Defect-Engineered Graphene Nanoribbons for Enhanced DNA Sequencing: A Study of Structural Defects and Their Impact on Nucleobase Interaction and Quantum Transport

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High Resolution Image Download MS PowerPoint Slide Graphene, a low-dimensional material, has shown significant promise in bioelectronics over the past two decades. Most research in this field has focused on pristine graphene. However, experimentally fabricated two-dimensional (2D) graphene and one-dimensional (1D) graphene nanoribbons (GNRs) often contain impurities, such as Stone–Wales (sw) and divacancy (dv) defects. In this study, we conducted a comparative analysis of the adsorption behavior of DNA nucleobases–adenine (A), guanine (G), thymine (T), and cytosine (C)─on three types of graphene nanoribbon (GNR) surfaces: pristine (prGNR), divacancy-defected (dvGNR), and Stone–Wales-defected (swGNR). Using semilocal (PBE) and van der Waals-corrected density functional theory methods (vdW-DF2 and PBE-D2), we evaluated the binding energies of the nucleobases on the different GNR surfaces. Our results show that defected GNRs exhibit less negative binding energies for all nucleobases compared to prGNR when dispersion interactions are taken into account. The binding energies calculated using PBE, PBE-D2, and vdW-DF2 methods range from −0.06 to −0.10, −0.55 to −0.80 and −0.59 to −0.78 eV, respectively. The vdW-DF2 method effectively captures vdW interactions, with binding energies following the order G > A > T > C. These interactions result in weak binding between nucleobase and the π-states of the GNR surfaces, inducing a small interfacial dipole and a shift in the energy bandgap. Quantum transport analysis reveals that while pristine GNRs exhibit distinct conduction channels, defects─such as dv and sw configurations─introduce localized states that interact with delocalized ones, generating pronounced Fano resonances characterized by sharp dips in the transmission spectra. Physisorption of DNA nucleobases on different GNR surfaces induces unique resonance peaks in the transmission function, influenced by the type and position of defects. Conductance sensitivity analysis indicates prGNR as a promising candidate for nucleobase detection, leveraging Fano resonances for precise electronic measurements. However, defected GNRs also exhibit significant sensitivity. Furthermore, Current–Voltage ( I – V ) analysis identifies dvGNR devices as the most effective for nucleobase detection due to their high current sensitivity and distinct responses across nucleobases. While prGNR devices detect certain nucleobases, they show less consistent performance due to uniform current trends at higher biases. In contrast, swGNR devices effectively differentiate all four nucleobases through distinct current signals in the 0.6–0.8 V range. These findings underscore the potential of defect-engineered GNRs for the next-generation DNA sequencing applications.

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