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization

The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (~50 μm) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (~3 μm) and scratched sample surfaces. Here, this work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.

42 ENGINEERING↗

DOE OSTI2021

Wyoming CarbonSAFE: Advancing Commercialization of Low-Carbon Energy Technologies in Fossil-Rich Wyoming

Wyoming’s Powder River Basin (PRB) is the most prolific coal producer and exporter in the United States and the State of Wyoming’s largest oil-producing basin. In addition to being a leading energy producer, the PRB is the site of research programs whose aim is to develop and integrate low-carbon technologies into existing fossil fuel energy industries. Much of the PRB’s low-carbon research is focused around Dry Fork Station (DFS), which is the newest coal-fired power station in the western US. Currently, DFS hosts five carbon capture projects, including pilot-scale capture projects that utilize different capture technologies and a full front-end engineering and design (FEED) study, a commercial CO 2 pipeline for nearby CO 2 -enhanced oil recovery industry, and is also co-located with the Wyoming Integrated Test Center, which is a host facility for unconventional carbon utilization research (i.e. flue gas carbon-to-products innovations). DFS is also the host site for the Wyoming CarbonSAFE project. Wyoming CarbonSAFE, funded by the Department of Energy/National Energy Technology Laboratory, is a multi-phased program (currently in Phase II) whose core objective is developing and validating storage sites within a complex capable of storing 50 million metric tonnes of CO 2 over a 30 year project period using carbon capture, utilization and storage (CCUS). This paper will provide an overview of the project to-date, showing that CarbonSAFE goals are achievable with respect to geologic, environmental, regulatory, CO 2 source and economic conditions, and why the State of Wyoming offers one of the more favorable environments to advance the commercialization studies. In 2019, the project team designed and completed a ~10,000 foot stratigraphic test well just south of DFS. From this well, the team collected over 600 feet of core, fluid samples from target injection zones, and a full petrophysical log suite. In addition, legacy 2D seismic lines were acquired and a 3D seismic survey was acquired in the fall of 2020. The objective of these field activities has been to identify and characterize target storage reservoirs and associated caprock. This complex has several reservoirs that could meet commercial injection goals, and over 4000 feet of associated caprock. Simulations of site performance suggest that stacked injection provides the most effective storage strategy, and would necessitate several sites within the greater complex to meet final project injection goals. Other work within this project includes the development of a business-case around proximal fields with CO 2 -enhanced oil recovery potential and existing tax credits, assessment of regulatory conditions, including pore space ownership and Class VI injection well permitting requirements, implementation of a robust public outreach Electronic copy available at: https://ssrn.com/abstract=3821220 GHGT-15 McLaughlin 2 program, and surface site characterization activities that have focused on environmental factors. In the PRB and at DFS, the State of Wyoming and other entities have made carbon management a priority of its future energy industry by providing a regulatory and business framework that is favorable to advancing these technologies. These endeavors will become more realistic with the successful implementation of Wyoming CarbonSAFE, and its ability to secure and validate commercial-scale CCUS at the center of Wyoming’s premier low-carbon research efforts.

McLaughlin, Fred↗

DOE OSTI2024

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗

DOE OSTI2025

Short-range spin freezing in the double trillium lattice spin-liquid candidate KSrFe 2 ⁢(PO 4 ) 3 revealed via 31 P NMR

A comprehensive 31 P nuclear magnetic resonance (NMR) study, combined with thermodynamic measurements and first-principles band-structure calculations, has been conducted to explore the ground state of the 𝑆=5/2 double trillium lattice antiferromagnet KSrFe 2 ⁢(PO 4 ) 3 . Our experimental results indicate that the magnetic ground state is neither a conventional three-dimensional (3D) long-range order (LRO) nor a pure gapless spin-liquid state, as conjectured previously [Boya et al., APL Mater. 10, 101103 (2022)]. Specifically, the observation of a nearly field-independent NMR linewidth below 𝑇* = (3.5 ± 0.4)⁢ K, and a significant enhancement of spin-spin relaxation rate 1/𝑇 2 below 2⁢𝑇* (where 𝑇* is the characteristic temperature identified from the magnetic susceptibility), indicate a complex magnetic ground state where spin freezing coexists with persistent dynamics. Furthermore, we argue that the lack of magnetic LRO and the persistence of strong magnetic fluctuations in KSrFe 2 ⁢(PO 4 ) 3 are unlikely to originate from intersite K/Sr disorder, rather they arise due to intrinsic magnetic frustration. In conclusion, our findings position KSrFe 2 ⁢(PO 4 ) 3 into a broader family of geometrically frustrated magnets characterized by coexisting spin freezing and pronounced antiferromagnetic fluctuations, marking it as a promising platform for investigating exotic phenomena in 3D frustrated magnets.

Exotic phases of matter↗

DOE OSTI2024

Polymer Additive Manufacturing for Marine Renewable Energy Applications: Best Practices, Research Trends, and Current Challenges

Additive manufacturing (AM) is a rapidly growing technology space, not only for prototyping, but is also becoming more feasible at larger scales and increasing component quantities. There are a large variety of AM processes and materials available to users and effectively applying those processes and materials to a specific use case can be challenging. One specific area where AM could be particularly beneficial is marine renewable energy (MRE). Not only is MRE a relatively nascent industry with a near-term need for rapid deployments and prototype testing, but developers could also see long-term benefits from the broad variety of environmentally resistant materials available and the ability to manufacture complex geometries that AM technologies offer. Over the past 4 years, AM materials have played an increasing role in the Advanced Materials project; a multi-year, multi-laboratory research project funded by the U.S. Department of Energy's Water Power Technologies Office, with the main goal of reducing barriers to the adoption of complex materials in the MRE industry. The primary focus of this project is to develop test methods and generate datasets to understand the long-term performance of advanced materials in marine environmental and address specific material challenges as they arise. This report provides an extensive overview of the research that has been performed specific to AM polymers as part of the Advanced Materials project. The intention of this document is to provide recommendations of best practices with regards to material selection, mechanical test method development, and design practices, lessons learned along the way, current research trends, and ongoing challenges with regards to AM polymers in marine environments. In particular, this report focuses on several key aspects: Material and process selection, Environmental conditioning and subsequent degradation quantification through mechanical characterization, Composite reinforcements on AM polymer substrates, Adhesion of instrumentation for mechanical characterization and loads measurements, Protective coatings for preventing biofouling and water ingress, Other MRE case studies where AM has proved particularly useful. Ultimately, we hope that the test methods that have been developed, data generated, and lessons learned from this research will be valuable to the MRE community (researchers and developers alike), as well as other industries, and can be used as a reference point as the respective MRE and AM industries continue to grow and mature.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

A competition between 2D and 3D magnetic orderings in novel mixed valent copper frameworks

Low-dimensional hybrid inorganic–organic frameworks exhibit high structural flexibility and allow for the inclusion of various magnetic and optically-active species into their host structures. The emergence of copper-based hybrid structures for various optical applications provides a promising foundation for exploring the integration of magnetic sublattices, paving the way for advancements in magneto-optical coupling and multifunctional materials. Herein, we introduce a novel class of hybrid copper frameworks with covalently-connected alternating magnetic 2D copper(II) formate and non-magnetic copper(I) bromide layers. The anionic framework is stabilized by A + cations to form ACu 5 Br 4 (COOH) 4 (A + = Na + , K + , Rb + , NH 4 + ) semiconductors (bandgaps 2.1–2.2 eV) with optical transitions suitable for optoelectronic applications. Comprehensive magnetometry studies show that ACu 5 Br 4 (COOH) 4 compounds exhibit low-dimensional 2D short-range antiferromagnetic order within the formate layers, characterized by strong exchange coupling (J/k B ∼ −100 K). Upon further temperature reduction, interactions between Cu(II) layers give rise to 3D long-range magnetic order at ∼40 K, despite the large (8.6–8.8 Å) spatial separation of the magnetic Cu(II) formate layers by nonmagnetic Cu(I)–Br bridging layers. This transition is further supported by electron paramagnetic resonance (EPR) spectroscopy. In conclusion, this study expands our understanding of low-dimensional hybrid frameworks and opens new avenues for the design of 2D multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Multi-Scale Thermo-Mechanical Modeling of Porous 3D Woven TPS Materials

This work summarizes the process to compute and analyze the thermal conductivity and mechanical properties of 3D woven TPS materials such as 3MDCP (3D Mid-Density Carbon-Phenolic). The PuMA [1,2] software, developed at NASA Ames, was used to characterize different 3MDCP samples from their constituents' data, averaging their thermal conductivity and elastic properties in the three main directions to obtain their effective orthotropic thermo-mechanical properties. This was performed in multiple steps: firstly, TPS samples were digitally reconstructed using micro computed tomography (µCT) and their constituents were segmented; then, the porous matrix phase was analyzed at the micro-scale and these results were used, along with the fibers’ constituents information, to model the tows at the meso-scale; finally, results from the constituents were homogenized and used to model the thermo-mechanical behavior of the unit cell at the macro-scale. Additionally, to gain a better understanding of the tows’ morphology and distribution of the carbon-phenolic blended fibers, microscopy images of the tows’ cross-section were segmented using deep learning techniques and analyzed with PuMA. This workflow can be applied to any TPS material to computationally obtain its thermo-mechanical properties, enabling more informed TPS design and manufacturing choices.

Multi-Scale↗