Adsorption properties and sensing capabilities of pristine and Stone–Wales defected BN nanosheets for lung cancer VOC biomarkers: A DFT investigation

Abstract

Lung cancer (LC) continues to be a predominant cause of global mortality, with early identification being a significant challenge due to the constraints of existing detection technologies, which are frequently invasive, expensive, and inaccessible. This study utilized density functional theory (DFT) to systematically examine the efficacy of both pristine and Stone–Wales (SW) defect-engineered BN nanosheets as selective biosensors for the early detection of LC-associated volatile organic compounds (VOCs): benzene (C₆H₆), isoprene (C₅H₈), and methyl-cyclopentane (C₆H₁₂). Thorough simulations demonstrated that the incorporation of software faults markedly modifies the electrical structure of BN nanosheets, thereby improving their sensitivity and selectivity for the target VOCs. The adsorption energy estimates (E_ads) were consistently negative across all systems, signifying stable and exothermic interactions. The adsorption energies of benzene, isoprene, and methyl-cyclopentane on virgin BN were −0.787 eV, −0.893 eV, and −0.740 eV, respectively; for the BN-SW substrate, the values were −0.770 eV, −0.839 eV, and −0.603 eV, respectively. These findings validate the thermodynamic favorability and strong interaction between the VOCs and the sensor surfaces. The computed global reactivity descriptors and recovery durations further substantiate the efficacy of BN and BN-SW nanosheets for real-time biosensing. This study illustrates that both pristine and defect-engineered BN nanosheets, especially those with Stone–Wales defects, present highly promising platforms for the early detection of lung cancer biomarkers, facilitating the future creation of efficient, non-invasive diagnostic devices.