Organic coatings microstructure: insights from molecular simulations

Watching paint dry can be fascinating. Painting a room can make it aesthetically pleasing, but paints can do much more than just please the eyes. Coatings for corrosion protection are specially formulated paints that protect bridges, machinery, ships, cars and airplanes from catastrophic failure due to corrosion. Understanding the microstructure of the interface between the polymer coating and the substrate it is protecting is key to understand how to better formulate coatings for corrosion protection.

We have recently developed a methodology to model polymer crosslinking near surfaces using molecular dynamics and found how the presence of the surface affects the formation of a3-dimensional network. We are now in a position to interrogate the interface to understand why different precursors and additives have different performances.

This project will focus on developing a workflow to assess the interface of epoxy and phenolic resins near solid surfaces, and use Machine Learning tools to identify features that can be linked to the performance of the coatings.

Eligibility

Applicants should have, or expect to achieve, at least a 1st honours degree or a master’s (or international equivalent) in chemical engineering, chemistry, physics, applied mathematics or materials science.

Some knowledge of programming is essential, and familiarity or experience with molecular simulations is beneficial. 

At The University of Manchester, we offer a range of scholarships, studentships and awards at university, faculty and department level, to support both UK and overseas postgraduate researchers.

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Before you apply

We strongly recommend that you contact the supervisor for this project before you apply. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project, as well as a CV. The email address of Prof. Siperstein is: [Email Address Removed]

How to apply

Apply online through our website: https://uom.link/pgr-apply-fap

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing [Email Address Removed].

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).