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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Wasatch Environmental Observatory: A mountain to urban research network in the semi‐arid western US

Abstract The 2085 km 2 Jordan River Basin, and its seven sub‐catchments draining the Central Wasatch Range immediately east of Salt Lake City, UT, are home to an array of hydrologic, atmospheric, climatic and chemical research infrastructure that collectively forms the Wasatch Environmental Observatory (WEO). WEO is geographically nested within a wildland to urban land‐use gradient and built upon a strong foundation of over a century of discharge and climate records. A 2200 m gradient in elevation results in variable precipitation, temperature and vegetation patterns. Soil and subsurface structure reflect systematic variation in geology from granitic, intrusive to mixed sedimentary clastic across headwater catchments, all draining to the alluvial or colluvial sediments of the former Lake Bonneville. Winter snowfall and spring snowmelt control annual hydroclimate, rapid population growth dominates geographic change in lower elevations and urban gas and particle emissions contribute to episodes of severe air pollution in this closed‐basin. Long‐term hydroclimate observations across this diverse landscape provide the foundation for an expanding network of infrastructure in both montane and urban landscapes. Current infrastructure supports both basic and applied research in atmospheric chemistry, biogeochemistry, climate, ecology, hydrology, meteorology, resource management and urban redesign that is augmented through strong partnerships with cooperating agencies. These features allow WEO to serve as a unique natural laboratory for addressing research questions facing seasonally snow‐covered, semi‐arid regions in a rapidly changing world and an excellent facility for providing student education and research training.

Follstad Shah, Jennifer J.↗
DOE OSTI2021

Grafted nickel-promoter catalysts for dry reforming of methane identified through high-throughput experimentation

High-throughput synthesis of a series of monometallic and bimetallic catalysts (45 bimetallic and 50 monometallic samples) consisting of nickel and one of nine different metal promoters (B, Co, Cu, Fe, Mg, Mn, Sn, V and Zn) supported on one of six different metal oxides alumina, ceria, magnesia, silica and titania) is carried out via organometallic grafting using a robotic platform. The catalysts are evaluated for their activity and selectivity for the dry reforming of methane at a feed ratio of CH 4 :CO 2 of 1 at 650–800 °C in a parallel flow reactor system. The type of oxide support prevails over the type of additive for both catalyst activity and stability. On Al 2 O 3 and MgO, Fe was found to be the best promoter; on SiO 2 , Cu is the best promoter at 700 °C and higher, while on TiO 2 , Mn is found to enhance the conversion at 800 °C. On CeO 2 , all additives except Fe have beneficial effects. Twenty-five catalysts show > 90% methane conversion with ten catalysts showing > 95% conversion at 800 °C with the H 2 :CO ratios ranging from 0.8 to 1.2. Amongst the ten highest performers, NiFe/Al 2 O 3 and NiFe/MgO are more active than Ni/Al 2 O 3 and Ni/MgO, respectively and were stable over a period of 25 h at 800 °C. Characterization on the as-prepared samples reveals highly dispersed phase, while after reduction in H 2 , highly dispersed and reduced nickel particles up to 10 nm are formed. The particles do not increase in size under dry reforming reaction conditions at 800 °C. An increased hydrogen consumption observed during H 2 -TPR of the nickel particles is positively correlated with methane conversion for Al 2 O 3 -based catalysts. The resistance to deactivation by coking and variation in coke structure are investigated by spectroscopic and microscopic methods to identify the relationship between metal promoters, alloy formation, and type of surface carbon deposits. Carbon whiskers were observed on the ten selected spent samples and are preferentially deposited on Ni rather than on the promoters. Carbon nanotube formation and metal particle removal from support were not observed to cause deactivation while amorphous carbon formation was clearly linked to catalyst deactivation, as amorphous carbon could encapsulate nickel, either on the support or at the end of the carbon nanotube. Furthermore, the organometallic grafting technique is an efficient and suitable technique for synthesizing highly dispersed and homogeneous phases which lead to high conversion and high durability for dry reforming of methane.

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

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Structurally Diverse Compound Screening Library to Identify Substrates for Diamine, Polyamine, and Related Acetyltransferases

Spermidine/spermine N-acetyltransferases (SSATs) and other types of polyamine acetyltransferases (PAATs) acetylate diamines and/or polyamines. These enzymes are evolutionarily related and belong to the Gcn5-related N-acetyltransferase (GNAT) superfamily, yet we lack a fundamental understanding of their substrate specificity and/or promiscuity toward different compounds. Many of these enzymes are known or are predicted to acetylate polyamines, but in the cell there are other types of compounds that contain moieties derived from polyamines that may be the native substrates for these enzymes. To learn more about the identity of substrates that are acetylated, we selected and screened 17 different GNAT enzymes for activity toward a set of structurally diverse compounds that contained different types of amine moieties (e.g., aminopropyl, aminobutyl, etc.). These compounds included diamines, triamines, and polyamines containing primary amino groups, and they had structural diversity with variation of the chain length and presence or absence of internal amino groups and other functional groups. We found 12 of the 17 enzymes acetylated at least one of the compounds. Some enzymes were selective toward acetylating only one compound while others exhibited substrate promiscuity toward numerous compounds. Our experimental results ultimately allowed us to pinpoint specific substrates that could be further investigated to more fully understand substrate specificity versus promiscuity of GNAT enzymes and the role of acetylated small molecules in cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A High-Fidelity Molecular Model of the Cu(111) Repeating Unit

Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.

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

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

In situ nanoscale imaging of moiré superlattices in twisted van der Waals heterostructures

Abstract Direct visualization of nanometer-scale properties of moiré superlattices in van der Waals heterostructure devices is a critically needed diagnostic tool for study of the electronic and optical phenomena induced by the periodic variation of atomic structure in these complex systems. Conventional imaging methods are destructive and insensitive to the buried device geometries, preventing practical inspection. Here we report a versatile scanning probe microscopy employing infrared light for imaging moiré superlattices of twisted bilayers graphene encapsulated by hexagonal boron nitride. We map the pattern using the scattering dynamics of phonon polaritons launched in hexagonal boron nitride capping layers via its interaction with the buried moiré superlattices. We explore the origin of the double-line features imaged and show the mechanism of the underlying effective phase change of the phonon polariton reflectance at domain walls. The nano-imaging tool developed provides a non-destructive analytical approach to elucidate the complex physics of moiré engineered heterostructures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Thermal tomography 3D imaging of additively manufactured metallic structures

Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with the laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer and through reconstruction of data obtained from experimental measurements. Thermal tomography reconstructions of structure shape and dimensions are shown for the Inconel 718 AM structure which has variations in the horizontal plane but is uniform along the depth dimension. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and the Inconel 718 plate is produced with the LPBF method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBHs have the same sizes as the imprinted defects in the LPBF specimens but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects and allow for estimation of their sizes and locations. Results of this study demonstrate that thermal tomography can be used for visualization and quality control in AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Measurement of Local Magnetic Fields in Actinide Tetrafluorides

Fluorine-19 magnetic shielding tensors have been measured in a series of actinide tetrafluorides (AnF4) by solid state nuclear magnetic resonance (NMR) spectroscopy. Tetravalent actinide centers with 0 to 8 valence electrons can form tetrafluorides with the same unit cell, making these compounds an attractive choice for a systematic study of the variation in electronic structure across the 5f row of the Periodic Table. Pronounced deviations from predictions based on localized valence electron models have been detected by these experiments, which suggests that this approach may be used as a quantitative probe of electronic correlations.

Walter, Eric D.↗
DOE OSTI2024

Thermal relaxation of strain and twist in ferroelectric hexagonal boron nitride moiré interfaces

New properties can arise at van der Waals (vdW) interfaces hosting a moiré pattern generated by interlayer twist and strain. However, achieving precise control of interlayer twist/strain remains an ongoing challenge in vdW heterostructure assembly, and even subtle variation in these structural parameters can create significant changes in the moiré period and emergent properties. Characterizing the rate of interlayer twist/strain relaxation during thermal annealing is critical to establish a thermal budget for vdW heterostructure construction and may provide a route to improve the homogeneity of the interface or to control its final state. Here, we characterize the spatial and temporal dependence of interfacial twist and strain relaxation in marginally-twisted hBN/hBN interfaces heated under conditions relevant to vdW heterostructure assembly and typical sample annealing. We find that the ferroelectric hBN/hBN moiré at very small twist angles (θ ≤ 0.1°) relaxes minimally during annealing in air at typical assembly temperatures of 170°C. However, at 400°C, twist angle relaxes significantly, accompanied by a decrease in spatial uniformity. Uniaxial heterostrain initially increases and then decreases over time, becoming increasingly non-uniform in direction. Structural irregularities such as step edges, contamination bubbles, or contact with the underlying substrate result in local inhomogeneity in the rate of relaxation.

2D materials↗
DOE OSTI2021

Role of uncertainties in protecting ecological resources during remediation and restoration

Cleanup of contaminated waste sites is a National priority to protect human health and the environment, while restoring land to productive uses. While there are uncertainties with under standing risk to individuals from exposure, the aim of this study was to focus on uncertainties and complexities for ecological systems, complicated by hundreds of species occupying any remediation site which participate in multiple-interacting food webs. The ability to better predict the effectiveness of remediation in fostering future ecosystems might facilitate remedy selection and improve strategic environmental management. This investigation examined (1) uncertainties in ecosystem processes, (2) uncertainties in exposure from contamination before remediation, and (3) uncertainties during remediation. Two Department of Energy sites Hanford Site and Savannah River Site were used as case studies to illustrate how the uncertainties affect eco-receptors. Several types of ecological, physical, and human dimension uncertainties are defined. Ecological uncertainties include temporal, spatial, individual, developmental, and exogenous types. Physical uncertainties are weather-related, watershed variations, slope/aspect, soil/sediment structure and form, unforeseen events, and temporal patterns. Human dimension uncertainties include current land use, future land use, extractive and non-extractive recreation. The effects of remedial strategies varied between the two sites because Hanford is a primarily arid shrub-steppe ecotype, while Savannah River is a wet forest ecotype. Defining the associated ecological sensitivities and uncertainties and providing examples might help policy-makers, managers, planners, and contractors to be aware of issues to consider throughout planning, remediation, and restoration. Adding ecological uncertainty analysis to risk evaluations and remediation planning is analogous to using safety factors in human health risk assessment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Giant Starship Elements Mobilize Accessory Genes in Fungal Genomes

Accessory genes are variably present among members of a species and are a reservoir of adaptive functions. In bacteria, differences in gene distributions among individuals largely result from mobile elements that acquire and disperse accessory genes as cargo. In contrast, the impact of cargo-carrying elements on eukaryotic evolution remains largely unknown. Here, we show that variation in genome content within multiple fungal species is facilitated by Starships, a newly discovered group of massive mobile elements that are 110 kb long on average, share conserved components, and carry diverse arrays of accessory genes. We identified hundreds of Starship-like regions across every major class of filamentous Ascomycetes, including 28 distinct Starships that range from 27 to 393 kb and last shared a common ancestor ca. 400 Ma. Using new long-read assemblies of the plant pathogen Macrophomina phaseolina, we characterize four additional Starships whose activities contribute to standing variation in genome structure and content. One of these elements, Voyager, inserts into 5S rDNA and contains a candidate virulence factor whose increasing copy number has contrasting associations with pathogenic and saprophytic growth, suggesting Voyager’s activity underlies an ecological trade-off. We propose that Starships are eukaryotic analogs of bacterial integrative and conjugative elements based on parallels between their conserved components and may therefore represent the first dedicated agents of active gene transfer in eukaryotes. Our results suggest that Starships have shaped the content and structure of fungal genomes for millions of years and reveal a new concerted route for evolution throughout an entire eukaryotic phylum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Direct measurement of Stokes–Einstein diffusion of Cowpea mosaic virus with 19 µs-resolved XPCS

Brownian motion of Cowpea mosaic virus (CPMV) in water was measured using small-angle X-ray photon correlation spectroscopy (SA-XPCS) at 19.2 µs time resolution. It was found that the decorrelation time τ(Q) = 1/DQ 2 up to Q = 0.091 nm -1 . The hydrodynamic radius R H determined from XPCS using Stokes–Einstein diffusion D = kT/(6πηR H ) is 43% larger than the geometric radius R 0 determined from SAXS in the 0.007 M K 3 PO 4 buffer solution, whereas it is 80% larger for CPMV in 0.5 M NaCl and 104% larger in 0.5 M (NH 4 ) 2 SO 4 , a possible effect of aggregation as well as slight variation of the structures of the capsid resulting from the salt–protein interactions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Stochastic Home Energy Management Systems with Varying Controllable Resources

This paper studies the performance of a model predictive control (MPC) algorithm in a home energy management system (HEMS) as the set of controllable resources varies and under both a constant and a time-of-use (TOU) electricity price structure. The set of controllable resources includes residentially-owned photovoltaic (PV) panels, a home battery system (HBS), an electric vehicle (EV), and a home heating, ventilation, and air conditioning (HVAC) system. The HEMS optimally schedules the set of controllable resources given user preferences such as indoor thermal comfort and electricity cost sensitivity. The home energy management system is built on a chance constrained, MPC-based algorithm, where the chance constraint ensures the indoor thermal comfort is satisfied with a high probability given uncertainty in the outdoor temperature and solar irradiance forecasts. Simulation results for varying sets of controllable resources under two different electricity price structures demonstrate the variation in the HEMS control with respect to HBS operation, electricity cost, and grid power usage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Genome‐wide association identifies a BAHD acyltransferase activity that assembles an ester of glucuronosylglycerol and phenylacetic acid

SUMMARY Genome‐wide association studies (GWAS) are an effective approach to identify new specialized metabolites and the genes involved in their biosynthesis and regulation. In this study, GWAS of Arabidopsis thaliana soluble leaf and stem metabolites identified alleles of an uncharacterized BAHD‐family acyltransferase (AT5G57840) associated with natural variation in three structurally related metabolites. These metabolites were esters of glucuronosylglycerol, with one metabolite containing phenylacetic acid as the acyl component of the ester. Knockout and overexpression of AT5G57840 in Arabidopsis and heterologous overexpression in Nicotiana benthamiana and Escherichia coli demonstrated that it is capable of utilizing phenylacetyl‐CoA as an acyl donor and glucuronosylglycerol as an acyl acceptor. We, thus, named the protein Glucuronosylglycerol Ester Synthase (GGES). Additionally, phenylacetyl glucuronosylglycerol increased in Arabidopsis CYP79A2 mutants that overproduce phenylacetic acid and was lost in knockout mutants of UDP‐sulfoquinovosyl: diacylglycerol sulfoquinovosyl transferase, an enzyme required for glucuronosylglycerol biosynthesis and associated with glycerolipid metabolism under phosphate‐starvation stress. GGES is a member of a well‐supported clade of BAHD family acyltransferases that arose by duplication and neofunctionalized during the evolution of the Brassicales within a larger clade that includes HCT as well as enzymes that synthesize other plant‐specialized metabolites. Together, this work extends our understanding of the catalytic diversity of BAHD acyltransferases and uncovers a pathway that involves contributions from both phenylalanine and lipid metabolism.

09 BIOMASS FUELS↗
DOE OSTI2022

Basin-scale biogeography of marine phytoplankton reflects cellular-scale optimization of metabolism and physiology

Extensive microdiversity within Prochlorococcus, the most abundant marine cyanobacterium, occurs at scales from a single droplet of seawater to ocean basins. To interpret the structuring role of variations in genetic potential, as well as metabolic and physiological acclimation, we developed a mechanistic constraint-based modeling framework that incorporates the full suite of genes, proteins, metabolic reactions, pigments, and biochemical compositions of 69 sequenced isolates spanning the Prochlorococcus pangenome. Optimizing each strain to the local, observed physical and chemical environment along an Atlantic Ocean transect, we predicted variations in strain-specific patterns of growth rate, metabolic configuration, and physiological state, defining subtle niche subspaces directly attributable to differences in their encoded metabolic potential. Predicted growth rates covaried with observed ecotype abundances, affirming their significance as a measure of fitness and inferring a nonlinear density dependence of mortality. Our study demonstrates the potential to interpret global-scale ecosystem organization in terms of cellular-scale processes.

59 BASIC BIOLOGICAL SCIENCES↗