A Digital Twin of the Coaxial Lamination Mixer for the Systematic Study of Mixing Performance and the Prediction of Precipitated Nanoparticle Properties

Abstract

The synthesis of nanoparticles in microchannels promises the advantages of small size, uniform shape and narrow size distribution. However, only with insights into the mixing processes can the most suitable designs and operating conditions be systematically determined. Coaxial lamination mixers (CLM) built by 2-photon polymerization can operate long-term stable nanoparticle precipitation without fouling issues. Contact of the organic phase with the microchannel walls is prevented while mixing with the aqueous phase is intensified. A coaxial nozzle allows 3D hydrodynamic focusing followed by a sequence of stretch-and-fold units. By means of a digital twin based on computational fluid dynamics (CFD) and numerical evaluation of mixing progression, the influences of operation conditions are now studied in detail. As a measure for homogenization, the mixing index (MI) was extracted as a function of microchannel position for different operating parameters such as the total flow rate and the share of solvent flow. As an exemplary result, behind a third stretch-and-fold unit, practically perfect mixing (MI>0.9) is predicted at total flow rates between 50 µL/min and 400 µL/min and up to 20% solvent flow share. Based on MI values, the mixing time, which is decisive for the size and dispersity of the nanoparticles, can be determined. Under the conditions considered, it ranges from 5 ms to 54 ms. A good correlation between the predicted mixing time and nanoparticle properties, as experimentally observed in earlier work, could be confirmed. The digital twin combining CFD with the MI methodology can in the future be used to adjust the design of a CLM or other micromixers to the desired total flow rates and flow rate ratios and to provide valuable predictions for the mixing time and even the properties of nanoparticles produced by microfluidic antisolvent precipitation.