Computational Exploration of Dopamine Adsorption on Carbon Nanotubes for Electrochemical Sensing

Dopamine (DA), has a variety of impacts on human health. Due to the high cost and labor-intensity of its current measurement methods, sensitive and low-cost electrochemical sensors with carbonaceous substrate materials have been proposed as an alternative. Single-chirality single-walled carbon nanotubes (SWCNTs) have gained interest for their chirality-dependent properties. In a recent study, we demonstrated that the sensing response of DA varies for SWCNT chiralities. In this study, we performed density-functional theory (DFT) simulations to identify low-energy conformers of DA and to gain atomic-level understanding of the interactions upon DA adsorption on (6,6) SWCNTs. We utilized Bayesian Optimization Structure Search (BOSS) to sample energy landscapes and identify the lowest-energy DA conformers and adsorption configurations. As a result, we found 6 low-energy conformers of DA and one adsorption configuration type of DA on the (6,6) SWCNT, where the aromatic ring of DA adsorbs flat on the SWCNT and the flexible side chain is oriented away from the substrate. Analysis of its electronic structure revealed that DA physisorbs on the (6,6) SWCNT via the aromatic ring. The present workflow can be expanded to other chiralities and molecules to support substrate material development for electrochemical sensors with applications in healthcare and environmental monitoring.