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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design of high-pressure iron Rayleigh–Taylor strength experiments for the National Ignition Facility

Iron is an important metal, scientifically and technologically. It is a common metal on Earth, forming the main constituent of the planet's inner core, where it is believed to be in solid state at high pressure and high temperature. It is also the main component of many important structural materials used in quasistatic and dynamic conditions. Laser-driven Rayleigh–Taylor instability provides a means of probing material strength at high pressure and high temperature. The unavoidable phase transition in iron at relatively low pressure induces microstructural changes that ultimately affect its strength in this extreme regime. This inevitable progression can make it difficult to design experiments and understand their results. Here, we address this challenge with the introduction of a new approach: a direct-drive design for Rayleigh–Taylor strength experiments capable of reaching up to 400 GPa over a broad range of temperatures. We use 1D and 2D hydrodynamic simulations to optimize target components and laser pulse shape to induce the phase transition and compress the iron to high pressure and high temperature. At the simulated pressure–temperature state of 350 GPa and 4000 K, we predict a ripple growth factor of 3–10 depending on the strength with minimal sensitivity to the equation of state model used. The growth factor is the primary observable, and the measured value will be compared to simulations to enable the extraction of the strength under these conditions. These experiments conducted at high-energy laser facilities will provide a unique way to study an important metal.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Degeneracy Removal of Spin Bands in Collinear Antiferromagnets with Non–Interconvertible Spin–Structure Motif Pair

Energy bands in antiferromagnets are supposed to be spin degenerate in the absence of spin–orbit coupling (SOC). Recent studies have identified formal symmetry conditions for antiferromagnetic crystals in which this degeneracy can be lifted, spin splitting, even in the vanishing SOC (i.e., non-relativistic) limit. Materials having such symmetries could enable spin-split antiferromagnetic spintronics without the burden of using heavy-atom compounds. However, the symmetry conditions that involve spin and magnetic symmetry are not always effective as practical material selection filters. Furthermore, these symmetry conditions do not readily disclose trends in the magnitude and momentum dependence of the spin-splitting energy. Here, it is shown that the formal symmetry conditions enabling spin-split antiferromagnets can be interpreted in terms of local motif pairs, such as octahedra or tetrahedra, each carrying opposite magnetic moments. Here, collinear antiferromagnets with such a spin-structure motif pair, whose components interconvert by neither translation nor spatial inversion, will show spin splitting. Such a real-space motif-based approach enables an easy way to identify and design materials (illustrated in real example materials) having spin splitting without the need for SOC, and offers insights into the momentum dependence and magnitude of the spin splitting.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New experimental approach to understanding the chemical reactivity of oxide surfaces

Metal oxides have been an attractive option for a range of applications, including hydrogen sensors, microelectronics, and catalysis, due to their reactivity and tunability. The properties of metal oxides can vary greatly on their precise surface structure; however, few surface science techniques can achieve atomistic-level determinations of surface structure, and fewer yet can do so for insulator surfaces. Low energy ion beam analysis offers a potential insulator-compatible solution to characterizing the surface structure of metal oxides. As a feasibility study, we apply low energy ion beam analysis to investigate the surface structure of a magnetite single crystal, Fe 3 O 4 (100). We obtain multi-angle maps using both forward-scattering low energy ion scattering (LEIS) and backscattering impact-collision ion scattering spectroscopy (ICISS). Both sets of experimental maps have intensity patterns that reflect the symmetries of the Fe 3 O 4 (100) surface structure. However, analytical interpretation of these intensity patterns to extract details of the surface structure is significantly more complex than previous LEIS and ICISS structural studies of one-component metal crystals, which had far more symmetries to exploit. To gain further insight into the surface structure, we model our experimental measurements with ion-trajectory tracing simulations using molecular dynamics. Our simulations provide a qualitative indication that our experimental measurements agree better with a subsurface cation vacancy model than a distorted bulk model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Excess Density as a Descriptor for Electrolyte Solvent Design

Electrolytes mediate interactions between the cathode and anode and determine performance characteristics of batteries. Mixtures of multiple solvents are often used in electrolytes to achieve desired properties, such as viscosity, dielectric constant, boiling point, and melting point. Conventionally, multi-component electrolyte properties are approximated with linear mixing, but in practice, significant deviations are observed. Excess quantities can provide insights into the molecular behavior of the mixture and could form the basis for designing high-performance electrolytes. Here we investigate the excess density of commonly used Li-ion battery solvents such as cyclic carbonates, linear carbonates, ethers, and nitriles with molecular dynamics simulations. We additionally investigate electrolytes consisting of these solvents and a salt. The results smoothly vary with mole percent and are fit to permutation-invariant Redlich-Kister polynomials. Mixtures of similar solvents, such as cyclic-cyclic carbonate mixtures, tend to have excess properties that are lower in magnitude compared to mixtures of dissimilar substances, such as carbonate-nitrile mixtures. We perform experimental testing using our automated test stand, Clio, to provide validation to the observed simulation trends. We quantify the structure similarity using SOAP fingerprints to create a descriptor for excess density, enabling the design of electrolyte properties. To a first approximation, this will allow us to estimate the deviation of a mixture from ideal behavior based solely upon the structural dissimilarity of the components.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Benchmarking Guanidinium Organosulfonate Hydrogen-Bonded Frameworks for Structure Determination of Encapsulated Guests

Single crystal X-ray diffraction (SCXRD) is arguably the most definitive method for molecular structure determination, but it is often challenged by compounds that are liquids or oils at room temperature or do not form crystals adequate for analysis. Our laboratory previously reported a simple, cost-effective, single-step crystallization method based on guanidinium organosulfonate (GS) hydrogen bonded frameworks for structure determination of a wide range of encapsulated guest molecules, including assignment of the absolute configuration of chiral centers. Herein, we expand on those results and report a head-to-head comparison of the GS method with adamantoid “molecular chaperones”, which have been reported to be useful hosts for structure determination. Inclusion compounds limited to only two GS hosts are characterized by low R1 values and Flack parameters, infrequent disorder of the host and guest, and manageable disorder when it does exist. The structures of some target molecules that were not included or resolved using the adamantoid chaperones were successfully included and resolved by the GS hosts, and vice versa. Of the 32 guests attempted by the GS method, 31 inclusion compounds afforded successful guest structure solutions, a 97% success rate. The GS hosts and adamantoid chaperones are complementary with respect to guest inclusion, arguing that both should be employed in the arsenal of methods for structure determination. Furthermore, the low cost of organosulfonate host components promises an accessible route to molecular structure determination for a wide range of users.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of thin metal contacts on few-layer van der Waals ferrielectric CuInP 2 S 6

Out-of-plane polarized ferroelectric materials in a capacitive structure provide a key component for several technological applications. Furthermore, two-dimensional materials are expected to aid in the quest for both ultrathin and flexible electronics. Of the various two-dimensional ferroelectrics with out-of-plane polarization, CuInP 2 S 6 is special in that the Cu atoms are highly mobile and it has been shown to possess both low- and high-polarization states. Here, using density-functional-theory calculations, we explore the stabilization of the ferroelectric state for several prototypical metal contacts (Gr, Ni, Cu, Au, and Ag). In all cases, we find that the ferroelectric state can be stabilized at fewer layers than in the freestanding case. For all of the considered conventional metal contacts, we also find the existence of a quasi-ferroelectric state that stabilizes a polar phase for thicknesses greater than two layers of CIPS. In the cases of Au and Ag, interfacial alignment and strain can be used to stabilize ferroelectricity at the bilayer limit. Furthermore, we find that the strength of the interaction between the contact and CuInP 2 S 6 also leads to stabilization of the high-polarization state when ferroelectricity is stabilized. Lastly, energy-barrier calculations show that the system is still switchable in the presence of contact doping from the metal contacts.

2D materials↗
DOE OSTI2023

Characterization of boundary precipitation in a heavy ion irradiated tungsten heavy alloy under the simulated fusion environment

In the concerted effort to identify materials capable of surviving the adverse environment of a fusion reactor interior, tungsten heavy alloys have been put forth as leading candidates. Experimental trials and behavioral studies have yielded positive results for their adoption by taking advantage of the alloy’s unique balance of inherently high fracture toughness and low sputter yields; yet due to their relative novelty in the fusion community, there remains a lack of understanding on the response of these materials to the extended high temperature irradiation environment of the reactor interior. Further, to alleviate this issue and provide the necessary data on the behavior of tungsten heavy alloys to the simulated fusion environment, a 90W-7Ni-3Fe alloy has been subjected to elevated temperature sequential Ni + and He + ion irradiations to mimic the expected displacement damage and gas production expected after five years of service as a plasma facing material component. Atomic-scale structural analyses and nanoscale chemical mapping have identified the formation of two distinct precipitation structures, a surface localized η-carbide and an a-W 2 C type tungsten carbide, both of which appear to originate at the bi-phase interface between W and the ductile phase. This irradiation assisted and induced precipitate formation respectively is anticipated to adversely affect these materials by selective embrittlement at bi-phase interfaces leading to a reduction in the material’s overall fracture toughness during prolonged high temperature irradiation. It is asserted that any potential exposure to C during fusion reactor operational service should be minimized as to prevent the formation of these phases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

NeRVI: Compressive neural representation of visualization images for communicating volume visualization results

We present NeRVI, a new deep-learning approach that compresses a large collection of visualization images generated from time-varying data for communicating volume visualization results. Based on an image-based implicit neural representation, our approach represents tens of thousands of high-resolution rendering images parametrized by different parameters via a hybrid model of multilayer perceptrons and convolutional neural networks. Here, our model predicts images and corresponding masks, and the masks are utilized for loss computation and network training to capture fine structural details and small components. In conjunction with model quantization and weight encoding, NeRVI yields highly compact compressive neural representations while preserving the image fidelity well. We demonstrate the effectiveness of NeRVI with isosurface rendering and direct volume rendering images generated from multiple data sets and compare NeRVI with other state-of-the-art deep learning-based (InSituNet, SIREN, NeRF, and NeRV) methods. Quantitative and qualitative results show that NeRVI provides an alternative solution that augments domain scientists' ability to manage, represent, and communicate scientific visualization output.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗
DOE OSTI2026

Multi-material additive manufacturing of aluminum 6061-T6 alloy with stainless steel 304: Suppression of intermetallic compounds and interface growth mechanism

Fabricating integrated aluminum-steel structures is difficult because of metallurgical incompatibilities that promote intermetallic compound (IMC) formation at their interfaces. This work introduces a practical route for additively manufacturing 6061-T6 aluminum alloy (AA6061-T6) directly onto 304 stainless steel (SS304) using a high shear strain rate-assisted interfacial bonding mechanism. Through the friction extrusion deposition-based additive manufacturing method, both single- and multi-layer deposits of AA6061-T6 were successfully fabricated on SS304, yielding a robust hybrid multi-material structure. Comprehensive analyses of deposition quality, interface porosity, and bonding performance showed that the interface achieved a tensile strength exceeding 154 MPa under quasi-static loading. Microstructural observations revealed that the deposited aluminum layers experienced severe plastic deformation, resulting in pronounced grain refinement. Importantly, the interfacial zone was found to be free of brittle IMCs, instead containing a thin amorphous layer that evolved through a non-linear reaction-zone growth law. This solid-state additive strategy establishes a promising pathway for lightweight structural systems, nuclear energy component cladding, and multifunctional engineering components, redefining how dissimilar metals can be integrated for advanced applications.

Aluminum alloy↗
DOE OSTI2022

Outstanding questions on xylan biosynthesis

Xylan is the second most abundant polysaccharide in plant biomass. It is a crucial component of cell wall structure as well as a significant factor contributing to biomass recalcitrance. Xylan consists of a linear chain of β-1,4-linked xylosyl residues that are often substituted with glycosyl side chains, such as glucuronosyl/methylglucuronosyl and arabinofuranosyl residues, and acetylated at O-2 and/or O-3. Xylan from gymnosperms and dicots contains a unique reducing end tetrasaccharide sequence that is not detected in xylan from grasses, bryophytes and seedless vascular plants. Grass xylan is heavily decorated at O-3 with arabinofuranosyl residues that are frequently esterified with hydroxycinnamates. Further, genetic and biochemical studies have uncovered a number of genes involved in xylan backbone elongation and acetylation, xylan glycosyl substitutions and their modifications, and the synthesis of the unique xylan reducing end tetrasaccharide sequence, but some outstanding issues on the biosynthesis of xylan still remain unanswered. Here, we provide a brief overview of xylan structure and focus on discussion of the current understanding and open questions on xylan biosynthesis. Further elucidation of the biochemical mechanisms underlying xylan biosynthesis will not only shed new insights into cell wall biology but also provide molecular tools for genetic modification of biomass composition tailored for diverse end uses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Characterizing leaf-scale fluorescence with spectral invariants

Sun-induced chlorophyll fluorescence (SIF) is increasingly recognized as a non-destructive probe for tracking terrestrial photosynthesis. Emerging developments in spectral invariants theory provide an innovative and efficient approach for representing SIF radiative transfer processes at the canopy scale. However, modeling leaf-scale fluorescence based on the spectral invariants properties (SIP) remains underexplored. In this study, the spectral invariants theory is employed for the first time to model the leaf-scale total, backward and forward fluorescence (leaf-SIP SIF). The leaf-SIP SIF model separates the leaf-scale radiative transfer process into two distinct components: the wavelength-dependent one associated with leaf biochemical properties, and the wavelength-independent component linked to leaf structural characteristics. The leaf structure-related effects are characterized by two spectrally invariant parameters: the photon recollision probability (p) and the scattering asymmetry parameter (q), which are parameterized using the directly measurable leaf dry matter. Evaluation against field measurements shows that the proposed leaf-SIP SIF model has a good performance, with coefficient of determination (R 2 ) of 0.89, 0.89, 0.90 and root mean squared errors (RMSE) of 1.28, 0.69, 0.74 Wm -2 µm -1 sr -1 , respectively for the total, backward, and forward fluorescence (660–800 nm). The leaf-SIP SIF model with a more concise formulation demonstrates comparable performance with the widely used Fluspect model. Further, the leaf-SIP SIF model provides a simple and efficient approach for simulating leaf-scale fluorescence, with the potential to be integrated into a unified SIP-based model framework for simulating the radiative transfer processes across the soil-leaf-canopy-atmosphere continuum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Accuracy in Resolving the First Hydration Layer on a Transition-Metal Oxide Surface: Experiment (AP-XPS) and Theory

Understanding the equilibrium conditions at the metal oxide/aqueous interface is a key component toward visualizing the structure of water in confined environments and differentiating the catalytic activity of transition-metal oxides. While ambient pressure X-ray photoelectron spectroscopy (AP-XPS) has been the primary technique to investigate the formation of a hydration layer on many surfaces, results over the extended relative humidity (RH) range accessible experimentally have not been compared quantitatively to theoretical predictions. With the use of first-principles theoretical methods and accumulated knowledge of AP-XPS spectral analysis, we do so here for a model surface, TiO 2 -terminated undoped SrTiO 3 (100) (STO). The measured distribution of OH and H 2 O coverages from vacuum up to the first hydration layer is in good agreement with a static density functional theory (DFT) configuration involving partial dissociation of H 2 O per Ti-atom mediated by H-bonding. Furthermore, ab initio molecular dynamics (AIMD) simulations at 300 K for select coverages (1/4, 1/2, and 1 ML) test the role of fluctuations and entropy in the competition between adsorption and dissociation with coverage. This comparison between theory and experiment for OH and H 2 O coverages on STO provides a foundation for a more quantitative assessment of the first hydration layer and associated competition between adsorption, dissociation, and H-bonding on transition-metal oxide surfaces.

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

Binary Superlattices of Gold Nanoparticles in Two Dimensions

Here, we have created two-dimensional (2D) binary superlattices by cocrystallizing gold nanoparticles (AuNPs) of two distinct sizes into √3 x √3 and 2 x 2 complex binary superlattices, derived from the hexagonal structures of the single components. The building blocks of these binary systems are AuNPs that are functionalized with different chain lengths of poly(ethylene glycol) (PEG). The assembly of these functionalized NPs at the air–water interface is driven by the presence of salt, causing PEG-AuNPs to migrate to the aqueous surface and assemble into a crystalline lattice. We have used liquid surface X-ray reflectivity (XR) and grazing incidence small-angle X-ray scattering (GISAXS) to examine the assembly and crystallization at the liquid interface.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Monolignol Benzoates Incorporate into the Lignin of Transgenic Populus trichocarpa Depleted in C3H and C4H

Lignin, an abundant renewable aromatic biopolymer, is an essential macromolecule in terrestrial vascular plants. Genetic modifications affecting monolignol biosynthesis, which produces lignin monomers, alter the metabolic flux through the pathway and are becoming increasingly explored for improving the lignin and biomass quality and for producing high-value commodity chemical feedstocks. Benzoate (BA) conjugates are important metabolites in plants that have not been adequately characterized as components of the lignin structure. In addition to finding trace levels of BA conjugates in wild-type (WT) Populus trichocarpa, these become significantly augmented in strategic triple transgenics. Genes for three key cytochrome P450 enzymes, two 4-hydroxylases (PtrC4H1 and PtrC4H2), and one 3-hydroxylase (PtrC3H3), were downregulated to produce the transgenic plants in which monolignol benzoate (ML-BA) conjugates were incorporated into their lignin at a level some 16-fold higher than in WT. The co-downregulation of PtrC4H1/PtrC4H2/PtrC3H3 genes may cause a rerouting or modification of the pathway due to the interaction of the benzoate biosynthetic pathway with the conventional pathway for monolignol biosynthesis. The total lignin content in the transgenics was decreased by 50%, and the lignin H-unit level was elevated some 70-fold. The wood from the transgenic trees showed reduced recalcitrance toward enzymatic saccharification, which has value for the conversion of plant biomass to bioenergy.

2D NMR↗
DOE OSTI2025

A bipartite bacterial virulence factor targets the complement system and neutrophil activation

Abstract The complement system and neutrophils constitute the two main pillars of the host innate immune defense against infection by bacterial pathogens. Here, we identify T-Mac, a novel virulence factor of the periodontal pathogen Treponema denticola that allows bacteria to evade both defense systems. We show that T-Mac is expressed as a pre-protein that is cleaved into two functional units. The N-terminal fragment has two immunoglobulin-like domains and binds with high affinity to the major neutrophil chemokine receptors FPR1 and CXCR1, blocking N -formyl-Met-Leu-Phe- and IL-8-induced neutrophil chemotaxis and activation. The C-terminal fragment functions as a cysteine protease with a unique proteolytic activity and structure, which degrades several components of the complement system, such as C3 and C3b. Murine infection studies further reveal a critical T-Mac role in tissue damage and inflammation caused by bacterial infection. Collectively, these results disclose a novel innate immunity-evasion strategy, and open avenues for investigating the role of cysteine proteases and immunoglobulin-like domains of gram-positive and -negative bacterial pathogens.

Kurniyati, Kurni↗