Lead Chief Investigator

Matthew A Addicoat Computer Science, Engineering and Information Technology, Australian National University

Project Title

Optimising a Genetic Algorithm for Functionalised Carbon Nanomaterials

Brief Description for General Publications

Carbon nanomaterials, such as fullerenes, nanotubes and graphenes have extensive applications in electronics, biological engineering and structural engineering. Functionalising these materials can enhance the range of applications by altering their chemical and electronic properties. Functionalised fullerenes, such as fullerols are large, water soluble molecules that have recently been shown to promote the growth of algae and fungi. However, computational study of these molecules is hampered by the large number of possible functionalisation patterns. In addition, the hydroxyl functional group possesses a rotational degree of freedom when bound to a fullerene and may also participate in hydrogen bonding networks. Our previously optimised Genetic Algorithm (GA) is an ideal solution to this combinatorial explosion problem. This project will determine the low-energy isomers of biologically relevant functionalised fullerenes.