Channel-based microfluidics was proven to be a helpful platform for reproducible preparation of nanoparticles (NPs), where controlled mixing of fluids allows homogeneous and tuned process of NPs formation. Nanoprecipitation is a popular method for polymeric NPs formation based on controlled precipitation of a polymer upon mixing of two miscible solvents. Conventionally, flow rate, flow rate ratio and polymer concentration have been utilized to control NPs size and polydispersity. However, minimum attention has been given to the effect of channel geometry on nanoprecipitation process. In our study, we investigated the effect of channel geometry and design on the size and polydispersity index (PDI) of poly (lactic-co-glycolic) acid (PLGA) NPs. Ten different designs with varied channel length, aspect ratio, number of interfaces and channel curvature were fabricated and tested. These variations were introduced to modify the diffusion rate, the interface area or to introduce Dean flow, all of which will change the mixing time . The effects of these variations were compared to that of different flow parameters. Change in channel length did not have a significant effect on particle size. However, increasing the diffusion area and reducing significantly reduced NPs’ size. Moreover, when curvature was introduced into the channel, mixing was enhanced, and particle size was decreased in a manner dependent on the velocity of the generated Dean flow. While different flow parameters continue to be the main approach for adjusting NPs properties, we demonstrate that channel geometry modification enables tuning of NPs’ size using simple designs that can be easily adapted.

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

This paper presents a non-destructive capacitance-based technique for rebars detection in reinforced concrete structure. The proposed technique depends on capacitance variation between the two electrodes of a co-planar capacitive sensor while scanning across different concrete sections with and without reinforcement bars. A mathematical model is used to provide meaningful interpretation for the effect of different sensor and concrete parameters on the measured capacitance. The finite element model is built and accompanied by a dedicated experimental setup to confirm theoretical estimations. Simulation and experimental results confirmed a detectable capacitance variation while scanning across the reinforced concrete slab in experimental setup for rebars detection.