A computational approach to magnesium corrosion engineering

Magnesium is the lightest metallic construction material and bears high potential for automotive components, medical implants and energy storage systems. However, the practical use of untreated magnesium alloys is restricted as they are prone to corrosion. An essential prerequisite for the inhibition or control of the degradation process is a deeper understanding of the underlying corrosion mechanisms. For instance, identifying the reaction pathways most relevant for the release of gaseous hydrogen — one of the main products during magnesium corrosion — builds the foundation for adapting the hydrogen evolution rate in general. A possible approach to modulate the hydrogen evolution and magnesium dissolution rate is the introduction of small organic molecules that either stabilize the corroding surface or capture corrosive species. Such molecules constitute benign and useful materials to modify the service environment of magnesium for applications that require tailored degradation properties. This thesis illuminates different aspects of magnesium degradation, ranging from atomistic insights into the corrosion process itself to further developing strategies for effective corrosion control. By combining atomistic simulations and machine learning techniques, a holistic framework is developed to improve understanding and enable more efficient magnesium corrosion engineering in the future.