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Research in the Habershon Group

We are a computational chemistry research group in the Department of Chemistry at the University of Warwick

Our interest lies at the intersection of chemistry, physics and computer science; we're developing new simulation tools which can help us to accurately model chemical dynamics in complex systems containing many-atoms. These simulation approaches are being used to understand chemical reaction dynamics in a wide-range of systems, from hydrogen-bond dynamics in simple anion solvation shells, to reactions taking place on water clusters, to catalytic reactions taking place on surfaces.


Current research

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Research in the Habershon group focuses on development and application of new methods for modelling chemical dynamics in complex many-particle systems. Recent projects include:

Nanostructure growth and heterogeneous catalysis. Current research is aimed at using automated chemistry discovery methods (see below) to investigate the atomic mechanisms of carbon nanostructure formation on nanoparticles. Right: Initial reaction path sampling for carbon atoms interacting with an iron nanoparticle; complex carbon nanostructures emerge from automated reaction path sampling.

 



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Predicting catalytic reaction mechanisms using random walks in chemical space. In two recent papers [J. Chem. Phys., 143, 094106 (2015) and J. Chem. Theory Comput., 12, 1786 (2016)], we've shown how the concept of connectivity graphs can be used to drive the search for reaction paths in molecular systems. Our new approach allows us to automatically sample reaction paths connecting different conformations and chemical isomers. In the initial application of this graph-based sampling approach, we've shown that the main steps in the accepted mechanism of cobalt-catalyzed ethene hydroformylation are captured; current work is focussed on expanding and improving this exciting new approach. 


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Network organization in photosynthetic complexes. In another recent paper, we have used simple quantum dynamics simulations of energy transport, combined with network-based analysis of Frenkel exciton Hamiltonians, to investigate the influence of network organization on photosynthetic efficiency. Our results revealed an interesting aspect of the Fenna-Matthews-Olson phototsynthetic complex: around 50% of the energy transport network can be removed with little impact on energy transport efficiency. The full paper can be found at J. Chem. Phys., 143, 105101 (2015).





News

August 2017: Both Max Saller and Lewis Baker have passed their PhD viva examinations - well done!

1 February 2017: New paper available online, describing implementation of direct excited-state dynamics using potential energy interpolation and diabatization propagation. See here.

21 November 2016: A new publication by the group has appeared in Journal of Chemical Physics titled "Efficient and accurate evaluation of potential energy matrix elements for quantum dynamics using Gaussian process regression", with Jon Alborzpour (Warwick MChem 2012-2016) and David Tew (Bristol).