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Modelling the dynamics of patchy nanoparticles in polymer melts

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  • Full or part time
    Dr Patti
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Polymer nanocomposites are hybrid materials incorporating organic and/or inorganic nanoparticles (NPs) with at least one dimension in the sub-micron range. The macroscopic properties of the polymer, such as refractive index, strength, conductivity and hardness, are significantly altered in the proximity of NPs and strongly depend on their surface area, shape anisotropy, orientation, interactions with the polymer chain, and degree of dispersion in the matrix .

A scientific and technological challenge in this context implies the addition in the polymer matrix of chemically modified (functionalised) NPs, able to provide selective interaction sites to improve their homogeneous spatial distribution, and thereby efficiently tailor the macroscopic properties of the material. By molecular simulation techniques, the aim of this project is to explore the dynamics of patchy NPs in polymer melts, how they influence the dynamics of polymer chains and determine the mechanical properties of the polymer nanocomposite.

Funding Notes

Candidates should have a degree in chemical engineering, chemistry, physics or related disciplines. Familiarity on molecular simulation techniques (Molecular Dynamics and/or Monte Carlo) and experience with programming is highly desirable.

This research project is one of a number of projects in the School. It is in competition for funding with other projects.

If you wish to apply for this project, please choose 'PhD Chemical Engineering and Analytical Science' from the list of available programmes.

How good is research at University of Manchester in Aeronautical, Mechanical, Chemical and Manufacturing Engineering?
Chemical Engineering

FTE Category A staff submitted: 33.90

Research output data provided by the Research Excellence Framework (REF)

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