Co(salen)-catalyzed aerobic oxidation of lignin models: investigating the role of ligands through data science

Abstract

The aerobic oxidation of lignin model compounds represents a promising strategy for lignin valorization, yet its success relies on designing catalysts with both high activity and stability under mild conditions. In this work, we demonstrated that rational modulation of steric and electronic features in Co(salen)-type complexes enables precise control over their reactivity and deactivation pathways. By integrating data science tools with experimental and computational analyses, we identified key molecular descriptors that govern catalytic behavior. For Bozell-type ligands, steric hindrance close to the metal center emerged as the dominant factor, acting as a protective barrier to prevent deactivation. In contrast, in the newly developed salen ligands based on a cyclohexyldiamine backbone and mapped via chemical space exploration of salicylaldehydes, the electronic properties played a central role in enhancing activity. These findings enabled the selection of a catalyst which displayed high reactivity and selectivity across various lignin model substrates and organosolv lignin, retaining excellent performance under greener conditions. Altogether, this work illustrates how a synergistic combination of computational analysis, and data-driven ligand design strategies can accelerate the development of sustainable oxidation catalysts.