Tailoring adsorbents for levodopa detection: a DFT study on Pt-encapsulated fullerene systems.

Despite its effectiveness in managing the motor symptoms of Parkinson's disease, levodopa therapy is often accompanied by adverse effects that can significantly reduce patients' quality of life. Hence, the need to detect levodopa has escalated among researchers and health experts. Herein, the intricacies of levodopa adsorption were studied using newly tailored fullerene-based adsorbents.

Computational modelling of graphene/aluminum nitride (GP/AlN) hybrid materials for the detection of 2,4 dichlorophenoxyacetic acid (DCP) pollutant.

Despite their efficacy in eliminating undesired crops and increasing yield, a range of environmental issues and chronic ailments arise when hazardous chemicals are highly concentrated in wastewater and then deposited into rivers, lakes or the air. Hence, the detection of these chemicals has become a cause of concern for researchers and scientists because they contribute largely to serious health problems. Herein, the potential of newly tailored nanomaterials for the detection of 2,4 dichlorophenoxyacetic acid (DCP) in humans was examined.

Adsorption and sensor performance of transition metal-decorated zirconium-doped silicon carbide nanotubes for NO gas application: a computational insight.

Owing to the fact that the detection limit of already existing sensor-devices is below 100% efficiency, the use of 3D nanomaterials as detectors and sensors for various pollutants has attracted interest from researchers in this field. Therefore, the sensing potentials of bare and the impact of Cu-group transition metal (Cu, Ag, Au)-functionalized silicon carbide nanotube (SiCNT) nanostructured surfaces were examined towards the efficient detection of NO gas in the atmosphere. All computational calculations were carried out using the density functional theory (DFT) electronic structure method at the B3LYP-D3(BJ)/def2svp level of theory.