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Preparation of Biomass-based Mesoporous Carbon with Higher Nitrogen-/Oxygen-chelating Adsorption for CuII Through Microwave Pre-Pyrolysis
Published on: February 12, 2019
Adsorption of Monocyclic Carbon Rings on Graphene: Energetics Revealed via Continuum Modeling
Mahroof Kalathingal1, Cheriyacheruvakkara Owais1, Devaraj Sundararaj Praveen Roy1
1School of Chemistry and Centre for Computation, Modelling and Simulation (CCMS), Indian Institute of Science Education and Research Thiruvananthapuram (IISER-TVM), Vithura, Thiruvananthapuram 695551, India.
Abstract:
Gas-phase spectroscopic detection of tiny carbon clusters is a recent success story in the area of carbon cluster research. However, experimental production and isolation of these clusters are extremely difficult because of their high reactivity. One possibility to isolate the generated clusters would be to deposit them on graphene and to desorb them for subsequent use. One of the pertinent questions toward realizing this would be the energetics of the adsorption process. Therefore, in this work, the energetics for the adsorption of the monocyclic carbon rings (C with n = 10, 12, 14, 16, 18, 20, and 22) on a graphene sheet are investigated using the analytical approaches, developed earlier by Hill and co-workers. The adsorption process here is driven by the noncovalent interactions between the carbon rings and the graphene sheet. The analyses of the interaction energies as a function of both the vertical distance Z and the rotational angle ϕ are performed in order to determine the preferred orientations, equilibrium positions, and binding energies for the adsorption of various carbon rings on graphene. We find that the preferred orientation of the rings with respect to the graphene sheet is the parallel orientation. The results from continuum, discrete-continuum, and discrete models are in good agreement. Further, computations using density functional theory and quantum mechanics/molecular mechanics approaches are performed, and comparisons of the computed energetics with the data from the models are reported. Finally, we highlight the scope and the limitations of the analytical models.
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