Carbon dioxide (CO2) is a greenhouse gas in the atmosphere and scientists are working on converting it to useful products, thereby reducing its quantity in the atmosphere. For converting CO2, different approaches are used, and among them, electrochemistry is found to be the most common and more efficient technique. Current methods for detecting the products of electrochemical CO2 conversion are time-consuming and complex. To combat this, a simple, cost-effective colorimetric method has been developed to detect methanol, ethanol, and formic acid, which are formed electrochemically from CO2. In the present work, the highly efficient sensitive dyes were successfully established to detect these three compounds under optimized conditions. These dyes demonstrated excellent selectivity and showed no cross-reaction with other products generated in the CO2 conversion system. In the analysis using these three compounds, this strategy shows good specificity and limit of detection (LOD, ~0.03–0.06 ppm). A cost-effective and sensitive Internet of Things (IoT) colorimetric sensor prototype was developed to implement these dyes systems for practical and real-time application. Employing the dyes as sensing elements, the prototype exhibits unique red, green, and blue (RGB) values upon exposure to test solutions with a short response time of 2 s. Detection of these compounds via this new approach has been proven effective by comparing them with nuclear magnetic resonance (NMR). This novel approach can replace heavy-duty instruments such as high-pressure liquid chromatography (HPLC), gas chromatography (G.C.), and NMR due to its extraordinary selectivity and rapidity.

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The measurement of blood glucose levels is essential for diagnosing and managing diabetes. Enzymatic and nonenzymatic approaches using electrochemical biosensors are used to measure serum or plasma glucose accurately. Current research aims to develop and improve noninvasive methods of detecting glucose in sweat that are accurate, sensitive, and stable. The carbon nanotube (CNT)-copper oxide (CuO) nanocomposite (NC) improved direct electron transport to the electrode surface in this study. The complex precipitation method was used to make this NC. X-ray diffraction (XRD) and scanning electron microscopy were used to investigate the crystal structure and morphology of the prepared catalyst. Using cyclic voltammetry and amperometry, the electrocatalytic activity of the as-prepared catalyst was evaluated. The electrocatalytic activity in artificial sweat solution was examined at various scan rates and at various glucose concentrations. The detection limit of the CNT-CuO NC catalyst was 3.90 µM, with a sensitivity of 15.3 mA cm−2 µM−1 in a linear range of 5–100 µM. Furthermore, this NC demonstrated a high degree of selectivity for various bio-compounds found in sweat, with no interfering cross-reactions from these species. The CNT-CuO NC, as produced, has good sensitivity, rapid reaction time (2 s), and stability, indicating its potential for glucose sensing. Graphical Abstract

The field of strain sensing involves the ability to measure an electrical response that corresponds to a strain.

The concentration of carbon dioxide (CO2) in unhealthy people differs greatly from healthy people. High-precision CO2 detection with a quick response time is essential for many biomedical applications. A major focus of this research is on the detection of CO2, one of the most important health biomarkers. We investigated a low-cost, flexible, and reliable strategy by using dyes for colorimetric CO2 sensing in this study. The impacts of temperature, pH, reaction time, reusability, concentration, and dye selectivity were studied thoroughly. This study described real-time CO2 analysis. Using this multi-dye method, we got an average detection limit of 1.98 ppm for CO2, in the range of 50–120 ppm. A portable colorimetric instrument with a smartphone-assisted unit was constructed to determine the relative red/green/blue values for real-time and practical applications within 15 s of interaction and the readings are very similar to those of an optical fiber probe. Environmental and biological chemistry applications are likely to benefit greatly from this unique approach.