Computational modelling of materials and catalysis is now indispensable in an industrial setting, fuelled by powerful algorithms and increasing computational speed. This article explores how multiscale modelling techniques are being used to accelerate product development cycles and innovate the way in which new materials are discovered. We discuss current multiscale approaches starting from the atomic simulation to the continuum methods, illustrating how these are applied to provide insight and understanding to real-world catalysts. We illustrate how understanding reactions at atomic and molecular levels directly affects large-scale industrial processes. A key focus is the essential link between model predictions and experimental validation, often requiring advanced characterization. We also address current methodological limitations and explore solutions offered by emerging techniques such as machine learning (ML). Ultimately, this article highlights the transformative role of multiscale modelling in connecting microscopic phenomena with macroscopic performance, significantly accelerating the design and development of new industrial products. This article is part of the theme issue 'Surfaces, interfaces and heterogeneous catalysis'.
Fonte et al. (Thu,) studied this question.