Droplet-based logic gates simulation of viscoelastic fluids under electric field

Abstract

Nano and microfluidic technologies are emerging tools for preparing drugs with controlled properties or creating microfluidic devices similar to logic circuits. This work investigates a droplet-based logic gate system for viscoelastic fluids since bio-fluids are mostly viscoelastic. We consider an AND/OR system evaluating the Weissenberg number, the Capillary number, and geometric parameters. In order to classify operational conditions, a deep learning classification algorithm is used to derive a reduced-order model. This deep learning classification model accelerates operating conditions predictions and can be used to combine different AND/OR branches without conducting complex simulations. We concluded that non-operating regions can become operational if an external force is applied. We also proposed an electrically induction technique that can transform non-operational conditions into operating ones by using an electric field to repel or attract the droplet.