Outreach Event at KCL - AI and ML in Materials Science
KCL organised an outreach event in which a group of EU-based high school students (~11 final-year A-level students from Warsaw, Poland, accompanied by five tutors) visited the NOMAD team based at the KCL Physics Department.
The students attended a tutorial session covering the fundamental concepts of Artificial Intelligence and Machine Learning in Physics and Materials Science with a particular focus on the challenges and benefits of data-driven science and big-data approaches.
NOMAD team members Dr. Henry Lambert and Dr. Adam Fekete contributed to the event with a tutorial/presentation session on the “Fe grain-boundaries (Fe-GB)” industrial case study they lead within NOMAD. In particular, they first introduced the general underlying scientific research field (modern metallurgy, involving much experimental and considerable modelling activity, and general concept of data generation, curation and inference) and then discussed in more depth the NOMAD Repository-hosted database and tools they developed for analysing and visualising the data. Finally, the presentations illustrated how a bespoke suite of NOMAD analytic tools works interactively using the GB database, enabling straightforward post-processing and in particular machine-learning from computational data.
The session generally highlighted the importance of being able to access large curated data sets, and how advanced computational tools have become necessary for fully revealing and exploiting the vast amount of information contained within big-data pools. This is of particular importance for classes of structural materials of strategic interest for industry – such as those involved in the Fe-GB case study.
The event was a great success!