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At least 109 records · Page 6

Strong surface magnetic field generation in relativistic short pulse laser–plasma interaction with an applied seed magnetic field

Abstract While plasma often behaves diamagnetically, we demonstrate that the laser irradiation of a thin opaque target with an embedded target-transverse seed magnetic field B seed can trigger the generation of an order-of-magnitude stronger magnetic field with opposite sign at the target surface. Strong surface field generation occurs when the laser pulse is relativistically intense and results from the currents associated with the cyclotron rotation of laser-heated electrons transiting through the target and the compensating current of cold electrons. We derive a predictive scaling for this surface field generation, B gen ∼ −2 πB seed Δ x / λ 0 (in the large spot size limit), where Δ x is the target thickness and λ 0 is the laser wavelength, and conduct 1D and 2D particle-in-cell simulations to confirm its applicability over a wide range of conditions. We additionally demonstrate that both the seed and surface-generated magnetic fields can have a strong impact on application-relevant plasma dynamics, for example substantially altering the overall expansion and ion acceleration from a μ m-thick laser-irradiated target with a kilotesla-level seed magnetic field.

Weichman, K. (ORCID:0000000234877922)↗

Effect of a surface-to-gap temperature discontinuity on the heat transfer to reusable surface insulation tile gaps

An experimental investigation is presented that was performed to determine the effect of a surface-to-gap wall temperature discontinuity on the heat transfer within space shuttle, reusable surface insulation, tile gaps submerged in a thick turbulent boundary layer. Heat-transfer measurements were obtained on a flat-plate, single-gap model submerged in a turbulent tunnel wall boundary layer at a nominal free-stream Mach number of 10.3 and free-stream Reynolds numbers per meter of 1.5 million, 3.3 million and 7.8 million. Surface-to-gap wall temperature discontinuities of varying degree were created by heating the surface of the model upstream of the instrumented gap. The sweep angle of the gap was varied between 0 deg and 60 deg; gap width and depth were held constant. A surface-to-gap wall temperature discontinuity (surface temperature greater than gap wall temperature) results in increased heat transfer to the near-surface portion of the gap, as compared with the heat transfer under isothermal conditions, while decreasing the heat transfer to the deeper portions of the gap. The nondimensionalized heat transfer to the near-surface portion of the gap is shown to decrease with increasing Reynolds number; in the deeper portion of the gap, the heat transfer increases with Reynolds number.

Throckmorton, D. A.↗

Antisoiling technology: Theories of surface soiling and performance of antisoiling surface coatings

Physical examination of surfaces undergoing natural outdoor soiling suggests that soil matter accumulates in up to three distinct layers. The first layer involves strong chemical attachment or strong chemisorption of soil matter on the primary surface. The second layer is physical, consisting of a highly organized arrangement of soil creating a gradation in surface energy from a high associated with the energetic first layer to the lowest possible state on the outer surfce of the second layer. The lowest possible energy state is dictated by the physical nature of the regional atmospheric soiling materials. These first two layers are resistant to removal by rain. The third layer constitutes a settling of loose soil matter, accumulating in dry periods and being removed during rainy periods. Theories and evidence suggest that surfaces that should be naturally resistant to the formation of the first two-resistant layers should be hard, smooth, hydrophobic, free of first-period elements, and have the lowest possible surface energy. These characteristics, evolving as requirements for low-soiling surfaces, suggest that surfaces or surface coatings should be of fluorocarbon chemistry. Evidence for the three-soil-layer concept, and data on the positive performance of candidate fluorocarbon coatings on glass and transparent plastic films after 28 months of outdoor exposure, are presented.

Cuddihy, E. F.↗

Surface roughness of flat and curved optical surfaces

Surface roughness measurement has several applications. Even a few A roughness will cause scattered light in optical systems. Smooth surfaces are required in a wide variety of instruments. For example, the outputs of the high power lasers are limited by the surface roughness of mirrors and windows. Similarly, the information storage capacity of magnetic media is limited by the roughness of the surface. Roughness reduces the resolving power of optics and distorts images. The performance of certain thin film components in electronic industries is affected by the roughness on the film surface. X-ray astronomical telescopes require smooth curved surfaces. To improve the surface quality, super sensitive detection methods are required. Wide ranging measurement techniques are developed based on interferometry, electron microscopy, C-rays, ellipsometry, light scattering, and using mechanical stylus, etc. Though there are several techniques available for measurement and evaluation of the surfaces, no single technique is fully adequate. Also, the technique used should be nondestructive and highly sensitive. So, an optical heterodyne profilometer was fabricated. Its current sensitivity is much better than 10A rms. It is a noncontact and nondestructive technique. The instrument can be operated even by unskilled personnel for routine measurements.

George, M. C.↗

Determining surface solar absorption from broadband satellite measurements for clear skies - Comparison with surface measurements

Using data from collocated satellite pixel measurements obtained during the Earth Radiation Budget Experiement and near-surface measurements carried out at the Boulder Atmospheric Observatory Tower, the shortwave (SW) surface radiation from broadband satellite measurements for clear-sky conditions was compared with surface measurements. Results demonstrate that the surface-SW absorption is a more meaningful quantity for climate studies than is surface insolation. It is also shown that a direct evaluation of the surface-SW absorption can be more accurately obtained from satellite measurements than can be surface insolation. An algorithm is presented for transferring satellite SW measurements to surface-SW absorption.

Cess, Robert D.↗

Near-surface temperature gradients and their effects on thermal-infrared emission spectra of particulate planetary surfaces

The infrared energy emitted from a planetary surface is generated within a finite depth determined by the material's absorption skin depth. This parameter varies significantly with wavelength in the infrared but has an average value of around 50 microns for most geologic materials. In solid rock, heat transfer is efficient enough so that this 50 micron zone of the near surface from which the radiation emanates will be more or less isothermal. In particulate materials, however, heat transfer is more complicated and occurs via a combination of mechanisms, including solid conduction within grains and across grain contacts, conduction through the interstitial gas, and thermal radiation within individual particles and across the void spaces in between grains. On planets with substantial atmospheres, the gas component dominates the heat transfer and tends to mitigate near-surface thermal gradients. However, on airless bodies, the gas component is absent and heat transfer occurs via solid conductions and radiation. If the particles are small relative to the average absorption skin depth, then the top 50-100 microns or so of the surface will be cooled by radiation to space allowing the creation of significant near-surface thermal gradients. In those regions of the spectrum where the absorption coefficient is low, the emission will come from the deeper, warmer parts of the medium, whereas in regions of high absorption, the emission will emanate from shallower, cooler parts of the medium. The resulting emission spectrum will show non-compositional features as a result of the thermal structure in the material. We have modeled the heat transfer in a particulate medium in order to determine the magnitude of near-surface thermal gradients for surfaces on airless bodies and on Mars. We use the calculated thermal structure to determine the effects it has on the infrared emission spectrum of the surface.

Henderson, B. G.↗

Near-surface thermal gradients and their effects on mid-infrared emission spectra of planetary surfaces

We model the heat transfer by radiation and conduction in the top few millimeters of a planetary surface to determine the magnitude of near-surface (approximately 100 micrometers) thermal gradients and their effects on mid-infrared emission spectra for a number of planetary environments. The model is one-dimensional and uses a finite difference scheme for approximately 10 micrometers layers. Calculations are peformed for samples heated at the base and from above by sunlight. Our results indicate that near-surface radiative cooling creates significant thermal gradients in the top few hundred microns of surfaces in which radiation is an importamnt heat transfer mechanism. The effect is maximized in evacuated, underdense particulate media with sufficiently high temperatures. Near-surface thermal gradients will be significant in fine-grained particulate surfaces on the Moon (40-60 K/100 micrometers) and Mercury (approximately 80 K/100 micrometers), increasing spectral contrast and creating emission maxima in the transparent regions of the spectra. They will be of lesser importance on the surface of Mars, with a maximum value of around 5 k/100 micrometers in areas of low thermal inertia, and will be negligible on planets with more substantial atmospheres (less than 1 K/100 micrometers). We conclude that the effects that thermal gradients have on mid-IR emission spectra are predictable and do not negate the utility of emission spectroscopy for remote determination of planetary surface composition.

Henderson, B. G.↗

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Bosilovich, Michael G.↗

Comparison of Surface Ground Temperature from Satellite Observations and the Off-Line Land Surface GEOS Assimilation System

The surface ground temperature (Tg) is an important meteorological variable, because it represents an integrated thermal state of the land surface determined by a complex surface energy budget. Furthermore, Tg affects both the surface sensible and latent heat fluxes. Through these fluxes. the surface budget is coupled with the atmosphere above. Accurate Tg data are useful for estimating the surface radiation budget and fluxes, as well as soil moisture. Tg is not included in conventional synoptical weather station reports. Currently, satellites provide Tg estimates globally. It is necessary to carefully consider appropriate methods of using these satellite data in a data assimilation system. Recently, an Off-line Land surface GEOS Assimilation (OLGA) system was implemented at the Data Assimilation Office at NASA-GSFC. One of the goals of OLGA is to assimilate satellite-derived Tg data. Prior to the Tg assimilation, a thorough investigation of satellite- and model-derived Tg, including error estimates, is required. In this study we examine the Tg from the n Project (ISCCP DI) data and the OLGA simulations. The ISCCP data used here are 3-hourly DI data (2.5x2.5 degree resolution) for 1992 summer months (June, July, and August) and winter months (January and February). The model Tg for the same periods were generated by OLGA. The forcing data for this OLGA 1992 simulation were generated from the GEOS-1 Data Assimilation System (DAS) at Data Assimilation Office NASA-GSFC. We examine the discrepancies between ISCCP and OLGA Tg with a focus on its spatial and temporal characteristics, particularly on the diurnal cycle. The error statistics in both data sets, including bias, will be estimated. The impact of surface properties, including vegetation cover and type, topography, etc, on the discrepancies will be addressed.

Yang, R.↗

Evaluation of Surface and Near-Surface Melt Characteristics on the Greenland Ice Sheet using MODIS and QuikSCAT Data

The Greenland Ice Sheet has been the focus of much attention recently because of increasing melt in response to regional climate warming. To improve our ability to measure surface melt, we use remote-sensing data products to study surface and near-surface melt characteristics of the Greenland Ice Sheet for the 2007 melt season when record melt extent and runoff occurred. Moderate Resolution Imaging Spectroradiometer (MODIS) daily land-surface temperature (LST), MODIS daily snow albedo, and a special diurnal melt product derived from QuikSCAT (QS) scatterometer data, are all effective in measuring the evolution of melt on the ice sheet. These daily products, produced from different parts of the electromagnetic spectrum, are sensitive to different geophysical features, though QS- and MODIS-derived melt generally show excellent correspondence when surface melt is present on the ice sheet. Values derived from the daily MODIS snow albedo product drop in response to melt, and change with apparent grain-size changes. For the 2007 melt season, the QS and MODIS LST products detect 862,769 square kilometers and 766,184 square kilometers of melt, respectively. The QS product detects about 11% greater melt extent than is detected by the MODIS LST product probably because QS is more sensitive to surface melt, and can detect subsurface melt. The consistency of the response of the different products demonstrates unequivocally that physically-meaningful melt/freeze boundaries can be detected. We have demonstrated that these products, used together, can improve the precision in mapping surface and near-surface melt extent on the Greenland Ice Sheet.

Hall, Dorothy K.↗

Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

Lake Chad, located in the middle of the African Sahel belt, underwent dramatic decreases in the 1970s and 1980s leaving less than ten percent of its 1960s surface water extent as open water. In this paper, we present an extended record (dry seasons 1988-2016) of the total surface water area of the lake (including both open water and flooded vegetation) derived using Land Surface Temperature (LST) data (dry seasons 2000-2016) from the NASA Terra MODIS sensor and EUMETSAT Meteosat-based LST measurements (dry seasons 1988-2001) from an earlier study. We also examine the total surface water area for Lake Chad using radar data (dry seasons 2015-2016) from the ESA Sentinel-1a mission. For the limited number of radar data sets available to us (18 data sets), we find on average a close match between the estimates from these data and the corresponding estimates from LST, though we find spatial differences in the estimates using the two types of data. We use these spatial differences to adjust the record (dry seasons 2000-2016) from MODIS LST. Then we use the adjusted record to remove the bias of the existing LST record (dry seasons 1988-2001) derived from Meteosat measurements and combine the two records. From this composite, extended record, we plot the total surface water area of the lake for the dry seasons of 1988-1989 through 2016-2017. We find for the dry seasons of 1988-1989 to 2016-2017 that the maximum total surface water area of the lake was approximately 16,800 sq. km (February and May, 2000), the minimum total surface water area of the lake was approximately 6400 sq. km (November, 1990), and the average was approximately 12,700 sq. km. Further, we find the total surface water area of the lake to be highly variable during this period, with an average rate of increase of approximately 143 sq. km per year.

Policelli, Frederick↗

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Here, in this paper, a novel hybrid wire arc additive manufacturing (WAAM) and ultrasonic nanocrystal surface modification (UNSM) on porosity manipulation and surface properties of aluminum 5356 alloys was studied. The goal is to improve the quality of the WAAM-built part by eliminating bigger pores and reducing its size, reducing surface roughness, and increasing surface hardness. The as-built WAAM and WAAM-UNSM-treated samples were quantitatively studied for porosity using an X-ray micro-computed tomography (μ-CT). The surface roughness was measured on the surface profile of the same samples before and after UNSM treatment. Followed by the Vickers micro-hardness tests to evaluate the hardness modified by the influence of the UNSM treatment. It was found that the bigger pores in the as-built WAAM samples were eliminated and the medium-sized pores were shrunk to almost half the size after the UNSM treatment. Further, the UNSM treatment showed a significant improvement in both surface roughness and hardness on the WAAM Al5356 samples. This experimental work demonstrates the critical advantages of hybrid WAAM-UNSM in improving the qualities of the WAAM processed parts.

Hardness↗

Effect of applied potential on metal surfaces: Surface energy, Wulff shape and charge distribution

Here we use grand canonical density functional theory to predict the surface energies, Wulff shapes, charge distributions and catalytically active sites of different metal surfaces under electrochemical conditions. We propose a method for computing surface energies from grand canonical density functional theory (GC-DFT) calculations of periodic slab models and use it to compute the surface energies of the facets of Pt, Cu, and Ag crystals to predict their Wulff shapes under electrochemical conditions. GC-DFT predicts that, for the pure metals studied, solvation only slightly affects the Wulff shape while applied potentials considerably affect the surface energies and corresponding Wulff shapes. We used Bader charge analysis of GC-DFT computed electron densities to investigate the effect of applied potential on the distribution of electron density over the atoms of the surfaces of Pt, Cu, Ag, and the 75–25 Ag-Pt and Au-Ni alloys. This analysis shows that, under an applied potential, the electron density is unevenly distributed over the surface atoms and that the charges of atoms more exposed to solvent are more sensitive to bias. Our results show that the most sensitive atom to bias can be used to identify the most favorable adsorption site and thus, the active sites of electrochemical reactions, which is computationally less demanding than calculating the adsorption energies on all possible adsorption sites.

36 MATERIALS SCIENCE↗

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE↗

Comparison of Surface Tension Generation Methods in Smoothed Particle Hydrodynamics for Dynamic Systems

Developing robust numerical models of dynamic surface tension dominated multiphase systems is an ongoing challenge, especially in scenarios with large density and viscosity ratios. This is critical to the design and understanding of various physical and engineering systems, such as fluidized beds, fuel injectors, and drug delivery schemes. Much of the computational work in surface tension dominated multiphase flows has employed the continuum surface force method (CSF) of Brackbill et al. [1], which recasts surface tension from a surface force to a volumetric force that can be imposed in the vicinity of an interface. The CSF method produces accurate results across a variety of systems, however it relies on the identication of surface normals, which can be unreliable under certain conditions. Alternative methods of simulating surface tension have been proposed. Here the advantages and disadvantages of the CSF method in comparison to a pairwise forces (PF) method proposed by Tartakovsky and Panchenko [2] are explored. The CSF and PF methods are used in a smoothed particle hydrodynamics (SPH) framework to model dynamic systems. Results are compared to existing test cases from the literature and to analytic solutions derived from fundamental normal mode behavior of bubbles and droplets. A physical system for which the PF method is more stable and physically appropriate than the CSF method is identied.

smoothed particle hydrodynamics, multiphase flow↗

Selective Adsorption of Thiol-Containing Molecules on Copper Sulfide Surfaces via Molecule–Surface Disulfide Bridges

Recent results in the fields of nanoenhanced agriculture and expanding interest in prebiotic chemistry have placed increased emphasis on understanding the chemically selective interaction of small molecules with the surfaces of metal sulfides. Here, we present an integrated experimental and computational study of the interaction of thiol-containing molecules with copper sulfide (covellite) surfaces in aqueous media. In situ Fourier-transform infrared (FTIR) measurements and ex situ X-ray photoelectron spectroscopy (XPS) measurements show that molecules bearing free thiol groups, including glutathione and cysteine, bind strongly to CuS (covellite) nanoparticles and to CuS (001) single crystals, while control studies show that similar molecules lacking the free thiol group exhibit much less binding. Additional experiments show that these thiol-containing molecules interact transiently with CuO nanoparticle surfaces but are readily removed by rinsing. The FTIR and XPS experiments demonstrate that adsorption of molecular thiols to CuS surfaces occurs in a chemically selective manner. Further experimental studies and density functional calculations show that the preferred mode of binding is through the surface S atoms, forming a Solid–S–S–Molecule disulfide linkage. While the role of disulfide linkages in controlling structure and function of proteins and other biomolecules is widely known, the formation of surface disulfide linkages as a motif for covalent molecular binding at surfaces has not been established previously.

36 MATERIALS SCIENCE↗