Efficient Sensing of Selected Amino Acids as Biomarker by Green Phosphorene Monolayers: Smart Diagnosis of Viruses

Effective techniques for the detection of selected viruses their amino acids (AAs) constituents are highly desired, especially in present COVID pandemic. Motivated by this, we have used density functional theory (DFT) simulations to explore potential applications green phosphorene monolayer (GPM) as efficient nanobio-sensor. We employed van der Waals induced calculations study ground-state geometries, binding strength, electronic structures, and charge transfer mechanism pristine, vacancy-induced metal-doped GPM detect AAs, such glycine, proline aspartic, both aqueous non-aqueous media. find that interactions studied AAs comparatively weak on pristine (?0.49 ?0.76 eV) compared (?0.62 ?1.22 eV). Among considered dopants, Ag-doping enhances stronger than others. In addition appropriate energies, significant transfers coupled with measurable changes properties further authenticate GPM. Boltzmann thermodynamic analysis been sensing under varied conditions temperatures pressure practical applications. Our findings signify based sensors towards AAs.