PhD Studentship: Kinetic Pathways to Control Nanocrystal Shapes

About the award

Supervisors

Dr Carlos Lange Bassani,  Department of Engineering, University of Exeter

Prof. Ana Neves, Department of Engineering, University of Exeter

The University of Exeter’s Department of Engineering is inviting applications for two PhD studentship funded by the European Research Council to commence on 21 September 2026 or as soon as possible thereafter. For eligible students, the studentship will cover Home/International tuition fees plus an annual tax-free stipend of at least £21,805 per year for 4 years full-time, or pro rata for part-time study. The student would be based in the Department of Engineering in the Faculty of Environment, Science and Economy at the Streatham Campus in Exeter.

The successful applicant will join the project kineticShapes - Kinetic Pathways to Control Nanocrystal Shapes, funded by the European Research Council by the ERC Starting Grant No 101220354.

This project aims to understand non-equilibrium aspects of nanocrystal growth in determined shapes.  The research will provide quantitative insights into the role of crystal lattice and solution concentration field on morphological features such as twinning, branching, and chirality. Research techniques majorly involve the use and further development of a kinetic Monte Carlo simulation framework, coded in C++. Other supportive research techniques may involve molecular dynamics, density functional theory, and lattice Boltzmann simulations. Results will be validated and applied in collaborations with experimentalists.

Activities

• Using and further developing C++ code for kinetic Monte Carlo simulations of nanocrystal growth
• Developing post-treatment code in Python for data analysis
• Performing simulations in High Performance Computer (HPC)
• Collaborating with experimentalists in applied cases for nanomaterials design
• Preparing scientific material for publications and conferences
• Support will be provided to get onboard of the existing code, algorithm logics, and necessary tools

Candidate profile (hard skills)

• An interest in mathematics and physical sciences is essential
• Experience in simulation and computer programming (C/C++, Python) is desirable
• Background in chemical-physics (particle-based simulation methods, statistical thermodynamics) is desirable
• The candidate must demonstrate the interest and ability to further enhance coding skills and fundamental understanding of chemical-physics during the PhD phase

Candidate profile (soft skills)

• Communication and collaboration skills in multicultural environments
• Pro-activity in searching solutions
• Detail-orientation

Further reading

Kinetically Trapped Nanocrystals with Symmetry-Preserving Shapes | Journal of the American Chemical Society

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