PhD Studentship: Multiscale physics of deformation and failure in polymer networks

University of Oxford; Oxford; On-site; GBP 20,000 - 24,000; Full time

Benefits offered by this job

Fees covered

Stipend £21,805 p.a.

Job summary

University of Oxford invites applications for a 3.5-year D.Phil. studentship in the Brassart Group, focusing on mesoscale modelling of polymer networks to predict time-dependent deformation and failure.

The project combines physics-based modelling with experimental validation and molecular simulations where appropriate. The successful candidate will develop physically grounded viscoelastic and chain-scission models, analyse network topology, and apply statistical mechanics and stochastic

Qualifications

• First class or strong upper second-class undergraduate degree with honours in Engineering, Physics, Mathematics, Materials, or Chemistry.
• Excellent English written and spoken communication skills.
• Strong analytical and mathematical skills.
• Programming experience (e.g. Matlab, Python, C/C++,...)

Responsibilities

• Develop a mesoscale modelling framework to predict time-dependent deformation and failure of polymer networks.
• Use a coarse-grained discrete-network model to represent network architecture.
• Test predictions against existing experimental data and simulations where appropriate.

Skills

Analytical skills

Computational skills

Programming experience

Education

First class or strong upper second-class undergraduate degree in Engineering, Physics, Mathematics, Materials or Chemistry

Tools

Matlab

Python

C/C++

Job description

3.5-year D.Phil. studentship

Supervisor: Professor Laurence Brassart

Many soft materials, such as elastomers and hydrogels, consist of networks of interconnected polymer chains. Their properties can be tuned through molecular composition, polymer chain length, network architecture, and interactions with solvents, resulting in a broad range of mechanical behaviours and functionalities. This versatility underpins applications ranging from soft structures and adhesives to medicine, energy, and sustainability technologies. A major challenge for the design of these materials is to understand and predict their deformation and failure behaviours and their relationships to the underlying network topology.

The aim of this DPhil is to develop a mesoscale modelling framework to predict the time-dependent deformation and failure of polymer networks based on a description of the underlying chain-level physics. Building on previous works in the Brassart Group, we will use a coarse-grained discrete-network model to explicitly represent the network architecture. A major focus will be the development of physically grounded descriptions of viscoelasticity and time-dependent chain scission, drawing on statistical mechanics and stochastic thermodynamics. The framework will be used to investigate time-dependent deformation and failure, with predictions tested against existing experimental data and, where appropriate, molecular simulations.

This project would particularly suit a student who enjoys physical and mathematical modelling, and who is excited by challenging theoretical problems in soft matter physics and mechanics. Candidates are not expected to have prior experience in this specific area, but intellectual curiosity, a desire to understand problems from first principles, and strong analytical and computational skills are essential. A background in mechanics, physics, applied mathematics, materials science, or chemistry could provide a suitable starting point.

Professor Laurence Brassart – [e-mail]

Eligibility

This studentship is funded through the Department of Engineering Science and is open to Home students.

Award Value

Course fees are covered at the level set for UK students (at least £10,940 p.a.).

The stipend (tax-free maintenance grant) is at least £21,805 p.a. for the first year, and at least this amount for a further two and half years.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

• A first class or strong upper second-class undergraduate degree with honours (or equivalent) in Engineering, Physics, Mathematics, Materials, or Chemistry
• Excellent English written and spoken communication skills
• Strong analytical and mathematical skills
• Programming experience (e.g. Matlab, Python, C/C++,...)

The following background is desirable but not essential:

• Foundations in Continuum Mechanics and/or Thermodynamics and/or Statistical Physics

Start date

October 2027

£21,805 please see advert