Facile synthesis of mesoporous silica nanoparticles and its electrochemical conversion of CO2 to fuels

The increasing amount of CO2 emissions from the industries is proving to have disastrous consequences on the environment. It would be highly beneficial if this CO2 is to be recycled and converted into useful fuel. The aim of this project involves synthesizing a suitable catalyst which can be used for the electrochemical (EC) conversion of CO2 to fuel. The developed catalyst should be mesoporous silica nanoparticles and loaded on to a metal oxide surface. The synthesis involved a relatively simple procedure of forming a homogenous mixture for the nanoparticles, drying the mixture for 2 days then loading on to the metal nitrate. Finally, multiple scans and tests were run on the synthesized sample to characterize its qualities. The results show that the synthesized mesoporous silica nanoparticles have suitable catalytic properties for electrochemical reduction of CO2 to fuel

Biosensing studies on CuO-MgO nanocomposites for glucose detection

Approximately 3 million people around the world suffer from diabetes. One of the basic indications of an individual suffering from diabetes can be observed in the form of peaked levels of glucose in the blood. Thus, it is imperative for a non-invasive mechanism to be derived through which glucose levels in the blood can be detected throughout a regular time frame. The aim of this project focuses on synthesis of a nanocomposite which can be used to detect glucose levels in the blood in a non-invasive manner. The selected nanocomposite was made from a mixture of CuO and MgO. Once synthesized, it was subjected to a series of tests and scans. The results demonstrated effective and efficient glucose detection activity of the CuO-MgO nanocomposite

Colorimetry-based detection of nitric oxide from exhaled breath for quantification of oxidative stress in human body

Monitoring exhaled breath is a safe, noninvasive method for determining the health status of the human body. Most of the components in our exhaled breath can act as health biomarkers, and they help in providing information about various diseases. Nitric oxide (NO) is one such important biomarker in exhaled breath that indicates oxidative stress in our body. This work presents a simple and noninvasive quantitative analysis approach for detecting NO from exhaled breath. The sensing is based on the colorimetric assisted detection of NO by m-Cresol Purple, Bromophenol Blue, and Alizaringelb dye. The sensing performance of the dye was analyzed by ultraviolet?visible (UV?Vis) spectroscopy. The study covers various sampling conditions like the pH effect, temperature effect, concentration effect, and selective nature of the dye. The m-Cresol Purple dye exhibited a high sensitivity towards NO with a detection limit of ~0.082 ppm in the linear range of 0.002?0.5 ppm. Moreover, the dye apprehended a high degree of selectivity towards other biocompounds present in the breath, and no possible interfering cross-reaction from these species was observed. The dye offered a high sensitivity, selectivity, fast response, and stability, which benchmark its potential for NO sensing. Further, m-Cresol Purple dye is suitable for NO sensing from the exhaled breath and can assist in quantifying oxidative stress levels in the body for the possible detection of COVID-19.Acknowledgments: This work was supported by the UREP grant #UREP27-044-3-016 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Development and Fabrication of Carbon Nanotube (CNT)/CuO Nanocomposite for Volatile Organic Compounds (VOCs) Gas Sensor Application

Volatile organic compounds (VOCs) have been recognized as one of the primary trace segments of atmospheric air pollutants. The change in the level of VOCs in the surrounding environment can lead to chronic health issues, respiratory problems, nerve system disorder, and toxicity in kidneys/liver. Thus, monitoring of VOCs concentration in the surrounding environment is significant for avoiding serious health problems. Herein, copper oxide (CuO) nanoparticle and carbon nanotube (CNT) nanocomposite (NC) are presented for the efficient detection of VOCs. The scalable sol-gel method is adopted for the controlled growth of CNT/CuO NC. The structural, elemental, and morphological analysis is performed by XRD, FTIR spectroscopy, and SEM characterization, respectively. The VOCs sensor was fabricated by drop-casting the as-synthesized CNT/CuO NC on interdigitated electrodes (IDEs). The CNT/CuO sensing response is analyzed for six VOCs that include toluene, methanol, acetone, chloroform, xylene, and benzene. The CNT/CuO response towards different VOCs is investigated with respect to change in resistance of the material in the presence of test VOC and in an inert atmosphere. In comparison to other VOCs, the sensor exhibits high sensitivity toward benzene. The estimated change in relative resistance (AR) for benzene is ?0.62% for 500 ppm concentration. Moreover, the sensor apprehended a detection of benzene with a concentration as low as 5 ppm. The as-synthesized CNT/CuO NC offers high sensitivity and low detection limit, which benchmark its potential for benzene detection.This work is carried by the UREP grant # UREP27-044-3-016 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu