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Energy landscapes: from molecules and nanodevices to machine learning

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Location: PLT

Prof David Wales, University of CambridgeLink opens in a new window, joins us as a guest speaker. This is a departmental lecture for all students and staff. Please come along. Tea, coffee and refreshments will be provided from 12:45.


The potential energy landscape provides a conceptual and computational framework for investigating structure, dynamics and thermodynamics in atomic and molecular science. This talk will summarise new approaches for global optimisation, quantum dynamics, the thermodynamic properties of systems exhibiting broken ergodicity, and rare event dynamics. Applications will be presented that range from prediction and analysis of high-resolution spectra, to coarse grained models and design principles for self-assembly of mesoscopic structures, with recent results for machine learning landscapes.

Selected Publications:
Ann. Rev. Phys. Chem., 69, 401-425, (2017). Exploring Energy Landscapes
Chem. Commun, 53, 6974-6988 (2017). Exploring biomolecular energy landscapes
Perspective: Energy Landscapes for Machine Learning, PCCP, 19, 12585-12603, 2017.
Perspective: Insight Into Reaction Coordinates and Dynamics From the Potential Energy Landscape, JCP, 142, 130901, 2015.
Energy Landscapes: Some New Horizons, Curr. Op. Struct. Biol., 20, 3-10, 2010.
Energy Landscapes, Cambridge University Press, Cambridge, 2003

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