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

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.