The A. J. Morris Group

Computational Modelling for Energy Materials


We are a computational materials modelling group in the Materials and Metallurgy Department of the University of Birmingham. We use density-functional theory and other atomistic level modelling techniques to discover new materials for energy applications.
The creation of new materials is both difficult and expensive. It is very difficult to “see” the structure of these materials over the length scales that they work and very expensive to create prototype materials to test. Whilst experimental physics can use x-rays, high energy electrons or neutrons to infer the structure of these materials, this inference is made much more robust when combined with theoretical predictions of the kinds of structures that can be formed. In a computer we use quantum mechanical calculations to simulate the results of these kinds of experiments, helping to understand materials and suggest new materials with the kind of properties desired.

Congratulations to Can Koçer for passing his PhD viva!

09 June 2021

Congratulations to Dr Can Koçer for passing his PhD viva on 9 June, 2021. During his PhD journey, Can published multiple computational research articles, including excellent work on the lithium insertion mechanism of crystallographic shear phases, which all led to a successful completion of his PhD. We wish him all...

Angela discusses how to use computational physics to study Li-ion batteries at CamFest

04 April 2021

As part of the 2021 virtual CamFest, Angela submitted a video explanation for the general public about how she uses computational physics to study Li-ion batteries as part of her PhD.

Full Video

Welcome Dr Hrishit Banerjee

01 April 2021

A warm welcome to Dr Hrishit Banerjee, a post-doctoral Research Associate whose research focuses on understanding the physics involved in the degradation of Li-ion batteries.

Congratulations to Jordan Dorrell for receiving the best poster prize at MCCM 2021!

07 January 2021

Jordan Dorrell was awarded the Midlands Computational Chemistry Meeting 2021 best poster prize. Jordan presented a poster titled “Machine Learning Random Structure Searching for Li-Ni-S Cathode Discovery”.