磁性纳米颗粒系统偶极相互作用的Monte Carlo研究

采用局域Monte Carlo方法模拟不同易轴分布的简单立方排列单分散单畴Fe纳米颗粒系统的ZFC-FC曲线及磁滞回线.结果表明：随着偶极相互作用的增强，系统的阻塞温度T_B逐渐增大，且ZFC曲线的峰变宽.说明偶极相互作用使得系统的有效能垒提高，分布宽度增加.研究FC曲线磁化强度的倒数与温度关系，发现偶极相互作用系统中存在反铁磁有序.系统的阻塞态及超顺磁态的磁滞回线表明，极低低温下，随着偶极相互作用的增强，系统的矫顽力和剩磁减小，偶极相互作用阻碍系统的磁化；系统处于超顺磁态，各向异性作用及偶极相互作用使得系统的磁化曲线偏离Langevin曲线且偶极相互作用展现出退磁相互作用效应.偶极相互作用增强，系统磁化曲线与Langevin曲线偏差量的最大值向低场移动.在偶极相互作用下，易轴与外场夹角为45°的磁性纳米颗粒系统的平均有效能垒和有效能垒分布宽度较易轴随机分布系统的大.     

材料中氦泡迁移-融合的蒙特卡罗模拟及其参数优化

基于迁移-融合机制, 建立了一套用于模拟材料中氦泡生长行为的蒙特卡罗程序, 探讨了时间步长等控制参数对演化的影响。 研究指出,在考察此类参数对计算的影响时必须考虑氦的初始分布,另外指出在选取邻居半径时除了要考虑到初始分布外还要考虑邻居更新的快慢。 The evolution of helium bubbles in materials has been simulated by Monte Carlo methods based on the migration coalescence mechanism. The influences of simulation parameters on the results are studied. It is found that the initial depth distribution must be considered when assessing the parameters influence, and the frequency of updating neighbor list should also be taken into account when selecting the cutoff range for neighbors.     

Monte Carlo model of CO adsorption on supported Pt nanoparticle

For molecular simulations with thousands of atoms it is desirable to use a lattice gas model because it is fast and easy-to-use for computations. Unfortunately, simulation of adsorption on heterogeneous surfaces within this model is rather complicated due to a large variety of available adsorption site types. We propose the combined model with lattice representation of adsorbent atoms and arbitrary location of adsorbate atoms. Using this model simulation of CO adsorption on supported Pt nanoparticles has been performed. With the proposed approach the above-mentioned difficulties were successfully overcome.     

Monte Carlo simulation of the effect of atomic diagonal transition on cluster diffusion

The effect of atomic diagonal transition on the cluster diffusion and its size dependence is simulated by kinetic Monte Carlo method. The thresholds of atomic diagonal transition barriers E_{dt} are found to be 0.2eV and 0.4eV, corresponding to with and without evaporation and condensation mechanism, respectively. The results indicate that the cluster diffusion is controlled primarily by the atomic diagonal transition, and the cluster diffusion coefficient D decreases drastically with increasing E_d when E_dE_{dt}, and the relationship between D and N changes into D∝N^{-1.08±0.027}.     

Monte Carlo simulation of ramified aggregates onhetero-substrates

We have studied the aggregation of particles on a hetero-substrate consisting of two different substrates A and B with finite surface barriers E_AB and E_BA between the AB and BA boundaries, respectively. With the diffusion energy limited aggregation (DELA) model, we find that the number of clusters and the mean radius of gyration of the clusters are dependent on the surface barriers E_AB and E_BA. For the case with a constant of E_BA, a series of minima are summarized as E_AB= (E₀- k_BAE_BA)/ k_AB with k_AB and k_BA being two integers, for main minima (k_BA=k_AB- 1) and two local minima (k_BA=k_AB and k_BA=k_AB + 1) between two neighbouring main minima.     

蒙特卡罗方法在低能电子致原子内壳层电离截面测量中的应用

在Monte Carlo方法模拟keV电子碰撞薄膜／厚衬底靶过程中,输入材料数据中采用的内壳层电离截面数据不同,得到的反映膜厚及村底对电离截面测量结果影响的修正因子值也有差别。讨论了Monte Carlo模拟得到的修正因子值受输入材料数据中内壳层电离截面影响的程度,并完成了入射keV电子在法拉第筒中逃逸率的估算工作。 The sensitivity of the correction factor, which describes the combined effect of finite film thickness and the thick substrate in the measurement of atomic inner-shell ionization cross-sections by low-energy electron impact, to the adopted ionization cross-sections in the Monte Carlo simulation is discussed. Moreover, the electron escape ratio from the Faraday cup in our experiment is also obtained by Monte Carlo method.     

Monte Carlo Simulations of the Yukawa One-Component Plasma

The excess free energy f of the Yukawa one-component plasma is investigated by means of Monte Carlo simulations. These simulations are performed in the canonical ensemble within hyperspherical boundary conditions and f is computed for various values of the coupling parameter in the range 0.1100 and of the screening parameter * in the range 0.1*6.     

A generalized optimization of Monte Carlo particle transport schemes

Formulations and algorithms for optimizing biased random walk problems in radiation transport are described. A matrix-integral equation is constructed by coupling the second moment and its derivative with respect to the biasing parameter. The optimization is based on estimation of the second moment around the score and the Monte Carlo perturbation algorithm to treat the variation in the biasing parameter.     

Monte Carlo simulation of phase separation and clustering in the ABV model

As a model for a binary alloy undergoing an unmixing phase transition, we consider a square lattice where each site can be either taken by an A atom, a B atom, or a vacancy (V), and there exists a repulsive interaction between AB nearest neighbor pairs. Starting from a random initial configuration, unmixing proceeds via random jumps of A atoms or B atoms to nearest neighbor vacant sites. In the absence of any interaction, these jumps occur at jump rates _A and _B, respectively. For a small concentration of vacancies (c _v=0.04) the dynamics of the structure factorS(k,t) and its first two momentsk ₁(t),k ₂ ² (t) is studied during the early stages of phase separation, for several choices of concentrationc _B of B atoms. Forc _B=0.18 also the time evolution of the cluster size distribution is studied. Apart from very early times, the mean cluster sizel(t) as well as the moments of the structure function depend on timet and the ratio of the jump rates (= _B/ _A) only via a scaled timet/(). Qualitatively, the behavior is very similar to the direct exchange model containing no vacancies. Consequences for phase separation of real alloys are briefly discussed.     

CdZnTe核探测器的蒙特卡罗模拟的初步研究

以CdZnTe核探测器的工作原理为依据,探测器内反应的随机性和反应产生的电子空穴对数目的统计规律为物理模型,应用Visual C + + 自行编制了蒙特卡罗模拟软件.模拟了γ射线在CdZnTe探测器中的响应能谱,并将模拟结果与实际器件的测试结果进行了比较讨论.模拟能谱与实际测得的能谱的主峰符合较好.此外,通过分析⁵⁷Co源辐照下探测效率与器件厚度的关系,可以推测探测效率达到最大时所对应CdZnTe探测器的理想厚度     

Monte Carlo simulation of magnetic multi-core nanoparticles

In this paper, a Monte Carlo simulation is carried out to evaluate the equilibrium magnetization of magnetic multi-core nanoparticles in a liquid and subjected to a static magnetic field. The particles contain a magnetic multi-core consisting of a cluster of magnetic single-domains of magnetite. We show that the magnetization of multi-core nanoparticles cannot be fully described by a Langevin model. Inter-domain dipolar interactions and domain magnetic anisotropy contribute to decrease the magnetization of the particles, whereas the single-domain size distribution yields an increase in magnetization. Also, we show that the interactions affect the effective magnetic moment of the multi-core nanoparticles.     

闪烁光纤时间特性的蒙特卡罗模拟

用蒙特卡罗模拟的方法，研究了影响闪烁光纤时间分辨的物理因素，包括光子在光纤中的发射，传输，吸收和最后在光电倍增管输出端形成电泳冲等过程，并和实验结果进行了比较。     

Monte Carlo simulation of the enantioseparation process

By means of Monte Carlo simulation, a study of enantioseparation by capillary electrophoresis has been carried out. A simplified system consisting of two enantiomers S (R) and a selector chiral C, which reacts with the enantiomers to form complexes RC (SC), has been considered. The dependence of Δμ$\Delta \mu$ (enantioseparation) with the concentration of chiral selector and with temperature have been analyzed by simulation. The effect of the binding constant and the charge of the complexes are also analyzed. The results are qualitatively satisfactory, despite the simplicity of the model.     

Diffusion and Growth of Metal Clusters in Nanocomposites: A Kinetic Monte Carlo Study

Noble metals that are deposited on a polymer surface exhibit surface diffusion and diffusion into the bulk. At the same time the metal atoms tend to form clusters because their cohesive energy is about two orders of magnitude higher than the cohesive energy of polymers. To selfconsistently simulate these coupled processes, we present in this paper a Kinetic Monte Carlo approach. Using a simple model with diffusion coefficients taken as input parameters allows us to perform a systematic study of the behavior of a large ensemble of metal atoms on a polymer surface eventually leading to polymer nanocomposites. Special emphasis is placed on the cluster growth, cluster size distribution and the penetration of clusters into the substrate. We also study the influence of surface defects and analyze how the properties of the resulting material can be controlled by variation of the deposition rate (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Finite Size Effect in Path Integral Monte Carlo Simulations of 4He Systems

Path integral Monte Carlo (PIMC) simulations are a powerful computational method to study interacting quantum systems at finite temperatures. In this work, PIMC has been applied to study the finite size effect of the simulated systems of ⁴He. We determine the energy as a function of temperature at saturated-vapor-pressure (SVP) conditions in the temperature range of T∈[1.0 K, 4.0 K], and the equation of state (EOS) in the ground state for systems consisted of 32, 64 and 128 ⁴He atoms, respectively. We find that the energy at SVP is influenced significantly by the size of the simulated system in the temperature range of T∈[2.1 K, 3.0 K] and the larger the system is, the better results are obtained in comparison with the experimental values; while the EOS appeared to be unrelated to it.     

The Convergence of Markov Chain Monte Carlo Methods: From the Metropolis Method to Hamiltonian Monte Carlo

From its inception in the 1950s to the modern frontiers of applied statistics, Markov chain Monte Carlo has been one of the most ubiquitous and successful methods in statistical computing. The development of the method in that time has been fueled by not only increasingly difficult problems but also novel techniques adopted from physics. Here, the history of Markov chain Monte Carlo is reviewed from its inception with the Metropolis method to the contemporary state‐of‐the‐art in Hamiltonian Monte Carlo, focusing on the evolving interplay between the statistical and physical perspectives of the method.     

Finite Size Effect in Path Integral Monte Carlo Simulations of ^4He Systems

Path integral Monte Carlo （PIMC） simulations are a powerful computational method to study interacting quantum systems at finite temperatures. In this work, PIMC has been applied to study the finite size effect of the simulated systems of ^4He. We determine the energy as a function of temperature at saturated-vapor-pressure （SVP） conditions in the temperature range of T ∈ [1.0 K,4.0 K], and the equation of state （EOS） in the grmmd state For systems consisted of 32, 64 and 128 ^4He atoms, respectively, We find that the energy at SVP is influenced significantly by the size of the simulated system in the temperature range of T ∈ [2.1 K, 3.0 K] and the larger the system is, the better results are obtained in comparison with the experimental values; while the EOS appeared to be unrelated to it.     

Monte Carlo Simulations of Chain Dimensions and Conformational Properties of Various Poly(n-alkyl methacrylates) in Solution

Rotational Isomeric State (RIS) Metropolis Monte Carlo (RMMC) simulations of the conformational properties and chain dimensions of a series of chemically different poly(n-alkyl methacrylates) including poly(methyl methacrylate), poly(n-butyl methacrylate), poly(n-hexyl methacrylate), and poly(phenyl methacrylate), in the θ state were investigated, and (〈r²〉/M)^1/2, (〈s²〉/M)^1/2 and C _n were calculated and compared in order to obtain fundamental understanding of the influence of the chemical structure. Simulations were conducted for different molecular weights. Results obtained from the simulations are compared with experimentally obtained dimensions in the literature using the Mark-Houwink relationship as well as, in some cases, data available from direct determinations in θ solvents. Good agreement between simulation and experimental data was obtained. The backbone conformation is predominantly trans in these polymers. Increase in bulkiness and rigidity of the substituting acrylate side group results in an increase in trans and a decrease in gauche backbone conformer population. In the case of rotatable bonds in the side-group structure, increase in rigidity of the side group leads to a decrease in the trans population, although this effect is not uniformly observed.     

A Monte Carlo method for simulating fractal surfaces

A Monte Carlo method is presented for simulating rough surfaces with the fractal behavior. The simulation is based on power-law size distribution of asperity diameter and self-affine property of roughness on surfaces. A probability model based on random number for asperity sizes is developed to generate the surfaces. By iteration, this method can be used to simulate surfaces that exhibit the aforementioned properties. The results indicate that the variation of the surface topography is related to the effects of scaling constant G and the fractal dimension D of the profile of rough surface. The larger value of D or smaller value of G signifies the smoother surface topography. This method may have the potential in prediction of the transport properties (such as friction, wear, lubrication, permeability and thermal or electrical conductivity, etc.) on rough surfaces.