Internship and thesis proposals
Molecular Simulations of Chiral Self-Assembly in Binary CNC-Polymer Mixtures

Domaines
Soft matter

Type of internship
Théorique, numérique
Description
Cellulose is the most abundant polymeric raw material on the planet and is found almost exclusively in the cell-walls of plants. It is environmentally friendly and sustainable to produce, on industrial scales and can be processed into nano-structured materials. This makes it one of the most prominent ‘green’ materials of modern times to be used in bio-based functional materials [1]. One of the aims of the project is to provide molecular level insights into the large-scale LC behaviour of CNCs and to understand the effect of depletion on the transfer of chirality across length-scales. We will also explore the morphology of mesoscale droplets formed by CNCs and non-adsorbing polymers. The presence of the polymers imparts strong depletion attractions between the CNCs which may potentially lead to droplets with reconfigurable shape such as membranes and twisted ribbons. Applicants should have a sound understanding of classical statistical mechanics and thermodynamics and an appetite for theoretical/numerical computations. Some experience with Linux, Python, C/C++ and LAMMPS is desirable but non-essential. Candidates can expect to learn the basics of MD simulations and the fundamental importance of chirality in nature.
Contact
Rik Wensink
+33698501392


Email
Laboratory : Laboratoire de Physique des Solids - UMR 8502
Team : Rik Wensink
Team Website
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