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Multiscale simulations of organic photovoltaics from first principles quantum mechanics


Project Description

Applications are invited for a prestigious industrial CASE PhD studentship, sponsored by Merck, in the Skylaris research group to work on applying large-scale first principles quantum mechanical simulations to Organic Photovoltaics (OPVs).

A great deal of research effort has been devoted to studying OPV physics, but the connection between molecular structure of materials and device performance is still far from clear. Computer modelling of OPVs has largely been limited to different regimes: on the one hand phenomenological or coarse-grained simulations which lose the molecular picture from sight; on the other hand, very detailed and accurate quantum mechanical calculations on model small molecules in vacuum which do not capture the scales where the relevant electronic processes occur.

This PhD project will use first principles quantum mechanical calculations to provide a detailed atomic-level understanding of OPV materials on a far larger scale than possible before by using the ONETEP program for linear-scaling first principles quantum mechanical calculations. The studies will investigate the reaction mechanisms of molecules that form the polymers used in OPVs and the ways in which they are formed/packed together with input from experimental data. We will utilise several of the capabilities of ONETEP, such as structure optimizations, transition state searches, and descriptors such as IP, EA and Eg for the various models. We will also use the novel capabilities for calculations of excited states with the linear-scaling time-dependent DFT (LS-TDDFT) method of ONETEP. As state-of-the-art and emerging simulation technologies will be used for this work it is expected that the project will also involve some method development within the ONETEP code. Having the capability for accurate simulation of the processes behind OPV operation on a scale that is relevant to the real materials is a fundamental advantage of the tools we will use for this work. However, a relevant question which we will have to address is how to construct models of this scale that correspond to real OPV structures and for this we will need to perform force-field based molecular dynamics simulations of these materials, together with input from experimental characterisation information that will be provided by our collaborators in Merck.

The project will be co-supervised by Professor Chris-Kriton Skylaris (University of Southampton) and Dr Michal Krompiec (Merck). It will be based in the group of Professor Chris-Kriton Skylaris in Southampton with frequent interaction and visits to collaborators in Merck.

Funding Notes

This is a fully funded PhD studentship for 3 years. Applications are encouraged from top-level graduates in Chemistry, Physics or related subject. Experience with first principles quantum mechanical calculations and/or classical molecular dynamics simulations is desirable but not essential.

If you wish to discuss any details of the project informally, please contact Professor Chris-Kriton Skylaris, Email:

Due to funding restrictions this position is only open to UK students and EU students who meet the RCUK eligibility criteria

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 2018-2019 in the academic year field and click on the Research radio button. Enter Chemistry in the search text field.

Please place Skylaris/OPV-Merck in the field for proposed supervisor/project

General enquiries should be made to Professor Chris-Kriton Skylaris at [email protected] Any queries on the application process should be made to [email protected]

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.

How good is research at University of Southampton in Chemistry?

FTE Category A staff submitted: 44.80

Research output data provided by the Research Excellence Framework (REF)

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