Insight into the micro scale dynamics of a micro fluidic wetting-based conveying system by particle based simulation

Abstract

We simulate a microfluidic conveying system using the many-body dissipative particle dynamics method (MDPD). The conveying system can transport micro parts to a specified spot on a surface by letting them float inside or on top of a droplet, which is pumped by changing the wetting behaviour of the substrate, e.g., with electrowetting on dielectrics. Subsequent evaporation removes the fluid; the micro part remains on its final position, where a second substrate can pick it up. In this way, the wetting control can be separate from the final device substrate. The MDPD method represents a fluid by particles, which are interpreted as a coarse graining of the fluid's molecules. The choice of interaction forces allows for free surfaces. To introduce a contact angle model, non-moving particles beyond the substrate interact with the fluid particles by MDPD forces such that the required contact angle emerges. The micro part is simulated by particles with spring-type interaction forces.

Modeling capillary forces for large displacements

“…By accounting for both liquid meniscus' partial wetting of solid surfaces (earlier attempted 26,27 ) and limited angle hysteresis over edges, the model portraits more accurately the behavior of finitely-deformable solid/liquid interfaces. For displacements larger than the elastic limit, we show that this behavior is distinctively characterized by the unpinning of triple contact lines.…”

Markovian equations of motion for non-Markovian coarse-graining and properties for graphene blobs

“…in analogy to (8). This also gives P 0 = P. L is the conventional Liouville operator introduced earlier.…”

“…The term 'coarse-graining' (CG) refers to a collection of methods used to reduce the number of degrees of freedom of complex atomistic systems such as polymers [1,2], proteins [3], fluids [4][5][6][7][8] or combinations thereof. The motivation for doing so is straightforward: computational time can be saved or larger systems over longer time-scales can be approached by keeping only the relevant part of the information.…”

SYMPLER: SYMbolic ParticLE simulatoR with grid-computing interface

“…In all these cases particle dynamics was used for an SPH-simulation of the fluid dynamics of the moulded material. Further fluid dynamic applications of SYMPLER have been the simulation and design of electrowetting based microfluidic devices for the transportation of pico-to nanoliter droplets [46,47], constraint SPH-simulations of haemodynamics for the estimation of blood flow measurements with magnetic resonance imaging [48], and hydrodynamics with convective transport and dynamics of local magnetisation [49].…”