Institute of Functional Interfaces

Organic surfaces exposed by self-assembled organothiol monolayers: preparation, characterization, and application

  • chair:

    Kind, M. / Wöll, Ch. (2009)

  • place: Prog. Surf. Sci. (2009)

  • Date: 2009
  • Kind, M. / Wöll, Ch. (2009): „Organic surfaces exposed by self-assembled organothiol monolayers: preparation, characterization, and application“. In: Prog. Surf. Sci. (2009)


Organic surfaces play a major role in materials science. Most surfaces that we touch in our daily lives are made from organic materials, e.g., vegetables, fruit, skin, wood, and textiles made from natural fibers. In the context of biology, organic surfaces play a prominent role too, proteins docking onto cell surfaces are a good example.

To better understand the characteristics of organic surfaces, including physico-chemical properties like wettability or chemical reactivities and physical properties like friction and lubrication, a structurally well-defined model system that can be investigated with numerous analytical techniques is desirable. In the last two decades, one particular system, self-assembled monolayers or SAMs, have demonstrated their suitability for this purpose.

In particular, organothiols consisting of an organic molecule with an attached SH-group are well suited to fabricating structurally well-defined adlayers of monolayer thickness on gold substrates using a simple preparation procedure. These ultrathin monolayers expose an organic surface with properties that can be tailored by varying the type of organothiol employed.

After a short introduction into the preparation of SAMs, this article provides an overview of the possibilities and limitations of organic surfaces exposed by Au-thiolate SAMs. Applications are as diverse as the metallization of organic surfaces, a fundamental problem in materials science, and the fabrication of surfaces that resist the adsorption of proteins. In addition to a number of different case studies, we will also discuss the most powerful analytical techniques needed to characterize these important model systems.


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