(414h) A Combined Experimental and Numerical Analysis of DNA-Functionalized Colloidal Particle Deposition in a Channel Flow

Aggregating particulate flows are at the heart of an extremely broad range of phenomena in science, medicine and engineering, including biofilm formation in pipes and cellular aggregation in blood flow. These phenomena also are extremely popular targets for computer simulations, and impressive algorithmic developments over the years have enabled sophisticated, multiscale simulations of aggregating particulate flows in a variety of settings [e.g., 1,2]. Although various numerical models for particulate flow have been shown to capture many qualitative phenomena correctly, in most cases their quantitative predictive ability is not well established. Often, this is due to the sheer complexity of the various coupled phenomena at play. One example in which this complexity is highly evident is the aggregation of platelets flowing over an injury in a blood vessel [1]. Here, each platelet represents a complex particle with time-dependent shape, activity (or ‘stickiness’) that is also able to communicate with its local environment via an intricate sequence of biochemical pathways. While microfluidic models of platelet aggregation greatly simplified the setting in which analysis may be performed [3], the complexity of platelet biology is still present and confounds model testing and validation.

Here, we describe a simplified microfluidic model system that removes much of this complexity, while retaining some of the essential physics related to particle flow hydrodynamics. In particular, DNA-functionalized spherical particles [4] are used to simulate activated platelets, which interact with, and stick to, a patch on the microfluidic channel that presents a brush of complementary DNA single-strands to flowing particles. The evolution of the particle areal density on the adhesive patch is measured experimentally under varying conditions of shear rate and particle density. The results are first interpreted using a simple random-sequential adsorption model, which is shown to capture the data well if all the details of the hydrodynamic interactions are lumped into a single effective parameter. High-resolution images of the adhered particles are then analyzed using various structural measures, such as the radial distribution function, to assess the impact of the fluid flow on the adhered particle distributions.

More detailed simulations that explicitly account for the fluid mechanics are then employed to develop predictive and transferable simulations of the particle flow and adhesion process. We employ a variant of the immersed boundary technique based on a coupled Lattice Boltzmann Method/Brownian dynamics framework, and find that the fluid flow around adhered particles must be carefully resolved to provide accurate descriptions of even relatively simple measures such as the areal density as a function of time. Given the prohibitive computational expense associated with such simulations over the long times characteristic of the experiments, we also investigate an alternative approach in which high resolution particle trajectories are used to populate a database and corresponding regression model that are used to inform Brownian dynamics simulations.

[1] M. H. Flamm et al., Blood 120, 190 (2012).

[2]. J. K. W. Chesnutt and J. S. Marshall, Comput Fluids 38, 1782 (2009).

[3] T. V. Colace, G. W. Tormoen, O. J. T. McCarty, and S. L. Diamond, Annu Rev Biomed Eng. 15, 283 (2013).