Tan Jifu, Keller Wesley, Sohrabi Salman, Yang Jie, Liu Yaling
Department of Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015, USA.
Department of Civil and Environmental Engineering, Lehigh University, Bethlehem, PA 18015, USA.
Nanomaterials (Basel). 2016 Feb 5;6(2):30. doi: 10.3390/nano6020030.
Nanodrug-carrier delivery in the blood stream is strongly influenced by nanoparticle (NP) dispersion. This paper presents a numerical study on NP transport and dispersion in red blood cell (RBC) suspensions under shear and channel flow conditions, utilizing an immersed boundary fluid-structure interaction model with a lattice Boltzmann fluid solver, an elastic cell membrane model and a particle motion model driven by both hydrodynamic loading and Brownian dynamics. The model can capture the multiphase features of the blood flow. Simulations were performed to obtain an empirical formula to predict NP dispersion rate for a range of shear rates and cell concentrations. NP dispersion rate predictions from the formula were then compared to observations from previous experimental and numerical studies. The proposed formula is shown to accurately predict the NP dispersion rate. The simulation results also confirm previous findings that the NP dispersion rate is strongly influenced by local disturbances in the flow due to RBC motion and deformation. The proposed formula provides an efficient method for estimating the NP dispersion rate in modeling NP transport in large-scale vascular networks without explicit RBC and NP models.
纳米药物载体在血流中的输送受到纳米颗粒（NP）分散的强烈影响。本文利用具有格子玻尔兹曼流体求解器的浸入边界流固相互作用模型、弹性细胞膜模型以及由流体动力载荷和布朗动力学驱动的颗粒运动模型，对剪切和通道流条件下红细胞（RBC）悬浮液中NP的传输和分散进行了数值研究。该模型能够捕捉血流的多相特征。进行模拟以获得一个经验公式，用于预测一系列剪切速率和细胞浓度下的NP分散速率。然后将该公式预测的NP分散速率与先前实验和数值研究的观测结果进行比较。结果表明，所提出的公式能够准确预测NP分散速率。模拟结果还证实了先前的发现，即NP分散速率受到RBC运动和变形引起的局部流动扰动的强烈影响。所提出的公式为在无需明确RBC和NP模型的情况下，在大规模血管网络中模拟NP传输时估计NP分散速率提供了一种有效方法。
