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