Theoretical model study of adsorbed antimalarial-graphene dimers: doping effects, photophysical parameters, intermolecular interactions, edge adsorption, and SERS

Abstract

Future diagnostics and therapy applications are in part riding on the discovery and implementation of new optical techniques and strategies (which often derive from dyads) for example, prediction of features in surface-enhanced Raman spectroscopy requires the study of chromophore-chromophore interactions involve intermolecular forces, drug delivery, and photo mechanisms which are of great interest. New matches between chromophore systems (i.e. FRET), and π-delocalized surfaces are important to study. We explore low-molecular weight drug molecules and their interaction with the reporter material/surface of graphene. Bonding, charge transfer and orbital interactions for 2-amino-5-(1-methyl-5-nitro-2-imidazolyl)-1,3,4-thiadiazole (megazol or AMIT) on graphene were carried out. The graphene model substrate was monotonically/monatomically substituted (doped) with one neutral heteroatom (N/O/S/B) in place of one carbon center; chemical adsorption of AMIT is due to charge transfer from doped graphene to AMIT (DFT). Our AMIT-nanocluster studies show that the nanoclusters will act as a sensor component for the detection of drugs due to SERS. Our findings identified that the greater the energy of the charge transfer, the stronger the calculated chemical adsorption. Additionally, charge transfer is highest for the N-doped systems and least for pristine graphene, resulting in a stronger adsorption energy for N-doped graphene. Mulliken charge analysis of structures confirms enhancement found in QD-AMIT systems.

Communicated by Ramaswamy H. Sarma

Keywords:

• DFT
• Megazol
• AMIT
• graphene
• nanoclusters
• SERS
• UV-vis

Acknowledgements

D.G.C. acknowledges financial support and resources from KAIST and the International Joint Usage Project with ICR, Kyoto University (2019-115 and 2020-124) to make this work possible. The Molecular Logic Laboratory is grateful for recent funding through the National Research Foundation of Korea (NRF) (2021R1F1A1046576). In addition, we are excited and grateful for the recent and perennial KC30 grant provided by KAIST (2021-). P.M.S. acknowledges the KGSP of Korea. B.C. would like to thank the BARC computer division for the supercomputing facility. This work was also supported by the Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1A6A1A03041954)

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No potential conflict of interest was reported by the authors.

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Funding

The author(s) reported there is no funding associated with the work featured in this article.