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Yusuf Hamied Department of Chemistry

 

Professor of Chemical Physics

The self-assembly of complex mesoscopic structures, the folding of proteins, and the complicated phenomenology of glasses are all manifestations of the underlying potential energy surface (PES). In each of these fields related ideas have emerged to explain and predict chemical and physical properties in terms of the PES. In studies of clusters and glasses the PES itself is often investigated directly, whereas for proteins and other biomolecules it is also common to define free energy surfaces, as the figure below illustrates for lysozyme.

Applications of energy landscape theory in my group range from studies of tunnelling splitting patterns in small molecules to computer simulation of protein folding and misfolding, including aggregation of misfolded proteins. Other active research topics include global optimisation and investigation of how the thermodynamic and dynamic properties of glasses are related to the underlying PES.

Two recent advances are now providing new insight into larger systems. Discrete path sampling enables dynamical properties to be obtained efficiently, and is being used to calculate folding rates for proteins. Unexpected connections between dynamics and thermodynamics have also been revealed by the application of catastrophe theory to energy landscapes, and new results are now being obtained to characterize phase transitions.

Publications

Exploiting sparsity in free energy basin-hopping
KH Sutherland-Cash, RG Mantell, DJ Wales
– Chemical Physics Letters
(2017)
685,
288
Machine learning techniques for improving prediction of unplanned intensive care readmission
– Intensive Care Medicine Experimental
(2017)
5,
44
Machine learning techniques for improving prediction of unplanned intensive care readmission
A Ercole, R Desautels, R Das, J Calvert, M Trivedi, C Summers, D Wales
(2017)
Prediction of early unplanned intensive care unit readmission in a UK tertiary care hospital: A cross-sectional machine learning approach
T Desautels, R Das, J Calvert, M Trivedi, C Summers, DJ Wales, A Ercole
– BMJ Open
(2017)
7,
e017199
Optimal Alignment of Structures for Finite and Periodic Systems
M Griffiths, SP Niblett, DJ Wales
– Journal of Chemical Theory and Computation
(2017)
13,
4914
Energy landscapes and dynamics of glycine on Cu(110)
M Sacchi, DJ Wales, SJ Jenkins
– Physical Chemistry Chemical Physics
(2017)
19,
16600
Exploring biomolecular energy landscapes
JA Joseph, K Röder, D Chakraborty, RG Mantell, DJ Wales
– Chemical communications (Cambridge, England)
(2017)
53,
6974
Machine learning landscapes and predictions for patient outcomes.
R Das, DJ Wales
– Royal Society open science
(2017)
4,
170175
Decoupled Associative and Dissociative Processes in Strong yet Highly Dynamic Host-Guest Complexes.
EA Appel, F Biedermann, D Hoogland, J Del Barrio, MD Driscoll, S Hay, DJ Wales, OA Scherman
– Journal of the American Chemical Society
(2017)
139,
12985
Energy landscapes for machine learning.
AJ Ballard, R Das, S Martiniani, D Mehta, L Sagun, JD Stevenson, DJ Wales
– Physical chemistry chemical physics : PCCP
(2017)
19,
12585
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Research Group

Research Interest Groups

Telephone number

01223 336354

Email address

dw34@cam.ac.uk