Executive Summary : | The proposal aims to understand spin states and predict chemical and photo-chemical reactions in metalloprotein systems, particularly the FeMo-complex. These systems are crucial in complex enzymatic processes due to their multiple spin states that are close in energy, facilitating changes in spin and oxidation states. However, they have been difficult to understand due to their closely spaced spin and energy levels. The project aims to build a framework using machine learning assisted matrix product state formalizations to accurately predict spin states and reactivities of these challenging systems. The project will incorporate features from previous methods developed by the Ghosh and Yanai groups, optimize a generalized matrix product ansatz using machine learning techniques, ascertain spin states for the lowest few states of these polymetallic clusters, and study their reactivities in water activation, oxidation, and water splitting. The project was part of the National Supercomputing Mission project by the Indian PI. |