Hu Ming, Chen Hongbo, Wang Hongru, Burov Stanislav, Barkai Eli, Wang Dapeng
State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China.
University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China.
ACS Nano. 2023 Nov 14;17(21):21708-21718. doi: 10.1021/acsnano.3c06897. Epub 2023 Oct 25.
In many disordered systems, the diffusion of classical particles is described by a displacement distribution (, ) that displays exponential tails instead of Gaussian statistics expected for Brownian motion. However, the experimental demonstration of control of this behavior by increasing the disorder strength has remained challenging. In this work, we explore the Gaussian-to-exponential transition by using diffusion of poly(ethylene glycol) (PEG) in attractive nanoparticle-polymer mixtures and controlling the volume fraction of the nanoparticles. In this work, we find "knobs", namely nanoparticle concentration and interaction, which enable the change in the shape of (,) in a well-defined way. The Gaussian-to-exponential transition is consistent with a modified large deviation approach for a continuous time random walk and also with Monte Carlo simulations involving a microscopic model of polymer trapping reversible adsorption to the nanoparticle surface. Our work bears significance in unraveling the fundamental physics behind the exponential decay of the displacement distribution at the tails, which is commonly observed in soft materials and nanomaterials.
在许多无序系统中，经典粒子的扩散由位移分布(P(r,t))描述，该分布呈现指数尾部，而非布朗运动预期的高斯统计。然而，通过增加无序强度来控制这种行为的实验证明仍然具有挑战性。在这项工作中，我们利用聚乙二醇（PEG）在有吸引力的纳米颗粒 - 聚合物混合物中的扩散并控制纳米颗粒的体积分数，来探索高斯到指数的转变。在这项工作中，我们发现了“旋钮”，即纳米颗粒浓度和相互作用，它们能够以明确的方式改变(P(r,t))的形状。高斯到指数的转变与连续时间随机游走的修正大偏差方法一致，也与涉及聚合物捕获（可逆吸附到纳米颗粒表面）微观模型的蒙特卡罗模拟一致。我们的工作对于揭示尾部位移分布指数衰减背后的基本物理具有重要意义，这种指数衰减在软材料和纳米材料中普遍存在。
