One of the greatest challenges facing the future of clean nuclear energy is scientists’ ability to recover heavy metals from nuclear waste, such as lanthanides and actinides. A new computational tool could help chemists design ligands to selectively bind valuable metals in organometallic complexes.
Nuclear waste contains a smorgasbord of elements from across the periodic table, including transition metals, lanthanides, and actinides. Ideally, scientists would like to reduce the amount of waste generated from nuclear reactors by separating out elements that could be repurposed elsewhere. To tackle these tricky chemical separation techniques, chemists often start with 3D structural models to design ligands that can selectively bind the desired metal to form an organometallic complex that can later be isolated.
Though researchers working with d-block organometallics have an arsenal of structural prediction tools at their disposal, there are no resources available to do the same for the full range of lanthanide and actinide complexes. That’s partly because these f-block elements can form higher coordinate complexes with ligands compared to d-block transition metals, according to Ping Yang and Michael G. Taylor, computational chemists at Los Alamos National Laboratory.
To address this data gap, Yang, Taylor, and their colleagues created a software application called Architector to predict 3D structures for complex f-block organometallics. When tasked with generating a structure from a given metal and ligands, Architector first considers features such as metal symmetry, ligand type, and binding site locations to map out different orientations the ligands might take when binding the metal center. The program then sorts through these potential configurations to propose chemically sensible conformers of the desired complex (Nat. Commun. 2023, DOI: 10.1038/s41467-023-38169-2). By presenting researchers with multiple plausible conformers, Architector could help chemists capture information about how these complexes might exist in both crystalline form and in dynamic environments, such as solution and gas phase conformers that are commonly missed in experimental data, Taylor says.
The researchers tested Architector’s chemical savvy by directing the application to predict 3D structures for 6,154 known organometallic compounds from the Cambridge Structural Database (CSD). This test set comprised a diverse collection of complexes with coordination numbers ranging from 4 to 11, including 1,645 f-block compounds, which could be checked against experimental X-ray diffraction measurements from CSD. The team found that the Architector successfully generated 3D structures that matched CSD reference data for 99.1% of this test set.
Taylor says this result demonstrates that among the pool of conformers Architector predicted, there exists something that has actually been observed experimentally. It also shows that Architector can handle structural predictions for organometallic complexes across the periodic table. That’s good for scientists faced with selectively separating one metal from nuclear waste materials that might contain more than half the elements in the periodic table. “That is what this package can enable,” Ping says.
Aurora E. Clark, a computational chemist at the University of Utah and Pacific Northwest National Laboratory, who was not involved in the study, says this is the first software program for performing robust structural predictions for f-block organometallic complexes. Architector’s ability to tackle high-coordinate complexes in high throughput across the periodic table could give chemists the tools they need to “think outside the box on what ligand architectures could be,” for chemical separations and catalysis, she says. “They were very thoughtful and very creative about the combination of algorithms that they employed,” Clark says. “This is the way software should be designed for this purpose.”