Highlight E (HE)

AI-driven design of materials

The mission of FCAI Highlight Program E is to develop AI technology for accelerated materials design and characterization.

Materials are the foundation of technological developments that shape our modern society. Their continuous development enables new applications and products, while the discovery of novel materials addresses such societal challenges as clean energy production, global prosperity, health and wellbeing. To meet these challenges, this highlight will develop AI technology for materials design and characterization.

The main goals of Highlight E include:

• Goal 1: AI knowledge transfer to materials science community 

• Goal 2: New AI enabled materials science applications 

• Goal 3: AI enabled materials design 

Highlight E works in close collaboration with Research Programs R2 Simulator-based inference (Jukka Corander and Samuel Kaski), R1 Agile probabilistic AI (Aki Vehtari), and R3 Next-generation data-efficient deep learning (Juho Kannala).

You can join the Highlight E mailing list if you want to be informed of events and developments regarding the Highlight.

Examples of publications:

• Kunal Ghosh, Annika Stuke, Milica Todorovic, Aki Vehtari, Patrick Rinke. 2019. Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra. Advanced Science, 6 (9).

• Lauri Himanen, Marc Jäger, Eiaki Morooka, Filippo Federici Canova, Yashasvi Ranawat, Patrick Rinke, Adam Foster. 2020. DScribe: Library of descriptors for machine learning in materials science. Computer Physics Communications, 247.

Program poster (pdf)

Coordinating professors: Milica Todorovic (milica.todorovic at utu.fi) and Mikko Mäkelä (mikko.makela at vtt.fi) – starting in spring 2024; Patrick Rinke (patrick.rinke at aalto.fi) – until spring 2024

People

The groups of following professors take part in this Highlight. If you would like to join the Highlight, please contact the coordinating professor.

• Jukka Corander, University of Helsinki, University of Oslo and Sanger Institute

• Flyura Djurabekova, University of Helsinki

• Adam Foster, Aalto University

• Alexander Ilin, Aalto University

• Juho Kannala, Aalto University

• Samuel Kaski, Aalto University

• Anssi Laukkanen, VTT

• Peter Liljeroth, Aalto University

• Kai Nordlund, University of Helsinki

• Patrick Rinke, Aalto University – coordinating professor

• Aki Vehtari, Aalto University