Brownian dynamics simulations of hydrophobic dendrimer adsorption

Abstract

The adsorption of an isolated hydrophobic dendrimer onto a flat surface is studied in this work using Brownian dynamics simulations. The dendrimer is modelled as a freely jointed bead-rod chain. Bead–bead and bead–surface hydrophobic interactions along with excluded-volume interactions are accounted for using a Lennard-Jones potential. Adsorption behaviour is studied as a function of the strength of hydrophobic interactions, dendrimer generation and distribution of hydrophobic groups within the dendrimer. The adsorbed dendrimer adopts a disk-like conformation by compressing in the direction normal to the surface and expanding in the direction parallel to the surface. As the strength of hydrophobicity decreases, the adsorbed dendrimer expands in the normal direction and contracts in the parallel direction. Eventually, at a very low level of hydrophobicity, the dendrimer desorbs and adopts a sphere-like conformation. Bead density profiles show that the adsorbed hydrophobic dendrimer forms a two-layer structure, with one layer corresponding to adsorbed groups, and another layer in free solution, similar to charged dendrimer adsorption. However, unlike charged dendrimer adsorption, all terminal groups can be attached to a surface using a dendrimer having all hydrophobic groups or hydrophobic terminal groups. In the case of a dendrimer having only hydrophobic branching groups, most of the terminal groups can be placed in free solution. Also, an adsorbed hydrophobic dendrimer forms a relatively compact structure unlike the stretched configuration of adsorbed charged dendrimers. The results presented here suggest how to tune the levels of hydrophobicity and charge to tailor dendrimer surface conformations, and may help guide hydrophobic dendrimer design for applications such as drug delivery and surface functionalisation.

Keywords:

• dendrimer
• adsoprtion
• hydrophobic
• Brownian dynamics

Acknowledgements

We thank Dr Jan Andzelm, Dr Joshua Orlicki, and Dr Adam Rawlett of the Army Research Laboratory for helpful discussions. This material is based upon work supported in part by the US Army Research Laboratory and the US Army Research Office under Grant W911 NF-04-1-0265. Our work was also supported in part by the Army High Performance Computing Research Centre under the auspices of the Department of the Army, Army Research Laboratory (ARL) under Cooperative Agreement DAAD19-01-2-0014. The content does not necessarily reflect the position or policy of the government, and no official endorsement should be inferred. B.S. thanks the Graduate School of the University of Minnesota for financial support through the Doctoral Dissertation Fellowship program.