In silico engineering of graphitic carbon nitride nanostructures through germanium mono-doping and codoping with transition metals (Ni, Pd, Pt) as sensors for diazinon organophosphorus pesticide pollutants
Abstract
The extensive use of pesticides has raised concerns about environmental contamination, which poses potential health risks to humans and aquatic life. Hence, the need for a healthy and friendly ecosystem initiated this study, which was modeled through profound density functional theory (DFT) at the B3LYP-D3(BJ)/def2svp level of theory to gain insights into the electronic characteristics of germanium-doped graphitic carbon nitride (Ge@C3N4) engineered with nickel group transition metals (Ni, Pt, and Pd) as sensors for diazinon (DZN), an organophosphorus pesticide pollutant. To effectively sense diazinon, this research employed a variety of methodologies, beginning with the analysis of electronic properties, intermolecular investigations, adsorption studies, and sensor mechanisms. These detailed assessments revealed insightful results, as clearly indicated by their narrow energy gap and other electronic properties. Noncovalent interactions characterized by van der Waals forces were revealed predominantly by quantum atoms in molecules (QTAIM) and noncovalent interaction (NCI) analyses. Furthermore, the results of the adsorption studies, which measured the strength of the interaction between the pesticide molecules and the nanostructures, revealed favorable results characterized by negative adsorption energies of − 1.613, − 1.613, and − 1.599 eV for DZN_Ge@C3N4, DZN_Ni_Ge@C3N4, and DZN_Pd_Ge@C3N4, respectively. The simulated mechanism through which diazinon is sensed revealed…
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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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