In-silico optimization of CO₂ adsorption on graphene nanoribbons via heteroatom edge-doping under competitive H2O conditions

Doped graphene nanoribbons (DGNRs), obtained from partial reduction of doped graphene oxide nanoribbons, exhibit tunable electronic properties that make them promising for CO2 capture. Using first-principles calculations, we investigated edge-modified DGNRs: B-, N-, and P-doped systems with ketidic groups, and BNcodoped DGNRs, to understand how edge manipulation tunes CO2 adsorption. N-doping enhances physisorption (-0.53 eV), while O-and P-functionalized systems show weaker interactions (-0.32 and-0.40 eV), consistent with physisorption. In contrast, CO2 chemisorbs on B-and BN-codoped DGNRs, with adsorption energies of-3.33 and-3.24 eV, due to covalent bonding at boron edge sites. PDOS and Lo & uml;wdin charge analyses rationalize these trends. To assess realistic conditions, H2O adsorption was also examined, revealing competition that may suppress CO2 capture. Nevertheless, BN-codoped motifs, with bifunctional character matching CO2 chemistry, emerge as promising candidates for CO2 adsorption and sensing under appropriate conditions.