Model-Informed Training Data Curation for Reactive All-Atom Potentials L. Dumortier Fri, 20/06/2025iGent tower, Technologiepark, ZwijnaardeSupervisors Prof. Dr. ir. Toon Verstraelen, dr. Jelle Vekeman, dr. Theodorus De Bruin and dr. Benoît Creton Read more about Model-Informed Training Data Curation for Reactive All-Atom Potentials
Development and Applications of the Frequency-Dependent Polarizable Force Field ACKS2ω Y.X. Cheng Mon, 13/11/2023Campus Sterre S2 Krijgslaan 281, 9000 Genthttps://biblio.ugent.be/publication/01HFBGCC96FYEQW0FVQBK4W101Supervisors Prof. Dr. ir. Toon Verstraelen Read more about Development and Applications of the Frequency-Dependent Polarizable Force Field ACKS2ω
Accurate description of phase transitions in flexible materials using transferable machine learning potentials S. DeKeyser Master of Science in Engineering Physics2022UGain (building 60, Magnel), Technologiepark, ZwijnaardeSupervisors Prof. Dr. ir. Veronique Van Speybroeck, Prof. Dr. ir. Toon Verstraelen Read more about Accurate description of phase transitions in flexible materials using transferable machine learning potentials
Beyond Tree Tensor Networks in quantum many-body physics J. Van Bever Master of Science in Physics and Astronomy2019Supervisors Prof. Dr. Dimitri Van Neck, Prof. Dr. ir. Toon Verstraelen Read more about Beyond Tree Tensor Networks in quantum many-body physics
Chemical bonds in crystals: a machine learning view Y. Degeyter Master of Science in Engineering Physics2021Supervisors Prof. Dr. Stefaan Cottenier, Prof. Dr. ir. Toon Verstraelen Read more about Chemical bonds in crystals: a machine learning view
Chemical bonds in crystals: a machine learning view F. Keutgens Master of Science in Engineering Physics2020Supervisors Prof. Dr. Stefaan Cottenier, Prof. Dr. ir. Toon Verstraelen Read more about Chemical bonds in crystals: a machine learning view
Boosting the discovery rate of energy materials using deep learning J. De Witte Master of Science in Engineering Physics2020Supervisors Prof. Dr. Stefaan Cottenier, Prof. Dr. ir. Toon Verstraelen Read more about Boosting the discovery rate of energy materials using deep learning
Understanding Noncovalent Interactions in Force Fields through Quantum Mechanics: Application to Gas Adsorption in Metal-Organic Frameworks S. Vandenbrande Wed, 08/05/2019Faculty of Engineering and Architecture, Jozef Plateaustraat, Ghenthttps://biblio.ugent.be/publication/8615972Supervisors Prof. Dr. ir. Veronique Van Speybroeck, Prof. Dr. ir. Toon Verstraelen Read more about Understanding Noncovalent Interactions in Force Fields through Quantum Mechanics: Application to Gas Adsorption in Metal-Organic Frameworks
Variational information-theoretic atoms-in-molecules F. Heidar-Zadeh Fri, 07/07/2017http://hdl.handle.net/1854/LU-8531565Supervisors Prof. Dr. Paul W. Ayers, Prof. Dr. Patrick Bultinck, Prof. Dr. ir. Toon Verstraelen Read more about Variational information-theoretic atoms-in-molecules
The development of hybrid MC/MD schemes to model the adsorption of guest molecules in flexible metal-organic frameworks R. Goeminne Master of Science in Engineering Physics2018Supervisors Prof. Dr. ir. Veronique Van Speybroeck, Prof. Dr. ir. Toon Verstraelen Read more about The development of hybrid MC/MD schemes to model the adsorption of guest molecules in flexible metal-organic frameworks