Computational identification of catalytic covalent organic frameworks

Description

Materials like zeolites, which have internal porosity, are widely used as catalysts. By containing chemical reactions within the pores of the material catalysts can be more selective and more active than catalysts in solution. Covalent organic frameworks (COFs) are a class of crystalline, permanently porous, two-dimensional or three-dimensional polymers with tuneable topology and functionality. COFs containing catalytically active sites should exhibit the enhanced selectivity of other catalytic systems in which the substrate is confined within a pore, but confinement effects of catalytic COFs are relatively unexplored to date.

In this project high-throughput computational modelling will be used to identify COFs in which the size, shape and surface chemistry of internal porosity will allow access of the catalytic substrate to the active site and drive selectivity by reducing the number of accessible conformations for the substrate, transition state and product. The project will focus on COFs functionalised with metal-complexes for metallophotoredox catalysis and chiral organocatalysts for asymmetric photoredox organocatalysis.

Modelling at increasing levels of approximation (e.g. analysis of porosity, molecular dynamics with classical or machine learned potentials, density functional theory) will enable candidate COFs to be rapidly screened identifying promising targets for experimental synthesis and testing within the experimental group of Dr John Ward. COF chemistries with predictable topologies will be used, with a variation in the constituent parts of the COF backbone, side chains and catalytic groups giving rise to the candidates to be considered.

The student will be primarily supervised by Dr Matthew Dyer, who has experience in the application of computational modelling of porous materials, including high-throughput screening studies and COFs (see references). Dr Dyer will provide the necessary technical training in computational materials chemistry.

The student recruited to this project will also be part of a wider cohort-training programme focused on the application of digital methods (data and physics based, robotics and automation) to materials chemistry and will be based in the Materials Innovation Factory at Liverpool.

Please apply by completing the online postgraduate research application form here: How to apply for a PhD - University of Liverpool 

Please ensure you include the project title and reference number CCPR117 when applying.

Applicants are advised to apply as soon as possible with applications considered when received and no later than 17/03/2024.

We want all of our staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, if you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.