Location

2.87 Chemistry West
School of Chemistry
University of Leeds
Leeds
West Yorkshire
LS2 9JT

Address

Call: +44(0)113 343 6468

Email: T.W.Chamberlain@leeds.ac.uk

Thomas Chamberlain

Professor of Digital and Materials Chemistry

University of Leeds

Professor Thomas Chamberlain comes from Matlock, in Derbyshire, and completed an MSci in Chemistry at the University of Nottingham in 2005.  He was then awarded a University Interdisciplinary award to study a PhD with Professors Andrei Khlobystov and Neil Champness in Chemistry and Peter Beton in the School of Physics working on the synthesis of novel functional fullerene molecules and the subsequent formation of fullerene/carbon nanotube peapod structures. He received his PhD in 2009 and then joined the Nottingham Nanocarbon group as a post-doctoral research associate studying the use of supramolecular forces, such as van der Waals and H-bonding, to organise molecules in 1D and 2D arrays utilising carbon nanotubes as quasi 1D templates. During this position he established the application of carbon nanotubes as catalytic nanoreactors for the formation of novel molecular and nanostructured products and developed a wide variety of techniques to study the interactions of carbon and metal species at both atomic and bulk length scales.

Dr Chamberlain moved to the University of Leeds in 2015, where he is currently Professor of Digital and Materials Chemistry with an established independent research group within the Institute of Process Research and Development applying his understanding of nanomaterials to both fundamental and applied research challenges. His interests are focussed on the development of new and efficient approaches to making known and novel nanomaterials and improving chemical processes, principally multi-phase systems. To achieve this he utilises automated continuous flow and digital chemistry, combined with routine and novel, in- and off-line characterisation techniques.  This enables the investigation of structure and formation mechanisms of materials, and evaluation of their functional electrical and catalytic properties using algorithm based self-optimisation and kinetic profiling.