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Multiscale Graphene Topographies Programmed by Sequential Mechanical Deformation.

Po-Yen Chen¹, Jaskiranjeet Sodhi¹, Yang Qiu¹

¹School of Engineering, Institute for Molecular and Nanoscale Innovation, Brown University, Providence, RI, 02912, USA.

Advanced Materials (Deerfield Beach, Fla.)

|March 22, 2016

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Multigenerational graphene oxide architectures exhibit structural memory through mechanical programming. These superhydrophobic materials show promise as advanced electrochemical electrodes.

Area of Science:

Materials Science
Nanotechnology
Surface Chemistry

Background:

Graphene oxide is a versatile material with tunable properties.
Programming material structures with mechanical stimuli is an emerging field.
Developing materials with inherent memory and advanced functionalities is crucial.

Purpose of the Study:

To investigate the programming of multigenerational graphene oxide architectures.
To explore the structural memory and multiscale features of these architectures.
To evaluate their superhydrophobic properties and electrochemical electrode functionality.

Main Methods:

Sequential mechanical deformations were applied to graphene oxide.
Structural evolution and feature decoration were analyzed.

Keywords:

electrochemical activity graphene multiscale surface architectures sequential patterning superhydrophobicity

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Superhydrophobicity was measured.

Electrochemical performance was tested.

Main Results:

Graphene oxide architectures could be programmed by mechanical deformations.
Progressively larger features decorated with smaller patterns indicated structural memory.
The architectures demonstrated superhydrophobicity.
Excellent functionality as electrochemical electrodes was observed.

Conclusions:

Multigenerational graphene oxide architectures possess programmable structural memory.
These materials exhibit desirable superhydrophobic properties.
The developed architectures are suitable for advanced electrochemical electrode applications.