Modeling separation of lanthanides via heterogeneous ligand binding.

Area of Science:

• Materials Science
• Computational Chemistry
• Chemical Engineering

Background:

• Lanthanide elements possess unique properties crucial for various applications.
• Lanthanides often coexist in ores, posing significant separation challenges due to their chemical similarity.
• Accurate prediction of lanthanide binding energies is essential for developing selective separation materials.

Purpose of the Study:

• To develop computational methods for predicting lanthanide selectivity.
• To calculate differential binding energies (ΔΔE) and free energies (ΔΔG) for lanthanide ions (Ln³⁺) with different ligands and environments.
• To guide the design of materials for efficient lanthanide separation.

Main Methods:

• Applied ab initio molecular dynamics (AIMD) and density functional theory (DFT) simulations.
• Calculated differential binding energies (ΔΔE) and free energies (ΔΔG) to avoid computationally expensive absolute values.
• Utilized perturbative AIMD for water-inundated systems and static DFT for coordination shells.

Main Results:

• Developed a method to calculate differential binding energies (ΔΔE) and free energies (ΔΔG) for lanthanide ion (Ln³⁺) selectivity.
• Identified that negatively charged ligands show higher selectivity for heavier lanthanides compared to neutral water molecules.
• Amine groups were found to be ineffective ligands for lanthanide binding.

Conclusions:

• Computational simulations offer a viable approach to predict and enhance lanthanide selectivity.
• The findings provide insights for designing novel materials for lanthanide separation and recovery.
• Cooperative binding strategies using multiple ligands can further improve lanthanide selectivity.