Chelator-Assisted Precipitation-Based Separation of the Rare Earth Elements Neodymium and Dysprosium from Aqueous Solutions.

The rare earth elements (REEs) are critical resources for many clean energy technologies, but are difficult to obtain in their elementally pure forms because of their nearly identical chemical properties. Here, an analogue of macropa, G-macropa, was synthesized and employed for an aqueous precipitation-based separation of Nd3+ and Dy3+. G-macropa maintains the same thermodynamic preference for the large REEs as macropa, but shows smaller thermodynamic stability constants. Molecular dynamics studies demonstrate that the binding affinity differences of these chelators for Nd3+ and Dy3+ is a consequence of the presence or absence of an inner-sphere water molecule, which alters the donor strength of the macrocyclic ethers. Leveraging the small REE affinity of G-macropa, we demonstrate that within aqueous solutions of Nd3+, Dy3+, and G-macropa, the addition of HCO3- selectively precipitates Dy2(CO3)3, leaving the Nd3+-G-macropa complex in solution. With this method, remarkably high separation factors of 841 and 741 are achieved for 50:50 and 75:25 mixtures. Further studies involving Nd3+:Dy3+ ratios of 95:5 in authentic magnet waste also afford an efficient separation as well. Lastly, G-macropa is recovered via crystallization with HCl and used for subsequent extractions, demonstrating its good recyclability.

Mutation Space of Spatially Conserved Amino Acid Sites in Proteins.

The mutation space of spatially conserved (MSSC) amino acid residues is a protein structural quantity developed and described in this work. The MSSC quantifies how many mutations and which different mutations, i.e., the mutation space, occur in each amino acid site in a protein. The MSSC calculates the mutation space of amino acids in a target protein from the spatially conserved residues in a group of multiple protein structures. Spatially conserved amino acid residues are identified based on their relative positions in the protein structure. The MSSC examines each residue in a target protein, compares it to the residues present in the same relative position in other protein structures, and uses physicochemical criteria of mutations found in each conserved spatial site to quantify the mutation space of each amino acid in the target protein. The MSSC is analogous to scoring each site in a multiple sequence alignment but in three-dimensional space considering the spatial location of residues instead of solely the order in which they appear in a protein sequence. MSSC analysis was performed on example cases, and it reproduces the well-known observation that, regardless of secondary structure, solvent-exposed residues are more likely to be mutated than internal ones. The MSSC code is available on GitHub: "https://github.com/Cantu-Research-Group/Mutation_Space".