Scott  Woodley
Scott Woodley
M3S Lecturer

Area of Research / Academic Interests

Reader of Computational Chemistry and Physics - within the Chemistry Department of UCL, I am currently a member of the Physical Chemistry and Chemical Physics Group (

For my recent Research Papers and Book Chapters, see 

There is a strong method, algorithm and software development aspects embedded within my research interests, which include:

1) Nanoclusters - predicting their atomic and electronic structure and properties

2) Global optimisation - developing algorithms for finding low energy atomic positions for nanoparticles, 1D rods and tudes, surfaces and interfaces, and crystals

3) Materials Chemistry - developing new interatomic potentials that can reproduce observed structures

Main author of KLMC - new inhouse code currently under development (global optimisation, solid solutions (incl. rdf outputs), exploration of ergodic regions, refinement of Shell Model (polarisation) ...) - see

Main author of WASP@N  - a database for nanoclusters - see

Manager of HPC Materials Chemistry Consortium - see

ResearchID page -

CCP5 Executive Committee Member (2007-2010) - see

BACG Committee Member (2010 - ) - see

GULP - developed new functionality: potentials for modelling open shell transition metal ions and genetic algorithms for predicting framework materials with a predesigned microporous architecture, as well as nanoclusters. See publications or visit

Interatomic Potential Database - see Photograph

I can be found within the Kathleen Lonsdale Building on the 3rd Floor, where the Kathleen Lonsdale Materials Chemists have their offices. If you do not have a security pass that gains you access to our offices, then please see security at the front entrance to the building who are always happy to help (my internal phone number is 30315). I am also the Fire Warden, First Aider and Webmaster for the KLMC group.  

Keywords / Tags
Structure Prediction, Global Optimisation, Nanoclusters, Solid State Modelling, High Performance Computing, Materials Chemistry, Code Development


MgAl2O4Nanoclusters are an active field of research and computer modelling and prediction has become the standard tool in furthering our understanding of nanoclusters.

In the present work, basin hopping and genetic algorithm global optimisation schemes were coupled with Shell and Density Functional Theory models to explore the interatomic potential and ab initio energy landscape of ternary oxides and ionic nanoclusters. The investigation produced a set of low-energy (meta)stable structures of interest which were subsequently refined using the FHI-aims ab initio package.

Global search of (meta)stable stoichiometric (MgAl2O4)n nanoclusters from n=1 to 8 was performed using the Shell model on the GULP package and previously unknown global minimum structures were reported for n=1, 2 and 5.

The study of GaAs nanocluster energy landscape was done completely on the ab initio level starting from unbiased configurations. The viability of DFT-based structure prediction was demonstrated and the lowest energy structures found for n=1 to 5 are shown. The problem with ab initio-based GA searches is the tremendous computational cost involved but, with the ever increasing computational power, ab initio-based global optimisation methods should find growing acceptance within the nanocluster community.

To view project, click here

The main aim of this work is develop interatomic potentials to model the non-spherical sp lone pairs on lead titanate and the potentials will be used to look at not only the bulk material, but its surface and nano-clusters properties. Potentially look to extend this to other interesting perovskites.

To view project, click here
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