Back to search results

PhD Studentship: Accelerated Prediction of Surface Reactions in Catalysts for H Generation using Machine Learning and Coarse-graining Methods

UCL

Qualification Type: PhD
Location: London
Funding for: UK Students, EU Students
Funding amount: Full Home tuition fees (currently £5,860/year) and maintenance stipend (currently £23,622/year)
Hours: Full Time
Placed On: 14th November 2023
Closes: 14th February 2024

Key information

Lead supervisors: Dr Enrique Galindo-Nava

Application deadline: ongoing

Project start date: 01 October 2024

Project duration: 4 years

Eligibility: UK Students

Studentship funding: 

Full Home tuition fees (currently £5,860/year) and maintenance stipend (currently £23,622/year)

PhD project description

Water electrolysis is regarded as the most viable solution to produce clean hydrogen but electrode materials used in commercial technologies face several challenges risking the mass production of hydrogen. Key issues include poor catalyst stability under harsh operating conditions and high cost of raw materials. Central to address these problems is delivering fundamental understanding of the kinetic processes occurring at the surface of catalysts, which govern material efficiency and stability. Atomistic modelling offers the possibility to address the above-mentioned challenges, but more work is needed to define multi-scale models that can predict the long-term kinetics associated to material degradation and which existing methods cannot tackle. 

This project will develop a (coarse-grained) self-learning kinetic Monte Carlo model -supported by various computational methods- to study main stability mechanisms, including phase transformations, material leaching, etc. and propose material-related enhancements for improved electrolyser performance. Ni-based oxides used in alkaline electrolysers will be considered initially in the study. 

Activities in the project will include:

  • Develop a machine-learning based interatomic potential of Ni-based oxides combining active learning models and ab-initio calculations to establish the Thermodynamics aspects of material stability.
  • Develop a self-learning kinetic Monte Carlo algorithm to predict the Kinetics of material degradation and identify pivotal material properties (e.g. alloy content, structure, defects, etc) dictating their efficiency.
  • Combine the results to study surface activity and mass transport under different material and operating conditions to propose and validate material changes for enhanced stability.

The studentship is sponsored by BP plc, via an iCASE award, and we expect the student to be actively engaged with their research team and other project partners. We offer a unique opportunity to collaborate with a highly interdisciplinary team of academics and industrialists using state-of-the-art computational techniques to help realising the Hydrogen economy. The successful candidate will be encouraged to attend national and international conferences and publish high-impact papers to disseminate the outcomes of the project.

Person specification

Applicants should have (or expected to be awarded) an upper second or first class UK honours degree at the level of MSci or MEng (or overseas equivalents) in a relevant Physics, Engineering or Science subject, including Materials Science, Engineering, Physics, Chemistry, Applied Mathematics or related disciplines.

Eligibility

Due to funding restrictions the studentship is only open to candidates who qualify for Home tuition fees: candidates from the UK or from the EU with settled or pre-settled status in the UK. Please refer to our website for further information about Home tuition fee eligibility.

Applicants whose first language is not English are required to meet UCL's English language entry requirements.

Please refer to this webpage for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should first contact Dr Enrique Galindo-Nava (e.galindo-nava@ucl.ac.uk). Please enclose the following documents:

  • A one-page statement outlining suitability for the project
  • A two pages CV (including contact details of two referees)

After discussing the project with Dr Galindo-Nava, eligible applicants should also submit a formal PhD application via the UCL website.

The supervisory team will arrange interviews for short-listed candidates.

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):

Location(s):

PhD tools
 

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Ok Ok

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Manage your job alerts Manage your job alerts

Account Verification Missing

In order to create multiple job alerts, you must first verify your email address to complete your account creation

Request verification email Request verification email

jobs.ac.uk Account Required

In order to create multiple alerts, you must create a jobs.ac.uk jobseeker account

Create Account Create Account

Alert Creation Failed

Unfortunately, your account is currently blocked. Please login to unblock your account.

Email Address Blocked

We received a delivery failure message when attempting to send you an email and therefore your email address has been blocked. You will not receive job alerts until your email address is unblocked. To do so, please choose from one of the two options below.

Max Alerts Reached

A maximum of 5 Job Alerts can be created against your account. Please remove an existing alert in order to create this new Job Alert

Manage your job alerts Manage your job alerts

Creation Failed

Unfortunately, your alert was not created at this time. Please try again.

Ok Ok

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

 
 
 
More PhDs like this
Join in and follow us

Browser Upgrade Recommended

jobs.ac.uk has been optimised for the latest browsers.

For the best user experience, we recommend viewing jobs.ac.uk on one of the following:

Google Chrome Firefox Microsoft Edge