Computational materials discovery

Graeme Day

Professor of Chemical Modelling

Chemistry, University of Southampton

Google Scholar Twitter: @graeme_day


Web of Science profile

Our group develops computational approaches to improve our understanding of molecular materials, and to accelerate the discovery of functional materials. 

A central method to our work is crystal structure prediction, computational methods to predict how molecules pack from first principles. 

The is a wide range of work going on in the group. See below for more (some of the sections are still in development).

Recent News

16/05/23 - Our paper reporting the realisation of a predicted crystal structure of a hydrogen bonded organic framework is selected as a VIP (Very Important Paper) by Angewandte Chemie. See here

30/6/22 - Welcome to Lucia Gigli, who starts today as a postdoc on the ERC ADAM project.

30/5/22 - Welcome to James Brixey, who has joined as a postdoc on the EPSRC Programme Grant - Digital navigation of chemical space for function

Recent lectures available on YouTube: "Accelerating structure prediction models for materials discovery", as part of the Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery seminar series, and "An introduction to molecular crystal structure prediction", at the MACSMIN conference.

Our recent Nature Communications paper "Digital navigation of energy-structure-function maps for hydrogen-bonded porous molecular crystals" was selected among the Editors' Highlights: