Computational design of hypergolic metal-organic frameworks through crystal structure prediction and machine learning

The aim of the project is the computational design of hypergolic metal-organic frameworks (MOFs), as the next generation solid rocket fuel materials that are rapidly ignitable upon contact with an oxidizer. This is achieved by using organic linkers that contain unsaturated double- and triple bond substituents, so-called trigger groups. Yet, there is ample evidence that hypergolic performance of MOFs strongly depends on the choice of metal nodes and overall crystal packing. The method of crystal structure prediction (CSP) allows us to explore the intricate relationships between node and linker composition, crystal structure and resulting MOF properties.

 We have recently reported the first computational design of hypergolic MOFs using CSP, demonstrating the wide opportunities presented by this approach. Thanks to CSP we can now perform computational screening of MOF structures and reliably select candidate structures with interesting properties for experimental synthesis.

 The PhD student will perform computational screening of hypergolic MOFs, where both node and linker types will be varied, in a quest to find materials with enhanced performance, that makes them worthy of experimental synthesis. Major focus will also be placed on enhancing the computational efficiency of the CSP calculations by bringing in methods for faster energy ranking of predicted structures through the use of machine-learnt potentials (MLPs).

 The successful candidate will work in a multidisciplinary team and will be engaged in the development of computationally efficient methods for crystal structure and property prediction of hypergolic MOFs. The work will involve the use of quantum-mechanical methods, particularly periodic density-functional theory (DFT) calculations and machine learning (ML) methods.

 The research activities will proceed in close collaboration with our international colleagues, Prof. Tomislav Friščić and Dr. Andrew Morris (University of Birmingham).

 To enquire about the project please email [email protected]. For further information about the Arhangelskis group please visit the group website www.arhangelskis.org

Necessary qualifications: 

·      MSc degree in chemistry, materials science or related fields

·      Experience with quantum chemical calculations

·      Good command of spoken and written English

Additional skills which would be advantageous:

·      Experience with periodic DFT calculations or other methods of modelling structures of crystalline materials

·      Experience with machine learning methods

Necessary documents:

§ Cover letter highlighting previous research experience and explaining the suitability of the candidate for the advertised position.

§ CV

§ Scan of the Masters’ degree certificate (if already available)

§ Contact details of two referees.

§ Signed consent for the processing of personal data by the University of Warsaw.

Please email all the documents no later than 30/08/2024 to [email protected] with a subject “PhD application CSP”. Applications submitted after the deadline will not be considered. Selected candidates will be informed about the date of the interview by e-mail no later than 10/09/2024. Interviews will be conducted remotely. Following the interview, the selected candidate will be appointed to the Doctoral School of Exact and Natural Sciences of the University of Warsaw.