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arXiv 2410.09481cond-mat.softcond-mat.stat-mech
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具有方向性相互作用的自聚集胶体系统的离散态模型

Discrete state model of a self-aggregating colloidal system with directional interactions

Salman Fariz Navas, Sabine H. L. Klapp

AI总结:

本文受马尔可夫状态模型启发,针对正交电磁场中的自聚集胶体系统提出一种粗粒化离散态模型,描述多聚集体同时形成与演化过程,并通过粒子解析模拟验证了其预测的准确性。

摘要:

构建系统动力学的粗粒化描述在生物物理学中已有成熟基础,蛋白质折叠动力学中的马尔可夫状态模型就是一个典型例子。本文受马尔可夫状态建模概念的启发,开发了一种自聚集胶体粒子系统的粗粒化离散态模型。此处研究的特定自聚集系统涉及处于正交电场和磁场中的场响应胶体粒子。我们从粒子解析(布朗动力学)模拟出发,通过根据每个粒子的局部结构对其进行分类来定义离散状态。随后,我们将这些状态之间的动力学描述为一系列随机的、无记忆的跳跃。与其他关于胶体自组装的研究不同,我们的粗粒化方法描述了由单个粒子同时形成并演化出多个聚集体的过程。我们的离散模型还考虑了随着最大团簇尺寸的增长,离散状态之间转变动力学的变化。我们通过将每个离散状态中预测的种群比例与直接从粒子解析模拟中计算出的比例(作为最大团簇尺寸的函数)进行比较,验证了该粗粒化模型。随后,我们预测了存在噪声平均化情况下的种群比例,以及在某一时间后模型参数发生瞬时改变情况下的种群比例。最后,我们探讨了在聚集的各个阶段细致平衡条件的有效性。

英文摘要:

The construction of coarse-grained descriptions of a system's kinetics is well established in biophysics. One prominent example is Markov state models in protein folding dynamics. In this paper, we develop a coarse-grained, discrete state model of a self-aggregating colloidal particle system inspired by the concepts of Markov state modelling. The specific self-aggregating system studied here involves field-responsive colloidal particles in orthogonal electric and magnetic fields. Starting from particle-resolved (Brownian dynamics) simulations, we define the discrete states by categorizing each particle according to it's local structure. We then describe the kinetics between these states as a series of stochastic, memoryless jumps. In contrast to other works on colloidal self-assembly, our coarse-grained approach describes the simultaneous formation and evolution of multiple aggregates from single particles. Our discrete model also takes into account the changes in transition dynamics between the discrete states as the size of the largest cluster grows. We validate the coarse-grained model by comparing the predicted population fraction in each of the discrete states with those calculated directly from the particle-resolved simulations as a function of the largest cluster size. We then predict population fractions in presence of noise-averaging and in a situation where a model parameter is changed instantaneously after a certain time. Finally, we explore the validity of the detailed balance condition in the various stages of aggregation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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