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<https://discovery.ucl.ac.uk/id/eprint/10204809> <http://purl.org/dc/terms/title> "The Multiscale Simulation of Graphene Polymer Nanocomposites"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10204809> <http://purl.org/ontology/bibo/abstract> "Through high-performance computing, we can simulate and accurately predict the properties of materials at a fraction of the time and cost of an experimental study. Moreover, we can select the appropriate resolution and, on the microscopic scale, understand the structure that may not have been practical empirically. This project is a UCL IMPACT PhD studentship co-funded by Hexcel, a company that develops and manufactures composite materials. By combining simulation techniques of different time and length scales, this thesis aims to predict the macroscopic properties of graphene-based nanocomposites commonly used in paints, coatings and adhesives in the aerospace industry.\r\n\r\nThe primary tool used for simulation in this thesis is molecular dynamics. While molecular dynamics simulations can accurately predict numerous material properties, independent simulations can converge to different metastable states due to the inherent randomness associated with the initial positions and velocities, even averaging over long timescales. For the simulations to be accurate and reproducible, the study of verification, validation, and uncertainty quantification is an integral part of this research, as only through averages over ensembles of molecular simulations can robust and actionable theoretical predictions be yielded.\r\n\r\nThis thesis covers four distinct scenarios relating to the modelling of nanocomposite materials. First, we present a study on the mechanical stability of a graphene polymer bilayer used in capacitive micromachined ultrasound transducers through repeated loading and unloading cycles. We then propose a new, faster method to obtain the glass transition temperature more suited to parallel supercomputers. We perform a rigorous statistical analysis comparing this new parallel method to the commonly used step-wise method. We follow this by investigating the effect of water molecules on the elastic moduli of graphene epoxy nano-composites. We conclude by developing a machine learning surrogate for a multiscale scheme that couples the finite element to molecular dynamics."^^<http://www.w3.org/2001/XMLSchema#string> .
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