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波动布朗偶极链的记忆

Memory of fluctuating Brownian dipolar chains.

作者信息

Toussaint Renaud, Flekkøy Eirik G, Helgesen Geir

机构信息

Institute of Globe Physics in Strasbourg (IPGS), UMR 7516 CNRS, 5 rue Descartes, F-67084 Strasbourg Cedex, France.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Nov;74(5 Pt 1):051405. doi: 10.1103/PhysRevE.74.051405. Epub 2006 Nov 20.

DOI:10.1103/PhysRevE.74.051405
PMID:17279907
Abstract

Nonmagnetic particles in suspension in a ferrofluid act as magnetic holes when an external magnetic field is exerted: They acquire an effective dipolar moment opposing the surrounding one, which induces dipolar magnetic interactions. For a large enough imposed field and particle size, the induced interactions dominate the thermal forces, dipolar chains form. At equilibrium, these chains fluctuate under the effect of brownian noise. When the imposed magnetic field is suddenly decreased, these chains roughen dynamically. We study the time and size scaling of these fluctuations and roughening, and the relationships between the equilibrium and out of equilibrium behavior. We compare the experimental data both to Brownian dynamics simulations, and to a simple theory of semiflexible polymer chains, a generalization of the Rouse model. The scaling behavior of the experiments agree with the predictions of both theory and simulations over 5 orders of magnitudes. The roughening follows three successive regimes: The root mean square width of the chain initially evolves as W approximately t1/2, then it enters a subdiffusive regime where W approximately t1/4 and eventually it saturates to a level W approximately N, where N is the number of particles in the chain. The exact prefactors as a function of the applied field, particle diameter, and temperature are also derived analytically. We also show that this phenomenon can be described equivalently as a non-Markovian diffusion process for a particle in an environment with memory effects. Within this framework, our system is shown to confirm the predictions of theories for anomalous diffusion in systems with memory.

摘要

当施加外部磁场时,铁磁流体中悬浮的非磁性粒子会充当磁洞:它们获得与周围粒子相反的有效偶极矩,从而引发偶极磁相互作用。对于足够大的外加磁场和粒子尺寸,诱导相互作用主导热力,形成偶极链。在平衡状态下,这些链在布朗噪声的作用下波动。当外加磁场突然降低时,这些链会动态地变得粗糙。我们研究了这些波动和粗糙化的时间和尺寸标度,以及平衡态和非平衡态行为之间的关系。我们将实验数据与布朗动力学模拟以及半柔性聚合物链的简单理论(Rouse模型的推广)进行了比较。实验的标度行为在5个数量级上与理论和模拟的预测相符。粗糙化过程遵循三个连续的阶段:链的均方根宽度最初以W∝t¹/²的形式演化,然后进入亚扩散阶段,其中W∝t¹/⁴,最终饱和到W∝N的水平,其中N是链中粒子的数量。还通过解析得出了作为外加磁场、粒子直径和温度函数的精确前置因子。我们还表明,这种现象可以等效地描述为具有记忆效应环境中粒子的非马尔可夫扩散过程。在这个框架内,我们的系统被证明符合具有记忆的系统中反常扩散理论的预测。

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