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  PhD Studentship – Realistic simulations of supported metal nanoparticle catalysts


   Chemistry

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  Prof Chris-Kriton Skylaris  Applications accepted all year round

About the Project

Department of Chemistry, University of Southampton
and Pacific Northwest National Labs (PNNL), USA

Application Deadline: Position open until it is filled

Metal nanoparticles are fascinating materials where effects such as quantum confinement of electrons lead to unique physical properties that are entirely different from the bulk material and find applications in numerous areas such as optics, biodiagnostics and magnetic materials. However, by far the area in which metallic nanoparticles have found most application is in heterogeneous catalysis which is at the core of many modern clean energy technologies such as fuel cells, car catalysts and production of chemicals and fuels from biomass. Most relevant for catalytic applications are metal nanoparticles in the size regime between 1-10 nm where the transition from “nanoparticle” to “bulk metal” occurs. To accurately explore the chemistry of such nanoparticles we need to describe their electronic structure with first principles quantum mechanical calculations with methods such as Density Functional Theory (DFT). In practice, the metal nanoparticles are not isolated in space but are positioned on a surface (the “support”) of a suitable material such as carbon or alumina. Up to now, with only a few notable exceptions, attempts to simulate these systems either ignored the presence of the support or the support was treated at the classical mechanics level where its electronic effects are not taken into account. However, recent studies from PNNL have shown that there is significant interaction (electronic polarisation and charge transfer) between the support and the nanoparticle, which controls and determines its catalytic behaviour. Realistic simulations of these systems taking into account these important electronic effects are particularly demanding in terms of size and time scales. As a result we feel that, we need to use linear or reduced-scaling approaches that take into account the electronic structure of the support at the same time as the nanoparticle, and this is the main goal of this PhD project. This represents a great challenge but also an opportunity to make an impact in the computational catalyst design field. The simulations in this project will provide an understanding at the atomic level of how different support materials affect the performance of metal nanoparticle catalysts and will be validated against experimental data. Also, model catalytic cycles will be investigated in order to determine the electronic and structural influence of the support on the actual catalytic activity.

This PhD studentship is in collaboration with Pacific Northwest National Laboratory (PNNL), USA who will provide periods of placement at their research laboratories. The research will be jointly supervised by Professor Chris-Kriton Skylaris and PNNL scientists, Drs. V.-A. Glezakou and R. Rousseau. The project will be based at the University of Southampton in the group of Professor Chris-Kriton Skylaris.


Funding Notes

Funding will cover fees and a stipend at current research council rates (201617) of £ 14,296 per annum.

Due to funding restrictions this position is only open to UK/EU applicants

References

Applications for a PhD in Chemistry should be submitted online at https://studentrecords.soton.ac.uk/BNNRPROD/bzsksrch.P_Search

Please ensure you select the academic session 2017-2018 in the academic year field when making your application and click on the Research radio button. Enter Chemistry in the search text

Please place Professor Chris-Kriton Skylaris in the field for proposed supervisor/project

General enquiries should be made to Professor Chris-Kriton Skylaris (c.skylaris@soton.ac.uk). Any queries on the application process should be made to pgafnes@soton.ac.uk

Applications will be considered in the order that they are received, and the position will be considered filled when a suitable candidate has been identified

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