Classes
Publications
- Faraday Discussions A machine learning approach for dynamical modelling of Al distributions in zeolites via 23Na/27Al solid-state NMR2025 | Faculty of Science
- Digital Discovery 27Al NMR chemical shifts in zeolite MFI via machine learning acceleration of structure sampling and shift prediction2025 | Faculty of Science
- Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials2024 | Faculty of Science
- A reactive neural network framework for water-loaded acidic zeolites2024 | Faculty of Science
- The role of defects in high-silica zeolite hydrolysis and framework healing2024 | Faculty of Science
- Catalysis: Science and Technology Germanium distributions in zeolites derived from neural network potentials2024 | Faculty of Science
- Constructing Collective Variables Using Invariant Learned Representations2023 | Faculty of Science, Faculty of Mathematics and Physics
- A themed collection in memory of Petr Nachtigall2023 | Faculty of Science, Central Library of Charles University
- Differentiable Simulations for Enhanced Sampling of Rare Events2023 | Faculty of Science, Faculty of Mathematics and Physics
- The need for operando modelling of 27Al NMR in zeolites: The effect of temperature, topology and water2023 | Faculty of Science
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