The development of sustainable chemical processes requires in-depth knowledge and optimisation at various levels.
Multi-scale computational models will therefore be the cornerstone of new process development through their implementation in process simulators. However, the high complexity of the models and the lack of experimental data prevent the use of this approach. Therefore, we develop:
(1) Multi-scale models with tailored complexity at the relevant scales for a given reaction/application;
(2) Innovative data scrapping and data science-based modelling methodologies that enable the construction of multi-scale models from open data.
