Adsorption and sensing of CO and NH3 on chemically modified graphene surfaces

Adsorption of singlet and triplet oxygen on B-doped graphene: adsorption and electronic characteristics

The density functional calculations of electronic and structural properties of the adsorption of dioxygen on boron-doped graphene surfaces are conducted using spin-polarized density functional theory methods, including van der Waals correction. The results show significant differences in the adsorption characteristics of singlet and triplet oxygen on boron-doped graphene surfaces. Both triplet and singlet show only weak attraction to intrinsic and singly doped graphene. The singlet oxygen adsorption on doped graphene shows fascinating features involving chemisorption with dioxetane ring formation with appreciable charge transfer. In contrast, the triplet oxygen is only weakly physisorbed on the boron-doped surfaces. Chemisorption of singlet oxygen occurs with noticeable charge transfer and leads to almost featureless band structures, while the triplet oxygen physisorption proceeds with a well-defined band structure. Chemisorption of the singlet oxygen is attributed to the enormous mixing of π* of dioxygen and the p-orbitals of dopant and carbon. Because of the difference in adsorption characteristics, chemically modified graphene can find use in detecting and trapping singlet oxygen, which has potential applications in photodynamic therapy.

Recent advances in density functional theory approach for optoelectronics properties of graphene

Graphene has received tremendous attention among diverse 2D materials because of its remarkable properties. Its emergence over the last two decades gave a new and distinct dynamic to the study of materials, with several research projects focusing on exploiting its intrinsic properties for optoelectronic devices. This review provides a comprehensive overview of several published articles based on density functional theory and recently introduced machine learning approaches applied to study the electronic and optical properties of graphene. A comprehensive catalogue of the bond lengths, band gaps, and formation energies of various doped graphene systems that determine thermodynamic stability was reported in the literature. In these studies, the peculiarity of the obtained results reported is consequent on the nature and type of the dopants, the choice of the XC functionals, the basis set, and the wrong input parameters. The different density functional theory models, as well as the strengths and uncertainties of the ML potentials employed in the machine learning approach to enhance the prediction models for graphene, were elucidated. Lastly, the thermal properties, modelling of graphene heterostructures, the superconducting behaviour of graphene, and optimization of the DFT models are grey areas that future studies should explore in enhancing its unique potential. Therefore, the identified future trends and knowledge gaps have a prospect in both academia and industry to design future and reliable optoelectronic devices.

Pyridinic Dominance N-Doped Graphene: A Potential Material for SO2 Gas Detection

The sensors based on graphene have shown great promise in the detection of toxic air pollutants that are detrimental to nature and create risks to human health. Many recent experimental and computational efforts have been dedicated to sensor concepts incorporating pure graphene, graphene oxide, and doped graphene. Herein, a combination of spin-polarized density functional theory (DFT) with van der Waals correction and ab initio molecular dynamics (AIMD) approaches are utilized to assess the gas sensing potential of pyridinic dominance N-doped graphene (PNG) toward SO₂ detection. The potential of PNG systems as SO₂ sensing can be explored through an in-depth analysis of adsorption energies, electronic parameters, charge transfer, selectivity, and thermal stability. It is further demonstrated that external strains and the modulation of external electric fields are two effective ways to modify the adsorption strength. In light of these findings, our studies suggest that PNG monolayers have the potential to be an essential substrate for the detection of SO₂.