稳恒磁场下金属电沉积枝晶生长的模拟

采用Monte-Carlo模拟方法,给出用于描述稳恒磁场作用下电沉积枝晶生长的模型.该模型综合考虑了外加磁场B,电解溶液浓度和离子在阴极发生还原反应的几率P_s等因素对电沉积过程的影响,模拟得到与实验结果一致的枝晶生长图形.模拟结果表明:团簇的形状和它们的分形维数都与外加磁场B的强弱,即体现在模型中离子的旋转角速度ω的大小有关;随着磁场强度的增加,沉积团簇会从分形向非分形转变;在相对强的外加磁场作用下,较高离子浓度时的沉积物是非分形的;离子在阴极的反应概率P_s越小,随着磁场强度的增加枝晶生长越易趋向非分形.     

Finite size effect of harmonic measure estimation in a DLA model: Variable size of probe particles

A finite size effect in the probing of the harmonic measure in simulation of diffusion-limited aggregation (DLA) growth is investigated. We introduce a variable size of probe particles, to estimate harmonic measure and extract the fractal dimension of DLA clusters taking two limits, of vanishingly small probe particle size and of infinitely large size of a DLA cluster. We generate 1000 DLA clusters consisting of 50 million particles each, using an off-lattice killing-free algorithm developed in the early work. The introduced method leads to unprecedented accuracy in the estimation of the fractal dimension. We discuss the variation of the probability distribution function with the size of probing particles.     

SIMULATION OF FRACTAL GROWTH OF THIN FILMS AT LOW TEMPERATURE

Fractal growth of thin films at low temperature (50－175 K) is simulated by Monte Carlo method. It is shown that the thin film growth is quite different from the diffusion-limited aggregation (DLA) model when the coverage is larger than 0.1 ML. The average branch width of clusters increases with increasing temperature and it usually larger than the branch width (1.9 atom) in the classic DLA model. The average fractal dimension of clusters increases also with increasing coverage while the fractal dimension of DLA model remains constant. This difference comes from the weak screening effect during the late stage of thin film growth. The relationship between the saturation island number n_s and deposition interval Δt is described in a power law: n_s∝Δt^γ, where γ=-0.332 is very close to the theoretical value -1/3 of rate equations from nucleation theory.     

Diffusion-limited aggregation: A continuum mean field model

Mean field theory is used as a basis for a new approach to analyzing fractal pattern formation by diffusion-limited aggregation. A coarse time scale is introduced to take into account the discrete nature of DLA clusters. A system of equations is derived and solved numerically to determine the fractal dimension and density of a cluster as a function of distance from its center. The results obtained are in good agreement with direct numerical simulations.     

Computer simulations of two-phase flow with surface tension in the percolation cluster

Percolation clusters with varying occupation probability were constructed. Viscous fingering (VF) in the percolation cluster, based on the assumption that throat radii are Rayleigh distributed, is investigated by means of a successive over-relaxation technique. The fractal dimension and the sweep efficiency of VF in the percolation cluster when surface tension is considered are larger than when surface tension is neglected. The fractal dimension of VF will increase as the percolation probability increases or the viscous ratio decreases. VF's fractal dimension of porous media in the limit viscous ratio → ∞ is found to be identical with the DLA. The topology and the geometry of the porous medium have a strong effect on the displacement processes and the structure of the VF.     

Effects of Monomer Size Distribution on the fractal dimensionality of diffusion-limited aggregates

Computer simulations of diffusion-limited aggregation (DLA) for monomers to investigate the effects of size and of lognormal distribution on the fractal dimensionality of the aggregates were conducted on a two-dimensional lattice. The results show the DLA clusters posses multifractal characteristics. For clusters consisting of monodisperse monomers, the bifurcation point on the graph of the pair correlation function (PCF) for each cluster is located right at the monomers size under investigation The textural dimension (D_f1) has a stable value of about 1.65, whereas the structural dimension (D_f2) decreased with increase in monomer size. For the cases with monomers in log-normal distributions, the textural dimension is around 1.67; however, the structural dimension decreases with increasing polydispersity of monomer size.     

DLA模型的最可几方法研究

用最可几方法对DLA模型进行了研究，求出了DLA集团粒子的最可几分布、分维数和屏蔽指数，所得结果与计算机模拟结果相符合 关键词：     

Scaling behavior of threshold epidemics

We numerically simulate the dynamics of atomic clusters aggregation deposited on a surface interacting with the growing island. We make use of the well-known DLA model but replace the underlying diffusion equation by the Smoluchowski equation which results in a drifted DLA model and anisotropic jump probabilities. The shape of the structures resulting from their aggregation-limited random walk is affected by the presence of a Laplacian potential due to, for instance, the surface stress field. We characterize the morphologies we obtain by their Hausdorff fractal dimension as well as the so-called external fractal dimension. We compare our results to previously published experimental results for antimony and silver clusters deposited onto graphite surface.     

Kinetic Simulation of Fractal Aggregation on Liquid Surfaces

A modified fractal growth model based on the deposition, diffusion, and aggregation (DDA) with cluster rotation is presented to simulate two-dimensional fractal aggregation on liquid surfaces. The mobility (including diffusion and rotation) of clusters is related to its mass, which is given by D_m=D₀ s^-γ_D and θ_m=θ₀s^-γ_θ, respectively. We concentrate on revealing the details of the influence of deposition flux F, cluster diffusion factor γ_D and cluster rotation factor γ_θ on the dynamics of fractal aggregation on liquid surfaces. It is shown that the morphologies of clusters and values of cluster density and fractal dimension depend dramatically on the deposition flux and migration factors of clusters.     

Flory theory of polymeric fractals - intersection,saturation and condensation

We consider swelling effects of polymeric fractals, recently introduced by Cates, by usual simple Flory arguments for the free energy. The Flory arguments can be formulated to give a unified view for all polymers, linear, branched, or percolation clusters, as long they are of fractal connectivity.If the size of solvent molecules, being fractals themselves, is comparable to the given cluster, new values of the fractal dimensions can be found. The upper critical dimension is reduced. This is due to usual screening of the excluded volume. By standing overlap and repulsive energies of fractals of different fractal dimensions we find condensation to non-fractal objects depending on the value of the fracton dimension. A melt of polymeric fractals of the same fractal dimension and the same size becomes compact if the spectral dimension exceeds a “critical” value.These considerations are of relevance concerning recent experiments, considering static and dynamic properties of mixtures of microgels and linear polymers of different or equal sizes.     

Scaling in the diffusion limited aggregation model

We present a self-consistent picture of diffusion limited aggregation (DLA) growth based on the assumption that the probability density P(r,N) for the next particle to be attached within the distance r to the center of the cluster is expressible in the scale-invariant form P[r/R{dep}(N)]. It follows from this assumption that there is no multiscaling issue in DLA and there is only a single fractal dimension D for all length scales. We check our assumption self-consistently by calculating the particle-density distribution with a measured P(r/R{dep}) function on an ensemble with 1000 clusters of 5×10{7} particles each. We also show that a nontrivial multiscaling function D(x) can be obtained only when small clusters (N<10?000) are used to calculate D(x). Hence, multiscaling is a finite-size effect and is not intrinsic to DLA.     

Aggregation on heterogeneous surface

Chessboard-like substrates are introduced in this paper, in order to study the diffusion-limited aggregation (DLA)and the motion of poly-atoms on heterogeneous surfaces. The effect of morphology of such substrates upon the cluster aggregation is investigated using the Monte Carlo simulation. It is found that the growth process and the cluster morphology are governed by the energetic topography of the substrates. Our simulation also indicate that the island density and the fractal dimension of the clusters depend strongly on the substrate topography and the activation energy.     

各向异性扩散DLA集团的豪斯道夫维数与标度性质

讨论了DLA集团的各向异性扩散效应.计算机模拟证实了具有各向异性扩散规则的DLA集团有严格的菱形结构.导出了一个粒子的各向异性扩散的新方程，计算了各向异性扩散DLA集团的豪斯道夫维数，结果表明，有效外半角β_eff=min(β_ix,β_iy).讨论了各向异性扩散DLA集团的广义维数，使用修改的楔模型得到了广义维数D_q的表达式. 关键词：     

Dimension of fractal growth patterns as a dynamical exponent

We consider a conformal theory of fractal growth patterns in two dimensions, including diffusion limited aggregation (DLA) as a particular case. In this theory the fractal dimension of the asymptotic cluster manifests itself as a dynamical exponent observable already at very early growth stages. Using a renormalization relation we show from early stage dynamics that the dimension D of DLA can be estimated, 1.69相似文献   

Dynamic Scaling of Ramified Clusters Formed on Liquid Surfaces

A comprehensive simulation model -- deposition, diffusion, rotation, reaction and aggregation model is presented to simulate the formation processes of ramified clusters on liquid surfaces, where clusters can disuse and rotate easily. The mobility （including diffusion and rotation） of clusters is related to its mass, which is given by Dm = Dos^-γD and θm = θos^-γθ, respectively. The influence of the reaction probability on the kinetics and structure formation is included in the simulation model. We concentrate on revealing dynamic scaling during ramified cluster formation. For this purpose, the time evolution of the cluster density and the weight-average cluster size as well as the cluster-size distribution scaling function at different time are determined for various conditions. The dependence of the cluster density on the deposition flux and time-dependence of fractal dimension are also investigated. The obtained results are helpful in understanding the formation of clusters or thin film growth on liquid surfaces.     

Effects of the screening breakdown in the diffusion-limited aggregation model

Several models based on the diffusion-limited aggregation (DLA) model were proposed and their scaling properties explored by computational and theoretical approaches. In this paper, we consider a new extension of the on-lattice DLA model in which the unitary random steps are replaced by random flights of fixed length. This procedure reduces the screening for particle penetration present in the original DLA model and, consequently, generates new pattern classes. The patterns have DLA-like scaling properties at small length of the random flights. However, as the flight size increases, the patterns are initially round and compact but become fractal for sufficiently large clusters. Their radius of gyration and number of particles at the cluster surface scale asymptotically as in the original DLA model. The transition between compact and fractal patterns is characterized by wavelength selection, and 1/k noise was observed far from the transition.Received: 2 March 2004, Published online: 14 December 2004PACS: 05.40.Fb Random walks and Levy flights - 05.50. + q Lattice theory and statistics (Ising, Potts, etc.) - 05.10.Ln Monte Carlo methods     

SIMULATION OF MULTIPLE FRACTAL AND COMPACT GROWTH OF ULTRA-THIN FILMS ON HEXAGONAL SUBSTRATE

The multiple cluster growth of ultra-thin films with different deposition rate and different substrate temperature has been studied by kinetic Monte-Carlo simulation. With increasing diffusion rate along cluster edges (corresponding to an increasing substrate temperature), pattern structures change smoothly from fractal islands, compact islands with random shapes, to regular islands, and the average branch width of clusters increases continuously up to some constant value in the compact island limit. The formation of the multiple fractal and compact clusters can be described quantitatively by multifractal. The results of multifractal analysis show that with pattern change from fractal to compact islands, the Hausdorff dimension D₀, the information dimension D₁, and the correlation dimension D₂ decrease, while the width and height of the multifractal spectra increase.     

Dipole clusters with nontrivial scale-invariant properties

In this paper the scale-invariant properties of the plane (2D) with the growth centre located on the charged particle have been considered. The dependence “number of particles with respect to radius of cluster” is presented by two power-law exponents that differs them from one power-law dependence characterizing the DLA (diffusion limited aggregation) clusters. In our case the interpretation the power-law exponents found in terms of the fractal dimension becomes unacceptable. The model considered it is supposed to be applied for consideration of similar clusters in polar liquids.     

Grayscale projection of finite size fractal clusters

Microscopy techniques are suitable to obtain structural information of colloidal clusters with high resolution, but yield only a two dimensional projection of the objects. When imaging finite size objects with fractal properties, such as clusters of colloidal particles, this projection process has to be taken into account for the calculation of the fractal dimension. In this paper we present a technique to calculate the fractal dimension of finite size clusters with fractal properties using grayscale projections such as images obtained by X-ray microscopy. The grayscales are interpreted as different occupation counts within a projection. It is shown, that the radial distribution of these occupation counts varies with the fractal dimension d of the cluster. Using the radius of maximum occupation probability the fractal dimension up to 2.2 of finite size clusters can be calculated. The theoretical predictions are verified by test calculations employing numerically generated clusters.