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Uncovering Descriptor-Property Relationships of Metal-Organic Frameworks (MOFs) for Catalytic Applications

   Department of Chemical & Biological Engineering

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  Dr S Vernuccio, Dr PZ Moghadam  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

Sheffield United Kingdom Chemical Engineering Industrial Chemistry Chemistry Materials Science

About the Project

Metal-organic frameworks (MOFs) represent a class of hybrid materials built from metal ions with well-defined coordination geometry and organic bridging ligands. The use of these structures for heterogeneous catalysis is extremely attractive because of their well-defined pore surface chemistry that allows much desired structure–activity relation to be established. Particularly, MOFs with excellent thermal/chemical stabilities have been recently explored for various catalytic applications. This project focuses on the computational design and discovery of MOFs as functional materials for advanced catalytic applications.

First, a mechanistic model will be developed to describe the kinetics of model reactions with industrial relevance (e.g. oligomerization, hydrogenation). Second, a library of MOFs with potential application in these catalytic processes will be computationally generated. The mechanistic model will be characterized by identifying a set of ‘kinetic’ and ‘catalyst’ descriptors, the latter accounting for the impact of the specific catalytic properties of the MOF on the kinetics of the process. In the last step the catalytic performance (e.g. conversion, selectivity) will be optimized by tuning the catalyst descriptors of the microkinetic model. The next iteration will start via consideration of the next MOF exhibiting descriptors closer to the optimal performance. The closure of this catalyst design cycle requires translating the optimized set of catalyst descriptors to physical properties that can be determined from material characterization and tuned during the MOF synthesis.

While the identification of catalytic properties of MOFs is the immediate objective of this proposal, our laboratory will utilize this methodology in several other research activities in the field of rational catalyst design. The proposed iterative methodology will provide a library of MOFs with catalytic properties and will facilitate discovery and characterization of a new class of functional materials.

This is a multidisciplinary project involving reaction engineering and first-principle kinetic analyses. The successful candidate will benefit from a top-level research environment, as well as acquire skills at the interface between computational catalysis and microkinetic modelling. We will offer advanced trainings on microkinetic modelling and DFT software (e.g. VASP, CASTEP, Gaussian09).

The applicant will join a vibrant and well-established research group that is interested in the discovery and design of novel catalytic materials that address fundamental challenges in the chemical, environmental and energy landscape.

Computational modelling is currently in high demand in both industry and academia. The area of catalytic applications of MOFs has been growing during the past years to become one of the most prospective technology in the fields of chemical synthesis and reaction engineering.

The successful student will have access to the University of Sheffield High Performance Computing (HPC) clusters (ShARC and Bessemer). Our group has access to VASP, CASTEP and Gaussian09 for quantum calculations, NetGen and RMG for kinetic network generation as well as Cambridge Cristallographic Data Centre’s software structural search program (ConQuest). The necessary infrastructure (office space, computational resources, etc.) will be available for the duration of the proposed fellowship.

Please see this link for information on how to apply: Please include the name of your proposed supervisor and the title of the PhD project within your application.

The ideal candidate will have a 1st class or 2nd upper class degree in chemical engineering, process engineering, chemistry, industrial chemistry, material sciences or related disciplines, experience in cross-disciplinary work, excellent laboratory and computational skills and a hands-on approach to problem solving. The successful candidate will benefit from a top-level research environment, as well as acquire skills at the interface between catalysis and reaction engineering, that are in high demand in both industry and academia. We are looking for highly motivated, committed, and creative individuals, able to work in a team and with excellent communication skills. If English is not your first language then you must have an International English Language Testing System (IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information:

Funding Notes

Please see this link for further information on the scholarships available:
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