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多分散纳米颗粒团聚体的迁移率和沉降速率。

Mobility and settling rate of agglomerates of polydisperse nanoparticles.

机构信息

Department of Mechanical and Process Engineering, ETH Zurich, Zurich 8092, Switzerland.

Department of Chemical Engineering, University of Patras, Patras 26504, Greece.

出版信息

J Chem Phys. 2018 Feb 14;148(6):064703. doi: 10.1063/1.5012037.

Abstract

Agglomerate settling impacts nanotoxicology and nanomedicine as well as the stability of engineered nanofluids. Here, the mobility of nanostructured fractal-like SiO agglomerates in water is investigated and their settling rate in infinitely dilute suspensions is calculated by a Brownian dynamics algorithm tracking the agglomerate translational and rotational motion. The corresponding friction matrices are obtained using the HYDRO++ algorithm [J. G. de la Torre, G. del Rio Echenique, and A. Ortega, J. Phys. Chem. B 111, 955 (2007)] from the Kirkwood-Riseman theory accounting for hydrodynamic interactions of primary particles (PPs) through the Rotne-Prager-Yamakawa tensor, properly modified for polydisperse PPs. Agglomerates are generated by an event-driven method and have constant mass fractal dimension but varying PP size distribution, mass, and relative shape anisotropy. The calculated diffusion coefficient from HYDRO++ is used to obtain the agglomerate mobility diameter d and is compared with that from scaling laws for fractal-like agglomerates. The ratio d/d of the mobility diameter to the gyration diameter of the agglomerate decreases with increasing relative shape anisotropy. For constant d and mean d, the agglomerate settling rate, u, increases with increasing PP geometric standard deviation σ (polydispersity). A linear relationship between u and agglomerate mass to d ratio, m/d, is revealed and attributed to the fast Brownian rotation of such small and light nanoparticle agglomerates. An analytical expression for the u of agglomerates consisting of polydisperse PPs is then derived, u=1-ρρg3πμmd (ρ is the density of the fluid, ρ is the density of PPs, μ is the viscosity of the fluid, and g is the acceleration of gravity), valid for agglomerates for which the characteristic rotational time is considerably shorter than their settling time. Our calculations demonstrate that the commonly made assumption of monodisperse PPs underestimates u by a fraction depending on σ and agglomerate mass mobility exponent. Simulations are in excellent agreement with deposition rate measurements of fumed SiO agglomerates in water.

摘要

团聚体沉降会影响纳米毒理学和纳米医学以及工程纳米流体的稳定性。在这里,研究了水中纳米结构化分形状 SiO 团聚体的迁移率,并通过布朗动力学算法跟踪团聚体的平移和旋转运动来计算其在无限稀释悬浮液中的沉降速率。使用 HYDRO++算法[J. G. de la Torre、G. del Rio Echenique 和 A. Ortega,J. Phys. Chem. B 111,955(2007)]从 Kirkwood-Riseman 理论获得相应的摩擦矩阵,该理论通过 Rotne-Prager-Yamakawa 张量考虑了初级粒子(PP)的流体动力学相互作用,该张量经过适当修改适用于多分散的 PP。团聚体通过事件驱动方法生成,具有恒定的质量分形维数,但具有变化的 PP 尺寸分布、质量和相对形状各向异性。从 HYDRO++获得的扩散系数用于获得团聚体迁移率直径 d,并与分形团聚体的标度定律进行比较。迁移率直径 d 与团聚体回旋直径 d 的比值 d/d 随相对形状各向异性的增加而减小。对于恒定的 d 和平均 d,团聚体沉降速率 u 随 PP 几何标准偏差σ(多分散性)的增加而增加。揭示了 u 与团聚体质量与 d 的比值 m/d 之间的线性关系,并归因于这种小而轻的纳米颗粒团聚体的快速布朗旋转。然后推导出由多分散 PP 组成的团聚体的 u 的解析表达式,u=1-ρρg3πμmd(ρ 是流体的密度,ρ 是 PP 的密度,μ 是流体的粘度,g 是重力加速度),对于特征旋转时间远短于沉降时间的团聚体有效。我们的计算表明,对于多分散性 PP,通常假定单分散性 PP 会低估 u,低估程度取决于σ和团聚体质量迁移率指数。模拟与水中烟硅团聚体沉积速率测量结果非常吻合。

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