带电液体中的非静电相互作用随机场。

IF 2.2 3区 物理与天体物理 Q2 PHYSICS, FLUIDS & PLASMAS
Li Wan
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引用次数: 0

摘要

我们推导了一个能处理带电液体中静电和非静电相互作用的方程。由此产生的方程是泊松-玻尔兹曼方程的复杂版本,其中非静电相互作用通过场论表示为随机场。因此,带电液体中离子的非静电相互作用可以很容易地通过根据这些随机场产生随机数来模拟。为了求解这个方程,我们采用了有限元法。纳入方程的非静电相互作用是一般的。在本研究中,我们以离子的位阻效应为例。结果表明,该方程能很好地捕捉到空间效应。空间效应排除了边界上的离子,改变了体域内离子的分布。在屏蔽域相交的带电液体中,体内的位阻效应减弱了边界处的位阻效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonelectrostatic interactions as random fields in charged liquids.

We derive an equation capable of treating both electrostatic and nonelectrostatic interactions in charged liquids. The resulting equation is a complex version of the Poisson-Boltzmann equation, where nonelectrostatic interactions are represented as random fields through field theory. Consequently, the nonelectrostatic interactions of ions in charged liquids can be easily simulated by generating random numbers in accordance with these random fields. To solve the equation, we employ the finite element method. The nonelectrostatic interactions incorporated into the equation are general. In this study, we take the steric effect of ions as an example. The results show that the equation can capture the steric effect clearly. The steric effect excludes ions at the boundaries and alters the ion distribution within the bulk domain. In charged liquids with screening domains intersected, the steric effect in the bulk diminishes the steric effect at the boundaries.

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来源期刊
Physical Review E
Physical Review E PHYSICS, FLUIDS & PLASMASPHYSICS, MATHEMAT-PHYSICS, MATHEMATICAL
CiteScore
4.50
自引率
16.70%
发文量
2110
期刊介绍: Physical Review E (PRE), broad and interdisciplinary in scope, focuses on collective phenomena of many-body systems, with statistical physics and nonlinear dynamics as the central themes of the journal. Physical Review E publishes recent developments in biological and soft matter physics including granular materials, colloids, complex fluids, liquid crystals, and polymers. The journal covers fluid dynamics and plasma physics and includes sections on computational and interdisciplinary physics, for example, complex networks.
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