Efficient detection of lung cancer biomarkers using functionalized transition metal dichalcogenides (MoS2) Monolayers: DFT study

Abstract

Selective sensing properties of transition metal dichalcogenides (MoX2, X = S, Se) towards specific volatile organic compounds (VOCs) associated with lung-cancer are investigated using state-of-the-art density-functional theory (DFT) methods. In the present investigation, a combination of DFT and the non-equilibrium Green’s functions (NEGF) formalism are employed to probe the sensing of four VOCs; namely: (i) Isoprene “C5H8”, (ii) Toluene “C7H8”, (iii) Cyclopropanone “C3H4O”, and (iv) Isopropanol “C3H8O”; and four interfering air molecules CO2, H2O, N2 and O2. We find that the doping of single atom of selected transition metals (TMs = Mn, Fe, Ni, Cu) can enhance both the sensitivity and the selectivity of MoX2. Our results show that the selectivity is rather distinct towards the detection of VOCs when TMs doping is targeting the chalcogenide site. Adsorption energies, charge transfers, electronic properties through density of states and band structures, and the sensor responses are obtained in all the cases, particularly for C5H8 and C3H8O, which show superior selectivities. Enhanced selectivity is attributed to the enhancement in the polarity of the substrate after the TMs doping targeting the chalcogenide sites. Our work demonstrates the potential of MoX2 based single atom catalysts as efficient biosensor towards the specific VOCs for the early diagnosis of lung cancer.PACS Numbers: 31.15.E-, 68.43.-h, 68.43.Fg, 82.33.Pt, 87.15.Aa, 87.15.Kg, 87.19.Xx, 87.19.xj.