Berkeley Lab unveils AI modelling breakthrough to accelerate advanced materials development
From left: Vir Karan, Gerbrand Ceder, and Kristin Persson are part of a research team that developed an AI model that reveals how best to synthesise promising new materials.
Credit: Thor Swift/Berkeley Lab
New machine learning framework predicts solid-state reactions to help researchers move promising materials from discovery to commercialisation faster
Register for FREE to keep reading
Join 12,000+ scientists, engineers, and IT professionals driving innovation through informatics, HPC, and simulation with:
- Insights into HPC, AI, lab informatics & data
- Curated content for life sciences, engineering & academia
- Access to Breakthroughs: real-world computing success
- Free reports & panels, including the Lab Informatics Guide
- White Papers & software updates for smarter research
Sign up now
Already a member? Log in here
Your data is protected under our privacy policy.
