Webpages tagged with «Machine Learning»

 A molecular dynamics study with machine learning potentials. The influence of the organic residue and the solvent in the Schlenk equilibrium for Grignard reagents in THF.In this paper we study the behaviour of different Grignard reagents in organic solution with a newly developed machine learning interatomic potential.

Presented at the Summer School 2025 on Machine Learning and Artificial Intelligence in Synthetic Chemistry, this lecture introduced how modern computational methods are accelerating discovery in chemical synthesis.

Nova gave a talk entitled “Bi-functional Catalyst Design for CO₂ Hydrogenation Reactions” and participated in a panel discussion on “Boosting Computational Catalysis with Machine Learning".

YoungCAS Principal Investigator Sigbjørn Løland Bore, together with Pablo Piaggi from nanoGUNE, organized a successful symposium on March 27-28, 2025, at the Norwegian Academy of Science and Letters, gathering 40 participants, including 20 invited speakers from abroad.

The Hylleraas Centre made a generous contribution with eight talks on a broad range of research topics at the Annual Meeting of the Quantum and Computational Chemistry Chapter of the Norwegian Chemical Society.

PhD student Sophia Burger from Johannes Gutenberg-University in Germany visited for research collaboration with Michele Cascella and Sigbjørn L. Bore as supervisors.

Doctoral candidate Marinella de'Giovanetti at Hylleraas Centre, the Department of Chemistry, is defending the thesis “The multifaceted nature of lithium derivatives, and its implications for Grignard chemistry - A computational study from first-principles to machine learning”.

New paper published: The study provides a comprehensive view of LiX in organic solvent through the use of machine learning potentials, revealing a dynamical polymorphism that is not easily observable experimentally. 

Hannes Kneiding and David Balcells have published a perspective in Chemical Science on the combination of evolutionary and deep learning methods for the inverse design of molecules 

Doctoral candidate Hannes Kneiding at Hylleraas Centre, the Department of Chemistry, is defending the thesis "Complex Learning – Machine learning approaches for transition metal complexes". 

Alejandra Pita Milleiro is a PhD-student visiting for three months the Hylleraas Centre in Oslo. She comes from The Institute for Chemical Research (IIQ) CSIC - University of Sevilla, Spain. Alejandra will be collaborating with David Balcells during her visit.

Manuela start her PhDs at the Hylleraas Center in Oslo with Michele Cascella as an supervisor.