Engineering Papers⌕ Search

SEARCH · Engineering Papers

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Surface lattice engineering for fine-tuned spatial configuration of nanocrystals

Hybrid nanocrystals combining different properties together are important multifunctional materials that underpin further development in catalysis, energy storage, et al., and they are often constructed using heterogeneous seeded growth. Their spatial configuration (shape, composition, and dimension) is primarily determined by the heterogeneous deposition process which depends on the lattice mismatch between deposited material and seed. Precise control of nanocrystals spatial configuration is crucial to applications, but suffers from the limited tunability of lattice mismatch. Here, we demonstrate that surface lattice engineering can be used to break this bottleneck. Surface lattices of various Au nanocrystal seeds are fine-tuned using this strategy regardless of their shape, size, and crystalline structure, creating adjustable lattice mismatch for subsequent growth of other metals; hence, diverse hybrid nanocrystals with fine-tuned spatial configuration can be synthesized. This study may pave a general approach for rationally designing and constructing target nanocrystals including metal, semiconductor, and oxide.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

From biowaste to BioPave: Biological pathways for sequestration of anthropogenic CO 2 and enhancing durability of roadway infrastructures

Biomass-derived bio-oils are emerging as sustainable, low-carbon alternatives for construction materials, particularly in innovative pavement applications, 'BioPave'. Here, this study evaluates bio-oils from various sources, including algae and wastewater biomass, revealing variations in carbon, nitrogen, and sulfur contents, along with viscosity. We focused on their application in outdoor construction, assessing their resistance to thermal and solar radiation, and moisture. The study also examines their interaction with siliceous surfaces and their influence on asphalt adhesion in BioPave systems under moisture conditions. Laboratory experiments and computational modeling demonstrated molecular composition significantly influenced bio-oils' responses to thermal and UV exposure. Bio-oils rich in polar groups showed hardening upon thermal treatment, while those with higher concentrations of saturated aliphatics remained more stable. Furthermore, our findings highlight the significance of dosage control in maximizing beneficial effects of bio-oils in intermolecular interactions at bitumen-aggregate interface in BioPave applications. These findings offer insights into the potential of bio-oils in sustainable construction and the need for dosage control to optimize pavement performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Benzene Ring Knitting Achieved by Ambient-Temperature Dehalogenation via Mechanochemical Ullmann-Type Reductive Coupling

The current approaches capable of affording conjugated porous networks (CPNs) still rely on solution-based coupling reactions promoted by noble metal complexes or Lewis acids, on-surface polymerization conducted in ultrahigh-vacuum environment at very high temperatures (>200 °C), or mechanochemical Scholl-type reactions limited to electron-rich substrates. To develop simple and scalable approaches capable of making CPNs under neat and ambient conditions, herein, a novel and complementary method to the current oxidative Scholl coupling processes is demonstrated to afford CPNs via direct aromatic ring knitting promoted by mechanochemical Ullmann-type reactions. The key to this strategy lies in the dehalogenation of aromatic halides in the presence of Mg involving the formation of Grignard reagent intermediates. Products (Ph-CPN-1) obtained via direct C-C bond formation between 1,2,4,5-tetrabromobenzene (TBB) monomer feature high surface areas together with mesoporous architecture. The versatility of this approach is confirmed by the successful construction of various CPNs via knitting of the corresponding aromatic rings (e.g., pyrene and triphenylene), and even highly crystalline graphite product was obtained. The CPNs exhibit good electrochemical performance as the anode material in lithium-ion batteries (LIBs). Overall, this approach expands the frontiers of CPN synthesis and provides new opportunities to their scalable applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

AdS 6 /CFT 5 with O7-planes

Type IIB AdS6 solutions with orientifold 7-planes are constructed. The geometry is a warped product of AdS 6 and S 2 over a Riemann surface Σ and the O7-planes correspond to a particular type of puncture on Σ. The solutions are identified as near-horizon limits of (p,q) 5-brane webs with O7-planes. The dual 5d SCFTs have relevant deformations to linear quiver gauge theories which have SO(•) or USp(•) nodes or SU(•) nodes with hypermultiplets in symmetric or antisymmetric representations, in addition to SU(•) nodes with fundamental hypermultiplets. The S 5 free energies are obtained holographically and matched to field theory computations using supersymmetric localization to support the proposed dualities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry

Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land subsidence, and flood risk management. The high cost and complex logistics of direct bathymetry surveys, i.e, depth imaging, have encouraged the use of indirect measurements such as surface flow velocities. However, estimating high-resolution bathymetry from indirect measurements is an inverse problem that can be computationally challenging. Here, we propose a reduced-order model (ROM) based approach that utilizes a variational autoencoder (VAE), a type of deep neural network with a narrow layer in the middle, to compress bathymetry and flow velocity information and accelerate bathymetry inverse problems from flow velocity measurements. In our application, the shallow-water equations (SWE) with appropriate boundary conditions (BCs), e.g., the discharge and/or the free surface elevation, constitute the forward problem, to predict flow velocity. Then, ROMs of the SWEs are constructed on a nonlinear manifold of low dimensionality through a variational encoder and the bathymetry inversion problem is derived on the low-dimensional latent space in a Hierarchical Bayesian setting. Further, the reformulation allows variational inference with a small number (e.g., $\mathscr{O}$ (100) of ROM runs and efficient uncertainty quantification. We have tested our inversion approach on a one-mile reach of the Savannah River, GA, USA. Once the neural network is trained (offline stage), the proposed technique can perform the inversion operation orders of magnitude faster than traditional inversion methods that are commonly based on linear projections, such as principal component analysis (PCA), or the principal component geostatistical approach (PCGA). Furthermore, tests show that the algorithm can estimate the bathymetry with good accuracy even with sparse flow velocity measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A hierarchical stochastic modeling approach for representing point bar geometries and petrophysical property variations

The flow of fluids in point bars is affected by the existence of heterogeneities like shale drapes that are found on the surfaces of inclined heterolithic stratifications. In fact, these shale drapes can act as fluid flow baffles; therefore, developing a framework for modeling point bars and their associated heterogeneities is vital. In this study, a stochastic process-based modeling approach is presented for capturing the main point bar heterogeneities: accretion surfaces (i.e., the aerial heterogeneity) and inclined heterolithic stratifications (i.e., the vertical heterogeneity). The former was modeled using a sine-generation function and the latter, with a sigmoidal function after which they were combined into a 3D point bar model. To ensure proper modeling of petrophysical properties, we developed a more representative gridding scheme which generates curvilinear grids representative of the point bar geometry. This grid was then transformed into a rectilinear grid to allow for geostatistical simulation after which all petrophysical properties were mapped back into the original curvilinear grid. An essential element of this modeling approach is the stochastic representation of shale drapes at the interface between successive accretion surfaces. The workflow was tested using a real field dataset for the Cranfield field, Mississippi. The constructed model was then subjected to a flow simulation study mimicking a CO 2 storage scenario. Various sensitivities were simulated to evaluate the effect of heterogeneities on CO 2 flow within the point-bar. Results demonstrate the importance of representing point-bar related heterogeneity and the spatial distribution of shale drapes on CO 2 plume migration and storage.

58 GEOSCIENCES↗
DOE OSTI2021

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Project 57 Air Monitoring Report: January 1 through September 30, 2020, with a Review of the Period of Record Radionuclide Analyses

The DOE Environmental Management Nevada Program (EM NV) identified the Project 57 contaminated area as Corrective Action Unit (CAU) 415, Project 57 No. 1 Plutonium Dispersion Site, which consisted of one Corrective Action Site (CAS): NAFR-23- 02, Pu Contaminated Soil (U.S. DOE, 2014). The CAS included several Project 57 operational facilities in addition to the plutonium-contaminated soil. With approval of the State of Nevada Division of Environmental Protection, the DOE closed the Project 57 surface soil contamination site in October 2020. Closure was accomplished by installing a clean soil cap constructed over ground zero and the surrounding areas of the CA that may be entrained with wind-transported soil particles. After completion of the ground zero cap in October 2020, DRI discontinued monitoring of meteorological and associated environmental conditions at the Project 57 site as directed by DOE EM NV. Navarro dismantled air monitoring stations P57-3 and P57-4 and removed the equipment on October 20, 2020. This report presents the meteorological and dust observations and radiological analyses accomplished during the approximately 10 months when the air monitoring data collection equipment was operational during CY2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Multiplexed Hybrid Velocimeter

Optical velocimetry systems play a crucial role in studying the dynamic behavior of materials under extreme conditions. Two prominent systems used at the Nevada National Security Site are the velocity interferometer system for any reflector(VISAR) and the photon Doppler velocimeter (PDV) system. Their ability to accurately measure surface motion ranging from 0 to > 20km=s without interacting with material flow enables experimenters to construct thermodynamic equations of state for materials of interest. A number of modifications to VISAR and PDV have taken place over the past five decades, leading to improved performance, increased recording capacity, and a reduction in operational burden. Prior efforts to develop a hybrid velocimeter combining the advantages of both PDV and VISAR into a single diagnostic did not take into account progress in PDV technology or new optical components that had not been developed. This thesis describes the design and implementation of a multiplexed hybrid velocimeter (MHV) based on time-multiplexing techniques, an optical hybrid, and polarization-maintaining fiber and components. Data from experiments, compared with current velocity systems, serve to demonstrate the hybrid's performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

A systematic approach to generating accurate neural network potentials: the case of carbon

Abstract Availability of affordable and widely applicable interatomic potentials is the key needed to unlock the riches of modern materials modeling. Artificial neural network-based approaches for generating potentials are promising; however, neural network training requires large amounts of data, sampled adequately from an often unknown potential energy surface. Here we propose a self-consistent approach that is based on crystal structure prediction formalism and is guided by unsupervised data analysis, to construct an accurate, inexpensive, and transferable artificial neural network potential. Using this approach, we construct an interatomic potential for carbon and demonstrate its ability to reproduce first principles results on elastic and vibrational properties for diamond, graphite, and graphene, as well as energy ordering and structural properties of a wide range of crystalline and amorphous phases.

Chemistry↗
DOE OSTI2023

First-Principles-Based Machine Learning Models for Phase Behavior and Transport Properties of CO 2

In this work, we construct distinct first-principles-based machine-learning models of CO 2 , reproducing the potential energy surface of the PBE-D3, BLYP-D3, SCAN and SCAN-rvv10 approximations of density functional theory. Here we employ the Deep Potential methodology to develop the models and consequently achieve a significant computational efficiency over ab initio molecular dynamics (AIMD) that allows for larger system sizes and time scales to be explored. Although our models are trained only with liquid phase configurations, they are able to simulate a stable interfacial system and predict vapor-liquid equilibrium properties, in good agreement with results from the literature. Because of the computational efficiency of the models, we are also able to obtain transport properties, such as viscosity and diffusion coefficients. We find that the SCAN-based model presents a temperature shift in the position of the critical point, while the SCAN-rvv10-based model shows improvement but still exhibits a temperature shift that remains approximately constant for all properties investigated in this work. We find that the BLYP-D3-based model generally performs better for liquid phase and vapor-liquid equilibrium properties, but the PBE-D3-based model is better suited for predicting transport properties.

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

Moisture-induced autonomous surface potential oscillations for energy harvesting

A variety of autonomous oscillations in nature such as heartbeats and some biochemical reactions have been widely studied and utilized for applications in the fields of bioscience and engineering. Here, we report a unique phenomenon of moisture-induced electrical potential oscillations on polymers, poly([2-(methacryloyloxy)ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide-co-acrylic acid), during the diffusion of water molecules. Chemical reactions are modeled by kinetic simulations while system dynamic equations and the stability matrix are analyzed to show the chaotic nature of the system which oscillates with hidden attractors to induce the autonomous surface potential oscillation. Using moisture in the ambient environment as the activation source, this self-excited chemoelectrical reaction could have broad influences and usages in surface-reaction based devices and systems. As a proof-of-concept demonstration, an energy harvester is constructed and achieved the continuous energy production for more than 15,000 seconds with an energy density of 16.8 mJ/cm 2 . A 2-Volts output voltage has been produced to power a liquid crystal display toward practical applications with five energy harvesters connected in series.

42 ENGINEERING↗
DOE OSTI2024

Role of Cell Wall Polysaccharides in Water Distribution During Seed Imbibition of Hymenaea courbaril L.

Seed water imbibition is critical to seedling establishment in tropical forests. The seeds of the neotropical tree Hymenaea courbaril have no oil reserves and have been used as a model to study storage cell wall polysaccharide (xyloglucan - XyG) mobilization.We studied pathways of water imbibition in Hymenaea seeds. To understand seed features, we performed carbohydrate analysis and scanning electron microscopy. We found that the seed coat comprises a palisade of lignified cells, below which are several cell layers with cell walls rich in pectin. The cotyledons are composed mainly of storage XyG. From a single point of scarification on the seed surface, we followed water imbibition pathways in the entire seed using fluorescent dye and NMRi spectroscopy. We constructed composites of cellulose with Hymenaea pectin or XyG. In vitro experiments demonstrated cell wall polymer capacity to imbibe water, with XyG imbibition much slower than the pectin-rich layer of the seed coat.We found that water rapidly crosses the lignified layer and reaches the pectin-rich palisade layer so that water rapidly surrounds the whole seed. Water travels very slowly in cotyledons (most of the seed mass) because it is imbibed in the XyG-rich storage walls. However, there are channels among the cotyledon cells through which water travels rapidly, so the primary cell walls containing pectins will retain water around each storage cell.The different seed tissue dynamic interactions between water and wall polysaccharides (pectins and XyG) are essential to determining water distribution and preparing the seed for germination.

arabinoxylan↗
DOE OSTI2024

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Engineering bimetallic interfaces and revealing the mechanism for carbon dioxide electroreduction to C 3+ liquid chemicals

Reduction reaction of CO 2 (CO 2 RR) to liquid C 3+ chemicals is a net-zero-carbon process and can increase local resiliency to power outages and fuel consumption. The mechanism and the catalyst design rules of CO 2 RR-to-C 3+ are unknown. Engineering bimetallic interface (e.g., Pd/Au) to tune the intermediate adsorption is promising for promoting C 3+ formation. Our density functional theory (DFT) calculations find that *CH 2 could be the key intermediate and C 1 -CH 2 coupling could be the rate-limiting step to generate C 3+ . High CO surface coverages can promote the bimetallic interfacial sites, lower the energetics of the C 1 -CH 2 coupling step, and enhance the C 3+ formation. We further construct a volcano plot of C 1 -CH 2 kinetics as a function of the binding strength of key intermediate *CH 2 via engineering the d-band center of the interfacial site. Our findings could guide the rational design of bimetallic interfaces and their near-surface microenvironment for enhancing CO 2 RR-to-C 3+ .

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Near surface structure of ultrathin epitaxial Ru films on graphene/amorphous SiO 2 revealed by azimuthal RHEED

Ru has been considered as an alternative metallic candidate for future local interconnects. The 2D reciprocal space map constructed from the azimuthal reflection high-energy electron diffraction patterns reveals that ultrathin Ru(0001) is epitaxially grown on transferred graphene on amorphous SiO 2 through quasi-van der Waals interaction. The in-plane and out-of-plane lattice constants are measured from streaks’ separation and intensity modulations along streaks, respectively. Weak and broad rings indicate that a low density of nanoscale polycrystals exist on the surface. In this work, The intensities of 00 and non-00 diffraction spots vs. azimuthal angles in the 2D map show a few degrees out-of-plane and in-plane angular misorientations among grains, respectively. As the film thickness decreases these angular misorientations increase. Transmission electron microscopy carried out in this study also provides precise values of lattice constant and sub-grain sizes in the films. These findings show that ultrathin Ru film is epitaxial but not exactly single crystalline.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Asymptotic solutions and convergence studies of the resistive inner region equations

A recent publication presents a detailed prescription for constructing global eigenfunctions and complex growth rates for resistive instabilities in axisymmetric toroidal systems, using the method of matched asymptotic expansions. At each singular surface in the plasma, the small-x asymptotic solutions of the ideal MHD outer-region equations are matched to the large-x asymptotic solutions of the resistive inner-region equations, with x being the distance from the singular surface. The success of this method depends upon accurate asymptotic solutions of the resistive inner region equations. Extensive studies have shown that there are not only regimes of excellent agreement with straight-through methods, without asymptotic matching, but also regimes of strong disagreement. As such, in an effort to find the cause of this discrepancy, we present here a different method of constructing asymptotic solutions of the inner region equations and we study the convergence properties of the new and old solutions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗