ChemAI 2024 Poster Session

1 - S. Abou: "Material Property Design Using Machine Learning"

2 - J. Dijkman: "Machine Learning for Classical Density Functional Theory"

3 - S. Acaru: "Artificial Intelligence in the Design of Sustainable Lignin-Polyurethane Films"

4 - R. Breebaart: "Enhanced Artificial Intelligence Molecular Mechanism Discovery of Reaction Paths in Complex Systems"

5 - K.J. van der Weg: "Towards the construction of a large foundation model for protein structures with message-passing Graph Neural Networks"

6 - E.Kempkes: "Predicting ion-responsive mechanical properties of biopolymers: A Bayesian Approach"

7 - G. Vogel: "Inverse Design of Copolymers Including Stoichiometry and Chain Architecture"

8 - T. van Heesch: "Learning The Hill-Climber’s Guide for Traversing Free-Energy Barriers in Molecular Dynamics"

9 - K. Nam: "Machine learning assisted realistic description of catalytic centers on M1 catalyst surfaces"

10 - G. Luchetti Sfondalmondo: "Artificial Intelligence-Driven Approaches for Next Generation Immunotherapies"

11 - G. Benedini: "Active Learning for ML potentials on infrared spectra prediction"

12 - R. Fedorov: "Exploration of Redox Properties in Chemical Space"

13 - A. Kryachkova: "Locked In or Breaking Free? Temperature Dependence of Water Diffusion within Fulleroid Cages"

14 - M. Pietrasik: "The Enabling Technologies for Digitalization in the Chemical Process Industry"

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