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Abstract

Solvent extraction is a crucial technology for the large-scale recovery of critical metals. One key challenge is to develop ligands with high ionic selectivity, especially for ions with similar properties. Manipulating ionic solvation emerges as a viable approach to enhance the selectivity. However, such manipulation requires a thorough understanding of the thermodynamics underlying ligand-induced variation in ionic solvation. We investigated the thermodynamics governing the binding of two organophosphorus ligands (Cyanex 272 and D2EHPA) with Co2+ and Ni2+ at the aqueous-organic liquid–liquid interface using a combination of experiments and computations. UV-vis and IR spectroscopy confirmed that extraction induces solvation structure changes of Ni2+ and Co2+. The free-energy landscapes obtained from well-tempered metadynamics illustrated two plausible routes for water–ligand substitution during extraction. In the first route, the ligand occupies the vacancy created by the departing water molecule. In the second route, the ligand associates with the ion to form an oversaturated solvation state that drives water expulsion. The ligand-binding process is a competition between the two routes. The free-energy landscapes further revealed that substitution of the first water molecule in the ionic solvation shell plays a determining role in ligand-induced ionic selectivity. Our results suggest a target for the rational design of Co2+/Ni2+ separation technology: engineering the free energy associated with substitution of the first water molecule.

Document Type

Article

Publication Date

2026

Notes/Citation Information

© the Owner Societies 2026

Digital Object Identifier (DOI)

https://doi.org/10.1039/d6cp00202a

Funding Information

This work was supported by the U.S. Department of Energy (DOE) under Award No. DE-SC0025346. This work used the Delta system at the National Center for Supercomputing Applications through allocation [CHM250076] from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. We thank the University of Kentucky Center for Computational Sciences and Information Technology Services Research Computing for their support and use of the Lipscomb Compute Cluster and associated research computing resources.

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