3D-Printed Microfluidic Nanoelectrospray Ionization Source Based on Hydrodynamic Focusing.

Nanoelectrospray ionization (nESI) mass spectrometry (MS) is an ideal detection method for microfluidic chips, and its performances depend on nESI emitters. However, the fabrication of monolithic nESI emitters in chips was difficult. Herein, we propose a three-dimensional (3D) printing method to develop a microfluidic nanoelectrospray ionization source (NIS), composed of a nESI emitter and other components. Firstly, the NIS was compatible with a 50 - 500 nL min-1 nanoflows by imposing 3D hydrodynamic focusing to compensate for the total flow rate, achieving a 7.2% best relative standard deviation in the total ion current (TIC) profiles. Additionally, it was applied to probe thirteen organic chemicals, insulin, and lysozyme with adequate signal-to-noise ratios and an accuracy of m/z between 9.02 × 10-1 and 1.48 × 103 ppm. Finally, the NIS achieved comparable limits of detection compared with its commercial counterpart. Considering the standardized preparation of NIS, it would be a potential option to develop 3D-printed customized Chip-MS platforms.

Analysis of the Diffusion Process by pH Indicator in Microfluidic Chips for Liposome Production.

In recent years, the development of nano- and micro-particles has attracted considerable interest from researchers and enterprises, because of the potential utility of such particles as drug delivery vehicles. Amongst the different techniques employed for the production of nanoparticles, microfluidic-based methods have proven to be the most effective for controlling particle size and dispersity, and for achieving high encapsulation efficiency of bioactive compounds. In this study, we specifically focus on the production of liposomes, spherical vesicles formed by a lipid bilayer encapsulating an aqueous core. The formation of liposomes in microfluidic devices is often governed by diffusive mass transfer of chemical species at the liquid interface between a solvent (i.e., alcohol) and a non-solvent (i.e., water). In this work, we developed a new approach for the analysis of mixing processes within microfluidic devices. The method relies on the use of a pH indicator, and we demonstrate its utility by characterizing the transfer of ethanol and water within two different microfluidic architectures. Our approach represents an effective route to experimentally characterize diffusion and advection processes governing the formation of vesicular/micellar systems in microfluidics, and can also be employed to validate the results of numerical modelling.