Deep learning-augmented T-junction droplet generation.

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis.

On-Demand Production of Femtoliter Drops in Microchannels and Their Use as Biological Reaction Compartments.

We present a method allowing to produce monodisperse droplets with volumes in the femtoliter range in a microchannel on demand. The method utilizes pulsed electric fields deforming the interface between an aqueous and an oil phase and pinching off droplets. Water and xanthan gum solutions are considered as disperse-phase liquids, and it is shown that the method can be applied even to solutions with a zero-shear rate viscosity more than 10-times higher than that of water.

Entropy Generation Analysis of Laminar Flows of Water-Based Nanofluids in Horizontal Minitubes under Constant Heat Flux Conditions.

During the last decade, second law analysis via entropy generation has become important in terms of entropy generation minimization (EGM), thermal engineering system design, irreversibility, and energy saving. In this study, heat transfer and entropy generation characteristics of flows of multi-walled carbon nanotube-based nanofluids were investigated in horizontal minitubes with outer and inner diameters of ~1067 and ~889 µm, respectively. Carbon nanotubes (CNTs) with outer diameter of 10-20 nm and length of 1-2 µm were used for nanofluid preparation, and water was considered as the base fluid.