Knowles Stuart F, Mackay Eleanor K R, Thorneywork Alice L
Cavendish Laboratory, Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE, United Kingdom.
Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, South Parks Rd., Oxford OX1 3QZ, United Kingdom.
J Chem Phys. 2024 Oct 14;161(14). doi: 10.1063/5.0231690.
The transport of molecules through biological and synthetic nanopores is governed by multiple stochastic processes that lead to noisy, fluctuating currents. Disentangling the characteristics of different noise-generating mechanisms is central to better understanding molecular transport at a fundamental level but is extremely challenging in molecular systems due to their complexity and relative experimental inaccessibility. Here, we construct a colloidal model microfluidic system for the experimental measurement of particle currents, where the governing physical properties are directly controllable and particle dynamics directly observable, unlike in the molecular case. Currents of hard spheres fluctuate due to the random arrival times of particles into the channel and the distribution of particle speeds within the channel, which results in characteristic scalings in the power spectral density. We rationalize these scalings by quantitatively comparing to a model for shot noise with a finite transit time, extended to include the distribution of particle speeds. Particle velocity distributions sensitively reflect the confining geometry, and we interpret and model these in terms of the underlying fluid flow profiles. Finally, we explore the extent to which details of these distributions govern the form of the resulting power spectral density, thereby establishing concrete links between the power spectral density and underlying mechanisms for this experimental system. This paves the way for establishing a more systematic understanding of the links between characteristics of transport fluctuations and underlying molecular mechanisms in driven systems such as nanopores.
分子通过生物和合成纳米孔的传输受多种随机过程支配，这些过程会导致电流产生噪声且波动。分辨不同噪声产生机制的特征对于从根本层面更好地理解分子传输至关重要，但在分子系统中极具挑战性，因为其复杂性以及相对难以进行实验研究。在此，我们构建了一个用于实验测量粒子电流的胶体模型微流控系统，与分子情况不同的是，该系统中起支配作用的物理性质可直接控制，粒子动力学可直接观察。硬球电流会因粒子进入通道的随机到达时间以及通道内粒子速度分布而波动，这导致功率谱密度出现特征性标度。我们通过与具有有限渡越时间的散粒噪声模型进行定量比较来解释这些标度，该模型已扩展到包括粒子速度分布。粒子速度分布灵敏地反映了限制几何结构，我们根据潜在的流体流动剖面来解释和建模这些分布。最后，我们探究这些分布的细节在多大程度上决定了所得功率谱密度的形式，从而为该实验系统建立了功率谱密度与潜在机制之间的具体联系。这为更系统地理解诸如纳米孔等驱动系统中传输涨落特征与潜在分子机制之间的联系铺平了道路。
