Greenness Assessment Profile of a QbD Screen-Printed Sensor for Real-Time Monitoring of Sodium Valproate

Environmentally sustainable DRS-FTIR probe assisted by chemometric tools for quality control analysis of cinnarizine and piracetam having diverged concentration ranges: Validation, greenness, and whiteness studies

A novel diffuse reflectance fourier transform infrared spectroscopic method accompanied by chemometrics was optimized to fulfill the white analytical chemistry and green analytical chemistry principles for the quantification of cinnarizine and piracetam for the first time without any prior separation in their challenging pharmaceutical preparation, which has a pretty substantial difference in the concentration of cinnarizine/piracetam (1:16). Furthermore, the suggested method was used for cinnarizine/piracetam dissolution testing as an effective alternative to traditional methods. For the cinnarizine/piracetam dissolution tests, we used a dissolution vessel with 900 mL of phosphate buffer pH 2.5 at 37 °C ± 0.5 °C, then the sampling was carried out by frequent withdrawal of 20 µl samples from the dissolution vessel at a one-minute interval, over one hour, then representative fourier transform infrared spectra were recorded. To create a partial-least-squares regression model, a fractional factorial design with 5 different levels and 2 factors was used. This led to the creation of 25 mixtures, 15 as a calibration set and 10 as a validation set, with varying concentration ranges: 1-75 and 16-1000 μg/mL for cinnarizine/piracetam, respectively. Upon optimization of the partial-least-squares regression model, in terms of latent variables and spectral region, root mean square error of cross-validation of 0.477 and 0.270, for cinnarizine/piracetam respectively, were obtained. The optimized partial-least-squares regression model was further validated, providing good results in terms of recovery% (around 98 to 102 %), root mean square error of prediction (0.436 and 3.329), relative root mean square error of prediction (1.210 and 1.245), bias-corrected mean square error of prediction (0.059 and 0.081), and limit of detection (0.125 and 2.786) for cinnarizine/piracetam respectively. Ultimately, the developed method was assessed for whiteness, greenness, and sustainability using five assessment tools. the developed method achieved a greener national environmental method index and complementary green analytical procedure index quadrants with higher eco-scale assessment scores (91), analytical greenness metric scores (0.87), and red-greenblue 12 algorithm scores (89.7) than the reported methods, showing high practical and environmental acceptance for quality control of cinnarizine/piracetam.

AirQuality Lab-on-a-Drone: A Low-Cost 3D-Printed Analytical IoT Platform for Vertical Monitoring of Gaseous H2S

The measurement of gaseous compounds in the atmosphere is a multichallenging task due to their low concentration range, long and latitudinal concentration variations, and the presence of sample interferents. Herein, we present a quadcopter drone deployed with a fully integrated 3D-printed analytical laboratory for H2S monitoring. Also, the analytical system makes part of the Internet of Things approach. The analytical method applied was based on the reaction between fluorescein mercuric acetate and H2S that led to fluorescence quenching. A 5 V micropump at a constant airflow of 50 mL min-1 was employed to deliver constant air into a flask containing 800 μL of the reagent. The analytical signal was obtained using a light-emitting diode and a miniaturized digital light detector. The method enabled the detection of H2S in the range from 15 to 200 ppbv, with a reproducibility of 5% for a sampling time of 10 min and an limit of detection of 9 ppbv. All devices were controlled using an Arduino powered by a small power bank, and the results were transmitted to a smartphone via Bluetooth. The proposed device resulted in a weight of 300 g and an overall cost of ∼50 USD. The platform was used to monitor the concentration of H2S in different intervals next to a wastewater treatment plant at ground and vertical levels. The ability to perform all analytical steps in the same device, the low-energy requirements, the low weight, and the attachment of data transmission modules offer new possibilities for drone-based analytical systems for air pollution monitoring.