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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Fluxes in ;Free; and Total Zinc Are Essential for Progression of Intraerythrocytic Stages of Plasmodium falciparum

Dynamic fluxes in the concentration of ions and small molecules are fundamental features of cell signaling, differentiation, and development. Similar roles for fluxes in transition metal concentrations are less well established. Here, we show that massive zinc fluxes are essential in the infection cycle of an intracellular eukaryotic parasite. Using single-cell quantitative imaging, we show that growth of the blood-stage Plasmodium falciparum parasite requires acquisition of 30 million zinc atoms per erythrocyte before host cell rupture, corresponding to a 400% increase in total zinc concentration. Zinc accumulates in a freely available form in parasitophorous compartments outside the food vacuole, including mitochondria. Restriction of zinc availability via small molecule treatment causes a drop in mitochondrial membrane potential and severely inhibits parasite growth. Thus, extraordinary zinc acquisition and trafficking are essential for parasite development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Mass balance implies Holocene development of a low-relief karst patterned landscape

We constructed mass balances of both calcium and phosphorus for two watersheds in Big Cypress National Preserve in southwest Florida (USA) to evaluate the time scales over which its striking landscape pattern developed. This low-relief carbonate landscape is dotted with evenly spaced, evenly sized, shallow surface depressions that annually fill with surface water and thus support wetland ecosystems (e.g. cypress domes) embedded in a pine-dominated upland matrix with exposed bedrock. Local and landscape scale feedbacks between hydrology, ecological dynamics and limestone dissolution are hypothesized to explain this karst dissolution patterning. This hypothesis requires the region to be wet enough to initiate surface water storage, which constrains landscape formation to interglacial periods. The time scale therefore would be relatively recent if creation of the observed pattern occurred in the current interglacial period (i.e. Holocene), and older time scales could reflect inherited patterns from previous inter-glacial periods, or from other processes of abiotic karstification. We then determined phosphorus stocks across four landscape compartments and estimated the limestone void space (i.e., wetland depression volume) across the landscape to represent cumulative calcium export. We calculated fluxes in (e.g., atmospheric deposition) and out (i.e., solute export) of the landscape to determine landscape denudation rates through mass balance. Comparing stocks and annual fluxes yielded independent estimates of landscape age from the calcium and phosphorus budgets. Our mass balance results indicate that the landscape began to develop in the early-mid Holocene (12,000–5000 ybp). Radiocarbon dating estimates implied similar rates of dissolution (~1 m per 3000–3500 years), and were in agreement with Holocene origin. This supports the hypothesis that ecohydrologic feedbacks between hydrology and vegetation occurring during the present interglacial period are sufficient to shape this landscape into the patterns we see today, and more broadly suggests the potential importance of biota in the development of macro-scale karst features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2022

A systematic study and framework of fringe projection profilometry with improved measurement performance for in-situ LPBF process monitoring

Fringe Projection Profilometry (FPP) is a cost-effective and non-invasive technology that has been shown to measure finer features. Here, in this work, we developed an in-situ FPP method to measure the dynamic topography of powder bed and printed layer during Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) process. A systematic study towards developing a comprehensive framework of LPBF-specific FPP is demonstrated to enhance and evaluate the performance of applying FPP for in-situ LPBF monitoring, including 1) a modified sensor model with localized correction; 2) improved phase unwrapping with FFT filtering 3) quantitative uncertainty analysis; and 4) experimental validation with ex-situ characterization. The developed LPBF-specific FPP system and methods are implemented on a commercial LPBF-AM machine, achieving better accuracy, more robustness, and increased field of view while maintaining sufficient measurement range and decent resolution, in contrast to literature methods. The established FPP framework will facilitate the development of closed-loop control strategies for advancing LPBF based AM.

42 ENGINEERING↗
DOE OSTI2026

Disorder-induced proximate quantum spin ice phase in Pr2Sn2O7

We report a comprehensive bulk characterization and neutron scattering investigation of single-crystalline Pr2Sn2O7, a magnetic pyrochlore synthesized via a flux-growth method. Unpolarized neutron diffuse scattering reveals the emergence of spin-ice correlations below T ∼ 1 K, evidenced by the development of anisotropic pinch-point features that are consistent with quantum-spin-ice (QSI) behavior. A.C. susceptibility measurements indicate a progressive slowing of spin dynamics in this regime, culminating in complete spin freezing below Tf ≈ 0.15 K. Inelastic neutron scattering at T = 0.5 K reveals a broad spectrum of quasi-elastic magnetic excitations, with intensity in the low-energy range [0, 0.2] meV significantly suppressed below Tf. Meanwhile, an incipient (100)-type magnetic order begins to nucleate, and a gapped excitation centered at ℏω = 0.23 meV persists. We further identify two distinct dynamical timescales above Tf , a slow component τ_slow ∼ 10^−5 s and a fast component τ_fast ∼ 10^−10 s, in quantitative agreement with theoretical predictions for QSI systems. Taken together, these results indicate that Pr2Sn2O7 enters a disorder-induced spin-frozen phase below Tf , lying in close proximity to a U(1) quantum spin liquid

Luo, Yi [ORNL] (ORCID:000900048710428X)↗
DOE OSTI2024

Effects of radiative heat loss on extinction limits of counterflow premixed ammonia-air flames

The effect of radiative heat loss on counterflow premixed ammonia-air flames has been investigated as a function of equivalence ratio and system pressure. Non-adiabatic counterflow premixed flame simulations incorporating detailed chemistry, transport, and radiative heat transfer in the optically thin limit have been employed to elucidate important underlying physics and extinction characteristics. Similar to methane-air flame systems, non-adiabatic counterflow premixed computations show that the combined effects of positive flame stretch, sub-unity Lewis number, and radiative heat loss lead to the extension of the lean flammability limit for ammonia-air flames, revealing a C-shaped curve near the lean flammability limit that exhibits both radiation-induced and stretch-induced extinction states. Here, the computations compare favorably with the experimentally determined extinction stretch rate values for the stretch-induced extinction states over a wide range of equivalence ratios at different pressures up to 5 atm. A novel feature sensitivity analysis has also been developed to highlight important sensitive reactions for the stretch- and radiation-induced extinction states. Furthermore, the controlling chemistry at the dual-extinction states and at varying pressures are compared and discussed.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Improving Oxygen Reduction Performance of Surface-Layer-Controlled Pt–Ni Nano-Octahedra via Gaseous Etching

This study demonstrates an atomic composition manipulation on Pt–Ni nano-octahedra to enhance their electrocatalytic performance. By selectively extracting Ni atoms from the {111} facets of the Pt–Ni nano-octahedra using gaseous carbon monoxide at an elevated temperature, a Pt-rich shell is formed, resulting in an ~2 atomic layer Pt-skin. The surface-engineered octahedral nanocatalyst exhibits a significant enhancement in both mass activity (~1.8-fold) and specific activity (~2.2-fold) toward the oxygen reduction reaction compared with its unmodified counterpart. After 20,000 potential cycles of durability tests, the surface-etched Pt–Ni nano-octahedral sample shows a mass activity of 1.50 A/mg Pt , exceeding the initial mass activity of the unetched counterpart (1.40 A/mg Pt ) and outperforming the benchmark Pt/C (0.18 A/mg Pt ) by a factor of 8. DFT calculations predict this improvement with the Pt surface layers and support these experimental observations. Therefore, this surface-engineering protocol provides a promising strategy for developing novel electrocatalysts with improved catalytic features.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Vanishing carrier-envelope-phase-sensitive response in optical-field photoemission from plasmonic nanoantennas

At the surfaces of nanostructures, enhanced electric fields can drive optical-field photoemission and thereby generate and control electrical currents at frequencies exceeding 100 THz. A hallmark of such optical-field photoemission is the sensitivity of the total emitted current to the carrier-envelope phase (CEP). In this work, we examine CEP-sensitive photoemission from plasmonic gold nanoantennas excited with few-cycle optical pulses. At a critical pulse energy, which we call a vanishing point, we observe a pronounced dip in the magnitude of the CEP-sensitive photocurrent accompanied by a sudden shift of π radians in the photocurrent phase. Analysis shows that this vanishing behaviour arises due to competition between sub-optical-cycle electron emission events from neighbouring optical half-cycles and that both the dip and phase shift are highly sensitive to the precise shape of the driving optical waveform at the surface of the emitter. As the mechanisms underlying the dip and phase shift are a general consequence of nonlinear, field-driven photoemission, they may be used to probe sub-optical-cycle emission processes from solid-state emitters, atoms and molecules. Improved understanding of these CEP-sensitive photocurrent features will be critical to the development of optical-field-driven photocathodes for time-domain metrology and microscopy applications demanding attosecond temporal and nanometre spatial resolution.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

O-GlcNAc forces an α-synuclein amyloid strain with notably diminished seeding and pathology

Amyloid-forming proteins such α-synuclein and tau, which are implicated in Alzheimer’s and Parkinson’s disease, can form different fibril structures or strains with distinct toxic properties, seeding activities and pathology. Understanding the determinants contributing to the formation of different amyloid features could open new avenues for developing disease-specific diagnostics and therapies. Here we report that O-GlcNAc modification of α-synuclein monomers results in the formation of amyloid fibril with distinct core structure, as revealed by cryogenic electron microscopy, and diminished seeding activity in seeding-based neuronal and rodent models of Parkinson’s disease. Although the mechanisms underpinning the seeding neutralization activity of the O-GlcNAc-modified fibrils remain unclear, our in vitro mechanistic studies indicate that heat shock proteins interactions with O-GlcNAc fibril inhibit their seeding activity, suggesting that the O-GlcNAc modification may alter the interactome of the α-synuclein fibrils in ways that lead to reduce seeding activity in vivo. Our results show that posttranslational modifications, such as O-GlcNAc modification, of α-synuclein are key determinants of α-synuclein amyloid strains and pathogenicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A predictive machine learning approach for microstructure optimization and materials design

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniqueness of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. In conclusion, experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Mass spectrometry-based monitoring of millisecond protein–ligand binding dynamics using an automated microfluidic platform

Characterizing protein-ligand binding dynamics is crucial for understanding protein function and developing new therapeutic agents. We have developed a novel microfluidic platform that features rapid mixing of protein and ligand solutions, variable incubation times, and on-chip electrospray ionization to perform label-free, solution-based monitoring of protein-ligand binding dynamics. This platform offers many advantages including automated processing, rapid mixing, and low sample consumption.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

Selection of components for the IDEALHY preferred cycle for the large scale liquefaction of hydrogen

In a future energy scenario, in which storage and transport of liquid hydrogen in large quantities will be used, the efficiency of the liquefaction of hydrogen will be of utmost importance. The goal of the IDEALHY working party is to identify the most promising process for a 50 t/d plant and to select the components, with which such a process can be realized. In the first stage the team has compared several processes, which have been proposed or realized in the past. Based on this information a process has been selected, which is thermodynamically most promising and for which it could be assumed that good components already exist or can be developed in the foreseeable future. Main features of the selected process are the compression of the feed stream to a relatively high pressure level, o-p conversion inside plate-fin heat exchangers and expansion turbines in the supercritical region. Precooling to a temperature between 150 and 100 K will be obtained from a mixed refrigerant cycle similar to the systems used successfully in natural gas liquefaction plants. The final cooling will be produced by two Brayton cycles, both having several expansion turbines in series. The selected overall process has still a number of parameters, which can be varied. The optimum, i.e. the final choice will depend mainly on the quality of the available components. Key components are the expansion turbines of the two Brayton cycles and the main recycle compressor, which may be common to both Brayton cycles. A six-stage turbo-compressor with intercooling between the stages is expected to be the optimum choice here. Each stage may consist of several wheels in series. To make such a high efficient and cost-effective compressor feasible, one has to choose a refrigerant, which has a higher molecular weight than helium. The present preferred choice is a mixture of helium and neon with a molecular weight of about 8 kg/kmol. Such an expensive refrigerant requires that the whole refrigeration loop is extremely tight.

42 ENGINEERING↗
DOE OSTI2014

Restricted active space calculations of L-edge X-ray absorption spectra: From molecular orbitals to multiplet states

The metal L-edge (2p → 3d) X-ray absorption spectra are affected by a number of different interactions: electron-electron repulsion, spin-orbit coupling, and charge transfer between metal and ligands, which makes the simulation of spectra challenging. The core restricted active space (RAS) method is an accurate and flexible approach that can be used to calculate X-ray spectra of a wide range of medium-sized systems without any symmetry constraints. Here, the applicability of the method is tested in detail by simulating three ferric (3d{sup 5}) model systems with well-known electronic structure, viz., atomic Fe{sup 3+}, high-spin [FeCl{sub 6}]{sup 3−} with ligand donor bonding, and low-spin [Fe(CN){sub 6}]{sup 3−} that also has metal backbonding. For these systems, the performance of the core RAS method, which does not require any system-dependent parameters, is comparable to that of the commonly used semi-empirical charge-transfer multiplet model. It handles orbitally degenerate ground states, accurately describes metal-ligand interactions, and includes both single and multiple excitations. The results are sensitive to the choice of orbitals in the active space and this sensitivity can be used to assign spectral features. A method has also been developed to analyze the calculated X-ray spectra using a chemically intuitive molecular orbital picture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Broadband surface-wave transformation cloak

Guiding surface electromagnetic waves around disorder without disturbing the wave amplitude or phase is in great demand for modern photonic and plasmonic devices, but is fundamentally difficult to realize because light momentum must be conserved in a scattering event. A partial realization has been achieved by exploiting topological electromagnetic surface states, but this approach is limited to narrow-band light transmission and subject to phase disturbances in the presence of disorder. Recent advances in transformation optics apply principles of general relativity to curve the space for light, allowing one to match the momentum and phase of light around any disorder as if that disorder were not there. This feature has been exploited in the development of invisibility cloaks. An ideal invisibility cloak, however, would require the phase velocity of light being guided around the cloaked object to exceed the vacuum speed of light—a feat potentially achievable only over an extremely narrow band. In this paper, we theoretically and experimentally show that the bottlenecks encountered in previous studies can be overcome. We introduce a class of cloaks capable of remarkable broadband surface electromagnetic waves guidance around ultrasharp corners and bumps with no perceptible changes in amplitude and phase. These cloaks consist of specifically designed nonmagnetic metamaterials and achieve nearly ideal transmission efficiency over a broadband frequency range from 0 + to 6 GHz. Finally, this work provides strong support for the application of transformation optics to plasmonic circuits and could pave the way toward high-performance, large-scale integrated photonic circuits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Three-dimensional structures of equatorial waves and the resulting super-rotation in the atmosphere of a tidally locked hot Jupiter

Three-dimensional (3D) equatorial trapped waves excited by stellar isolation and the resulting equatorial super-rotating jet in a vertical stratified atmosphere of a tidally locked hot Jupiter are investigated. Taking the hot Jupiter HD 189733b as a fiducial example, we analytically solve linear equations subject to stationary stellar heating with a uniform zonal-mean flow included. We also extract wave information in the final equilibrium state of the atmosphere from our radiative hydrodynamical simulation for HD 189733b. Our analytic wave solutions are able to qualitatively explain the 3D simulation results. Apart from previous wave studies, investigating the vertical structure of waves allows us to explore new wave features such as the wavefronts tilts related to the Rossby-wave resonance as well as dispersive equatorial waves. We also attempt to apply our linear wave analysis to explain some numerical features associated with the equatorial jet development seen in the general circulation model by Showman and Polvani. During the spin-up phase of the equatorial jet, the acceleration of the jet can be in principle boosted by the Rossby-wave resonance. However, we also find that as the jet speed increases, the Rossby-wave structure shifts eastward, while the Kelvin-wave structure remains approximately stationary, leading to the decline of the acceleration rate. Our analytic model of jet evolution implies that there exists only one stable equilibrium state of the atmosphere, possibly implying that the final state of the atmosphere is independent of initial conditions in the linear regime. Limitations of our linear model and future improvements are also discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Adventures in Holographic Dimer Models

We abstract the essential features of holographic dimer models, and develop several new applications of these models. Firstly, semi-holographically coupling free band fermions to holographic dimers, we uncover novel phase transitions between conventional Fermi liquids and non-Fermi liquids, accompanied by a change in the structure of the Fermi surface. Secondly, we make dimer vibrations propagate through the whole crystal by way of double trace deformations, obtaining nontrivial band structure. In a simple toy model, the topology of the band structure experiences an interesting reorganization as we vary the strength of the double trace deformations. Finally, we develop tools that would allow one to build, in a bottom-up fashion, a holographic avatar of the Hubbard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Uncovering obscured phonon dynamics from powder inelastic neutron scattering using machine learning

The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional analysis methods. In this study, we present a machine learning framework designed to reveal obscured phonon dynamics from powder spectra. Using a variational autoencoder, we obtain a disentangled latent representation of spectra and successfully extract force constants for reconstructing phonon dispersions. Notably, our model demonstrates effective applicability to experimental data even when trained exclusively on physics-based simulations. The fine-tuning with experimental spectra further mitigates issues arising from domain shift. Analysis of latent space underscores the model’s versatility and generalizability, affirming its suitability for complex system applications. Furthermore, our framework’s two-stage design is promising for developing a universal pre-trained feature extractor. This approach has the potential to revolutionize neutron measurements of phonon dynamics, offering researchers a potent tool to decipher intricate spectra and gain valuable insights into the intrinsic physics of materials.

domain adaptation↗
DOE OSTI2021

The Crown Pearl: a draft genome assembly of the European freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758)

Abstract Since historical times, the inherent human fascination with pearls turned the freshwater pearl mussel Margaritifera margaritifera (Linnaeus, 1758) into a highly valuable cultural and economic resource. Although pearl harvesting in M. margaritifera is nowadays residual, other human threats have aggravated the species conservation status, especially in Europe. This mussel presents a myriad of rare biological features, e.g. high longevity coupled with low senescence and Doubly Uniparental Inheritance of mitochondrial DNA, for which the underlying molecular mechanisms are poorly known. Here, the first draft genome assembly of M. margaritifera was produced using a combination of Illumina Paired-end and Mate-pair approaches. The genome assembly was 2.4 Gb long, possessing 105,185 scaffolds and a scaffold N50 length of 288,726 bp. The ab initio gene prediction allowed the identification of 35,119 protein-coding genes. This genome represents an essential resource for studying this species’ unique biological and evolutionary features and ultimately will help to develop new tools to promote its conservation.

Gomes-dos-Santos, André (ORCID:0000000199734861)↗