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

Abstract

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