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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Suppression of surface charge accumulation on Al{sub 2}O{sub 3}-filled epoxy resin insulator under dc voltage by direct fluorination

Surface charge accumulation on insulators under high dc voltage is a major factor that may lead to the reduction of insulation levels in gas insulated devices. In this paper, disc insulators made of Al{sub 2}O{sub 3}-filled epoxy resin were surface fluorinated using a F{sub 2}/N{sub 2} mixture (12.5% F{sub 2}) at 50 °C and 0.1 MPa for different durations of 15 min, 30 min and 60 min. A dc voltage was applied to the insulator for 30 min and the charge density on its surface was measured by an electrostatic probe. The results revealed significant lower surface charge densities on the fluorinated insulators in comparison with the original one. Surface conductivity measurements indicated a higher surface conductivity by over three orders of magnitude after fluorination, which would allow the charges to transfer along the surface and thus may suppress their accumulation. Further, attenuated total reflection infrared analysis and surface morphology observations of the samples revealed that the introduction of fluoride groups altered the surface physicochemical properties. These structure changes, especially the physical defects reduced the depth of charge traps in the surface layer, which was verified by the measurement of energy distributions of the electron and hole traps based on the isothermal current theory. The results in this paper demonstrate that fluorination can be a promising and effective method to suppress surface charge accumulation on epoxy insulators in gas insulated devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Interactions Between Clouds and Wind-Driven Surface Heat Exchanges over Land

Earth system model experiments show that increasing horizontal resolution fundamentally alters the simulated soil-moisture-precipitation feedback. Kilometer-scale simulations often produce weaker or even negative feedback compared to coarse-resolution models. A key difference of kilometer-scale models is that they resolve mesoscale secondary circulations, including boundary layer horizontal rolls and cellular structures, in addition to cold pools and downdrafts associated with convective precipitation. However, because the relevant processes occur on yet-smaller scales, these circulations are often poorly resolved. This project demonstrated that boundary layer secondary circulations significantly affect surface heat exchanges and wind gusts, and that current model parameterizations can misrepresent these processes at kilometer-scale resolution. Using DOE Atmospheric Radiation Measurement (ARM) observations and targeted experiments with the DOE Energy Exascale Earth System Model (E3SM), we identified physically unrealistic wind gust and surface flux responses to secondary circulations, diagnosed a systematic overestimation of wind shear in convective cold pools, and uncovered a multivariate relationship between land surface fluxes and the scales of updrafts that form shallow cumulus clouds. These findings provide observation-based recommendations for improving parameterizations of surface fluxes and wind gusts in high-resolution Earth system models, thereby reducing uncertainty in convective storm prediction and land-atmosphere feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A small-volume, high-throughput approach for surface tension and viscosity measurements of liquid fuels

An ongoing effort looking at bioblendstocks to function as drop-in replacements or blending components for gasoline has identified a large number of candidate fuels. This work documents an approach for rapid screening of candidate fuels using relatively small sample sizes ($\mathcal{O}(\mu\,{\rm l})$) that targets two key physical properties of liquid fuels—surface tension and viscosity. The approach utilizes shape oscillation dynamics of single droplets generated by a piezo-electric device and their decay over time. Strobed imaging of the oscillation process is used along with image processing, edge detection, and data analysis to capture the decay of the oscillation over time. The time constant of the decay process along with oscillation frequency are then used to estimate viscosity and surface tension using a theory for small amplitude droplet oscillations. Measurements are obtained for primary reference fuels (isooctane and n-heptane) as well as candidate fuels from four bio-derived functional groups of interest. Measurement results for surface tension and viscosity are correlated with literature data as well as measurements from standard reference instruments. The measurement results show that the droplet oscillation based approach is capable of reproducing surface tension and viscosity values for the tested fuels within deviations of 7% and 13% respectively from literature data. Results are obtained using an average of 5 µl per fuel within about 20 s, thus demonstrating a small-volume, high-throughput approach that can be used for screening of candidate bioblendstock fuels.

09 BIOMASS FUELS↗
DOE OSTI2025

Measuring Vibronic Coupling and Ultrafast Charge Delocalization on Nanocrystal Surfaces Using Ligand-Specific Vibrational Probes

The primary goal of this proposal was to measure and quantify how vibronic ligand-exciton interactions at the inorganic-organic interface of semiconductor nanocrystals (NCs) govern femtosecond non-radiative relaxation and charge delocalization mechanisms as a function of nanocrystal and ligand structures – including NC size, shape, and ligand identity. Molecular-scale chemical and physical properties and interactions of surface ligands dictate nanocrystal exciton dynamics on the femto-to-microsecond timescales. Improvements in synthesis, experimental, and theoretical characterizations have enhanced our understanding of NC photophysics. However, quantitative descriptions of complex ligand-exciton interactions at the NC surface have remained elusive, which limits elucidation of relaxation mechanisms that determine overall carrier transfer dynamics at the exciton-ligand interface. Thus, the central motivation for this proposal was to fill a significant knowledge gap for judicious selection of ligand-functionalized nanocrystals for targeted isolation and capture of charge carriers to drive selective organic photocatalytic transformations in NC photocatalysts and NC-assembled photonic materials. Our unique two-pronged experimental approach combining nanocrystal synthesis and ligand-specific nonlinear spectroscopy has resulted in (i) four peer-reviewed publications; (ii) 12+ invited and contributed posters and talks at national and international scientific meetings and seminars, (iii) two completed PhD theses, (iv) training of two postdoctoral researchers, three PhD students, and two undergraduate students, and (v) two manuscripts under preparation.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Response of nickel surface to pulsed fusion plasma radiations

Nickel based alloys are being projected as suitable materials for some components of the next generation fusion reactor because of compatible thermal, electrical and mechanical properties. Pure nickel material is tested here for possibility of similar application purpose. Nickel samples (> 99.5 % purity) are exposed here to plasma radiations produced due to D-D fusion reaction inside an 11.5 kJ plasma focus device. The changes in the physical properties of the nickel surface at microscopic level which in turn change the mechanical properties are analyzed using scanning electron microscope, optical microscope, glancing incident X-ray diffractometer and Vicker's hardness gauge. The results are reported here.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Multiresolution molecular mechanics: Surface effects in nanoscale materials

Surface effects have been observed to contribute significantly to the mechanical response of nanoscale structures. The newly proposed energy-based coarse-grained atomistic method Multiresolution Molecular Mechanics (MMM) (Yang, To (2015), ) is applied to capture surface effect for nanosized structures by designing a surface summation rule SR{sup S} within the framework of MMM. Combined with previously proposed bulk summation rule SR{sup B}, the MMM summation rule SR{sup MMM} is completed. SR{sup S} and SR{sup B} are consistently formed within SR{sup MMM} for general finite element shape functions. Analogous to quadrature rules in finite element method (FEM), the key idea to the good performance of SR{sup MMM} lies in that the order or distribution of energy for coarse-grained atomistic model is mathematically derived such that the number, position and weight of quadrature-type (sampling) atoms can be determined. Mathematically, the derived energy distribution of surface area is different from that of bulk region. Physically, the difference is due to the fact that surface atoms lack neighboring bonding. As such, SR{sup S} and SR{sup B} are employed for surface and bulk domains, respectively. Two- and three-dimensional numerical examples using the respective 4-node bilinear quadrilateral, 8-node quadratic quadrilateral and 8-node hexahedral meshes are employed to verify and validate the proposed approach. It is shown that MMM with SR{sup MMM} accurately captures corner, edge and surface effects with less 0.3% degrees of freedom of the original atomistic system, compared against full atomistic simulation. The effectiveness of SR{sup MMM} with respect to high order element is also demonstrated by employing the 8-node quadratic quadrilateral to solve a beam bending problem considering surface effect. In addition, the introduced sampling error with SR{sup MMM} that is analogous to numerical integration error with quadrature rule in FEM is very small. - Highlights: • Surface effect captured by Multiresolution Molecular Mechanics (MMM) is presented. • A novel surface summation rule within the framework of MMM is proposed. • Surface, corner and edges effects are accuterly captured in two and three dimension. • MMM with less 0.3% degrees of freedom of atomistics reproduces atomistic results.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

The carbon challenge: Design, synthesis, and chemisorption behavior of solid sorbents in direct air capture of carbon dioxide

Direct air capture (DAC) of CO 2 is a promising solution for reducing the carbon footprint through "negative emission" technology. However, the low CO 2 concentration (~400 ppm) and the dynamic nature of DAC processes present challenges in designing effective sorbent systems. Recent advancements in material design and structural engineering have led to the development of high-performance solid sorbents, offering a more stable, safe, and energy-efficient alternative to traditional liquid CO 2 capture methods. This review highlights progress in solid sorbent-based DAC, focusing on amine-modified materials, hydrogen-bonded frameworks, and ionic liquid-engineered scaffolds. The discussion covers design principles, synthesis methodologies, and their impact on CO 2 chemisorption, comparing the advantages and limitations of each approach. Characterization techniques, especially operando methods and computational tools, are reviewed to understand sorbent behavior during CO 2 integration and release. The reaction pathways and interaction mechanisms of these sorbents with CO 2 are analyzed to guide future design. Additionally, the CO 2 chemisorption behaviors, including capacity, sorption kinetics, recyclability, and durability in the presence of gaseous impurities and under humid conditions will be evaluated and compared. Further, the review offers unique insights into the physical properties, chemical structures, and surface engineering effects of these sorbents, based on comprehensive characterization and evaluation techniques.

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

Passive Antifrosting Surfaces Using Microscopic Ice Patterns

Despite exceptional recent advances in tailoring the wettability of surfaces, to date, no engineered surface can passively suppress the in-plane growth of frost that invariably occurs in humid, subfreezing environments. Here, we show that up to 90% of a surface can exhibit passive antifrosting by using chemical or physical wettability patterns to template “ice stripes” across the surface. As ice exhibits a depressed vapor pressure relative to liquid water, these sacrificial ice stripes siphon the supersaturated water vapor to keep the intermediate surface areas dry from dew and frost. Further, we show that when these sacrificial ice stripes are elevated atop microfins, they diffusively coarsen in a suspended state above the surface. As a result, the suspended state of the coarsening ice results in a diffusive growth rate an order of magnitude slower than frost coarsening directly on a solid substrate and should also minimize its adhesive strength to the surface.

36 MATERIALS SCIENCE↗
DOE OSTI2019

LiOH corrosion growth and thermal stability investigated by diffuse reflectance infrared Fourier Transform (DRIFT) spectroscopy

In this period, we have measured the kinetics of LiOH corrosion growth on LiH substrate at 35 ppm of moisture for over 2 months. The serial DRIFT spectra are being analyzed to build the growth kinetics for LiOH interfacial states, surface states, and bulk states. Physical chemistry insight is being employed to describe the observed parabolic-linear growth of the corrosion layer grown on LiH samples that have been previously vacuum baked then re-exposed to low moisture over a long time. The thermal stabilities of LiOH interfacial states, surface states, and bulk states are also being quantified by measuring the reduction in LiOH DRIFT signals as a function of vacuum level and temperature, and will be needed to add an on/off switch to the current outgassing modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Learning for Improving Surface-Layer-Flux Estimates

Abstract Flows in the atmospheric boundary layer are turbulent, characterized by a large Reynolds number, the existence of a roughness sublayer and the absence of a well-defined viscous layer. Exchanges with the surface are therefore dominated by turbulent fluxes. In numerical models for atmospheric flows, turbulent fluxes must be specified at the surface; however, surface fluxes are not known a priori and therefore must be parametrized. Atmospheric flow models, including global circulation, limited area models, and large-eddy simulation, employ Monin–Obukhov similarity theory (MOST) to parametrize surface fluxes. The MOST approach is a semi-empirical formulation that accounts for atmospheric stability effects through universal stability functions. The stability functions are determined based on limited observations using simple regression as a function of the non-dimensional stability parameter representing a ratio of distance from the surface and the Obukhov length scale (Obukhov in Trudy Inst Theor Geofiz AN SSSR 1:95–115, 1946), $$z/L$$ z / L . However, simple regression cannot capture the relationship between governing parameters and surface-layer structure under the wide range of conditions to which MOST is commonly applied. We therefore develop, train, and test two machine-learning models, an artificial neural network (ANN) and random forest (RF), to estimate surface fluxes of momentum, sensible heat, and moisture based on surface and near-surface observations. To train and test these machine-learning algorithms, we use several years of observations from the Cabauw mast in the Netherlands and from the National Oceanic and Atmospheric Administration’s Field Research Division tower in Idaho. The RF and ANN models outperform MOST. Even when we train the RF and ANN on one set of data and apply them to the second set, they provide more accurate estimates of all of the fluxes compared to MOST. Estimates of sensible heat and moisture fluxes are significantly improved, and model interpretability techniques highlight the logical physical relationships we expect in surface-layer processes.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Geometry and dynamics of passive scalar structures in compressible turbulent mixing

We present a structure-based numerical analysis of passive scalar mixing in decaying homogeneous isotropic turbulence (DHIT) and shock-turbulence interaction canonical configurations. The analysis focuses on the temporal evolution of ensembles of passive scalar structures, initialized as spheres of different sizes relative to the Taylor microscale. An algorithm is introduced to track the evolution of each individual structure and the interactions with other structures in the ensemble, relating changes in the surface geometry and the underlying physical processes (turbulent transport, scalar dissipation, and shock compression). The tracking algorithm is applied to datasets from shock-capturing direct numerical simulations of DHIT, with Taylor microscale Reynolds number Re λ =40 and turbulence Mach number M t =0.2 ⁠, and STI cases in which the turbulence is processed by a shock wave at Mach numbers M = 1.5 and 3.0. Temporal surface convolution increases for initially larger structures, resulting in a higher probability of locally hyperbolic geometries where breakup into smaller structures occurs. Shock-induced deformation of the structures amplifies breakup processes, enhancing mixing, particularly for larger structures. Mixing enhancement by the shock is manifested as an amplification of the surface-averaged scalar gradient, which increases for initially larger structures. The alignment between the scalar gradient and the most extensional strain-rate eigendirection on the scalar isosurfaces also increases across the shock. Larger magnitudes of the scalar gradient and its alignment with the most compressive strain-rate eigendirection correlate with flatter surface regions. Shock-induced structure compression increases the area coverage of flat regions, where the amplification of scalar gradient is localized.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

In situ measurement of fixed charge evolution at silicon surfaces during atomic layer deposition

Interfacial fixed charge or interfacial dipoles are present at many semiconductor-dielectric interfaces and have important effects upon device behavior, yet the chemical origins of these electrostatic phenomena are not fully understood. We report the measurement of changes in Si channel conduction in situ during atomic layer deposition (ALD) of aluminum oxide using trimethylaluminum and water to probe changes in surface electrostatics. Current-voltage data were acquired continually before, during, and after the self-limiting chemical reactions that result in film growth. Our measurements indicated an increase in conductance on p-type samples with p{sup +} ohmic contacts and a decrease in conductance on analogous n-type samples. Further, p{sup +} contacted samples with n-type channels exhibited an increase in measured current and n{sup +} contacted p-type samples exhibited a decrease in current under applied voltage. Device physics simulations, where a fixed surface charge was parameterized on the channel surface, connect the surface charge to changes in current-voltage behavior. The simulations and analogous analytical relationships for near-surface conductance were used to explain the experimental results. Specifically, the changes in current-voltage behavior can be attributed to the formation of a fixed negative charge or the modification of a surface dipole upon chemisorption of trimethylaluminum. These measurements allow for the observation of fixed charge or dipole formation during ALD and provide further insight into the electrostatic behavior at semiconductor-dielectric interfaces during film nucleation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

SNF Interim Storage Canister Corrosion and Surface Environment Investigations (FY2020 Status Report)

This progress report describes work performed during FY20 at Sandia National Laboratories (SNL) to assess the localized corrosion performance of container/cask materials used in the interim storage of spent nuclear fuel (SNF). Of particular concern is stress corrosion cracking (SCC), by which a through-wall crack could potentially form in a canister outer wall over time intervals that are shorter than possible dry storage times. Work in FY20 further defined our understanding of the potential chemical and physical environment present on canister surfaces, evaluated the relationship between the environment and the resultant corrosion that occurs, and initiated crack growth rate testing under relevant environmental conditions. In FY20, work to define dry storage canister surface environments included several tasks. First, collection of dust deposition specimens from independent spent fuel storage installation (ISFSI) site locations helped to establish a more complete understanding of the potential chemical environment formed on the canister. Second, the predicted evolution of canister surface relative humidity RH) values was estimated using ISFSI site weather data and the horizontal canister thermal model used by the SNL probabilistic SCC model. These calculations determined that for typical ISFSI weather conditions, seasalt deliquescence to produce MgCl2-rich brines could occur in less than 20 years at the coolest locations on the canister surface, and, even after nearly 300 years, conditions for NaCl deliquescence (75% RH) are not reached. This work illustrates the importance of understanding the stability of MgCl2-rich brines on the heated canister surface, and the potential impact of brine composition on corrosion processes, including pitting and stress corrosion cracking. In an additional study, the description of the canister surface environment was refined in order to define more realistic corrosion testing environments including diurnal cycles, soluble salt chemistries, and inert mineral particles. The potential impacts of these phenomena on canister corrosion are being evaluated experimentally. Finally, work over the past few years to evaluate the stability of magnesium chloride brines continued in FY20. MgCl2 degassing experiments were carried out, confirming that MgCl2 brines slowly degas HCl on heated surfaces, converting to less deliquescent magnesium hydroxychloride phases and potentially leading to brine dryout.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Non-adiabatic ab initio molecular dynamics of supersonic beam epitaxy of silicon carbide at room temperature

In this work, we investigate the processes leading to the room-temperature growth of silicon carbide thin films by supersonic molecular beam epitaxy technique. We present experimental data showing that the collision of fullerene on a silicon surface induces strong chemical-physical perturbations and, for sufficient velocity, disruption of molecular bonds, and cage breaking with formation of nanostructures with different stoichiometric character. We show that in these out-of-equilibrium conditions, it is necessary to go beyond the standard implementations of density functional theory, as ab initio methods based on the Born-Oppenheimer approximation fail to capture the excited-state dynamics. In particular, we analyse the Si-C{sub 60} collision within the non-adiabatic nuclear dynamics framework, where stochastic hops occur between adiabatic surfaces calculated with time-dependent density functional theory. This theoretical description of the C{sub 60} impact on the Si surface is in good agreement with our experimental findings.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Quantifying the role of land-atmosphere feedbacks in mediating near-surface temperature persistence

Weather persistence from month to month is an important source of predictability on the intraseasonal time-scale. Persistence in the lower troposphere is thought to be mainly due to dynamical feedbacks between the atmosphere and physical variables at or below the surface. Many recent improvements of dynamical seasonal forecasting models have been due to better initialisations and representations of the lower boundary. While many physical mechanisms that mediate persistence are well-understood, they have not previously been considered simultaneously in a causal framework. Here we use linear methods that are widely used in the field of causal inference in statistics to identify mediators between persistent near-surface temperature anomalies from one month to the next. The variables considered are soil temperature and soil moisture at four levels, and snow depth. In Northern Europe, the high persistence of temperature in summer is shown to be mediated mainly by soil temperature anomalies. The high persistence in winter is mediated by snow depth and soil moisture in addition to soil temperature. The annual cycles of persistence are also investigated for the mid- and high latitudes of the Northern Hemisphere, confirming the important role of soil temperature in summer. Snow depth is an important mediator when, and where, its interannual variability is large: in winter at midlatitudes and in spring and autumn at high latitudes. The novel contribution of this study is the introduction of a linear causal methodology and a holistic approach that allows quantification and comparison of the different roles of soil variables and snow depth in mediating near-surface temperature persistence.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Open-source generation of sigma profiles: impact of quantum chemistry and solvation treatment on machine learning performance

The combination of machine learning (ML) models with chemistry-related tasks requires the description of molecular structures in a machine-readable way. The nature of these so-called molecular descriptors has a direct and major impact on the performance of ML models and remains an open problem in the field. Structural descriptors like SMILES strings or molecular graphs lack size-independence and can be memory intensive. Machine-learned descriptors can be of low dimensionality and constant size but lack physical significance and human interpretability. Sigma profiles, which are unnormalized histograms of the surface charge distributions of solvated molecules, combine physical significance with low dimensionality and size-independence, making them a suitable candidate for a universal molecular descriptor. However, their widespread adoption in ML applications requires open access to sigma profile generation, which is currently not available. This work details the development of OpenSPGen – an open-source tool for generating sigma profiles. Also presented are studies on the effect of different settings on the efficacy of the generated sigma profiles at predicting thermophysical material properties when used as inputs to a Gaussian process as a simple surrogate ML model. We find that a higher level of theory does not translate to more accurate results. We also provide further recommendations for sigma profile calculation and use in ML models.

Salih, Fathya Y. M. [University of Notre Dame, IN ↗