Nanoscale Dynamics and Protein Adhesivity of Alkylamine Self-Assembled Monolayers on Graphene

S. O’Mahony, C. O’Dwyer, C. A. Nijhuis, J. C. Greer, A. J. Quinn, D. Thompson

Atomic-scale molecular dynamics computer simulations are used to probe the structure, dynamics, and energetics of alkylamine self-assembled monolayer (SAM) films on graphene and to model the formation of molecular bilayers and protein complexes on the films. Routes toward the development and exploitation of functionalized graphene structures are detailed here, and we show that the SAM architecture can be tailored for use in emerging applications (e.g., electrically stimulated nerve fiber growth via the targeted binding of specific cell surface peptide sequences on the functionalized graphene scaffold). The simulations quantify the changes in film physisorption on graphene and the alkyl chain packing efficiency as the film surface is made more polar by changing the terminal groups from methyl (-CH3) to amine (-NH2) to hydroxyl (-OH). The mode of molecule packing dictates the orientation and spacing between terminal groups on the surface of the SAM, which determines the way in which successive layers build up on the surface, whether via the formation of bilayers of the molecule or the immobilization of other (macro)molecules (e.g., proteins) on the SAM. The simulations show the formation of ordered, stable assemblies of monolayers and bilayers of decylamine-based molecules on graphene. These films can serve as protein adsorption platforms, with a hydrophobin protein showing strong and selective adsorption by binding via its hydrophobic patch to methyl-terminated films and binding to amine-terminated films using its more hydrophilic surface regions. Design rules obtained from modeling the atomic-scale structure of the films and interfaces may provide input into experiments for the rational design of assemblies in which the electronic, physicochemical, and mechanical properties of the substrate, film, and protein layer can be tuned to provide the desired functionality.