<br/>Nuclear energy represents a critical tool available to meet the increasing energy demand, while at the same time reducing green house gas emission. To reduce the need for long-term nuclear waste storage, it is important to develop efficient strategies for selective separation. Density Functional Theory-based approaches are highly successful at characterizing chemical properties, such as thermodynamics, bonding interactions, and chemical reactivity, and are good complements to modern experimental spectroscopic techniques. We will present recent progress in quantum chemical computations applied to heavy element chemistry and demonstrate how the synergy between theory and experiment has greatly accelerated progress in this field. We will show the predictive capability of DFT for coordination modes and affinity of ligands composed of multiple competitive binding sites to actinide centers. Such ligands can help address environmental and health concerns associated with actinides. The theoretical results are validated by spectroscopic characterizations. A better molecular-level understanding of the coordination, energetics, and reaction mechanisms will pave the way to computer-aided optimization of chelating ligands with improved extraction efficiency and selectivity for separation sciences.<br/>

Chemical predictive modeling in actinide chemistry

251st National Meeting (2016)

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