An Electrochemical Approach for the Selective Detection of Cancer Metabolic Creatine Biomarker with Porous Nano-Formulated CMNO Materials Decorated Glassy Carbon Electrode

Assessment of Melamine in Different Water Samples with ZnO-doped Co3 O4 Nanoparticles on a Glassy Carbon Electrode by Differential Pulse Voltammetry

In this investigation, a melamine electrochemical sensor has been developed by using wet-chemically synthesized low-dimensional aggregated nanoparticles (NPs) of ZnO-doped Co₃ O₄ as sensing substrate that were decorated onto flat glassy carbon electrode (GCE). The characterization of NPs such as UV-Vis, FTIR, XRD, XPS, EDS, and FESEM was done for detailed investigations in optical, functional, structural, elemental, and morphological analyses. The ZnO-doped Co₃ O₄ NPs decorated GCE was used as a sensing probe to analyze the target chemical melamine in a phosphate buffer at pH 5.7 by applying differential pulse voltammetry (DPV). It exhibited good performances in terms of sensor analytical parameters such as large linear dynamic range (LDR; 0.15-1.35 mM) of melamine detection, high sensitivity (80.6 μA mM^-1  cm^-2 ), low limit of detection (LOD; 0.118±0.005 mM), low limit of quantification (LOQ; 0.393 mM), and fast response time (30 s). Besides this, the good reproducibility (in several hours) and repeatability were investigated under identical conditions. Moreover, it was implemented to measure the long-time stability, electron mobility, less charge-transfer resistance, and analyzed diffusion-controlled process for the oxidation reaction of the NPs assembled working GCE electrode, which showed outstanding chemical sensor performances. For validation, real environmental samples were collected from various water sources and investigated successfully with regard to the reliability of the selective melamine detection with prepared NPs coated sensor probe. Therefore, this approach might be introduced as an alternative route in the sensor technology to detect selectively unsafe chemicals by an electrochemical method with nanostructure-doped materials for the safety of environmental, ecological, healthcare fields in a broad scale.

Using High-Frequency Information and RH to Estimate AQI Based on SVR

The Environmental Protection Administration of Taiwan’s Executive Yuan has set up many air quality monitoring stations to monitor air pollution in the environment. The current weather forecast also includes information used to predict air pollution. Since air quality indicators have a considerable impact on people, the development of a simple, fast, and low-cost method to measure the AQI value is a worthy topic of research. In this study, a method was proposed to estimate AQI. Visibility had a clear positive relationship with AQI. When images and AQI were compared, it was easy to see that visibility decreased with the AQI value increase. Distance is the main factor affecting visibility, so measuring visibility with images has also become a research topic. Images with high and low PM_2.5 concentrations were used to obtain regions of interest (RoI). The pixels in the RoI were calculated to obtain high-frequency information. The high-frequency information of RoI, RH, and true AQI was used for training via SVR, which was used to generate the model for AQI estimation. One year of experimental samples was collected for the experiment. Two indices were used to evaluate the performance of the proposed method. The results showed that the proposed method could be used to estimate AQI with acceptable performance in a simple, fast, and low-cost way.