Effect of Fractal Silver Electrodes on Charge Collection and Light Distribution in Semiconducting Organic Polymer Films
Abstract not provided
14 SOLAR ENERGY↗
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Fractal analysis of collision cascades in pulsed-ion-beam-irradiated solids [Collision cascade densities in ion pulsed ion irradiated solids { a fractal approach]
The buildup of radiation damage in ion-irradiated crystals often depends on the spatial distribution of atomic displacements within collision cascades. Although collision cascades have previously been described as fractals, the correlation of their fractal parameters with experimental observations of radiation damage buildup remains elusive. Here, we use a pulsed-ion-beam method to study defect interaction dynamics in 3C-SiC irradiated at 100 °C with ions of different masses. These data, together with results of previous studies of SiC and Si, are analyzed with a model of radiation damage formation which accounts for the fractal nature of collision cascades. Our emphasis is on the extraction of the effective defect diffusion length from pulsed beam measurements. Results show that, for both Si and SiC, collision cascades are mass fractals with fractal dimensions in the range of ~1–2, depending on ion mass, energy, and the depth from the sample surface. Within our fractal model, the effective defect diffusion length is ~10 nm for SiC and ~20 nm for Si, and it decreases with increasing cascade density. These results demonstrate a general method by which the fractal nature of collision cascades can be used to explain experimental observations and predict material’s response to radiation.
36 MATERIALS SCIENCE↗
Fractal dimension of cohesive sediment flocs at steady state under seven shear flow conditions
The morphological properties of kaolin flocs were investigated in a Couette-flow experiment at the steady state under seven shear flow conditions (shear rates of 5.36, 9.17, 14, 24, 31, 41 and 53 s -1 ). These properties include a one-dimensional (1-D) fractal dimension (D 1 ), a two-dimensional (2-D) fractal dimension (D 2 ), a perimeter-based fractal dimension (D pf ) and an aspect ratio (AR). They were calculated based on the projected area (A), equivalent size, perimeter (P) and length (L) of the major axis of the floc determined through sample observation and an image analysis system. The parameter D 2 , which characterizes the relationship between the projected area and the length of the major axis using a power function, A ∝ L D 2 , increased from 1.73 ± 0.03, 1.72 ± 0.03, and 1.75 ± 0.04 in the low shear rate group (G = 5.36, 9.17, and 14 s -1 ) to 1.92 ± 0.03, 1.82 ± 0.02, 1.85 ± 0.02, and 1.81 ± 0.02 in the high shear rate group (24, 31, 41 and 53 s -1 ), respectively. The parameter D 1 characterizes the relationship between the perimeter and length of the major axis by the function P ∝ L D 1 and decreased from 1.52 ± 0.02, 1.48 ± 0.02, 1.55 ± 0.02, and 1.63 ± 0.02 in the low shear group (5.36, 9.17, 14 and 24 s -1 ) to 1.45 ± 0.02, 1.39 ± 0.02, and 1.39 ± 0.02 in the high shear group (31, 41 and 53 s -1 ), respectively. The results indicate that with increasing shear rates, the flocs become less elongated and that their boundary lines become tighter and more regular, caused by more breakages and possible restructurings of the flocs. The parameter D pf , which is related to the perimeter and the projected area through the function , decreased as the shear rate increased almost linearly. The parameter AR, which is the ratio of the length of the major axis and equivalent diameter, decreased from 1.56, 1.59, 1.53 and 1.51 in the low shear rate group to 1.43, 1.47 and 1.48 in the high shear rate group. These changes in D pf and AR show that the flocs become less convoluted and more symmetrical and that their boundaries become smoother and more regular in the high shear rate group than in the low shear rate group due to breakage and possible restructuring processes. To assess the effects of electrolyte and sediment concentration, 0.1 mol/L calcium chloride (CaCl 2 ) and initial sediment concentration from 7.87 × 10 -5 to 1.57 × 10 -5 were used in this preliminary study. The addition of electrolyte and increasing sediment concentration could produce more symmetrical flocs with less convoluted and simpler boundaries. In addition, some new information on the temporal variation of the median size of the flocs during the flocculation process is presented.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Fractal textured surfaces for high temperature corrosion mitigation in molten salts
Not provided.
Energy & Fuels↗
Large-Scale Structure of Chromatin: A Fractal Globule or a Logarithmic Fractal?
Two physical models are considered to describe the large-scale structure of chromatin in the nucleus of a biological cell in the interphase state: a fractal globule model and a logarithmic fractal model. Based on the classification of fractal objects developed by the small-angle neutron scattering (SANS) method, it is shown that the fractal globule model does not satisfy the experimental data on small-angle neutron scattering by the nuclei of biological cells. Conversely, the logarithmic fractal model well describes the experimental data on SANS and, hence, provides a good approximation to describe the large-scale structure of chromatin. The logarithmic fractal model predicts that the nuclear space is exactly half-filled with chromatin, and the second half consists of interchromatin voids filled with nucleoplasma in which various nuclear processes occur. Thus, two opposing trends are balanced in the structural organization of chromatin: an increase in the surface area of chromatin in the cell nucleus (accessibility to external agents) and a decrease in the volume occupied by chromatin (compactness of the nucleus).
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
The Calculation of Fractal Dimension in the Presence of Non-Fractal Clutter
The area of information processing has grown dramatically over the last 50 years. In the areas of image processing and information storage the technology requirements have far outpaced the ability of the community to meet demands. The need for faster recognition algorithms and more efficient storage of large quantities of data has forced the user to accept less than lossless retrieval of that data for analysis. In addition to clutter that is not the object of interest in the data set, often the throughput requirements forces the user to accept "noisy" data and to tolerate the clutter inherent in that data. It has been shown that some of this clutter, both the intentional clutter (clouds, trees, etc) as well as the noise introduced on the data by processing requirements can be modeled as fractal or fractal-like. Traditional methods using Fourier deconvolution on these sources of noise in frequency space leads to loss of signal and can, in many cases, completely eliminate the target of interest. The parameters that characterize fractal-like noise (predominately the fractal dimension) have been investigated and a technique to reduce or eliminate noise from real scenes has been developed. Examples of clutter reduced images are presented.
Herren, Kenneth A.↗
Fractal breakage of porous carbonate sand particles: Microstructures and mechanisms
In situ, three-dimensional (3D) characterizations of particle breakage in porous carbonate sands are presented, for the first time, with synchrotron-based micro computed tomography. Evolution of grain-scale characteristics are identified and quantified via elaborate image processing and topology analyses. The sequential 3D images reveal distinctly different fracture mechanisms for carbonate sands from silica sands. The angular shape of carbonate sand particles facilitates bending fracture, and particles with a lower sphericity and a higher porosity are more prone to break. 3D crack networks extracted from fractured particles imply considerable cleavage along initial pores. The fractal dimension of crack networks increases with external loading due to crack branching via cleavage. The resultant fragment size distribution also appears fractal and the fractal feature is valid down to the breakage limit of calcium carbonate. Crack propagation along the initial pores reduces the energy barrier for particle breakage and thus fracture strength of particles
Carbonate sands↗
Fractal Model for Drag Reduction on Multiscale Nonwetting Rough Surfaces
Rough surfaces in contact with a flow of fluid exhibit alternating no-slip and free shear boundary conditions at the solid–liquid and air–liquid interfaces, respectively, thereby potentially offering drag reduction benefits. The balance between the dynamic pressure in the flow and the restoring capillary pressure in the interasperity spaces determines the stability of the Cassie state of wettability and is a function of the relative extent of no-slip and free shear regions per unit surface area. In the present study, using a fractal representation of rough surface topography, an analytical model is developed to quantify the stability of the Cassie state of wettability as well as drag reduction and the friction factor for laminar flow in a rectangular channel between nonwetting multiscale rough surfaces. A systematic study is conducted to quantify the effects of fractal parameters of the surfaces and the flow Reynolds number on drag reduction and the friction factor. The studies are used to develop friction factor curves extending the classical Moody diagram to hydrophobic and superhydrophobic surfaces. On the basis of the studies, regime maps are derived for estimating the extent of drag reduction offered by hydrophobic and superhydrophobic surfaces, revealing that superhydrophobic surfaces do not always offer the best drag reduction performance. The application of the fractal model to practical topographies of nonwetting surfaces of copper, aluminum, and zinc oxide fabricated via electrodeposition and etching is also discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A hybrid of fractal image coding and fractal dimension for an efficient retrieval method
Fractal image coding (FIC) based on the inverse problem of an iterated function system plays an essential role in several areas of computer graphics and in many other interesting applications. Through FIC, an image can be transformed to compressed representative parameters and be expressed in a simple geometric way. Dealing with digital images requires storing a large number of images in databases, where searching such databases is time consuming. Therefore, finding a new technique that facilitates this task is a challenge that has received increasing attention from many researchers. In this study, a new method that combines fractal dimension (FD) which is an indicator of image complexity with the FIC scheme is proposed. Classifying images in databases according to their texture by using FD helps reduce the retrieval time of query images. The validity of the proposed method is evaluated using geosciences images. Result shows that the method is computationally attractive.
97 MATHEMATICS AND COMPUTING↗
Optical properties and radiative forcing of fractal-like tar ball aggregates from biomass burning
Tar balls are frequently found in slightly aged biomass burning plumes. They are spherical in shape, have diameters between ~100 and 300 nm, are amorphous and composed mostly of oxygen and carbon. Tar balls are light absorbing and considered to be a component of brown carbon. Tar balls have been typically reported and analyzed as individual spheres; however, in a recent study, we reported the presence of significant fractions of fractal-like tar ball aggregates in fire plumes from different geographical locations. Aggregation affects the optical properties of particles; therefore, we use T-Matrix and Lorenz-Mie simulations to explore the effects of aggregation on the tar balls’ optical properties in the 350 – 1150 nm wavelength range. We also evaluate the effects of different index of refraction values available from the literature, different monomer numbers, and monomer sizes, as these are key factors determining the aggregates optical properties. Furthermore, we estimate the direct radiative forcing for low and high surface albedos. The single scattering albedo of aggregates exceed by up to 77% that of individual tar balls. The hemispherical upscatter fraction of tar ball aggregates are more than 100% larger than for individual tar balls in many cases. The top of the atmosphere simple forcing efficiency over dark surfaces shows large variabilities with differences up to ~53% between the tar ball aggregates and individual tar balls. These results demonstrate that aggregation of tar balls can have a significant impact on their optical properties and radiative forcing.
Tar balls, aggregates, brown carbon, biomass burni↗
Fractal-like Tar Ball Aggregates from Wildfire Smoke
Explore the source record for details and available documents.
aerosol, biomass burning↗
Applications of Fractal Analytical Techniques in the Estimation of Operational Scale
The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.
Emerson, Charles W.↗
Multi-Scale Fractal Analysis of Image Texture and Pattern
Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.
Emerson, Charles W.↗
Order-fractal transitions in abstract paintings
In this study, we determined the degree of order for 22 Jackson Pollock paintings using the Hausdorff–Besicovitch fractal dimension. Based on the maximum value of each multi-fractal spectrum, the artworks were classified according to the year in which they were painted. It has been reported that Pollock’s paintings are fractal and that this feature was more evident in his later works. However, our results show that the fractal dimension of these paintings ranges among values close to two. We characterize this behavior as a fractal-order transition. Based on the study of disorder-order transition in physical systems, we interpreted the fractal-order transition via the dark paint strokes in Pollock’s paintings as structured lines that follow a power law measured by the fractal dimension. We determined self-similarity in specific paintings, thereby demonstrating an important dependence on the scale of observations. We also characterized the fractal spectrum for the painting entitled Teri’s Find. We obtained similar spectra for Teri’s Find and Number 5, thereby suggesting that the fractal dimension cannot be rejected completely as a quantitative parameter for authenticating these artworks. -- Highlights: •We determined the degree of order in Jackson Pollock paintings using the Hausdorff–Besicovitch dimension. •We detected a fractal-order transition from Pollock’s paintings between 1947 and 1951. •We suggest that Jackson Pollock could have painted Teri’s Find.
97 MATHEMATICS AND COMPUTING↗