Mean Separation Distance Research Articles

Multivariate analysis of morphometric traits of the horse ecotypes reared in highlands of Bale Zone, Ethiopia

This study was conducted to evaluate morphometric traits of horse ecotypes reared in four districts of the Bale highlands, southeastern Ethiopia. Twenty-seven morphometric traits were measured from 500 horses (294 males and 206 females) of both sexes. Data were analyzed using SAS 2012. This study revealed that certain traits, such as head length, loin length, bi-ischial width, and sternum height of horses were similar. However, significant differences (p < 0.0001, p < 0.01, p < 0.05) were observed in other traits across the districts. All traits were affected by age (p < 0.05) except rump width and canon perimeter. All 27 morphometric traits were subjected to STEPDISC analysis, of which 21 had the best discriminating power. The uppermost distances of 32.2 and, 28.8 were reported between the Agarfa and Dinsho and, Agarfa and Sinana horse populations, respectively. Mean separation distance among districts ranges from -1.75 to 3.57, -2.42 to 2.43, and -1.61 to 0.92 for CAN1, CAN2 and CAN3, respectively. The quadratic discriminate function classified 95.2, 94.4, 96.0, and 96.8 % of the sampled horses into source populations of the Dinsho, Agarfa, Sinana, and Goba districts, respectively. In addition, the cross-validation summary revealed reduced consistency of membership among each districts with 5 % average success rates and 4, 8, 4, and 4 % for the Dinsho, Agarfa, Sinana, and Goba districts, respectively. Therefore, the presence of variation in morphometric traits within the Bale Highland horse ecotypes has the potential for selection and further genetic interventions.

Effect of ammonia on the soot properties in a laminar ethylene flame

Ammonia, as a non-carbon fuel, has been regarded as an alternative fuel for combustion. In this investigation, the effect of ammonia on the soot properties such as morphology, nanostructure, graphitization degree, surface functional groups, and oxidation energy in a laminar ethylene flame has been studied using different detection techniques at 15 mm and 30 mm height above burner (HAB). The results show that the soot basically appears as a chain-like aggregate, which is composed of several tens of primary particles, and it also finds that the use of ammonia decreases diameters of primary particles, the diameter of A60 (ethylene with 60 ml/min ammonia) decreases by 28.0 % compared with that of A0 (ethylene without ammonia) at 30 mm HAB. Moreover, the addition of ammonia promotes the regularity degree of soot, slightly increases the mean separation distance at 30 mm HAB, and decreases the mean fringe tortuosity both of 15 mm and 30 mm HAB based on the results from high-resolution transmission electron microscope (HRTEM). Meanwhile, the ratio of ID1/IG, ID3/IG, and ID4/IG has been used to evaluate the degree of graphitization, it indicates that the use of ammonia increases the degree of graphitization, but both of the hybridization degree of sp3 and sp2 in amorphous carbon and carbon atoms decrease. Furthermore, the proportion of oxygenated functional groups decreases with the increase of ammonia. The highest content of C-OH functional group is about 9 % to 15 %, followed by C=O and O-C=O functional groups, which is about 3 % to 6 % and 2.5 % to 3.5 %, respectively. Eventually, the oxidation process of the particles has been analyzed, it is indicated that the use of ammonia decreases the oxidation activity, which is more difficult to oxidize.

Effects of incoming particle energy and cluster size on the G-value of hydrated electrons

In hydrated electron (e−aq) dosimetry, absorbed radiation dose to water is measured by monitoring the concentration of radiation-induced e−aq. However, to obtain accurate dose, the radiation chemical yield of e−aq, G(e−aq), is needed for the radiation quality/setup under investigation. The aim of this study was to investigate the time-evolution of the G-values for the main generated reactive species during water radiolysis using GEANT4-DNA. The effects of cluster size and linear energy transfer (LET) on G(e−aq) were examined. Validity of GEANT4-DNA for calculation of G(e−aq) for clinically relevant energies was studied. Three scenarios were investigated with different phantom sizes and incoming electron energies (1 keV to 1 MeV). The time evolution of G(e−aq) was in good agreement with published data and did not change with decreasing phantom size. The time-evolution of the G-values increases with increasing LET for all radiolytic species. The particle tracks formed with high-energy electrons are separated and the resulting reactive species develop independently in time. With decreasing energy, the mean separation distance between reactive species decreases. The particle tracks might not initially overlap but will overlap shortly thereafter due to diffusion of reactive species, increasing the probability of e−aq recombination with other species. This also explains the decrease of G(e−aq) with cluster size and LET. Finally, if all factors are kept constant, as the incoming electron energy increases to clinically relevant energies, G(e−aq) remains similar to its value at 1 MeV, hence GEANT4-DNA can be used for clinically relevant energies.

Structure transitions in arrays of point-vortices upon free space propagation

We study the free space propagation of arrays of N × N point vortices with equal unitary topological charge embedded in a Gaussian beam, initially distributed into either a square lattice or a disordered array with the same mean vortex density and separation. The far-field patterns and the near-field evolution are analyzed as a function of different control parameters, such as the size of the carrier beam, the number of vortices, the mean separation distance among them P, and a geometrical parameter S p , defined as the ratio of the size of the array to the size of the host beam. The value of S p turns out to be determinant for the final spatial distribution of the optical vortices in the far-field pattern and also plays a very relevant role in the near-field evolution. While the initial array structure is basically preserved, rotated and scaled up when , the vortices redistribute forming a circumference around the propagation axis for , depleting most of the central intensity, even if the vortex density is far lower than the previously predicted limit for depletion. In the near field, we find an expression for the rotation angle of the whole structure when preserved, as a function of the propagation distance, which depends on P, but it is around eight-fold larger than the Gouy phase shift of the host. Also, we observe the formation of a high intensity ring pattern, whose radius is independent of the size of the carrier and the initial distribution of vortices, but it is only determined by the number of vortices. We verified our numerical results with experiments, finding a very good agreement between them.

Closely spaced co-rotating helical vortices: long-wave instability

We consider as base flow the stationary vortex filament solution obtained by Castillo-Castellanos et al. (Phys. Rev. Fluids, vol. 6, 2021, 114701) in the far wake of a rotor with tip-splitting blades. The cases of a single blade and of two blades with a hub vortex are studied. In these solutions, each blade generates two closely spaced co-rotating tip vortices that form a braided helical pattern in the far wake. The long-wave stability of these solutions is analysed using the same vortex filament framework. Both the linear spectrum and the linear impulse response are considered. We demonstrate the existence of different types of instability modes. A first type corresponds to the local pairing of consecutive turns of the helical pattern, which is well described by the instability of a uniform helical vortex with a core size given by the mean separation distance of the vortices in the pair. A second type corresponds to the pairing of consecutive turns of the vortex pair and is observed only for densely braided patterns, which is well described by the instability of two interlaced helical vortices by straightening out the baseline helix. A third type of unstable modes modifies the separation distance between the vortices in each pair and amplifies specific (linear) wavelengths. These unstable modes also spread spatially with a weaker rate.

Evaluating high-frequency radar data assimilation impact in coastal ocean operational modelling

Abstract. The impact of the assimilation of HFR (high-frequency radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consist of assimilating (i) sea surface temperature, sea level anomaly, and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset, two different initialization methods are assessed: (a) restarting directly from the analysis after the assimilation or (b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provide the best results, reducing by 53 % the average separation distance between drifters and virtual particles after the first 48 h of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities with a reduction of the mean separation distance by around 48 %. Results show that the integration of HFR observations in the data assimilation system enhances the prediction of surface currents inside the area covered by both antennas, while not degrading the correction achieved thanks to the assimilation of generic data sources beyond it. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step.

Impact of Polymer Residue Level on the In-Plane Thermal Conductivity of Suspended Large-Area Graphene Sheets.

The presence of polymer transfer residues on graphene surfaces is a major bottleneck to overcome for the commercial and industrial viability of devices incorporating graphene layers. In particular, how clean the surface must be to recover high (>2500 W/mK) thermal conductivity and maximize the heat spreading capability of graphene for thermal management applications remains unclear. Here, we present the first systematic study of the impact of different levels of polymer residues on the in-plane thermal conductivity (κr) of single-layer graphene (SLG) fabricated by chemical vapor deposition (CVD). Control over the quantity of surface residue was achieved by varying the length of time each sample was rinsed in toluene to remove the poly(methyl methacrylate) (PMMA) support layer. The level of residue contamination was assessed using atomic force microscopy (AFM) and optical characterization. The thermal conductivity of the suspended SLG was measured using an optothermal Raman technique. We observed that the presence of polymer surface residue has a significant impact on the thermal properties of SLG, with the most heavily contaminated sample exhibiting a κr as low as (905 +155/-100) W/mK. Even without complete eradication of surface residues, a thermal conductivity as high as (3100 +1400/-900) W/mK was recovered, where the separation between adjacent clusters was sufficiently large (>700 nm). The proportion of the SLG surface covered by residues and the mean separation distance between clusters were found to be key factors in determining the level of κr suppression. This work has important implications for future large-scale graphene fabrication and transfer, particularly where graphene is to be used as a heat spreading layer in devices. The possibility of new opportunities for manipulation of the thermal properties of SLG via PMMA nanopatterning is also raised.

819 molecular knot: a theoretical analysis of the electronic structure using an ONIOM approach.

The present work analyzes the electronic and molecular properties of the 819 ([Fe(II)4]Cℓ) and metal-free knot ligand complexes obtained from X-ray crystal structure of molecular 819 knot complex [Fe(II)4(PF6)7]Cℓ. The studies were theoretically investigated by means of DFT, TD-DFT, and ONIOM approaches. Basis sets functions from all-electron calculations for bromine, iodine, and iron atoms were adapted to be used along with relativistic effective core potential, while H, C, N, O, and Cℓ atoms were described by Pople basis sets. The diffusion effect of halogen into the 819 cavity, UV-Vis, and Electronic Circular Dichroism spectra were also analyzed. All calculations were performed using solvent effect through the SCRF/SMD model and dispersion effects by Grimme methodology. The value of mean separation distance between Cℓ and iron atom (7.218 Å) is in good agreement with X-ray experimental result (7.258 Å). Circular dichroism spectrum of metal-free 819 knot ligand was calculated and the maximum absorption in 262 nm, Δ𝜖 obtained was 67 L mol- 1 cm- 1. These results are qualitatively similar to those obtained experimentally, 295 nm and 80 L mol- 1 cm- 1, respectively. In this study, we report the electronic and molecular properties of the 819 ([Fe(II)4]Cl and metal-free knot ligand complexes and compare with the results obtained from X-ray crystallographic data of 819 knot complex [Fe(II)4(PF6)7]Cl. The 819 knot were investigated by means of DFT, TD-DFT, and ONIOM approaches. Basis sets functions from all-electron for Br, I, and Fe atoms were adapted to be used along with relativistic effective core potential, while H, C, N, O, and Cl atoms were described by Pople basis sets. The objective was to understand the stability of the 819 knot as a function of the substitution of the central halogen atom (Cl), and the signal in the circular dichroism spectra. From the equilibrium geometries, we have obtained good results for values of the bond distance, bond angle, and dihedral angle along the molecular structure when these variables are compared with the results obtained from X-ray data. The diffusion effect of halogen into the 819 cavity, UV-Vis, and Electronic Circular Dichroism spectra was also analyzed. Circular dichroism spectrum of metal-free 819 knot ligand was calculated, and the maximum absorption is in good agreement with the experimental value. The ONIOM methodology combined with the relativistic effective core potential and the atomic basis sets provide good results for systems with a complex topology, such as knots.

The Stokes drift in ocean surface drift prediction

ABSTRACT The importance of explicitly resolving the Stokes drift in ocean surface drift modelling is demonstrated by comparing four models with 58,612 observational data points obtained from undrogued drifting buoys in the Estuary and Gulf of St. Lawrence, Canada. Drift model inputs are obtained from regional atmosphere and ocean circulation, and spectral wave models. The control drift model considers near-surface currents provided by the top grid cell of the ocean circulation model, which is 5-m thick, and a correction term proportional to the near-surface wind. The three other drift models account for the unresolved near-surface current shear by extrapolating the near-surface currents to the surface assuming Ekman dynamics. Two of these models consider explicitly the Stokes drift, with and without a wind correction term. Proposed models reduce the mean separation distance between observed and predicted trajectories by 34–40% relative to the control model, on average, for forecast times ranging from 3 to 72 h. The best improvement with respect to all metrics used is, however, obtained for the model that takes into account the near-surface shear correction and the Stokes drift, without any wind correction term (skill score of 0.93 after 3 h and 0.81 after 72 h).

Spatial Distribution and Scaling Properties of Lidar‐Derived Snow Depth in the Extratropical Andes

AbstractWe characterize elevational gradients, probability distributions, and scaling patterns of lidar‐derived snow depth at the hillslope scale along the extratropical Andes. Specifically, we analyze snow depth maps acquired near the date of maximum accumulation in 2018 at three experimental sites: (i) the Tascadero catchment (31.26°S, 3,270–3,790 m), (ii) the Las Bayas catchment (33.31°S, 3,218–4,022 m); and (iii) the Valle Hermoso (VH) catchment (36.91°S, 1,449–2,563 m). We examine two subdomains in the latter site: one with (VH West) and one without (VH East) shrub cover. The comparison across sites reveals that elevational gradients are site‐dependent, and that the gamma and normal distributions are more robust than the lognormal function to characterize the spatial variability of snow depth. Multiscale behavior in snow depth is obtained in all sites, with up to three fractal regimes, and the magnitude of primary scale breaks is found to be related to the mean separation distance between local snow depth peaks. The differences in snow depth fractal parameters between VH West—the only vegetated subdomain—and the remaining sites suggest that local topographic and land cover properties are dominant controls on the spatial structure of snow, rather than average hydroclimatic conditions. Overall, the results presented here provide, for the first time, insights into the spatial structure of snow depth along the extratropical Andes Cordillera, showing notable similarities with other mountain regions in the Northern Hemisphere and providing guidance for future snow studies.

An intercomparison of subtropical cut-off lows in the Southern Hemisphere using recent reanalyses: ERA-Interim, NCEP-CFRS, MERRA-2, JRA-55, and JRA-25

Four recent reanalysis products ERA-Interim, NCEP-CFSR, MERRA-2 and JRA-55 are evaluated and compared to an older reanalysis JRA-25, to quantify their confidence in representing Cut-off lows (COLs) in the Southern Hemisphere. The climatology of COLs based on the minima of 300-hPa vorticity (xi_{300}) and 300-hPa geopotential (Z_{300}) provides different perspectives of COLs and contributes to the understanding of the discrepancies observed in the literature regarding their numbers and seasonality. The COLs compare better among the newest reanalyses than compared to the older reanalysis JRA-25. The difference in number between the latest reanalyses are generally small for both xi_{300} and, with more COLs identified in xi_{300} than in Z_{300} for all reanalyses. The spatial differences observed between the newest reanalyses are mainly due to differences in the track lengths, which is larger in ERA-Interim and JRA-55 than in NCEP-CFSR and MERRA-2, resulting in disparities in the track density. This is likely due to the difference in the assimilation data system used in each reanalysis product. The largest differences in intensities occur in the xi_{300}, because this field is very sensitive to the reanalysis resolution. The mean separation distance of the COLs that match between the latest reanalyses are generally small, while the older JRA-25 has a broader distribution and larger number of matches with relatively large distances, indicating larger uncertainties in location of COLs. The results show significant improvements for the most recent reanalyses compared to the older JRA-25 reanalysis, indicating a progress in representing the COL properties.

On the dynamics of the lyophobic colloids

According to the standard theory, a spatially-extended (diffuse) double layer is assumed to occur in charged colloids (suspensions), leading to repulsive forces that might compensate, at relevant distances, the attractive molecular forces. It is shown in this paper that, in contrast with this standard double-layer theory, the electric interaction of the ions and the charged colloidal particles requires the application of the cohesion theory of electrically-interacting particles, which may lead to stabilization, or even aggregation of the colloid, independently of attractive molecular forces. The screened two-particle interaction which occurs in this case (in the dilute limit) is attractive at long distances and repulsive at short distances, with a negative minimum. Many-particle forces occur over short distances, which complicate considerably the situation. Solid and liquid phases are identified here in charged colloids (and even a non-ideal gaseous phase with attractive interaction), the equilibrium mean separation distance between the particles is estimated and the transition between various phases is discussed.

SPONTANEOUS IMBIBITION OF A WETTING FLUID INTO A FRACTURE WITH OPPOSING FRACTAL SURFACES: THEORY AND EXPERIMENTAL VALIDATION

Spontaneous imbibition (SI) is a capillary-driven flow process, in which a wetting fluid moves into a porous medium displacing an existing non-wetting fluid. This process likely contributes to the loss of fracking fluids during hydraulic fracturing operations. It has also been proposed as a method for an enhanced recovery of hydrocarbons from fractured unconventional reservoirs. Numerous analytical and numerical approaches have been employed to model SI. Invariably, these idealize a fracture as the gap formed between parallel flat surfaces. In reality, rock fracture surfaces are rough over multiple scales, and this roughness will influence the contact angle and rate of fluid uptake. We derived an analytical model for the early-time SI behavior within a fracture bounded by parallel impermeable surfaces with fractal roughness assuming laminar flow. The model was tested by fitting it to experimental data for the SI of deionized water into air-filled rock fractures. Twenty cores from two rock types were investigated: a tight sandstone (Crossville) and a gas shale (Mancos). A simple Mode I longitudinal fracture was produced in each core by compressive loading between parallel flat plates using the Brazilian method. Half of the Mancos cores were fractured perpendicular to bedding, while the other half were fractured parallel to bedding. The two main parameters in the SI model are the mean separation distance between the fracture surfaces, [Formula: see text], and the fracture surface fractal dimension [Formula: see text]. The [Formula: see text] was estimated for each core by measuring the geometric mean fracture aperture width through image analysis of the top and bottom faces, while [Formula: see text] was estimated inversely by fitting the SI model to measurements of water uptake obtained using dynamic neutron radiography. The [Formula: see text] values ranged from 45[Formula: see text][Formula: see text]m to 190[Formula: see text][Formula: see text]m, with a median of 93[Formula: see text][Formula: see text]m. The SI model fitted the height of uptake versus time data very well for all of the rock cores investigated; medians of the resulting root mean squared errors and coefficients of determination were 0.99[Formula: see text]mm and 0.963, respectively. Estimates of [Formula: see text] ranged from 2.04 to 2.45, with a median of 2.24. Statistically, all of the [Formula: see text] values were significantly greater than two, confirming the fractal nature of the fracture surfaces. Future research should focus on forward prediction through independent measurements of [Formula: see text] and extension of the existing SI model to late times (through the inclusion of gravity) and fractures with permeable surfaces.

A registration method for improving quantitative assessment in probabilistic diffusion tractography

Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible – determining where tracts “should” lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity.We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (−35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts “peak-to-peak” is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2 mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts.We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.

How to evaluate the quality of coarse‐resolution DEM‐derived drainage networks

AbstractThe quality of digital elevation model (DEM)‐derived river drainage networks (RDNs) is influenced by DEM quality, basin physical characteristics, scale, and algorithms used; these factors should not be neglected. However, few research studies analyse the different evaluation approaches used in the literature with respect to adequacy, meaning of the results, advantages, and limitations. Focusing on coarse‐resolution networks, this paper reviews the use of these techniques and offers new insights on these issues. Additionally, we propose adaptations for selected metrics and discuss distinct interpretations for the evaluation of RDNs derived at different spatial resolutions (1, 5, 10, 20, and 30 km) considering the Uruguay River basin (206,000 km2) as a case study. The results demonstrate that lumped basin/river characteristics and basin delineation analysis should not be used as evaluation criteria for RDN quality; however, some of these metrics offer useful complementary information. Percentage of the DEM‐derived RDN within a uniform buffer placed around a river network considered as reference and mean separation distance between these two networks are more suitable metrics, but the former is insensitive to serious errors. The change in reference from a fine‐scale network to a coarse‐resolution manual tracing network significantly augments the discrepancy of these largest errors when the mean distance metric was applied, and visual comparison analysis is necessary to interpret the results for other metrics. We recommend the use of the mean distance metric in combination with a detailed visual assessment, the importance of which increases as the resolution coarsens. In both cases, the impact of network quality can be further refined by quantifying the basin shape and river length errors.

Looking for new emperor penguin colonies? Filling the gaps

Detecting and predicting how populations respond to environmental variability are crucial challenges for their conservation. Knowledge about the abundance and distribution of the emperor penguin is far from complete despite recent information from satellites. When exploring the locations where emperor penguins breed, it is apparent that their distribution is circumpolar, but with a few gaps between known colonies. The purpose of this paper is therefore to identify those remaining areas where emperor penguins might possibly breed. Using the locations of emperor penguin breeding colonies, we calculated the separation distance between each pair of geographically adjacent colonies. Based on mean separation distances between colonies following a circumpolar distribution, and known foraging ranges, we suggest that there may yet be six undiscovered breeding locations with half of these in Eastern and the remainder in Western Antarctica. Productivity in these regions suggests that food resources are likely to sustain emperor penguin populations.Our analysis highlights a fundamental requirement, that in order to predict how species might respond to regional climate change, we must better understand their biogeography and the factors that lead to their occupation of particular sites. Regarding emperor penguins, remote sensing should target the identified gaps apparently devoid of penguins in order to update the total number of colonies, to re-evaluate both the regional and global population of emperor penguins, and to gain a better understanding of their biogeography.

Self-organized growth and magnetic properties of epitaxial silicide nanoislands

Self-organized transition-metal (Ni and Fe) and rare-earth (Er) silicide nanostructures were grown on Si(111) and Si(001) surfaces under low coverage conditions, in a “solid phase” and “reactive deposition” epitaxial regimes. Island evolution was continuously monitored in-situ, using real-time scanning tunneling microscopy and surface electron diffraction. After anneal of a Ni/Si(111) surface at 700°C, we observed small hemispherical Ni-silicide nanoislands ∼10nm in diameter decorating surface steps in a self-ordered fashion and pinning them. Fe-silicide nanoislands formed after a 550°C anneal of a Fe-covered surface, were also self-ordered along the surface step-bunches, however were significantly larger (∼70×10nm) and exhibited well-developed three-dimensional polyhedral shapes. Ni-silicide islands were sparsely distributed, separated by about ∼100nm from one another, on average, whereas Fe-silicide islands were more densely packed, with only ∼50nm mean separation distance. In spite of the above differences between both types of island in size, shape, and number density, the self-ordering in both cases was close to ideal, with practically no islands nucleated on terraces. Superconducting quantum interference device magnetometry showed considerable superparamagnetism, in particular in Fe-silicide islands with ∼1.9μB/Fe atom, indicating stronger ferromagnetic coupling of individual magnetic moments, contrary to Ni-silicide islands with the calculated moments of only∼0.5μB/Ni atom. To elucidate the effects of the island size, shape, and lateral ordering on the measured magnetic response, we have controllably changed the island morphology by varying deposition methods and conditions and even using differently oriented Si substrates. We have also begun experimenting with rare-earth silicide islands. In the forthcoming experiments we intend to compare the magnetic response of these variously built and composed islands and correlate between their composition, crystal and morphological characteristics, and the resultant magnetic properties.

Extraction of thermal contact conductance of metal–metal contacts from scale-resolved direct numerical simulation

The thermal contact conductance (TCC) between two conforming metallic rough surfaces was extracted from scale-resolved direct numerical simulation (DNS) of thermal transport across the interface. To compute thermal transport across the interface, microscale models of the interface geometry were created by stochastically reconstructing the topography of the two metallic surfaces, followed by generation of meshes that resolved all fine-scale features of the interface, including the air pockets. Steady state conjugate heat conduction computations were then conducted, and the TCC values were extracted and expressed as a function of the applied pressure (which translates into a mean separation distance) and the mean interface temperature. When compared with experimental data, the extracted TCC values were found to be in good agreement, thereby validating the approach. To lend practical value to the methodology and data presented in this paper, a relationship was also established between the extracted TCC and the number of contacts between the two surfaces. Further, it was shown that the number of contacts generated using surface reconstruction (numerically computed) correlates well with the theoretically calculated number of contacts using the joint probability distributions of the asperity heights on the two surfaces. The implication of these relationships is that irrespective of the actual topography of the surface, for a given pressure (separation distance) and metallic pair combination, the TCC can be estimated from the correlations presented in this paper (TCC versus number of contacts) without the need to conduct any additional numerical computations.

Optical metabolic imaging quantifies heterogeneous cell populations.

The genetic and phenotypic heterogeneity of cancers can contribute to tumor aggressiveness, invasion, and resistance to therapy. Fluorescence imaging occupies a unique niche to investigate tumor heterogeneity due to its high resolution and molecular specificity. Here, heterogeneous populations are identified and quantified by combined optical metabolic imaging and subpopulation analysis (OMI-SPA). OMI probes the fluorescence intensities and lifetimes of metabolic enzymes in cells to provide images of cellular metabolism, and SPA models cell populations as mixed Gaussian distributions to identify cell subpopulations. In this study, OMI-SPA is characterized by simulation experiments and validated with cell experiments. To generate heterogeneous populations, two breast cancer cell lines, SKBr3 and MDA-MB-231, were co-cultured at varying proportions. OMI-SPA correctly identifies two populations with minimal mean and proportion error using the optical redox ratio (fluorescence intensity of NAD(P)H divided by the intensity of FAD), mean NAD(P)H fluorescence lifetime, and OMI index. Simulation experiments characterized the relationships between sample size, data standard deviation, and subpopulation mean separation distance required for OMI-SPA to identify subpopulations.

A comparative study of the physical properties of in-cylinder soot generated from the combustion of n-heptane and toluene/n-heptane in a diesel engine

This study examines the similarities and dissimilarities in the physical properties of in-cylinder soot obtained during combustion of n-heptane and a toluene/n-heptane mixture (TRF20, 20% toluene by volume) in a heavy-duty diesel engine. A total cylinder sampling system was used to sample the in-cylinder soot during different combustion phases. For each sample, the morphology, size, fractal dimension and nanostructure of the soot particles were analyzed using high-resolution transmission electron microscopy and Raman scattering spectrometry. The oxidation reactivity of soot particles was also evaluated in terms of apparent activation energy using thermogravimetric analysis. Throughout the combustion process, soot aggregates from the combustion of TRF20 generally exhibited more primary particles and larger-sized clusters than the n-heptane soot aggregates. Despite the different fuel formulations, both n-heptane and TRF20 showed similar trends during the combustion process in terms of changes in fractal dimension of soot aggregates, mean primary particle size and nanostructure (as characterized by fringe length, separation distance and tortuosity). The presence of toluene, however, led to a decrease in the fractal dimensions of the aggregates and a concurrent increase in the mean size of primary particles. Moreover, in the same combustion stages, the mean fringe length for the TRF20 soot was smaller than that for the n-heptane soot, while the mean separation distance and tortuosity for the TRF20 soot were both larger than those for the n-heptane soot. Relative to the n-heptane soot, the TRF20 soot had less graphitic organization and lower resistance to oxidation.