The University of Bath Institute of Sustainability and Climate Change is inviting applications for the following funded PhD project commencing at the end of September 2025.
The PhD project will combine cutting-edge materials simulations, development of machine learning tools, and vibrational spectroscopy techniques to locate active proton sites in complex functional materials.
The project will focus on locating active sites in zeolite materials, which underpin many industrial chemical processes in catalysis, gas separation, water treatment and environmental protection applications. These processes depend on species such as Brønsted acid (proton) sites inside the structure. While optimal positioning of these sites is crucial to the performance of the materials, the challenge of locating them persists due to the vast number of possible configurations within the crystal structure.
Inelastic neutron scattering (INS) — a uniquely powerful vibrational spectroscopy tool for probing proton environments — allows us to observe subtle changes in the spectrum related to different proton environments. By comparing experimental INS spectra with those generated from quantum mechanical (QM) simulations of different zeolite structures, we aim to pinpoint the locations of different proton sites in zeolites. Machine learning (ML) methods will streamline the prediction of site locations by iteratively learning from both experimental and QM simulation data. The project will develop an ML tool that improves its ability to efficiently predict active site locations as each new experimental result is added.
The successful candidate will develop expertise and skills in computational materials science, ML methods, materials characterisation and INS spectroscopy using large scale facilities at the forefront of sustainability-focused materials research. The PhD project will be based at the ISIS Neutron and Muon Source, a world leading facility in materials research, and will be co-supervised by experts in applying ML methods to materials modelling at UCL, in sustainable software development at STFC Scientific Computing and in simulation-led data analysis and characterisation at the University of Bath.
This interdisciplinary project will gain insights into the position of active sites in a crucially important set of materials to the chemical industry. However, the techniques developed during the project, linking machine learning with materials simulation and vibrational spectroscopy, will have wider applications for national facilities users across the field of sustainable chemical technologies.
Subject to the signing of contracts, this project is co-funded by the Ada Lovelace Centre, a centre of expertise in scientific software, research software engineering and data management with the primary objective of maximising the scientific impact of the STFC national facilities.
Project keywords: computational chemistry, materials science, physical chemistry, solid state physics, artificial intelligence, machine learning, software engineering
Candidate Requirements:
Applicants should hold, or expect to receive, a First Class or good Upper Second-Class UK Honours degree (or the equivalent) in a relevant subject. A master’s level qualification would also be advantageous.
Non-UK applicants must meet the programme’s English language requirement prior to a formal offer being made.
For more information and to apply visit https://www.findaphd.com/phds/project/locating-protons-in-zeolite-materials-combining-molecular-simulation-machine-learning-and-vibrational-spectroscopies/?p177167