Seminar: Chemical Engineering / Materials Science / Computational Science | November 11 | 3.00 p.m.-4.00 p.m. | Room 8.2.38
Dinis O. Abranches, Department of Chemistry and CICECO – Institute of Materials of Aveiro, University of Aveiro
AI as a Laboratory Companion: Accelerating Materials Discovery and Design
Host: Nelson Nunes
This lecture will explore how artificial intelligence (AI), particularly stochastic machine learning models like Gaussian processes (GPs), can accelerate the discovery of novel sustainable materials. Traditional trial-and-error approaches to materials design are slow and resource-intensive, but GPs offer an efficient alternative by learning from limited experimental data while quantifying uncertainty. Several case studies will be presented, demonstrating how GPs guide solvent design, predict physicochemical properties, and reveal meaningful structure–property relationships. Ultimately, this lecture highlights how interpretable, data-efficient AI can act as a true laboratory companion, driving faster, greener innovation in materials science.