I was attracted by modelling during my undergraduate days at Queen's University Belfast. I liked the idea of getting very clean information at the atomic scale and being able to test things in a very ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Interatomic Potentials and modelling as a tool in materials science – Prof Sir Richard Catlow, Dept. of Chemistry, UCL; School of Chemistry, Cardiff University; UK Catalysis Hub, Research Complex at ...

While the concept of quantum computing has been discussed for more than 40 years, only recently have experiments indicated that a practical quantum computer may be possible. Recent developments in ...

Scientists have used machine learning tools to create the first atomic-level model that accurately predicts the thermal properties of stanene, a 2-D material made up of a one-atom-thick sheet of tin.

Abstract: This presentation discusses computational modeling of complex materials behaviors under multi-physics conditions for Aerospace applications. We develop chemistry, physics, and ...

Researchers are constantly seeking more efficient and economical electronic materials for next-generation energy storage devices to meet the demands of electric vehicles (EVs) and other devices that ...