Rational design and understanding of the intrinsic mechanism are critical to develop highly active and durable electrocatalysts. In this study, a series of bi-metallic boride catalysts based on Ni and Co were prepared, and their activities were evaluated. The synthesised Co-10Ni-B catalyst exhibited excellent activity for water splitting in a 1 M KOH electrolyte. The overpotential was 330 mV at a current density of 10 mA cm-2, better than previously reported mono-metallic borides and even IrO2. The synergistic effect of Co and Ni was proved by X-ray photoelectron spectroscopy and electrochemical impedance spectroscopy. The facile formation of critical intermediates CoOOH and NiOOH during the catalytic processes and a significant increase in surface area owing to the introduction of a second metal into mono-metallic boride were attributed to the superior catalytic performance of catalysts for the oxygen evolution reaction. A Co-10Ni-B-sp catalyst with a higher surface area than the Co-10Ni-B catalyst was also synthesised to evaluate the effect of a high surface area on the catalytic activity. A lower overpotential of 310 mV at a current density of 10 mA cm-2 was achieved.

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We designed a silicon-based fast-generated static droplets array (SDA) chip and developed a rapid digital polymerase chain reaction (dPCR) detection platform that is easy to load samples for fluorescence monitoring. By using the direct scraping method for sample loading, a droplet array of 2704 microwells with each volume of about 0.785 nL can be easily realized. It was determined that the sample loading time was less than 10 s with very simple and efficient characteristics. In this platform, a pressurized thermal cycling device was first used to solve the evaporation problem usually encountered for dPCR experiments, which is critical to ensuring the successful amplification of templates at the nanoliter scale. We used a gradient dilution of the hepatitis B virus (HBV) plasmid as the target DNA for a dPCR reaction to test the feasibility of the dPCR chip. Our experimental results demonstrated that the dPCR chip could be used to quantitatively detect DNA molecules. Furthermore, the platform can measure the fluorescence intensity in real-time. To test the accuracy of the digital PCR system, we chose three-channel silicon-based chips to operate real-time fluorescent PCR experiments on this platform.

With the evolution of the pandemic caused by the Coronavirus disease of 2019 (COVID-19), reverse transcriptase-polymerase chain reactions (RT-PCR) have invariably been a golden standard in clinical diagnosis. Nevertheless, the traditional polymerase chain reaction (PCR) is not feasible for field application due to its drawbacks, such as time-consuming and laboratory-based dependence. To overcome these challenges, a microchip-based ultrafast PCR system called SWM-02 was proposed to make PCR assay in a rapid, portable, and low-cost strategy. This novel platform can perform 6-sample detection per run using multiple fluorescent channels and complete an ultrafast COVID-19 RT-PCR test within 40 min. Here, we evaluated the performance of the microdevice using the gradient-diluted COVID-19 reference samples and commercial PCR kit and determined its limit-of-detection (LoD) as 500 copies/mL, whose variation coefficients for the nucleocapsid (N) gene and open reading frame 1 ab region (ORF1ab) gene are 1.427% and 0.7872%, respectively. The system also revealed an excellent linear correlation between cycle threshold (Ct) values and dilution factors (R2 > 0.99). Additionally, we successfully detected the target RNAs and internal gene in the clinical samples by fast PCR, which shows strong consistency with conventional PCR protocol. Hence, with compact dimension, user-friendly design, and fast processing time, SWM-02 has the capability of offering timely and sensitive on-site molecular diagnosis for prevention and control of pathogen transmission.

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Point-of-care (POC) real-time polymerase chain reaction (PCR) has become one of the most important technologies for many fields such as pathogen detection and water-quality monitoring. POC real-time PCR usually adopts chips with small-volume chambers for portability, which is more likely to produce complex noise that seriously affects the accuracy. Such complex noises are difficult to be eliminated by the traditional fixed area algorithm that is most commonly used at present because they usually have random shape, location, and brightness. To address this problem, we proposed a novel image analysis method, Dynamic Deep Learning Noise Elimination Method (DIPLOID), in this paper. Our new method could recognize and output the mask of the interference by Mask R-CNN, and then subtract the interference and select the maximum valid contiguous area for brightness analysis by dynamic programming. Compared with the traditional method, DIPLOID increased the accuracy, sensitivity, and specificity from 57.9 to 94.6 % , 49.1 to 93.9 % , and 65.9 to 95.2 % , respectively. DIPLOID has great anti-interference, robustness, and sensitivity, which can reduce the impact of complex noise as much as possible from the aspect of the algorithm. As shown in the experiments of this paper, our method significantly improved the accuracy to over 94 % under the complex noise situation, which could make the POC real-time PCR have greater potential in the future. Supplementary Information The online version contains supplementary material available at 10.1007/s00216-022-03950-7.