Professor Scott M. Woodley


 Scott Woodley is a Professor of Computational Chemistry and Physics. His group is multidisciplinary and currently consists of 2 postdocs, 1 PhD student and 2 MRes students. Research within his group includes the development and implementation of software for modelling the atomic and electronic structure of materials, along with their properties. He is also the manager of UK’s HEC Materials Chemistry Consortium, which allocates a significant proportion of UK’s national computer resource, ARCHER, and SLA support for development and porting of key software. He was worked at UCL since 2007. Before this, he was a postdoctoral research associate at The Royal Institution of Great Britain, working with Professors Richard Catlow, Julian Gale and Peter Battle.
Summary of research group
 The prediction of structure at the atomic level is one of the most fundamental challenges in condensed matter science. In my research, novel state of the art approaches have been developed and applied to dense and microporous inorganic solids and nanoparticles. There is a strong emphasis on developments in methodology, paying particular attention to approaches for surveying energy landscapes and the design of advanced models that define the energy hypersurfaces. The former is typically based on combining global and local optimisation techniques in a bid to reduce the number of candidate structures required to assess during the search for the lowest energy configurations. The latter aims at reducing the computational cost of evaluating each candidate structure whilst including key interactions required in the model. Implementation manifests itself in the form of new software, which leads to application work. Key physical and chemical properties become accessible once the atomic structure is known using both atomistic and electronic structure techniques. A particular interest arises from the structure-property relationships at nanoscale. The phase or atomic structure is dependent on the size of the particle – small nanoparticles do not always resemble cuts from their bulk phase – and thus potentially size provides a tuning parameter for a desired property.

Currently, members of my group and my collaborators are developing a database for published atomic structures of nanoparticles. The database is accessible to the general public via a webpage, and registered members can also upload their own data. As well as being searchable, and providing tools to visualise the atomic structures, the database has a dedicated cluster of CPUs for making links between different data entries of essential the same structure (the predicted atomic structure of a nanoparticle will depend on the model employed - definition of energy - and tolerances used in relaxing this structure) or structural type (e.g. connectivity the same, only bond lengths rescaled). 

In our spare time I am also developing the Knowledge Led Master Code (KLMC) to enable new science via the exploitation of National High Performance Platforms (HPC) , or High End Computing (HEC), e.g. ARCHER, as well as local computer resources. This branch of my research is aimed at resolving the problems occurring in modelling complex materials, their structure and properties, which require massive samplings of configurational spaces and/or hierarchical simulations. KLMC automates many tasks traditionally performed by the user of a range of third party codes; enable a multistage approach where the KLMC code learns on the fly and refines input files that are submitted for new calculations – hence the name knowledge led; and is able to exploit massively parallel computer platforms for a more general set of applications that may require statistical sampling. Previous work includes the development of the global optimisation routines and the angular overlap interatomic potential within the General Utilities Lattice Package (GULP).

For more details of my work, including details on KLMC software and the WASP@N database visit http://www.ucl.ac.uk/klmc.
Research highlights

Our aim is to develop a novel nanocluster database available to the scientific community and general public (including schools) for search, discovery and dissemination. WASP@N (Web Assisted Structure Prediction at the Nanoscale) is the name of this EPSRC funded five-year project (grant number EP/I03014X), in which we intend to link the web-interfaced database and new software (Bee) that has access to compute nodes dedicated to this project. The database, or Hive, is already available via the current version of the WASP@N interface (this website) for both users who would like to make a search as well as users who would like to upload their data (energy and atomic coordinates of nanoclusters that have been published in the form of coordinates or as a picture and therefore have an associated a DOI) for use by the community. A "lite" version of the WASP@N interface is freely available without the need to register and allows: a search through the entire database for a particular structural motif – in the form of an xyz file you need to supply; and provides access to a very small set of example nanoclusters (to aid those who are not familiar with what we mean when referring to nanoclusters). Note that clicking on any nanocluster thumbnail will activate a useful graphical interface where: the view of the nanocluster can be rotated; properties of the nanocluster are displayed; as well as a hyperlink to the original source of the data. Upon registering, a more comprehensive search form is made available. The Bee software – the working drone behind the Hive – is designed (or at least is still under development) to compute physical properties of the uploaded nanoclusters (e.g. symmetry, moments of inertia) as well as finding links between different nanoclusters based on connectivity ideas. Physical properties and any links found will be fed back into the Hive so that they can be exploited by the user via the WASP@N interface. Like most software, newer versions of the WASP@N interface are planned so that the effects of support and environment about the nanoclusters can be included.

For more details, and a hyperlink to the WASP interface of our database, please go-to http://www.ucl.ac.uk/klmc/Hive.

Scott Woodley - WASP…
Research Facilities
  • BACG (2010-current)
  • Elected Committee Member, CCP5 (2007-2010)
Research interests
  • Materials Physics and Chemistry
  • Methodology Development and Implementation (via New Software)
  • Global Optimisation Techniques
  • Nanoparticles
  • High Performance Computing and Web-Database Applications
  • M3S Lecturer (Industrial Doctorate Centre in Molecular Modelling and Materials Science)
  • CHEMGM04: Course organiser and lecturer for postgraduate course on “Simulation Methods in Materials Chemistry”, which consists of 30 hours of lectures and 45 hours of workshops.
  • Teaching/marking postgraduate modules CHEMGM01-03.
  • Physical Chemistry Lecturer (Department of Chemistry)
  • CHEM1001-3: Course organiser and lecturer for 1st Year Undergraduates – “Quantitative Chemistry”, which consists of 40 hours of lectures and 40 hours of problem classes.
  • CHEMM302: Lecturer for Final Year Undergraduates, “Variation and Perturbation Theory” part of “Topics in Quantum Mechanics” that consists of 12 hours of lectures.
  • Supervise a student project as part of undergraduate module CHEMM901