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arXiv 2605.06293cond-mat.softphysics.chem-ph
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溶剂诱导的记忆效应在模型电解质中的表现

Solvent-induced memory effects in a model electrolyte

Sorbonne Université(索邦大学);CNRS(法国国家科学研究中心)

Sleeba Varghese, Benjamin Rotenberg, Pierre Illien

AI总结:

本文研究了极性溶剂中离子波动的理论机制,通过构建布朗粒子模型和随机密度泛函理论,推导出离子电荷密度的广义 Langevin 方程,揭示了溶剂介导的记忆效应,并通过 BD 模拟验证了动态电荷结构因子,预测了慢速溶剂中离子动力学的两步松弛现象。

摘要:

极性溶剂中离子波动的理论理解仍受限于离子运动与溶剂极化之间的复杂耦合。尽管数值模拟可实现原子级分辨率,但分析方法需要合适的粗粒化水平。本文将离子和溶剂分子视为相互作用的布朗粒子,并利用随机密度泛函理论推导出离子电荷密度的广义 Langevin 方程,明确考虑了溶剂介导的记忆效应。在溶剂动力学快于离子动力学的时间尺度分离区域,我们获得了简单的动态电荷结构因子表达式,并通过 BD 模拟进行了验证。对于慢速溶剂,我们预测了离子动力学中出现的两步松弛现象。这些结果为离子-溶剂动力学提供了介观方法,并为研究电解质中的波动诱导现象开辟了新途径。

英文摘要:

The fluctuations of ions in polar solvents remain poorly understood theoretically due to the complex coupling between ionic motion and solvent polarization. Indeed, while all-atom resolution can be achieved in numerical simulations, analytical approaches require suitable levels of coarse-graining. In this work, we describe ions and solvent molecules as interacting Brownian particles and use stochastic density functional theory to derive a generalized Langevin equation for the ionic charge density, explicitly accounting for solvent-mediated memory effects. In the regime where there is a clear timescale separation between fast solvent and slow ion dynamics, we obtain simple expressions for dynamical charge structure factors, which are validated by BD simulations. For slow solvents, we predict an emerging two-step relaxation in ionic dynamics. These results provide a mesoscopic approach for ion-solvent dynamics and open pathways to study fluctuation-induced phenomena in electrolytes.

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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