Enhancing drop mixing in powder bed by alternative particle arrangements with contradictory hydrophilicity

Abstract

Background: Drop mixing in porous media is critical to printing quality of inkjet printing and binder jetting 3D printing, however, the mixing is poor due to restricted pore space. In this study, an alternative hydrophobic/hydrophilic particle arrangement was proposed to enhance dual droplets mixing in a powder bed. Methods: A computational fluid dynamic (CFD) model was first developed to simulate the fluid flow for drops falling on a powder bed by using volume of fluid (VOF) technique. Two drops containing separate solutes sequentially impact an assembly of particles. An index of mixing was proposed to quantitatively describe the degree of mixing by calculating the standard deviation of species concentrations. Significant Findings: To enhance mixing, a new approach was developed to improve liquid mixing by arranging hydrophobic/hydrophilic particles alternatively. Furthermore, drops falling with a horizontal offset was shown to prolong the vorticity for convective mass transportation. With an optimal offset distance of 15μm, the mixing degree can be enhanced from 34.2% to 56.2%. The printing strategy developed from this study could apparently enhance drop mixing in porous media and provided potential developments for multiple-component mixing in binder jetting 3D printing. ? 2021 Taiwan Institute of Chemical Engineers