Estimation Of Grain Size Research Articles

Stagnant-lid convection with diffusion and dislocation creep rheology: Influence of a non-evolving grain size

SUMMARY Heat transfer in one-plate planets is governed by mantle convection beneath the stagnant lid. Newtonian diffusion creep and non-Newtonian dislocation creep are the main mechanisms controlling large-scale mantle deformation. Diffusion creep strongly depends on the grain size (d), which in turn controls the relative importance of the two mechanisms. However, dislocation creep is usually neglected in numerical models of convection in planetary mantles. These mostly assume linear diffusion creep rheologies, often based on reduced activation parameters (compared to experimental values) that are thought to mimic the effects of dislocation creep and, as a side benefit, also ease the convergence of linear solvers. Assuming Mars-like parameters, we investigated the influence of a non-evolving grain size on Rayleigh–Bénard convection in the stagnant lid regime. In contrast to previous studies based on the Frank–Kamentskii approximation, we used Arrhenius laws for diffusion and dislocation creep—including temperature as well as pressure dependence—based on experimental measurements of olivine deformation. For d ≲ 2.5 mm, convection is dominated by diffusion creep. We observed an approximately equal partitioning between the two mechanisms for d ≈ 5 mm, while dislocation creep dominates for d ≳ 8 mm. Independent estimates of an average grain size of few mm up to 1 cm or more for present-day Mars suggest thus that dislocation creep plays an important role and possibly dominates the deformation. Mimicking dislocation creep convection using an effective linear rheology with reduced activation parameters, as often done in simulations of convection and thermal evolution of Mars, has significant limitations. Although it is possible to mimic mean temperature, mean lid thickness and Nusselt number, there are important differences in the flow pattern, root mean square velocity, and lid shape. The latter in particular affects the amount and distribution of partial melt, suggesting that care should be taken upon predicting the evolution of crust production when using simplified rheologies. The heat transport efficiency expressed in terms of the Nusselt number as a function of the Rayleigh number is thought to depend on the deformation mechanisms at play. We show that the relative volume in which dislocation creep dominates has nearly no influence on the Nusselt–Rayleigh scaling relation when a mixed rheology is used. In contrast, the flow pattern influences the Nusselt number more strongly. We derived a scaling law for the Nusselt number based on the mean lid thickness (〈L〉) and on the effective Rayleigh number (Raeff) obtained by suitably averaging the viscosity beneath the stagnant lid. We found that the Nusselt number follows the scaling $\mathrm{Nu} = 0.37 \langle L \rangle ^{-0.666} \mathrm{Ra}_{\mathrm{eff}}^{0.071}$ regardless of the deformation mechanism.

Introducing <i>PebbleCounts</i>: a grain-sizing tool for photo surveys of dynamic gravel-bed rivers

Abstract. Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 m2 scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 m2 orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel−1 images, and 0.07 and 0.05 ψ for one 0.32 mm pixel−1 image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel−1 images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel−1 image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 m2 patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 m2 areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 m2). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.

$${\mathrm{{Cu}}_2\mathrm{{ZnSnS}}_4}$$ thin films prepared with a Joule-heated graphite closed-space sulfurization system

Non-stoichiometric $${\mathrm{{Cu}}_2\mathrm{{ZnSnS}}_4}$$ (CZTS) thin films were prepared using a closed-space sulfurization process of vacuum-evaporated stacks of ZnS, Cu and Sn in a custom-designed Joule-heated graphite reactor. In the first sulfurization step, at 250 °C, Cu and Sn transform into CuS and SnS. In a second sulfurization step, at 510 °C, the stack finally transforms into CZTS. Sample compositions were determined by energy-dispersive X-ray spectroscopy. Three different Cu-poor/Zn-rich samples and one slightly Cu-rich/Zn-poor sample were obtained, with Cu/(Zn$$\,+\,$$Sn) ratios of 0.64, 0.85, 0.91 and 1.02. The effect of the closed-space sulfurization process in the morphology was analyzed by scanning electron microscopy, allowing to obtain estimates of grain sizes in the range from 0.50 to 0.75 $$\upmu \mathrm{{m}}$$. X-ray diffraction confirmed the polycrystalline structure of the kesterite CZTS thin films with crystallite sizes that vary from 48 to 64 nm as the Cu content increases in the samples. An estimate of lattice microstrain indicates larger values for samples with larger grains and higher Cu/(Zn$$\,+\,$$Sn) ratios. Raman spectroscopy reveals the characteristic kesterite structure with the main peak shifted to a lower wave number, a signature associated with partially disordered kesterite. Optical characterization shows a decreasing bandgap from 1.47 to 1.39 eV and an increasing Urbach energy from 77 to 200 meV as the relation Cu/(Zn$$\,+\,$$Sn) increases, indicating a decrease in the localized states in the bandgap for Cu-poor samples. Results indicate that CZTS thin films obtained from the custom-made Joule-heated graphite reactor have similar characteristics to the films obtained from more conventional methods like sulfurization in a tubular furnace with the advantage of a precise and fast-response temperature control that could allow novel sulfurization strategies.

Gravel Image Auto-Segmentation Based on an Improved Normalized Cuts Algorithm

The study of the grain-size distribution of gravels is always an important and challenging issue in stratigraphy and morphology, especially in the field of automated measurement. It largely reduces many manual processes and time consumption. Precise segmentation method plays a very important role in it. In this study, a digital image method using an improved normalized cuts algorithm is proposed for auto-segmentation of gravel image. It added grain-size estimation, and used the feature vector based on color. It has made great improvements in many respects, especially in accuracy of edge segmentation and automation. Compared with manual measurement methods and other image processing methods, the method studied in this paper is an efficient method for precisely segmenting gravel images.

Estimation of volume-weighted average grain size in Fe-based nanocrystalline soft magnetic materials by autocorrelation function

The coercivity of Fe-based nanocrystalline soft magnetic materials depends critically on the grain size of bcc-Fe grains. Accurately estimating the volume-weighted mean grain size is extremely important to develop new Fe-based nanocrystalline soft magnetic materials with low coercivity. This article shows that autocorrelation analysis of dark-field transmission electron microscope (TEM) images provides a very good estimation of bcc-Fe grain size in nanocrystalline soft magnetic materials. This method can be used to efficiently estimate the volume-weighted average grain size from multiple TEM images with much less inherent bias than manual measurement techniques. The estimated grain sizes show good consistency to the grain sizes estimated by X-ray diffraction (XRD) and manual measurement. In contrast to XRD, this method can also reveal the differences in grain size from different micron-sized regions of a sample.

ALMA Observations of Polarization from Dust Scattering in the IM Lup Protoplanetary Disk

Abstract We present 870 μm ALMA observations of polarized dust emission toward the Class II protoplanetary disk IM Lup. We find that the orientation of the polarized emission is along the minor axis of the disk, and that the value of the polarization fraction increases steadily toward the center of the disk, reaching a peak value of ∼1.1%. All of these characteristics are consistent with models of self-scattering of submillimeter-wave emission from an optically thin inclined disk. The distribution of the polarization position angles across the disk reveals that, while the average orientation is along the minor axis, the polarization orientations show a significant spread in angles; this can also be explained by models of pure scattering. We compare the polarization with that of the Class I/II source HL Tau. A comparison of cuts of the polarization fraction across the major and minor axes of both sources reveals that IM Lup has a substantially higher polarization fraction than HL Tau toward the center of the disk. This enhanced polarization fraction could be due a number of factors, including higher optical depth in HL Tau, or scattering by larger dust grains in the more evolved IM Lup disk. However, models yield similar maximum grain sizes for both HL Tau (72 μm) and IM Lup (61 μm, this work). This reveals continued tension between grain-size estimates from scattering models and from models of the dust emission spectrum, which find that the bulk of the (unpolarized) emission in disks is most likely due to millimeter-sized (or even centimeter-sized) grains.

Estimation of the Effective Grain Size Controlling Brittle Crack Arrest Toughness of High-strength Steel

Estimation of the Effective Grain Size Controlling Brittle Crack Arrest Toughness of High-strength Steel

Estimation of Ferrite Grain Size and Mechanical Properties of a 22MnVNb6 Microalloyed Low Carbon Cast Steel

The ferrite grain size of a 22MnVNb6 microalloyed steel can be estimated by developing a relationship between ferrite grain size, austenitising temperature and cooling rate from austenitising time, temperature. An extended Hall-Petch relationship was used to estimate the yield stress from the estimation ferrite grain size. Heat treatment as the annealing was used to improve the tensile and hardness properties of the steel. It was shown that the best combination of tensile and hardness properties were achieved when a higher austenitising temperature was used. Transmission electron and optical microscopy were used to study the morphology of ferrite and pearlite formed by the heat treatments. The microstructural studies showed that partition of grain by as-cast state was probably the reason for austenite and ferrite grain size improvement. Considering the experimental results, maximum errors of 14.5% and 7.5% were found in the estimation of ferrite grain size and tensile strength, respectively.

Analysis of mechanical-hydraulic bedload deposition control measures

During floods, the bedload transport of steep headwaters can exceed the hydraulic transport capacity of milder downstream reaches where settlements are often situated. Therefore, sediment retention barriers are typically installed upstream of such sensible areas. These barriers trigger bedload trapping via two control mechanisms, either hydraulic or mechanical. Both deposition controls, pertaining to instream sediment trapping structures, are analyzed experimentally in this study. Bedload trapping by hydraulically controlled barriers is prone to sediment flushing, i.e., the remobilization of formerly deposited sediment, in particular when the barrier is simultaneously under- and overflown. In this case, the remobilization rate is close to the bedload transport capacity of the nonconstricted channel. Mechanical deposition control by screens is in turn sensible to the grain size. Thus, both deposition control concepts may fail, and bedload may be transported downstream at a rate corresponding to the transport capacity of headwaters, thereby endangering urban areas. This study shows that the combination of both deposition control concepts is suitable for improving the control of bedload retention. With this combination, undesired sediment flushing of upstream deposits in the channel caused by insufficient hydraulic control is prevented. Furthermore, the uncertainty related to the estimation of the representative grain size in the design of mechanical control barriers is reduced.

Evaluating Stream Restoration Projects: What Do We Learn from Monitoring?

Two decades since calls for stream restoration projects to be scientifically assessed, most projects are still unevaluated, and conducted evaluations yield ambiguous results. Even after these decades of investigation, do we know how to define and measure success? We systematically reviewed 26 studies of stream restoration projects that used macroinvertebrate indicators to assess the success of habitat heterogeneity restoration projects. All 26 studies were previously included in two meta-analyses that sought to assess whether restoration programs were succeeding. By contrast, our review focuses on the evaluations themselves, and asks what exactly we are measuring and learning from these evaluations. All 26 studies used taxonomic diversity, richness, or abundance of invertebrates as biological measures of success, but none presented explicit arguments why those metrics were relevant measures of success for the restoration projects. Although changes in biodiversity may reflect overall ecological condition at the regional or global scale, in the context of reach-scale habitat restoration, more abundance and diversity may not necessarily be better. While all 26 studies sought to evaluate the biotic response to habitat heterogeneity enhancement projects, about half of the studies (46%) explicitly measured habitat alteration, and 31% used visual estimates of grain size or subjectively judged ‘habitat quality’ from protocols ill-suited for the purpose. Although the goal of all 26 projects was to increase habitat heterogeneity, 31% of the studies either sampled only riffles or did not specify the habitats sampled. One-third of the studies (35%) used reference ecosystems to define target conditions. After 20 years of stream restoration evaluation, more work remains for the restoration community to identify appropriate measures of success and to coordinate monitoring so that evaluations are at a scale capable of detecting ecosystem change.

Cathodoluminescence of YAG:Nd optical nanoceramics in the visible and UV ranges

Results of cathodoluminescence studies of optical YAG:Nd nanoceramics with different microstructure are presented. The composition of the samples was studied by the electron-probe microanalysis. The estimation of the average grain size was performed with the use of scanning electron microscopy and based on X-ray diffraction analysis. Local cathodoluminescence technique was used to collect the emission spectra and decays of emission in the UV and visible range. The “memory effect” in YAG:Nd nanoceramics luminescence was noticed and discussed. In particular, it was observed that the initial electron beam irradiation of sample leads to the increase of luminescence efficiency in the visible and UV ranges. It was confirmed also that the observed effect is long-lasting and remains for years. To understand the mechanism of the effect, the estimation of temperature annealing under continuous irradiation by electron beam was done. The model of memory effect involving trap states was proposed and discussed.

Effect of RF Plasma on Gridded Gate Pt/SiO2/Si MOS Sensor for Detection of Hydrogen

The effect of RF oxygen plasma treatment on SiO2 surfaces has been investigated and compared with nonplasma treated sensors. Eight samples of thermally grown $\sim 120$ A SiO2 film are treated with a different RF O2 plasma power and time. All sensors have been tested for different concentrations of H2 at 25 °C. It is observed that the sensitivity of sensors increases for high duration (8 min) of plasma exposure at 40-W RF plasma power. The sensors treated at 50-W RF plasma for 8- and 12-min duration exhibited the decrease in sensitivity. Surface morphology of plasma treated SiO2 film surfaces has been studied by automic force microscopy (AFM) to have the estimation of porosity, grain size, and surface roughness. The high sensitivity can be attributed to the fact that O2 plasma treatment increases the porosity, grain size, and surface roughness of the SiO2 film. Fixed oxide charge density has also been evaluated as a function of hydrogen concentration for varying exposure time and RF power.

Retrieval of snow physical parameters by neural networks and optimal estimation: case study for ground-based spectral radiometer system

A new retrieval algorithm for estimation of snow grain size and impurity concentration from spectral radiation data is developed for remote sensing applications. A radiative transfer (RT) model for the coupled atmosphere-snow system is used as a forward model. This model simulates spectral radiant quantities for visible and near-infrared channels. The forward RT calculation is, however, the most time-consuming part of the forward-inverse modeling. Therefore, we replaced it with a neural network (NN) function for fast computation of radiances and Jacobians. The retrieval scheme is based on an optimal estimation method with a priori constraints. The NN function was also employed to obtain an accurate first guess in the retrieval scheme. Validation with simulation data shows that a combination of NN techniques and optimal estimation method can provide more accurate retrievals than by using only NN techniques. In addition, validation with in-situ measurements conducted by using ground-based spectral radiometer system shows that comparison between retrieved snow parameters with in-situ measurements is acceptable with satisfactory accuracy. The algorithm provides simultaneous, accurate and fast retrieval of the snow properties. The algorithm presented here is useful for airborne/satellite remote sensing.

Detection of inner core solidification from observations of antipodal PKIIKP

AbstractPKIIKP waves, reflected from the underside of the inner core boundary, are very sensitive to the S velocity in the uppermost 80 km of the inner core at antipodal distances, undergoing a phase change and a factor of 4 amplification as the distance approaches 180°. Modeled PKIIKP waveforms are consistent with a near‐zero shear modulus in the uppermost inner core in a 20–40 km thick patch beneath the eastern equatorial hemisphere. This bright spot of PKIIKP reflection correlates with a thin zone of low P velocity inferred from the complexity of PKIKP waveforms sampling this patch. Estimates of grain sizes from seismic attenuation, the absence of backscattered PKiKP coda in this region, and a prediction for enhanced heat flow through this patch suggest that it is a region of solidification rather than melting.

Electrical resistivity and magnetic properties of electrodeposited nanocrystalline CoFe thin films

Nanocrystalline CoFe thin films were electrodeposited from baths containing sodium citrate as complexing agent. Cyclic voltammogrames of CoFe baths showed that addition of sodium citrate to the electrolytes shifted reduction potential of metals toward more negative values. X-ray diffraction patterns of CoFe thin films deposited at different current densities illustrated a transition from FCC(Co) phase to FCC(Co) + BCC(Fe) phases with increasing applied current density. Estimation of average grain size (D) of CoFe thin films by Scherrer’s equation showed all coatings had nanocrystalline structures. The accuracy of results obtained by Scherrer’s equation was confirmed by transmutation electron microscope images. Study of magnetic properties by vibrating sample magnetometer indicated that reduction in grain size of CoFe films resulted in noticeable decrease in coercivity, according to “D6” law. Moreover, decreasing grain size in CoFe thin films led to reduction in resistivity which could be attributed to scattering of conduction electrons, according to “Scattering Hypotheses”. However, average grain size of nanocrystalline CoFe films had no effect on the saturation magnetization which is mostly controlled by chemical composition. The results showed that increasing iron content in the deposited CoFe films from 17 to 31 at.% caused enhancement of saturation magnetization.

Structure of MoCN films deposited by cathodic arc evaporation

Molybdenum carbonitride (MoCN) coatings were deposited onto HS6-5-2 steel substrate using pure Mo targets in mixed acetylene and nitrogen atmosphere by cathodic arc evaporation. The structural properties of MoCN coatings with different carbon contents (as an effect of the C2H2 flow rate) were investigated systematically. Phase and chemical composition evolution of the coatings were characterized both by the glancing angle of X-ray diffraction (XRD) and wavelength dispersive spectrometry, respectively. These analyses have been supplemented by estimates of grain sizes and stress in the coatings. The XRD results show that the increase in acetylene flow rate causes the formation of molybdenum carbide (MoC) hexagonal phase in the coatings, a reduction of grain size and an increase in internal stress.

Comparative Analysis of Hyperspectral and Multispectral Data for Mapping Snow Cover and Snow Grain Size

Abstract. The present study demonstrates the potential of imaging spectroscopy to produce the snow cover maps and estimation of snow grain size in the Himalayan region. Snow cover maps and snow grain size produce from imaging spectroscopy data were also compared with multispectral imagery (i.e. Landsat 8 and ASTER). Snow grain size was estimated using the snow grain index and compared with the asymptotic radiative transfer (ART) theory method. The overall matching area was 78.29 % among different snow grain size classes using grain index Method and ART method. An attempt has been made to derive the snow grain size using Landsat 8 and ASTER data for the same area. It was found that grain size derived from Landsat 8 and ASTER data show correlation of 81.67 % and 86.34 % respectively. The snow cover maps were produced using Normalized Difference Snow Index (NDSI). Snow cover maps were also produced using ASTER imagery for the same area and compared with Hyperion snow cover maps. The correlation between both snow cover maps were show 91 % correlation.

Effect of concentration substitution on the size factor in Li1 − x Na x NbO3 solid solutions

The article presents the results of a study of the microstructure of Li1 − x Na x NbO3 solid solutions by electron microscopy as a function of the concentration substitution (x = 0, 2, and 3 mol %). The introduction of a small amount of sodium niobate leads to considerable changes in the morphology of the crystal. Estimation of the average grain size shows that the average size decreases from 34.9 μm (for LiNbO3) to 4.94 μm, when 2 mol % NaNbO3 is introduced. A further increase in the concentration of sodium niobate to 3 mol % leads to a decrease in the average grain size to 3.19 μm.

Anisotropy of Earth's inner core intrinsic attenuation from seismic normal mode models

The Earth's inner core, the slowly growing sphere of solid iron alloy at the centre of our planet, is known to exhibit seismic anisotropy. Both normal mode and body wave studies have established that, when the global average is taken, compressional waves propagate faster in the North–South direction than in the equatorial plane. Recent body wave studies also indicate that this fast direction may be more attenuating, and interpret this anisotropic attenuation in terms of anisotropic scattering due to inner core texturing. Here we use the Earth's normal modes to study the attenuation anisotropy of both compressional and shear waves in the inner core. As normal modes have wavelengths several orders of magnitude longer than estimates of inner core grain size, any attenuation anisotropy quantified using normal modes must reflect the anisotropy of intrinsic (viscoelastic) attenuation of the crystalline inner core alloy. By inverting zonal anelastic and elastic normal mode splitting function coefficients of twenty inner core sensitive modes, we construct models of inner core intrinsic attenuation and velocity anisotropy. We find that, for compressional waves, the North–South direction is both fast and more strongly attenuating. The existence of intrinsic inner core attenuation anisotropy can be interpreted in terms of anisotropic Zener relaxation in the metallic alloy comprising the inner core. Such anisotropic Zener relaxation has only been observed in the presence of solute atoms, and is thus entirely consistent with the presence of a few atomic per cent of light elements in the Earth's inner core.

Paleoenvironmental shifts and precipitation variations recorded in tropical maar lake sediments during the Holocene in Southern China

Tropical ocean–atmosphere system exerts powerful control on the precipitation variations around the Pacific Ocean area where interactions among monsoon system, Intertropical Convergence Zone (ITCZ) migration, and other tropical ocean circulations modulate the regional climate changes in centennial-scale. However, little high-resolution information is known about the paleoenvironment changes in this area during the Holocene. In this study, a composite sediment profile, approximately 16 m in length, recovered from Shuangchiling (SCL) maar lake in Hainan Island, northern margin of western tropical Pacific, was selected to investigate the lake-level fluctuations, net precipitation variations, and the influence of the ocean–atmosphere system. Stable isotope (δ13C, δ15N) analyses, total organic carbon (TOC), and total nitrogen (TN) concentration measurements, as well as grain-size estimations revealed a two-stage evolution scenario for the lake dating back to 9 cal. kyr BP. The first stage spans a period of time from ~9 to ~3 cal. kyr BP, once the lake was characterized by shallow or ephemeral conditions. The second stage occurred from 3 to 0.6 cal. kyr BP and was characterized by a deeper water environment with substantial lake-level changes. All climate proxies suggest that the ocean–atmosphere variabilities, such as El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) activities, had a dominant influence on the regional net precipitation (the difference between precipitation and evaporation) and lake-level fluctuations. A three-step change of clay percentage at ~3, ~2.2, and ~1.3 cal. kyr BP correlate well with the ENSO proxy records from the eastern tropical Pacific.