Electrophoresis and electric conduction in a salt-free suspension of charged particles

The electrophoresis and electric conduction of a suspension of charged spherical particles in a salt-free solution are analyzed by using a unit cell model. The linearized Poisson-Boltzmann equation (valid for the cases of relatively low surface charge density or high volume fraction of the particles) and Laplace equation are solved for the equilibrium electric potential profile and its perturbation caused by the imposed electric field, respectively, in the fluid containing the counterions only around the particle, and the ionic continuity equation and modified Stokes equations are solved for the electrochemical potential energy and fluid flow fields, respectively. Explicit analytical formulas for the electrophoretic mobility of the particles and effective electric conductivity of the suspension are obtained, and the particle interaction effects on these transport properties are significant and interesting. The scaled zeta potential, electrophoretic mobility, and effective electric conductivity increase monotonically with an increase in the scaled surface charge density of the particles and in general decrease with an increase in the particle volume fraction, keeping each other parameter unchanged. Under the Debye-Hückel approximation, the dependence of the electrophoretic mobility normalized with the surface charge density on the ratio of the particle radius to the Debye screening length and particle volume fraction in a salt-free suspension is same as that in a salt-containing suspension, but the variation of the effective electric conductivity with the particle volume fraction in a salt-free suspension is found to be quite different from that in a suspension containing added electrolyte.     

质子水合结构的振动态密度分析

使用基于多态经验价键模型的分子动力学模拟, 对水溶液中质子的水合结构及其在质子传递过程中的动力学过程进行了研究. 在价键模型的方法下, 质子的水合结构主要以H₉O₄⁺(Eigen)以及过渡态的H₅O₂⁺(Zundel)结构形态存在, 且在这两种结构中以Eigen的形态表现明显. 通过对质子传递过程中不同水合结构的态密度频谱分析, 发现一个在2000~3000 cm^-1范围内的明显连续的宽吸收谱带, 主要归因于Eigen结构的贡献, 这些特征峰的出现与水合氢离子第一溶剂化层内的强氢键作用密切相关. 对于Zundel的结构, 在1760 cm^-1处出现一个较为明显的肩峰, 归属为质子传递模式的特征振动. 通过对质子水合结构态密度频谱的分析, 可望增强对于稀酸溶液红外光谱中的连续宽吸收带以及质子传递的微观动力学过程的理解.     

纳米Pd和Au催化CO2还原粒径效应的密度泛函理论计算研究

以可再生能源为能量来源,在水溶液中进行的光(电)催化CO₂还原生成高附加值化学品和燃料是解决能源危机与环境污染的有效途径之一.CO是一种简单却很重要的CO₂还原产物,它可以作为水煤气变换反应与费托合成的重要原料.具有较高CO选择性的贵金属纳米颗粒催化剂(如Au和Pd)一直受到研究者的广泛关注.一般来说,金属颗粒催化剂的催化性能与粒径大小密切相关,即所谓的粒径效应.然而在实际的理论计算研究中,由于受到计算能力的限制,催化剂模型都仅局限于简单的周期性模型或小的金属团簇模型,无法准确描述真实颗粒上复杂的反应位点的性质,导致了对催化行为的误解.因此,建立更加真实的颗粒模型对探究纳米颗粒催化剂上活性位点的性质,解释其粒径效应至关重要.本文旨在阐述Au与Pd纳米颗粒催化剂不同活性位点上CO₂还原反应与产H2副反应的竞争机制,并解释Au与Pd纳米颗粒催化剂在CO₂电还原中表现出不同粒径效应的原因.本文基于密度泛函理论,采用VASP软件,BEEF-vdW泛函进行计算.分别建立了原子数为55,147,309和561的颗粒模型和高CO^*覆盖度模型,避免了传统周期性模型的局限性,探究了金属颗粒催化剂不同反应位点上的CO选择性.结果表明,对于颗粒模型来说,(100)位点对CO的选择性优于边缘位点;但对于周期性模型来说,Au(211)对CO的选择性则优于Au(100).产生这种反差的主要原因在于Au颗粒的边缘位点对H*的吸附过强.通过对比,我们直观地展现了颗粒模型上平面位点和Edge位点与相对应的周期性模型上CO选择性的区别,突出了模型选择对揭示活性位点性质的重要性.在此基础上,通过计算理论CO法拉第效率,发现Au颗粒随着粒径的减小,CO选择性降低,与实验的趋势一致.对于Pd催化剂来说,低覆盖度模型无法正确预测活性位点的性质;而高CO覆盖度的情况下,Pd颗粒的边缘位点对COOH^*吸附能更强,这是导致边缘位点上CO选择性更高的主要原因.同样通过计算理论CO法拉第效率,发现随着粒径的减小,Pd颗粒上CO选择性升高.本文不仅成功揭示了Au与Pd颗粒催化剂上活性位点的性质,对粒径效应做出了合理解释,也强调了合理的计算模型是理论研究的基础.     

A domain decomposition method for three species modeling of multi-electrode negative corona discharge – With applications to electrostatic precipitators

The negative corona discharge problem for multi-electrode geometries is modeled by a three species model. The equations are solved using domain decomposition, by recognizing that multiple species are only present in a small part of the domain, and hence only need to be incorporated locally in the model.The method is applied to an industrially relevant three wire electrostatic precipitator geometry. The calculated current density is in good agreement with experimental data. To further illustrate applications of the three species solution, it is used for coupled particle, fluid, and electrostatic simulations to analyze particle collection properties.     

基于语义的软件服务故障自动诊断模型

模仿学习是机器人仿生机制研究的主要内容之一,即通过观察、理解、学习、模仿示教行为实现机器人的仿生特性。基于高斯过程分别表达采集离散示教信号所构成的示教轨迹和含有未知参数策略的模仿轨迹,构建模仿学习方法框架,将概率模型匹配引入到模仿学习中,以KL散度为代价函数比较两种轨迹的概率分布,运用梯度下降法寻求使KL散度最小的最优模仿控制策略,将策略应用于模仿机器人以完成与示教相同的模仿任务。以关节型机器人的机械臂摆动行为模仿为学习任务进行仿真,结果表明基于概率轨迹匹配的模仿学习方法能够实现机械臂摆动行为模仿,学习过程较传统方法简易且学习效果较好。     

基于Demons算法改进的图像去噪模型研究

在Demons算法的基础上, 将扩散过程看作图像配准, 建立一种新的基于图像配准的Demons 去噪模型. 实验表明, 该模型去噪效果优于经典的Perona-Malik模型, 排除了模型的病态性. 考虑到新模型在图像去噪过程中仅靠梯度信息表示图像的局部特征还不完善, 故将水平集曲率作为控制图像结构的驱动力因素引入到此模型中, 提出了一种新的梯度和曲率双重驱动力的图像去噪模型. 分析和仿真结果表明, 两种新模型都可有效抑制噪声, 清晰度也有明显的提高, 其中双重驱动力的图像去噪模型去噪效果更具优越性.     

Hubbard模型中的相位弦效应与交互Chern-Simons理论

费米子符号在费米液体理论中至关重要. 然而, 在Mott绝缘体中, 很强的电子Coulomb相互作用抑制了体系的电荷涨落并消除了电子交换带来的费米子符号问题. 本文首先回顾二分晶格上Hubbard模型的相位弦理论, 从弱关联的费米液体到强关联的反铁磁Mott绝缘体的转变可以由此得到统一理解. 在任意Coulomb作用强度U下, 我们首先导出Hubbard模型的严格的符号结构. 在小U极限下, 它回到通常的费米子符号; 在大U极限下, 它给出了t-J模型的相位弦符号. 在半满情形下, 我们构造了一种电子分数化的表象, 其中, 电荷子与自旋子通过演生的交互Chern-Simons规范场相互耦合. 由此导出的基态波函数拟设与低能有效理论可以定性刻画Hubbard模型的基态相图. 在弱关联区域, 费米液体的准粒子由电荷子与自旋子的束缚态构成, 其长程相位相干性取决于背景自旋的关联性质. 体系的Mott转变可以通过电荷子打开能隙或是通过自旋子玻色凝聚来实现.     

An efficient splitting technique for two‐layer shallow‐water model

We consider the numerical approximation of the weak solutions of the two‐layer shallow‐water equations. The model under consideration is made of two usual one‐layer shallow‐water model coupled by nonconservative products. Because of the nonconservative products of the system, which couple both one‐layer shallow‐water subsystems, the usual numerical methods have to consider the full model. Of course, uncoupled numerical techniques, just involving finite volume schemes for the basic shallow‐water equations, are very attractive since they are very easy to implement and they are costless. Recently, a stable layer splitting technique was introduced [Bouchut and Morales de Luna, M2AN Math Model Numer Anal 42 (2008), 683–698]. In the same spirit, we exhibit new splitting technique, which is proved to be well balanced and non‐negative preserving. The main benefit issuing from the here derived uncoupled method is the ability to correctly approximate the solution of very severe benchmarks. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 1396–1423, 2015     

AN INDIVIDUAL‐BASED MODEL FOR FERAL HOGS IN GREAT SMOKY MOUNTAINS NATIONAL PARK

The expansion of feral hog (Sus scrofa) populations in the United States has resulted in increased efforts to develop and implement control strategies designed to minimize the impacts done by this invasive species. We describe an individual‐based model for feral hogs in Great Smoky Mountains National Park (GSMNP). The objectives of the model are to provide an understanding of the population dynamics of this feral hog population and to determine the efficacy of the annual harvest as a population control method. Results suggest that the dynamics of the population are driven by fall hard mast production and the GSMNP harvests currently limit growth of the population, but these control efforts have not reduced the population.     

Exact Finite-Dimensional Filter for Exponential Functionals of the State of Beneš Systems

The purpose of this article is to derive finite-dimensional filters for exponential functionals of the state of nonlinear Bene? type filtering systems with correlated noises. These new filters can be applied in the state reconstruction of doubly–stochastic auto–regressive processes.