Computational Identification of Catalytic Covalent Organic Frameworks

Description

Materials which have internal porosity, such as zeolites, are widely used as catalysts. By containing chemical reactions within the pores of the material these 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 global need for researchers with capabilities in materials chemistry, digital intelligence and automation is intensifying because of the growing challenge posed by Net Zero and the need for high-performance materials across multiple sectors. The disruptive nature of recent advances in artificial intelligence (AI), robotics, and emerging quantum computing offers timely and exciting opportunities for PhD graduates with these skills to make a transformative impact on both R&D and society more broadly.

The University of Liverpool EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2025. These students will develop core expertise in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme they will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.

This training is based on our decade-long development of shared language and student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory (MIF), the largest industry-academia colocation in UK physical science. The training content has been co-developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent related to Physical Science, Engineering or Computational Science. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

Application Process

Applicants are advised to apply as soon as possible no later than 17^th February 2025. The CDT will hold two rounds of applications assessment:

• Assessment Round 1: for all applications received between 11^th December 2024 – 15^th January 2025.
• Assessment Round 2: for all applications received between 16^th January 2025 – 17^th February 2025

Applicants who wish to be considered in Assessment Round 1 must apply by 15^th January 2025. Projects will be closed when suitable candidate has been identified (this could be before the 17th February 2025 deadline).

Please review our guide on How to apply for a PhD | Postgraduate research | University of Liverpool carefully and complete the online postgraduate research application form to apply for this PhD project in Chemistry.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project.

We want all 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.

Please ensure you include the project title and reference number CCPR139 for example when applying.