Web Release Date: February 5,
Polymer Brushes Grafted to "Passivated" Silicon Substrates Using Click Chemistry





and
Université Claude Bernard Lyon 1, Laboratoire des Matériaux Polymères et Biomatériaux (IMP/LMPB, UMR CNRS 5223), 15 Boulevard Latarjet, 69622 Villeurbanne Cedex, France, Laboratoire des polymères, propriétés aux interfaces et composites (L2PIC), Université Bretagne sud, rue Sainte Maudé, 56321 Lorient Cedex, France, and Laboratoire de Physique des Solides (LPS, UMR 8502), Université Paris-Sud, 91405 Orsay, France
Received October 5, 2007
In Final Form: November 22, 2007

Abstract:
We present herein a versatile method for grafting polymer brushes to passivated silicon surfaces based on the
Cu(I)-catalyzed Huisgen 1,3-dipolar cycloaddition (click chemistry) of
-azido polymers and alkynyl-functionalized
silicon substrates. First, the "passivation" of the silicon substrates toward polymer adsorption was performed by the
deposition of an alkyne functionalized self-assembled monolayer (SAM). Then, three tailormade
-azido linear brush
precursors, i.e., PEG-N3, PMMA-N3, and PS-N3 (Mn ~20 000 g/mol), were grafted to alkyne-functionalized SAMs
via click chemistry in tetrahydrofuran. The SAM, PEG, PMMA, and PS layers were characterized by ellipsometry,
scanning probe microscopy, and water contact angle measurements. Results have shown that the grafting process
follows the scaling laws developed for polymer brushes, with a significant dependence over the weight fraction of
polymer in the grafting solution and the grafting time. The chemical nature of the brushes has only a weak influence
on the click chemistry grafting reaction and morphologies observed, yielding polymer brushes with thickness of ca.
6 nm and grafting densities of ca. 0.2 chains/nm2. The examples developed herein have shown that this highly versatile
and tunable approach can be extended to the grafting of a wide range of polymer (pseudo-) brushes to silicon substrates
without changing the tethering strategy.
Download the full text: PDF | HTML