Data-driven analysis of excited states in metal-organic frameworks

About the Project

Interview date: TBC

Start date: 22 September 2025

Location: London (1.5 years), Singapore (2 years)

Subject areas: excited states, molecular organic frameworks (MOFs), high-throughput computing, machine learning, materials discovery

The studentship

This position is fully funded by the UCL-A*STAR (Agency for Science, Technology and Research, Singapore) Collaborative Programme via the Centre for Doctoral Training in Molecular Modelling and Materials Science (M3S CDT) at UCL. The student will be registered for a PhD at UCL where he/she will spend year one followed by second and third years of the PhD at the A*STAR Institute of HPC and National Supercomputing Centre in Singapore, then return to UCL for the final six months to write up the thesis. If successful, the PhD will be awarded from UCL. The studentship will cover tuition fees at the home rate, and an annual stipend of no less than £21237 increasingly annually with inflation (tax free) pro rata in years 1 and 4. During years 2 and 3, the student will receive a stipend of S$3200 per month directly from A*STAR. In addition, A*STAR will provide the student a one-off relocation allowance.

The Project

Metal-organic frameworks (MOFs) are crystalline materials with metal nodes and organic linkers forming porous structures with high surface areas. Their tuneable properties make MOFs ideal for applications in gas storage, catalysis, drug delivery, and optoelectronics. A critical challenge in advancing MOF applications lies in understanding excited-state processes, which influence their performance. However, describing excited states in MOFs is difficult due to large unit cells and the limitations of conventional computational methods like DFT. Advanced techniques, such as TDDFT and GW, are rarely applied due to their complexity and computational expense. The Crespo-Otero group has developed embedding techniques to model excited states in molecular crystals, offering potential for MOFs. However, these methods require significant manual input, limiting their scalability for high-throughput studies. This project aims to develop automated workflows for excited-state calculations in MOFs using fromage software. The student will develop automatic workflows for cluster model generation, input preparation, and calculations for large-scale MOF databases using fromage, will contribute a database for the excited states of MOFs and will develop tools to identify MOFs with desirable excited-state properties for applications, integrating machine learning for accelerated discovery.

The Candidate

The applicants should have, or be expecting to achieve, a first or upper second-class integrated Masters degree (MSci, MChem, MEng etc.) or a 2:1 minimum BSc plus a stand-alone Masters degree with at least a Merit in Chemistry, Physics, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject, good experimental practice and the ability to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative interdisciplinary research environment is highly desirable but not necessary as training will be provided.

Interested candidates should initially contact the supervisors (r.crespo-otero@ucl.ac.uk and michael@ihpc.a-star.edu.sg) with a CV, a degree transcript and a motivation letter expressing interest in the project. Informal inquiries are encouraged.

Please note that a suitable applicant will first be required to complete MS Form entitled Application for Research: degree Chemistry programme. In addition, it is essential that suitable applicants complete an electronic application form at https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/chemistry-mphil-phd (Select Research degree: Chemistry programme) prior to the application deadline and advise their referees to submit their references as soon as they possibly can. All shortlisted applicants will be invited for an interview no more than 4 weeks after the application deadline. Any admissions queries should be directed to Dr. Zhimei Du (z.du@ucl.ac.uk).

---