Computational Tools and Techniques in Designing Ligands for the Selective Separation of Actinide and Lanthanide: A Review

ABSTRACT

The development of density functional theory (DFT) has significantly enhanced the use of computational chemistry as a tool in the design and development of ligands for the separation of actinides (An) and lanthanides (Ln) in the nuclear waste management. In the past, identifying new ligands involved either making incremental structural changes to existing ligands or conducting extensive laboratory testing of numerous compounds. However, these experimental methods are often costly and time-consuming. With the advancements in hardware and software, theoretical and computational chemistry has become a powerful and cost-effective approach in nuclear waste management research. The density functional theory (DFT), in particular, has played a pivotal role by enabling scientists to accurately predict the effectiveness of ligands based on electronic and molecular properties, as well as reactivity indices. This computational approach provides valuable insights into the separation efficiencies of ligands without the need for extensive experimental efforts. This review highlights the role of computational chemistry in the design of ligands for the separation of lanthanides and actinides in spent nuclear fuel processing. It discusses various design strategies and computational analyses used in ligand optimization, highlighting the potential applications of computational tools in guiding ligand design and improving separation processes. The work emphasizes the synergy between computational insights and experimental observations in lanthanide/actinide chemistry, which enhances understanding of complex phenomena and aids in the interpretation of experimental results. It also explores different design approaches that allow for fine-tuning of ligand properties and selectivity toward specific metal ions, ultimately improving separation efficiency. In this review, we will discuss some widely used computational tools in chemistry without delving into complex mathematical formulas. This will be particularly helpful for researchers who come from an experimental background and may not be as familiar with advanced mathematical concepts. The tools covered are bond order analysis, population analysis, quantum theory of atoms in molecules (QTAIM) analysis, Energy Decomposition Analysis (EDA), and thermodynamic analysis. These methods are explored in a more accessible manner for non-theoretical researchers. They provide valuable insights into bonding, binding, stability, non-bonding interactions, coordinating abilities and selectivity of organic ligands in extraction of actinides and lanthanides, thus providing useful information in the designing of ligands to enhance separation strategies. This review serves as an excellent resource for future ligand design, offering valuable insights into computational techniques used to understand the coordination and complexation behaviors of ligands. Also an attempt has been made to understand the role of DFT functionals in the calculations. It provides a foundation for researchers to comprehend and apply computational tools effectively in their investigations.

Graphical abstract

KEYWORDS:

• Solvent extraction
• Lanthanide/Actinide separation
• Nuclear waste management
• Coordination complex
• Density functional theory (DFT)
• Selective separation

Acknowledgments

RVS thanks the Department of Science and Technology - Science and Engineering Research Board (DST-SERB) for the Early Career Research award (Ref. No. ECR/2017/001147) and CE acknowledges the financial support from RVS’s DST-SERB-ECR project. The authors also thank Priya Ranjan Dev for designing the graphical abstract. RVS dedicates this review to his PhD supervisor and mentor, Professor Dr. P. Venuvanalingam, on the occasion of his 70^th birthday.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Science and Engineering Research Board [ECR/2017/001147].