Efficient detection of gastric cancer biomarkers on functionalized carbon nanoribbons using DFT analysis

Early diagnosis of gastric cancer (GC) is crucially important to initiate a therapy plan aiming at rescue and cure. In this regard, the detection of volatile organic compounds (VOCs), related to GC in the patient's exhaled breath, is known to be an efficient and cost-effective technique for early diagnosis. The scope of the present study is to develop a nano-biosensor with great sensitivity and suitable selectivity towards specific VOCs related to GC, such as 2-pentanone, butanone, isoprene, methylglyoxal, N-decanal, N-pentanal, and pyridine. We employed van der Waals corrected density functional theory (DFT) to study the adsorption properties of the mentioned VOCs along with interfering air molecules (N₂, O₂, H₂O, CO₂) using recently synthesized carbon nanoribbons (CNRs). We found that pristine CNRs weakly adsorbed the VOCs with adsorption energies ([Formula: see text]), which is not suitable for practical sensing applications. However, the incorporation of selected transition metals (Co, Fe, Mn, Ni) in nitrogen-functionalized CNRs (N-CNRs) enhanced the [Formula: see text] values to -0.802, -0.899, -1.566, -1.260, -1.482, -1.057, and - 0.674 eV for 2-pentanone, butanone, isoprene, methylglyoxal, N-decanal, N-pentanal, and pyridine, respectively. Appropriate [Formula: see text] values along with distinct variations in the electronic and magnetic properties, measured through band structures, density of states, work function and charge transfer analysis, validated the potential of TM-doped N-CNRs as efficient biosensors towards GC-related VOCs. Consequently, the TM-doped N-CNRs are proposed as candidates for platforms of nano biosensors to detect GC biomarkers with high selectivity.