Projects

Below is an overview of suitable student projects across BSc, Capita Selecta, and MSc tracks.

BSc projects Capita Selecta projects MSc projects How to apply

BSc projects

BSc Microkinetics Catalysis Reaction networks Python

Microkinetic modelling of CO hydrogenation to methanol on a Cu surface

Construct and analyze a microkinetic model for CO hydrogenation on copper, linking surface reaction mechanisms, energetics, and reactor-scale observables.

  • Build a tractable elementary-step reaction network for methanol synthesis.
  • Connect activation barriers and adsorption energetics to observable rates.
  • Explore how temperature and pressure shift dominant pathways and coverages.

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Capita Selecta projects

Capita Selecta Quantum chemistry Orbital localization Geometry Linear algebra

Molecular orbital localization and geodesic paths between resonance structures

Apply Foster-Boys localization to obtain chemically intuitive molecular orbitals and explore the shortest unitary transformation paths between different localized solutions.

  • Compare canonical and localized orbital pictures in chemically meaningful systems.
  • Study alternative resonance-like solutions through unitary transformations.
  • Frame orbital transformations in terms of shortest paths on a mathematical manifold.

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Capita Selecta Group theory Electronic structure Basis sets Symmetry

Symmetry-adapted basis sets in electronic structure calculations

Use group theory to construct symmetry-adapted basis functions and explore how this transforms and simplifies electronic structure calculations.

  • Translate abstract point-group ideas into concrete computational tools.
  • Show how symmetry-adapted bases reveal block structure in quantum-chemical matrices.
  • Discuss how symmetry can reduce computational effort and sharpen interpretation.

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MSc projects

MSc Fischer-Tropsch Surface science Coverage effects Microkinetics

Coverage effects and lateral interactions in Fischer–Tropsch synthesis on Co surfaces

Investigate how lateral adsorbate–adsorbate interactions at elevated surface coverage influence energetics, kinetics, and product formation in Fischer-Tropsch synthesis on cobalt.

  • Move beyond dilute-coverage assumptions toward realistic crowded catalyst surfaces.
  • Compare idealized and interaction-aware kinetic models under industrial conditions.
  • Relate lateral interactions to activity, selectivity, and apparent activation energies.

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MSc Machine learning potentials MACE Nanoparticles Atomistic modelling

Machine-learned modelling of supported cobalt nanoparticles under Fischer-Tropsch conditions

Use a MACE machine-learned force field to explore the structure and phase transformations of cobalt nanoparticles supported on a refractory oxide under oxidative and carburizing environments relevant to renewable Fischer–Tropsch synthesis.

  • Use machine-learned force fields to probe catalyst structures beyond small DFT models.
  • Study how oxidative and carburizing environments reshape supported cobalt particles.
  • Produce interpretable structural descriptors for realistic nanoparticle transformations.

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MSc Fischer-Tropsch Nanoparticles Multi-site models Catalysis

Microkinetic modelling of site synergy in supported nanoparticle Fischer-Tropsch catalysts

Develop a microkinetic model with terrace, step-edge, and interfacial sites to investigate how the nanoparticle perimeter and more distant sites act together during Fischer-Tropsch synthesis.

  • Model terrace, step-edge, and interfacial chemistry within one reaction framework.
  • Test how transport between site types changes observed activity and selectivity.
  • Link nanoparticle size and perimeter effects to catalyst performance.

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How to apply

If one of these topics fits your interests, feel free to get in touch. A concise application is usually enough to start the conversation.

  • Specify whether you are looking for a BSc, Capita Selecta, or MSc project.
  • Mention the specific project title or the topics you would like to explore further.
  • Include your CV and, if relevant, a recent transcript.
  • Briefly note any background in chemistry, modelling, mathematics, or programming.