Search NASA⌕ Search

SEARCH · Search NASA

Results for “surface product”

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 73 records · Page 4

Origin of deactivation of aqueous Na–CO 2 battery and mitigation for long-duration energy storage

Here, the development of long-duration energy storage technology is crucial to facilitate the efficient utilization of renewable energy sources while mitigating carbon dioxide production. In this study, we investigate the deactivation and reactivation mechanisms of the aqueous Na–CO 2 battery during extended cycling. We have designed the cathode to include non-precious intermetallic catalysts. As the cell undergoes repeated cycles, the voltage polarization during discharge progressively rises, eventually leading to the cell's deactivation and formation of decomposition products clogging the electrode surface. Results obtained from comprehensive characterization techniques, including conductive atomic force microscopy (cAFM), Raman spectroscopy, X-ray photoelectron spectroscopy, X-ray diffraction, and inductively coupled plasma-mass spectrometry provide insight into the decomposition products. We also showcase an electrochemical approach for regeneration of these aqueous cells. Our findings, along with the insights we have gained, provide a path toward creating long-duration systems with self-healing properties.

25 ENERGY STORAGE↗

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhanced Selectivity for C 2 H 4 Production from C 2 H 6 on Partially Chlorinated IrO 2 (110) Surfaces

Modifying metal oxide surfaces to limit their oxidizing activity can provide a means of improving catalytic selectivity toward the partial oxidation of light alkanes. Here, in this study, we investigated the oxidation of C 2 H 6 on Cl-modified IrO 2 (110) surfaces using temperature-programmed reaction spectroscopy (TPRS) and first-principles microkinetic modeling. We find that substituting Cl for O in the IrO 2 (110) surface enhances the selectivity for C 2 H 6 conversion to C 2 H 4 during TPRS by suppressing extensive oxidation to CO x products, while also either enhancing C 2 H 4 production or altering it to a lesser extent, depending on the initial C 2 H 6 coverage. The C 2 H 4 selectivity increased with increasing C 2 H 6 and Cl coverage, but reached a limiting value below 50%. The Cl coverage changed negligibly during C 2 H 6 oxidation, and the surface reactivity decreased only marginally for Cl coverages up to 0.5 ML (monolayer). TPRS simulations using a microkinetic model predict C 2 H 4 and CO x product yields as a function of the Cl coverage that agree closely with the experimental results. According to the simulations, C 2 H 6 conversion to C 2 H 4 occurs on Cl-IrO 2 (110) by the hydrogenation of C 2 H 3 * species adsorbed in blocked states, in which neighboring sites are occupied only by unreactive HO and Cl species. The microkinetic modeling shows that H-hopping away from surface HO groups provides a relatively efficient route for C 2 H 3 * to escape blocked configurations and dehydrogenate, and that this process can limit the C 2 H 4 selectivity on Cl-IrO 2 (110) under the conditions studied. Overall, our results demonstrate that Cl-substitution into IrO 2 (110) enhances the selectivity for C 2 H 4 production from C 2 H 6 and provides insights into the reaction mechanism that can guide strategies to further improve the C 2 H 4 selectivity.

IrO2↗

NCAR/EOL ISFS Data for LASSO-CACTI Overview Paper

5 minute averages of surface meteorology and flux data collected by the NCAR/EOL Integrated Surface Flux System (ISFS) at 15 sites during the RELAMPAGO field campaign. These data have been quality-controlled and are available in NetCDF format. Winds reported by the sonic anemometers have been tilt corrected and rotated into geographic coordinates. Data providence, citation, and acknowledgement This ARM data set is a copy of v2.0 of the NCAR data set obtained on 6-Jun-2024 from https://doi.org/10.26023/ZPHJ-JW9W-2B0Y. The citation for the original data source is: NCAR/EOL In-situ Sensing Facility, Oncley, S. 2021. NCAR/EOL ISFS Surface Meteorology and Flux Products, 5-minute. Version 2.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.26023/ZPHJ-JW9W-2B0Y Accessed 06 Jun 2024. In addition to the citation reference and any other acknowledgements, please acknowledge NCAR/EOL in your publications with text such as: "Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/"

atmosphere: surface↗

Role of chemical production and depositional losses on formaldehyde in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM)

Abstract. Formaldehyde (HCHO) is an important air pollutant with direct cancer risk and ozone-forming potential. HCHO sources are complex because HCHO is both directly emitted and produced from oxidation of most gas-phase reactive organic carbon. We update the secondary production of HCHO in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) in the Community Multiscale Air Quality (CMAQ) model. Production of HCHO from isoprene and monoterpenes is increased, correcting an underestimate in the current version. Simulated June–August surface HCHO during peak photochemical production (11:00–15:00 LT, local time) increased by 0.6 ppb (32 %) over the southeastern USA and by 0.2 ppb (13 %) over the contiguous USA. The increased HCHO compares more favorably with satellite-based observations from the TROPOspheric Monitoring Instrument (TROPOMI) and from aircraft-based observations. Evaluation against hourly surface observations indicates a missing nighttime sink that can be improved by increased nighttime deposition, which reduces June–August nocturnal (20:00–04:00 LT) surface HCHO by 1.1 ppb (36 %) over the southeastern USA and 0.5 ppb (29 %) over the contiguous USA. The ability of CRACMM to capture peak levels of HCHO at midday is improved, particularly at sites in the northeastern USA, while peak levels at sites in the southeastern USA are improved, although still lower than observed. Using established risk assessment methods, lifetime exposure of the population in the contiguous USA (∼ 320 million) to ambient HCHO levels predicted here may result in 6200 lifetime cancer cases, with 40 % from controllable anthropogenic emissions of nitrogen oxides and reactive organic compounds. Chemistry updates will be available in CRACMM version 2 (CRACMM2) in CMAQv5.5.

Skipper, T. Nash↗

Surrogate models for development of unconventional shale reservoirs by an integrated numerical approach of hydraulic fracturing, flow and geomechanics, and machine learning

We develop well-completion surrogate models by taking an integrated workflow of hydraulic fracturing, flow, geomechanics, and machine learning simulation. There are three steps in the proposed workflow. First, history-matching processes are conducted with the field data including pumping and production data for characterization. Second, full-physics simulation is performed with various parameters of the field development (e.g., cluster spacing, clusters per stage, pumping rates and times, amount of proppant, and well spacing) to generate multiple simulation results by changing the parameters of the completion design with well-known hydraulic fracturing, reservoir, geomechanics simulators to calculate fracture geometry, reservoir depressurization, induced stress changes. The workflow is demonstrated over a field in the Southern Midland Basin. Here, we take two completion scenarios: a single well case followed by a multi-well case. Finally, a Long Short-Term Memory (LSTM) machine learning algorithm is employed to create surrogate models that can replicate the full-physics simulation results. Furthermore, results show that the trained models applied in the single well and multi-well cases for a particular geological system can provide good accuracy close to those provided by full-physics simulations. Specifically, the site-specific surrogate models can predict fracture parameters (length, height, and surface area) and cumulative production accurately with computational efficiency, suggesting our proposed workflow can be used as a pragmatic tool for expediting the well completion optimization process.

Geomechanics↗

Thermal decomposition pathways of bulk electrolytes on vanadium oxide nanocrystals

The thermal stability of electrolytes at an elevated temperature induced by battery charge-discharge cycling is critical for the long cycling performance of a rechargeable battery. For many multivalent systems, such as rechargeable magnesium batteries, which offer great potential for high energy density and utilize earth-abundant resources, electrolyte instability and electrode surface passivation, arising from electrolyte decomposition, remain as major roadblocks. Understanding the electrolyte decomposition pathways at the electrode-electrolyte interface is essential to provide guidance in overcoming this challenge. In this work, in situ 13 C magic angle spinning nuclear magnetic resonance (MAS NMR) and first-principles calculations were used to investigate the thermal decomposition of the electrolyte in a system consisting of MgV 2 O 4 , a novel cathode for magnesium batteries, mixed with a bulk electrolyte consisting of magnesium bis(trifluoromethanesulfonyl)imide (Mg(TFSI) 2 ) in diglyme (G2). We show that significant electrolyte decomposition is observed in bulk 1.0 M Mg(TFSI) 2 in G2 mixed with nanometer sized MgV 2 O 4 powder at elevated temperatures. This observation is to mimic the possible thermal decomposition that might happen during battery cycling. We demonstrate that the MgV 2 O 4 surface is covered by a layer of decomposed G2 products. We conclude that the dominant reaction pathway for electrolyte decomposition is the thermal decomposition of the pure electrolytes at elevated temperatures, followed by adsorption of G2 decomposition products to the MgV 2 O 4 surface. The activation energy for the major decomposition pathway is obtained. In conclusion, this work highlights the importance of studying thermal decomposition of electrolytes for overall system stability and explores electrolyte stability at significantly elevated temperatures.

25 ENERGY STORAGE↗

Dielectric and magnetic properties of microwave-absorbing FeAl x O y catalysts fabricated via solution combustion synthesis

Iron-based alumina (FeAl x O y ) nanocomposites are microwave-absorbers and catalysts, which makes them promising for emerging microwave-assisted thermocatalytic technologies. Solution combustion synthesis (SCS) has been used to synthesize FeAl x O y powders, and prior work has demonstrated that adjusting SCS parameters significantly changes phase composition and specific surface area of the products. However, it is unclear how synthesis parameters affect their microwave-absorbing properties, which are essential for optimizing microwave-assisted technologies. To address this challenge, in the present work, twelve different FeAl x O y products were synthesized at different combinations of the SCS parameters such as two fuels (citric acid and glycine), two heating modes (hotplate and muffle furnace), and three Fe:Al molar ratios (2:1, 1:1, 1:2). Dielectric and magnetic properties of the products were characterized using a network analyzer and a vibrating sample magnetometer. Based on the measured permittivity and permeability, penetration depth and reflection loss were calculated as a function of frequency and bed thickness. The products were heated by microwaves at 2.45 GHz and then examined with X-ray diffraction (XRD) analysis. For all products, the magnetic saturation was lower than for bulk iron oxides because of the small crystallite size and aluminum substitution. The use of glycine induced high dielectric losses and enabled fast microwave-heating rates compared to citric acid. Higher Fe:Al ratio also led to higher dielectric and magnetic losses. With glycine fuel, SCS in a furnace induced larger penetration depth and lower microwave absorption than SCS on a hotplate. The minimization of reflected power was more sensitive to the thickness of the product bed than to the frequency of the electromagnetic field. Post-heating XRD analysis revealed different phase transformations in the FeAl x O y powders depending on the SCS parameters. As a result, an FeAl x O y material, synthesized via incipient wetness impregnation, lacked magnetic losses and did not heat well as compared to the SCS products.

Combustion synthesis↗

Analytical ab initio hessian from a deep learning potential for transition state optimization

Identifying transition states—saddle points on the potential energy surface connecting reactant and product minima—is central to predicting kinetic barriers and understanding chemical reaction mechanisms. In this work, we train a fully differentiable equivariant neural network potential, NewtonNet, on thousands of organic reactions and derive the analytical Hessians. By reducing the computational cost by several orders of magnitude relative to the density functional theory (DFT) ab initio source, we can afford to use the learned Hessians at every step for the saddle point optimizations. We show that the full machine learned (ML) Hessian robustly finds the transition states of 240 unseen organic reactions, even when the quality of the initial guess structures are degraded, while reducing the number of optimization steps to convergence by 2–3× compared to the quasi-Newton DFT and ML methods. All data generation, NewtonNet model, and ML transition state finding methods are available in an automated workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma Assisted Combustion and Chemical Processing: Chapter 9 - Plasma Diagnostics

Plasma dynamics and chemistry have a broad range of timescales from picoseconds to milliseconds. In addition, it involves nonequilibrium energy transfer between electrons, ions, electronically and vibrationally excited states, radicals, intermediate species, and reactants and products as well as surface charges and chemistry. To understand plasma physics and chemistry, it is essential to conduct time and space resolved, quantitative detection of nonequilibrium temperature distributions, electron energy and number density, electric field, and species concentrations. There are enormous publications and review articles on this subject. The focus of this chapter is to be placed on the most recent progress in gas phase plasma properties and chemistry, especially on optical emission spectroscopy, laser absorption spectroscopy, Faraday rotational spectroscopy, Raman and Thompson scattering, femtosecond and picosecond (fs/ps) coherent anti-Stokes Raman scattering (CARS) spectroscopy, and electric field-induced second harmonic generation methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

ESIAS Pseudocode

The Explosive Shock Image Analysis System (ESAIS) is designed to provide a semiautomated quantitative analysis of fast-frame imagery taken during the detonation of high explosive (HE) rate sticks. ESIAS does this by assisting the user in identifying the HE stick geometry on the image (i.e., sides of the undetonated HE stick, detonation front, an axial reference point to assist in the inter-comparison of images); scaling the images based on the known diameter of the undetonated HE stick; identifying the profiles of various surfaces resulting from the detonation process such as the shock wave and product gases or the outer pipe surface; calculating the detonation speed of the HE by tracking the distance it travels between two images with a known time lapse between the images; and determining the slit velocities resulting from the detonation. ESIAS will also import scope traces from oscilloscopes and assist in identifying the time of arrival of significant peaks.

97 MATHEMATICS AND COMPUTING↗

FY24 Q4 quarterly report: LLNL's node activity within HydroGEN STCH

In this quarterly report, we Computed the driving force for the water splitting reaction as a function of reaction progress and continued Development of the numerical method for water splitting reactions of H 2 production on the particle surface within 3D porous microstructures.

08 HYDROGEN↗

Thermal Management for Planar Package Power Electronics (CRADA Final Report)

The National Renewable Energy Laboratory (NREL) and John Deere Electronic Solutions (JDES) collaborated to develop and evaluate computer models and simulations related to the thermal performance of semiconductor device packaging for an inverter of an off-road vehicle ("Semiconductor Packaging"). The objective of the research was for NREL and JDES to develop a two or three-dimensional computer-aided design model of the Semiconductor Packaging ("Computer Model") for thermal performance evaluation in a simulation. The project developed computer models of a Semiconductor Package of silicon-carbide semiconductor devices with appropriate thermal dissipation via one or more of the following thermal features: a double-sided planar cooling configuration, an air-cooled configuration, a liquid-cooled configuration for off-road inverter applications in a relevant simulated operating environment. It is noted that surface area and prototype product embodiment consisting of air-cooled and liquid-cooled configurations may and may not be in direct contact with power semiconductor chips. The idea was to explore and develop packaging and thermal management technology for power semiconductors that was most effective in the performance yet had least burden in overall product cost for a given application.

33 ADVANCED PROPULSION SYSTEMS↗

Monthly Quality-filtered Aggregation of NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5

This dataset contains gridded monthly Leaf Area Index (LAI) derived from the daily NOAA Climate Data Record (CDR) of AVHRR Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Version 5. This data record spans from 1981 to 2018 using data from eight NOAA polar orbiting satellites: NOAA-7, -9, -11, -14, -16, -17, -18 and -19. The data are projected on a 0.05 degree x 0.05 degree global grid, as in the original CDR. The original CDR is one of the Land Surface CDR Version 5 products produced by the NASA Goddard Space Flight Center (GSFC) and the University of Maryland (UMD), which is accompanied by algorithm documentation, data flow diagram and source code for the NOAA CDR Program. This dataset is in the netCDF-4 file format following ACDD and CF Conventions. This dataset has applied quality assurance information to only include "OK" data from the original CDR in the monthly aggregation.

Vermote, Eric [NASA Goddard Space Flight Center (G↗

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Bertrand, Leah (ORCID:0009000001607558)↗

Disentangling top-down drivers of mortality underlying diel population dynamics of Prochlorococcus in the North Pacific Subtropical Gyre

Photosynthesis fuels primary production at the base of marine food webs. Yet, in many surface ocean ecosystems, diel-driven primary production is tightly coupled to daily loss. This tight coupling raises the question: which top-down drivers predominate in maintaining persistently stable picocyanobacterial populations over longer time scales? Motivated by high-frequency surface water measurements taken in the North Pacific Subtropical Gyre (NPSG), we developed multitrophic models to investigate bottom-up and top-down mechanisms underlying the balanced control of Prochlorococcus populations. Here, we find that incorporating photosynthetic growth with viral- and predator-induced mortality is sufficient to recapitulate daily oscillations of Prochlorococcus abundances with baseline community abundances. In doing so, we infer that grazers in this environment function as the predominant top-down factor despite high standing viral particle densities. The model-data fits also reveal the ecological relevance of light-dependent viral traits and non-canonical factors to cellular loss. Finally, we leverage sensitivity analyses to demonstrate how variation in life history traits across distinct oceanic contexts, including variation in viral adsorption and grazer clearance rates, can transform the quantitative and even qualitative importance of top-down controls in shaping Prochlorococcus population dynamics.

54 ENVIRONMENTAL SCIENCES↗

Catalytic Resonance Theory: Turnover Efficiency and the Resonance Frequency

Programmable catalysts exhibiting forced oscillation in the free energy of reacting surface species were simulated to understand the general mechanisms leading to efficient use of the input energy. Catalytic ratchets with either positive or negative adsorbate scaling exhibited oscillation conditions of both high and low turnover efficiency, yielding catalytic turnover frequencies either close to or significantly lower than the applied catalyst oscillation frequency, respectively. The “effective rate”, defined as the product of the catalytic turnover frequency and the turnover efficiency (ηTOE), was limited via two catalytic mechanisms: a leaky catalytic ratchet existed when molecules repeatedly traversed backward through the catalytic transition state upon catalyst oscillation, while a catalytic ratchet with low surface participation exhibited reduced formation of a gas-phase final product due to low surface product coverage. Furthermore, a single applied frequency yielding a maximum effective catalytic rate defined as the “resonance frequency” provided maximum combined benefit for catalytic rate and efficiency.

25 ENERGY STORAGE↗