From Waste to Functional Biomicroreactors: Exploration of Wool-Based Stimuli-Triggered Reversible Pickering Emulsions for Transition Metal Catalysis in Water

This study presents the first application of micronized waste wool, as a biogenic solid emulsifier for generating Pickering-type emulsions under microwave stimulus, in organic solvent-free metal-catalyzed transformations, including Suzuki–Miyaura and copper-free Heck–Cassar cross-couplings, and hydroformylation. Under dielectric MW heating in the presence of a metal catalyst, this wool-water system forms Pickering emulsion-like micelles that effectively compartmentalize the Pd or Rh catalyst at the protein–water interface, allowing these transformations to be highly efficient in terms of yields and regioselectivities. Scalability studies (10 mmol scale) confirmed the robustness of the approach and demonstrated the possibility of recycling the wool emulsifier and aqueous catalytic phase after simple centrifugation. Protein analysis by SDS-PAGE and amino acid analysis revealed that the performance of the biomasses correlated with their high sulfur-rich protein (HSP) content and amino acid distribution. The versatility of the stimuli-triggered reversible Pickering emulsions (STRePEs) here proposed is demonstrated through an extensive substrate scope involving 57 examples across Suzuki–Miyaura (22 cases), copper-free Heck–Cassar–Sonogashira (14 cases), hydroformylation (15 cases), and tandem hydroformylation-hemiacetalyzation (6 cases) reactions, showcasing high tolerance toward diverse functional groups. This study demonstrates the untapped potential of protein-based agricultural waste as a functional material for sustainable catalysis in organic synthesis. This provides a solution for circular chemistry that converts waste streams into valuable synthetic tools, eliminating the need for synthetic surfactants, organic cosolvents, and separation solvents in transition metal-catalyzed processes. The sustainability of the processes was quantified through comparative green metrics (e.g., E -factor) and life cycle assessment (LCA), showing a significant improvement over traditional methods.