The thinnest sensors: 2D materials in liquid solution
This is a fully-funded 4-year PhD position based in the HetSys Centre for Doctoral Training at the University of Warwick.
Project outline
Two-dimensional materials, such as graphene, could be used in molecular sensors - if we can control and tune their properties.
You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions, including in liquids. Combining quantum mechanics and atomic simulation with AI-driven sampling techniques, you will determine terahertz and Raman spectrograms to directly compare to measurements obtained in the THz labs at Warwick and by our collaborators at the Institute of Saint-Louis (ISL).
By suggesting design modifications to the molecular structures, your work will improve the next generation of molecular sensors.
Supervisors
Primary: Dr Peter Brommer (Engineering)
Prof. Nicholas Hine (Physics)
Dr. Hungyen Lin (Engineering)
Project Partner: French-German Research Institute of Saint-Louis
The aim of the project is to quantitatively understand doping and environmental effects on 2D materials in liquid solutions. Simulations of vibrational properties and hence predicted terahertz (THz) and Raman spectroscopy will be directly linked to measurements of the electrical response of this system. The specific objectives are:
- Develop a machine learning interatomic potential (MLIPs) for use in vibrational spectroscopy of 2D materials in the presence of liquids, building on recent work in the team [1].
- Link computational vibrational spectroscopy (THz and Raman) to experimental measurements, using AI-powered sampling strategies to account for variations in the material.
- Explore effects of variation of defects and doping of the 2D material to suggest design changes to the experimental collaborators.
[1] Siddiqui, A., Hine, N.D.M. npj Comput Mater 10, 169 (2024)
You will deliver:
- a publicly released, rigorously validated MLIP for 2D materials in liquids, enabling the community to perform accurate atomistic simulations;
- open-source simulation workflows to create THz and Raman spectrograms;
- predictive understanding of the impact of defects, doping and liquid immersion on the sensor response of 2D materials;
- a set design changes to defects and doping to be explored by our experimental collaborators;
- methodological advances in computational spectroscopy beyond the specific system.
Technical skills: Machine Learning and AI (active learning, sampling techniques, uncertainty quantification), atomistic simulation methods (Density Functional Theory/molecular dynamics), high-performance computing and research software development (version control, testing, documentation).
Domain expertise: Computational spectroscopy, 2D materials.
Link to experiment: While you will not be doing experiments yourself, the close collaboration with an experimental supervisor and with external partners at ISL will allow you to develop a keen understanding of the capabilities and limitations of experimental spectroscopy.
Professional and transferable skills: Python/C/Fortran programming, scientific communication, responsible research practice, international collaboration.
These skills position you for careers in AI research, computational materials science, national laboratories, tech industry or academic research. The HetSys training provides a foundation for these skills through dedicated courses and cohort activities.
We require at least a II(i) honours degree at BSc or an integrated masters degree (e.g. MPhys, MChem, MSci, MEng etc.) in a physical sciences, mathematics or engineering discipline. We do not accept applications from existing PhD holders.
If you are an overseas candidate please check here that you hold the equivalent grades before applying.
For postgraduate study in HetSys, the term “overseas” or “international” student refers to anyone who does not qualify for UK home fee status. This includes applicants from the European Union (EU), European Economic Area (EEA), and Switzerland, unless they hold settled or pre-settled status under the UK’s EU Settlement Scheme.
If you are a European applicant without UK residency or immigration status that qualifies you for home fees, you will be classified as an overseas student.