Multiscale modelling and simulation of graphene and graphene-oxide polymer composites

The UCL Centre for Doctoral Training in Molecular Modelling and Materials Science is offering a fully funded studentship to a highly motivated candidate to start in September 2018.

The project will involve a collaboration with Hexcel (http://www.hexcel.com) whose laboratories are in close proximity to UCL. Hexcel will be able to perform a range of performance tests on the same materials as the student will be modelling, thereby providing experimental validation of the theoretical and simulation work. The overarching goal for this work is to assess the accuracy, precision and reliability of such computer-based predictions of the properties of these nanomaterials.

The student will develop and refine the multiscale modelling methodologies required to investigate polymer nanocomposites with particular focus on epoxy – resins. These composite materials are expected to exhibit properties of importance to aerospace industries owing to their anticipated properties (lightweight, strong, durable, as well as being environmentally friendly and sustainable). While the student will need to perform some amount of electronic structure calculations in order to extract certain key parameters (pertaining to charge distributions and dispersion interactions), he or she will employ a combination of modelling methods, primarily focussed at the level of classical molecular dynamics (both all atom and coarse-grainded) and its connections to higher levels of modelling in order to make predictions of large scale materials properties. The central theme for the project is to make high fidelity, chemically specific predictions from the nanoscale description of both the mesoscale structure of these composites, and from that to predict emergent macroscopic behaviour and properties. These predictions will be tested against experimental measurements made by Hexcel specifically for the purpose of validating the student’s modelling results.

Interested candidates should contact [Email Address Removed] with a degree transcript and a motivation letter expressing interest in this project. Informal inquiries are encouraged. The applicants should have, or be expecting to achieve, a first or upper second class Honours degree or equivalent in physics, chemistry or related subject ideally must be able to demonstrate significant computational experience including use of high level programming languages (such as Fortran, C/C++, and Python or other scripting methods).