(84f) Alcohol Clustering Mechanisms in Supercritical Carbon Dioxide Using Diffusion NMR and Network Analysis

Co-solvent clustering in complex fluids is fundamental to solution phase processes, specifically related to the use of mixed solvents and chelating agents for the extraction of lanthanides and actinides from nuclear fuel waste. The mixture of methanol in supercritical CO₂ is frequently used to enhance the extraction and recovery using phosphine-based ligands. Methanol (MeOH) clustering in supercritical carbon dioxide is explored with diffusion-based NMR (DOSY-NMR) and molecular dynamics (MD) simulations. Improved self-association models including both cooperative cluster assembly and entropic penalties for the formation of large clusters to predict the clustering will be presented. A network analysis of MD simulations show an enhanced stability of cyclic clusters, specifically tetrameric, across all MeOH concentrations and was consistent with experimental DOSY-NMR molecular cluster distributions calculated with self-association models. Simulations also reveal the emergence of cluster assembly and disassembly reactions that deviate from stepwise, monomer addition or removal. The powerful combination of experiment, simulation, and novel analyses removes the need for contemporary approximations and enables refinement of models that describe co-solvent aggregation with far-reaching impact to the prediction of solution phase properties of complex fluids. Understanding the conditions near the alcohol cluster is critical to controlling the chemistry of extraction and will provide new engineering opportunities to improve nuclear fuel processing.