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MD 模拟中浓度驱动离子通过硅纳米孔流的不确定性量化。I. 对孔物理参数的敏感性。

Uncertainty quantification in MD simulations of concentration driven ionic flow through a silica nanopore. I. Sensitivity to physical parameters of the pore.

机构信息

Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA.

出版信息

J Chem Phys. 2013 May 21;138(19):194104. doi: 10.1063/1.4804666.

Abstract

In this article, uncertainty quantification is applied to molecular dynamics (MD) simulations of concentration driven ionic flow through a silica nanopore. We consider a silica pore model connecting two reservoirs containing a solution of sodium (Na(+)) and chloride (Cl(-)) ions in water. An ad hoc concentration control algorithm is developed to simulate a concentration driven counter flow of ions through the pore, with the ionic flux being the main observable extracted from the MD system. We explore the sensitivity of the system to two physical parameters of the pore, namely, the pore diameter and the gating charge. First we conduct a quantitative analysis of the impact of the pore diameter on the ionic flux, and interpret the results in terms of the interplay between size effects and ion mobility. Second, we analyze the effect of gating charge by treating the charge density over the pore surface as an uncertain parameter in a forward propagation study. Polynomial chaos expansions and Bayesian inference are exploited to isolate the effect of intrinsic noise and quantify the impact of parametric uncertainty on the MD predictions. We highlight the challenges arising from the heterogeneous nature of the system, given the several components involved, and from the substantial effect of the intrinsic thermal noise.

摘要

本文将不确定性量化方法应用于通过二氧化硅纳米孔的浓度驱动离子流的分子动力学 (MD) 模拟。我们考虑了一个连接两个储层的二氧化硅孔模型,其中包含在水中的钠离子 (Na(+)) 和氯离子 (Cl(-)) 离子的溶液。开发了一个特定的浓度控制算法来模拟离子通过孔的浓度驱动反向流动,从 MD 系统中提取主要可观察到的离子通量。我们探索了系统对孔的两个物理参数的敏感性,即孔径和门控电荷。首先,我们对孔径对离子通量的影响进行了定量分析,并根据尺寸效应和离子迁移率之间的相互作用来解释结果。其次,我们通过将孔表面上的电荷密度视为正向传播研究中的不确定参数来分析门控电荷的影响。利用多项式混沌展开和贝叶斯推断来隔离固有噪声的影响,并量化参数不确定性对 MD 预测的影响。我们强调了由于系统涉及的几个组件的不均匀性质以及固有热噪声的显著影响而产生的挑战。

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