Computational Chemistry

Computational Research Image

UCL's computational chemists work closely with experimentalists to provide atomic or electronic level insights into a wide range of molecules, in isolation, complexes or condensed phases. This involves developing computational chemistry methodology and expanding the scale and efficiency to provide realistic simulations.

Below is a brief overview of some of the discoveries and inventions that have taken place in UCL's Computational Chemistry department in recent months as well as the on going research.

Peter Coveney

Peter Coveney Research Image

Peter Coveney leads the Centre for Computational Science, based in the Department of Chemistry. Our research focusses on many different areas, from molecular and mesoscale fluid dynamics simulations, to computational biomedicine, all based on high performance computational techniques. Our investigations span time and length-scales from the macro-, through the meso- and to the nano- and microscales. We also embrace grid computing as a means to push our research beyond the boundaries of what can be achieved using a single computational resource, often performing single simulations that span multiple grid machines, and invoke tools such as computational steering and high performance visualisation. 

Nik Kaltsoyannis - Quantum chemical calculation of molecular electronic structure

Nik Kaltsoyannis - Quantum chemical calculation of molecular electronic structure

N.Kaltsoyannis Research Summary

We use ab initio and density functional quantum chemistry to study the electronic structure and reactivity of molecules drawn from all areas of the periodic table, with particular emphasis on the f block. We have a number of collaborations with experimental groups, most notably at the Los Alamos National Laboratory in the USA, and the Universities of Oxford, Edinburgh, California and Glamorgan.

Dewi Lewis - Understanding the formation of nanoporous solids

The ultimate success for a materials synthesis programme would be to first determine the structure we would like to make - with particular properties, such as shape-selective catalysis - which we would then predict how to make and then simply synthesise! As part of this effort, we are trying to both develop tools to aid with the synthesis design - through our template design efforts - and to develop an understanding of the self-assembly processes that occur during such syntheses. We employ a range of methods as appropriate - from ab initio modelling of key nucleation steps to forcefield-based Monte Carlo and de novo molecular assembly methods. 

Angelos Michaelides - First principles studies of materials

Angelos Michaelides - First principles studies of materials

Angelos Michaelides research images

Our research involves simulations of catalytic and environmental interfaces, aiming at reaching fundamental new understanding of elementary processes at such interfaces. Water is major focus of our work.

Sally Price - Predicting Organic Crystal Structures

Sally Price - Predicting Organic Crystal Structures

Sally Price Research Image

Sally Price's group is developing the accurate modelling of organic crystal structures, in order to predict which crystal structures of an organic molecule are thermodynamically feasible. These are contrasted with experimental searches for polymorphs in order to understand the factors which lead to polymorphism, in a multi-disciplinary project "Control and Prediction of the Organic Solid State".

Ben Slater - Surface and interface chemistry of materials

Ben Slater Research Image

We use ab-initio and force-field approaches to gain a deeper insight into the true structure of materials, with emphasis on determining surface structure so we can better understand processes at interfaces (such as reaction chemistry, catalysis or separation). Part of our work is in direct collaboration with experimental groups and industry to understand how nanoporous materials (zeolites, metal-organic frameworks, aluminophosphates) grow and dissolve at the nanoscale and the chemical driving forces that dictate which phase crystallises from the mother liquor and with what morphology. Another focus is on water ice and hydrate chemistry where the goal is to develop accurate models of icy materials to help predict their role in atmospheric chemistry and astrochemical reactions.

Antonio Tilocca - Modeling oxide materials and their surface chemistry

Antonio Tilocca - Modeling oxide materials and their surface chemistry


The research activity focuses on structural, dynamical and electronic properties of oxide materials and of their (bio)interfaces, relevant to their application in areas of technological interest, such as biomedicine and photocatalysis. We employ classical and ab-initio (Car-Parrinello / DFT) Molecular Dynamics simulations to investigate systems like bioactive glasses, TiO2 surfaces and "Maya Blue" hybrid materials.

Scott Woodley - Physical Properties from Structure Prediction

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.


Email: Scott Woodley