Search NASA⌕ Search

SEARCH · Search NASA

Results for “Surface Construction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nanoparticles caged with DNA nanostructures

Nanoparticles (NPs) offer many benefits in biotechnology because of their small size and unique properties. Furthermore, many applications require precise positioning of the NPs or biological targeting molecules on their surfaces. DNA cages constructed from DNA tile, origami, or wireframe nanostructures offer a promising path forward because of their simplicity and programmability that can be used to generate complex, dynamic 2D and 3D geometries. Such materials can be used to pattern DNA on NP surfaces and organize NPs into specific supramolecular structures. DNA-caged NPs can be implemented in biosensing and drug delivery applications with cavities precisely designed to encapsulate-specific biomolecules. Ultimately, such approaches provide a springboard for future DNA robot designs that will enable controlled interactions with biological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assessing the Role of Interfacial and Metal Sites in Pt/TiO2-Catalyzed Acetic Acid Hydrodeoxygenation

Thermochemical conversion of biomass to produce drop-in quality biofuels typically involves hydrodeoxygenation (HDO) steps following catalytic fast pyrolysis (CFP) to remove excess oxygen and create a more-stable bio-oil product. HDO reactions are performed by co-feeding the CFP vapor-phase product and H2 gas over a bi-functional catalyst. Noble-metal catalysts supported on reducible metal oxides (e.g., Pt/TiO2) are active and selective toward these HDO reactions. Griffin and co-workers showed that Pt/TiO2 catalysts promote the desired deoxygenation steps for m-cresol HDO while mitigating undesired C-C bond-breaking steps that reduce the overall value/energy density of the biofuel. Such model-compound studies to inform the design of improved catalysts for HDO chemistry are necessary to improve the overall process economics/efficiencies for biofuels production. One important class of bio-derived compounds that has not been studied extensively with respect to HDO chemistry, particularly at the atomic level, is carboxylic acids. Past experimental work indicates that Pt/C and Pt/TiO2 catalysts are selective toward C-C and C-O bond-dissociation products for acetic acid HDO, respectively. To understand the role of Pt/TiO2 active sites in this observed change in selectivity and guide catalyst development, the work in this presentation focuses on modeling the role of Pt-metal and Pt-TiO2-interfacial sites in promoting key C-C bond-breaking, C-O bond-breaking, and (de)hydrogenation steps in acetic acid HDO. Density functional theory (DFT) calculations were performed using the Vienna Ab initio Simulation Package (VASP). The exchange-correlation functional was approximated by the Perdew-Burke-Ernzerhof functional. Dispersion interactions were captured using the D3 method. Projector augmented-wave potentials described electron-ion interactions, and electron wavefunctions were expanded via a planewave basis with an energy cutoff of 500 eV. Activation barriers were calculated using the climbing image nudged elastic band method. Results and Discussion: To discern the role of Pt-metal and Pt-TiO2 interface sites in promoting acetic acid HDO chemistry, Pt(111) slab and anatase TiO2(101)-supported Pt-nanowire (PtNW/OH-TiO2) surface models were constructed, respectively. Because H2 is co-fed in HDO reactions, the anatase support was terminated with OH groups. Interfacial vacancies have been shown to facilitate Ru/TiO2-catalyzed phenol HDO; thus, an interfacial model with an OH vacancy was also considered (PtNW/OHv-TiO2). Pt-TiO2-interface sites stabilize adsorption of all studied acetic acid HDO surface intermediates relative to terrace Pt-metal sites, particularly when an interfacial-OH vacancy is present. Oxygenated species prefer to bind at the OH vacancy through the O atom, suggesting a preference for C-O over C-C bond cleavage at these sites. This hypothesis is supported by net-negative and net-positive average shifts in the reaction energy and activation energy barriers for C-O and C-C bond-breaking steps, respectively, at Pt-TiO2-interface sites relative to Pt-metal sites. Using the calculated energetics, the predicted minimum-energy pathway was determined for each surface. Pt(111) is predicted to follow decarboxylation, producing undesired methane and carbon dioxide. Conversely, PtNW/OH-TiO2 and PtNW/OHv-TiO2 are both predicted to produce desired acetaldehyde and ethane. The interfacial vacancy may also play a key role in facilitating the first C-O bond-breaking step in acetic acid HDO, lowering the barrier by 0.6 eV relative to the defect-free interface model. These results demonstrate the critical role of the Pt-TiO2 interface in the shift in acetic acid HDO selectivity experimentally observed on Pt/C and Pt/TiO2 catalysts. The results herein demonstrate the important role of the Pt-TiO2 interface and interfacial oxygen vacancies in improving the carbon efficiency for HDO reactions in CFP upgrading.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2022

Experimental Demonstration of Dark‐State Metasurface Laser with Controllable Radiative Coupling

Abstract Lasing at the nanoscale using plasmonic nanoparticles offers the prospect of strong field concentration, hence strong light−matter interactions, low lasing thresholds, and ultrafast operation. However plasmonic nanoparticles suffer from high dissipative and radiative losses, the latter being rigidly tied to the shape of the nanoparticles and symmetry of their localized plasmon resonant modes. To overcome this limitation, recent theoretical work proposes using direct lasing into dark surface states to construct lasers that conceptually allow for independent implementation of the lasing state and its coherent radiation output. Here, lasing in dark resonant states of a metasurface laser and controllable coherent outcoupling of radiation with the aid of a tightly coupled, weakly radiative metasurface are demonstrated experimentally. The laser is implemented using a thin, low‐loss dielectric film supporting surface mode‐like dark dielectric bound states and the coupling metasurface is composed of small non‐resonant scatterers that controllably but weakly perturb the dark mode and turn it partially bright. Distinct far‐field signatures that can be observed experimentally for both dark and bright lasing are identified and demonstrated. The scalability of this design, here implemented for lasing in the near‐infrared, enables large‐aperture ultra‐thin coherent light sources with controllable emission from the infrared to the visible.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lithium‐Containing Hybrid SEI Layer Enabling High Mass Loading and Anode‐Less Sodium Metal Batteries

Abstract The continuous rupturing and rebuilding of unstable solid electrolyte interphase (SEI) layer during cycling would block Na + diffusion and induce Na dendrite formation, ultimately limiting the practical application of high‐energy‐density sodium metal batteries. Herein, a hybrid SEI layer containing Li‐species is dexterously constructed on the surface of sodium metal anode. Li‐containing inorganic components (Li 3 N, LiF, and Li 2 CO 3 ) are introduced to stabilize the Na/electrolyte interface and enhance the mechanical and diffusion kinetic properties of the SEI layer, which can reduce the side reactions and gas generation, regulate Na + flux during cycling and promote rapid Na + migration for uniform dendrite‐free Na deposition. As a result, the constructed Na symmetric cells achieve low overpotential and long cycle life of 5900, 1800, and 500 h at current densities of 3, 10, and 30 mA cm −2 , respectively. Furthermore, the full cells paired with the Na₃V₂(PO₄)₃ cathode demonstrate high specific capacity and excellent cycle stability, even at an ultra‐high cathode loading of 39.3 mg cm −2 and a low N/P ratio (negative/positive electrode capacity ratio of 1.21).

Xia, Li [State Key Laboratory of Physical Chemistr↗
DOE OSTI2025

Lithium‐Containing Hybrid SEI Layer Enabling High Mass Loading and Anode‐Less Sodium Metal Batteries

The continuous rupturing and rebuilding of unstable solid electrolyte interphase (SEI) layer during cycling would block Na + diffusion and induce Na dendrite formation, ultimately limiting the practical application of high-energy-density sodium metal batteries. Herein, a hybrid SEI layer containing Li-species is dexterously constructed on the surface of sodium metal anode. Li-containing inorganic components (Li 3 N, LiF, and Li 2 CO 3 ) are introduced to stabilize the Na/electrolyte interface and enhance the mechanical and diffusion kinetic properties of the SEI layer, which can reduce the side reactions and gas generation, regulate Na + flux during cycling and promote rapid Na + migration for uniform dendrite-free Na deposition. As a result, the constructed Na symmetric cells achieve low overpotential and long cycle life of 5900, 1800, and 500 h at current densities of 3, 10, and 30 mA cm −2 , respectively. Furthermore, the full cells paired with the Na₃V₂(PO₄)₃ cathode demonstrate high specific capacity and excellent cycle stability, even at an ultra-high cathode loading of 39.3 mg cm −2 and a low N/P ratio (negative/positive electrode capacity ratio of 1.21).

Diffusion kinetic↗
DOE OSTI2024

Training models using forces computed by stochastic electronic structure methods

Abstract Quantum Monte Carlo (QMC) can play a very important role in generating accurate data needed for constructing potential energy surfaces. We argue that QMC has advantages in terms of a smaller systematic bias and an ability to cover phase space more completely. The stochastic noise can ease the training of the machine learning model. We discuss how stochastic errors affect the generation of effective models by analyzing the errors within a linear least squares procedure, finding that there is an advantage to having many relatively imprecise data points for constructing models. We then analyze the effect of noise on a model of many-body silicon finding that noise in some situations improves the resulting model. We then study the effect of QMC noise on two machine learning models of dense hydrogen used in a recent study of its phase diagram. The noise enables us to estimate the errors in the model. We conclude with a discussion of future research problems.

Ceperley, David M. (ORCID:0000000150826271)↗
DOE OSTI2025

Global Gyrokinetic Simulations of Isotope Effects under Ambipolar Electric Fields and Advances Toward Whole-Volume Modeling

We review global gyrokinetic simulation studies on plasma transport in the Large Helical Device using XGC-S. XGC-S is an extended version of X-point Gyrokinetic Code for stellarators and has been progressively verified throughout the code development process. Verification tests of neoclassical transport successfully demonstrate the generation of an ambipolar electric field due to ripple-trapped particles. We perform quasi-linear analyses of the ion temperature gradient mode under the influence of the ambipolar electric field. The results reveal that the ambipolar electric field and the heavy hydrogen component in mixed isotope plasmas can lead to the favorable isotope effect observed in recent deuterium experiments. We also present recent efforts in code development toward whole-volume simulations, including the helical divertor region. A mesh generation scheme based on field-line tracing and the construction of curved surfaces perpendicular to the magnetic field would be promising for global field calculations in the whole-volume simulations.

Basic Plasma Phenomena and Gas Discharges↗
DOE OSTI2023

Automated extraction of interfacial dislocations and disconnections from atomistic data

Here we introduce Interfacial Line Defect Analysis (ILDA), a method for identifying and extracting interfacial dislocations and disconnections with little-to-no input from the user on the nature of the interface. By simply providing the orientations and coherency strains for the crystals in a coherent reference state of the interface, ILDA provides exact Burgers vectors. Alternatively, these orientations and strains can be estimated using local atomic deformation gradients, making ILDA fully automated and providing estimated Burgers vectors. ILDA also determines the step height associated with each defect line segment, in case the associated defect is a disconnection. The heart of the method is the identification of atoms residing at co-incidence sites between the two crystals and the construction of a surface mesh connecting these sites that is used to compose Burgers circuits and insert defect line segments. We demonstrate the performance of ILDA in two test cases: a twist grain boundary and a phase boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Calibration of reactive burn and Jones-Wilkins-Lee parameters for simulations of a detonation-driven flow experiment with uncertainty quantification

Here, uncertainties in the explosive-specific parameters of the Jones-Wilkins-Lee (JWL) equation of state (EOS) are carefully considered in hydrodynamic simulations of an explosive experiment to minimize the error in the flow prediction. Experimental data of the leading shock position in the transverse direction over time serves as the prediction metric for quantifying simulation prediction error. The uncertainty quantification technique, global sensitivity analysis, is utilized to determine the JWL parameters to which the transverse shock propagation is most sensitive. A polynomial response surface (PRS) is constructed in the space of the most influential JWL parameters, and the point of minimum error between the experimental data and the PRS yields calibrated JWL parameters for the experimental flow. The simulation results following the parameter calibration show good agreement with the experimental data. It was found that two significant parameters, the heat release per unit mass of reactant Q and JWL model exponent R 1 are strongly related, which makes it difficult to identify accurate values.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effects of anisotropy and disorder on the superconducting properties of niobium

We report results for the superconducting transition temperature and anisotropic energy gap for pure niobium based on Eliashberg’s equations and electron and phonon band structures computed from density functional theory. The electronic band structure is used to construct the Fermi surface and calculate the Fermi velocity at each point on the Fermi surface. The phonon bands are in excellent agreement with inelastic neutron scattering data. The corresponding phonon density of states and electron–phonon coupling define the electron–phonon spectral function, α 2 F(p, p'; ω), and the corresponding electron–phonon pairing interaction, which is the basis for computing the superconducting properties. The electron–phonon spectral function is in good agreement with existing tunneling spectroscopy data except for the spectral weight of the longitudinal phonon peak at ℏω LO = 23 meV. We obtain an electron–phonon coupling constant of λ = 1.057, renormalized Coulomb interaction μ* = 0.218, and transition temperature T c = 9.33 K. The corresponding strong-coupling gap at T = 0 is modestly enhanced, Δ 0 = 1.55 meV, compared to the weak-coupling BCS value $Δ^{\text {wc}}_{0}$ = 1.78 k B T c = 1.43 meV. The superconducting gap function exhibits substantial anisotropy on the Fermi surface. We analyze the distribution of gap anisotropy and compute the suppression of the superconducting transition temperature using a self-consistent T-matrix theory for quasiparticle-impurity scattering to describe niobium doped with non-magnetic impurities. We compare these results with experimental results on niobium SRF cavities doped with nitrogen impurities.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Unveiling the Essential Parameters Driving Mineral Reactions during CO2 Storage in Carbonate Aquifers through Proxy Models

Numerical simulation is a commonly employed technique for studying carbon dioxide (CO2) storage processes in porous media, particularly saline aquifers. It enables the representation of diverse trapping mechanisms and the assessment of CO2 retention capacity within the subsurface. The intricate physicochemical phenomena involved necessitate the incorporation of multiphase flow, accurate depiction of fluid and rock properties, and their interactions. Among these factors, geochemical reaction rates and mechanisms are pivotal for successful CO2 trapping in carbonate reactive rocks. However, research on kinetic parameters and the influence of lithology on CO2 storage remains limited. This limitation is partly due to the challenges faced in laboratory experiments, where the time scale of the reactions and the lack of in situ conditions hinder accurate measurement of mineral reaction rates. This study employs proxy models constructed using response surfaces calibrated with simulation results to address uncertainties associated with geochemical reactions. Monte Carlo simulation is utilized to explore a broader range of parameters and identify influential factors affecting CO2 mineralization. The findings indicate that an open database containing kinetic parameters can support uncertainty assessment. Additionally, the proxy models effectively represent objective functions related to CO2 injectivity and mineralization, with calcite dissolution playing a predominant role. pH, calcite concentration, and CO2 injection rate significantly impact dolomite precipitation, while quartz content remains unaffected.

58 GEOSCIENCES↗
DOE OSTI2020

Effect of Many Modes on Self-Polarization and Photochemical Suppression in Cavities

The standard description of cavity-modified molecular reactions typically involves a single (resonant) mode, while in reality the quantum cavity supports a range of photon modes. In this work we demonstrate that as more photon modes are accounted for, physico-chemical phenomena can dramatically change, as illustrated by the cavity-induced suppression of the important and ubiquitous process of proton-coupled electron-transfer. Using a multi-trajectory Ehrenfest treatment for the photonmodes, we find that self-polarization effects become essential, and we introduce the concept of selfpolarization- modified Born-Oppenheimer surfaces as a new construct to analyze dynamics. As the number of cavity photon modes increases, the increasing deviation of these surfaces from the cavityfree Born-Oppenheimer surfaces, together with the interplay between photon emission and absorption inside the widening bands of these surfaces, leads to enhanced suppression. The present findings are general and will have implications for the description and control of cavity-driven physical processes of molecules, nanostructures and solids embedded in cavities.

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

Correlated metals and unconventional superconductivity in rhombohedral trilayer graphene: A renormalization group analysis

Here, motivated by recent experimental observations of correlated metallic phases and superconductivity in rhombohedral trilayer graphene (RTG), we perform an unbiased study of electronic ordering instabilities in hole-doped RTG. Specifically, we focus on electronic states energetically proximate to Van Hove singularities (VHSs), where a large density of states promotes different interaction-induced symmetry-breaking electronic orders. To resolve the Fermi surface near VHSs, we construct a fermionic hot-spot model and demonstrate that a perpendicular electric field can tune different nesting structures of the Fermi surface. Subsequently, we apply a renormalization group analysis to describe the low-energy phase diagrams of our model under both short-range repulsive interactions as well as realistic (long-range) Coulomb interactions. Our analysis shows instabilities towards either intervalley coherent metallic phases or superconducting phases. The dominant pairing channel depends crucially on the nature of Fermi surface nesting—repulsive Coulomb interaction favors spin-singlet d-wave pairing for relatively small displacement field and spin-singlet i-wave pairing for larger displacement field. We argue that the phase diagram of RTG can be well-understood by modeling the realistic Coulomb interaction as the sum of repulsive density-density interaction and ferromagnetic spin-triplet intervalley coherence (IVC) Hund's coupling, while phonon-mediated electronic interactions have a negligible effect on this system, in sharp contrast to twisted graphene multilayers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

First-principles study of the surface properties of uranium carbides

Uranium carbides have attracted renewed interest as advanced nuclear fuels for Generation IV reactors. As an important property required for gas bubble modeling in nuclear fuels, the surface energy of uranium carbides is scarce in literature. In this work, we study the surface properties of uranium carbides by first-principles density functional theory calculations. Surface orientations with maximum Miller index up to 3, 2 and 2 are investigated for UC, U 2 C 3 and α-UC 2 , respectively. By studying the effects of surface termination and chemical potential on surface energy, we identify the factors that determines the surface stability. From the calculated surface energies, the surface properties of uranium carbide single crystals are obtained from Wulff construction, including equilibrium morphology, dominant surface orientation and area weighted surface energy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evaluation of changes in the microbial community structure in the sediments of a constructed wetland over the years

This study presents the results of the long term (2007–2014) monitoring of the microbial community structure in the surface sediments of the H-02 constructed wetland system, which was built on the Savannah River Site in Aiken, SC, USA, to treat the waste water generated at the Tritium facility. Microbial community structure provides valuable information about the functioning of constructed wetlands and helps understand the biogeochemical cycling of nutrients and contaminants. Phospholipids fatty acid (PLFA) analysis and qPCR were used to identify major bacterial phyla in the sediments. The physiochemical properties of the sediments were also used to deduce potential effects on the microbial community structure over the years. Sulfate-reducing bacteria (SRB) were the most dominant bacterial groups, and their prevalence was progressively increasing throughout the years most likely on the account of methane producers. Concentrations of trace metals (copper and zinc) were negatively associated with methane producers and oxidizer while positively correlated with SRB. Overall, the H-02 wetland system was efficient in immobilizing copper and zinc through the anaerobic respiration of sulfate by SRB and minimizing methane emission through the progressive elimination of methane producers by SRB and Geobacter. Furthermore, the aim of this study was to monitor the changes in the microbial community structure in the surface sediments of a constructed wetland during the first 7 years of operation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation and mitigation of trace 210Pb contamination on copper surfaces

Clean materials are required to construct and operate many low-background physics experiments. High-purity copper has found broad use because of its physical properties and availability. In this paper, we describe methods to assay and mitigate Pb-210 contamination on copper surfaces, such as from exposure to environmental radon or coming from bulk impurities. We evaluated the efficacy of wet etching on commercial samples and observed that Po-210 contamination from the copper bulk does not readily pass into solution. During the etch, the polonium appears to trap at the copper-etchant boundary, such that it is effectively concentrated at the copper surface. We observed a different behavior for Pb-210; high-sensitivity measurements of the alpha emissivity versus time indicate the lowest level of Pb-210 contamination ever reported for a commercial copper surface: 0 +/- 12 nBq/cm2 (1-sigma). Additionally, we have demonstrated the effectiveness of mitigating trace Pb-210 and Po-210 surface backgrounds using custom, high-purity electroplating techniques. These approaches were evaluated utilizing assays performed with an XIA UltraLo-1800 alpha spectrometer.

radon, copper, copper cleaning, dark matter, Pb-21↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗