The traditional quantitative analysis methods of ascorbic acid (AA), which require expensive equipment, a large amount of samples and professional technicians, are usually complex and time-consuming. A low-cost and high-efficiency AA detection device is reported in this work. It integrates a three-electrode sensor module prepared by screen printing technology, and a microfluidic chip with a finger-actuated micropump peeled from the liquid-crystal display (LCD) 3D printing resin molds. The AA detection process on this device is easy to operate. On-chip detection has been demonstrated to be 2.48 times more sensitive than off-chip detection and requires only a microliter-scale sample volume, which is much smaller than that required in traditional electrochemical methods. Experiments show that the sample and buffer can be fully mixed in the microchannel, which is consistent with the numerical simulation results wherein the mixing efficiency is greater than 90%. Commercially available tablets and beverages are also tested, and the result shows the reliability and accuracy of the device, demonstrating its broad application prospects in the field of point-of-care testing (POCT).

This work presents a magnetic-driven deterministic lateral displacement (m-DLD) microfluidic device. A permanent magnet located at the outlet of the microchannel was used to generate the driving force. Two stages of mirrored round micropillar array were designed for the separation of magnetic beads with three different sizes in turn. The effects of the forcing angle and the inlet width of the micropillar array on the separating efficiency were studied. The m-DLD device with optimal structure parameters shows that the separating efficiencies for the 10 μm, 20 μm and 40 μm magnetic beads are 87%, 89% and 94%, respectively. Furthermore, this m-DLD device was used for antibody recognition and separation among a mixture solution of antibodies. The trajectories of different kinds of magnetic beads coupled with different antigens showed that the m-DLD device could realize a simple and low-cost diagnostic test.

Transition metallic binary alloys have attracted enormous attention in regard to the non-enzymatic detection of glucose due to their high electrocatalytic activities induced by the synergistic effect between the individual metallic species. However, the easy aggregation of the bimetallic particles has limited their performance. Herein, a facile metal–organic framework (MOF)-derived strategy is developed to synthesize a hybrid containing binary Co–Ni nanoparticles decorated on an N-doped porous carbon matrix (Co_xNi_y/N-C) for the non-enzymatic detection of glucose. The Co/Ni ratio in the hybrid is investigated to regulate its electrocatalytic behaviors for glucose sensing. A hybrid with the optimal Co/Ni ratio of 1:1 displays two linear detection ranges (0.5 µM to 1 mM and 1 mM to 10 mM) with a detection limit of 0.11 µM for glucose. The feasibility of using this hybrid-modified SPE for glucose detection in real serum samples has also been validated.