Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Area of Science:

• Computational Chemistry
• Materials Science
• Spectroscopy

Background:

• Ab initio molecular dynamics (AIMD) simulations predict extended X-ray absorption fine structure (EXAFS) signals, but are computationally expensive.
• Solvated lanthanide ions present challenges due to complex, nonrigid geometries and high coordination numbers.

Purpose of the Study:

• To accelerate the characterization of lanthanide ion structures in solution.
• To develop a more efficient method for screening first-shell coordination structures.

Main Methods:

• Employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm.
• Screened first-shell structures for Eu(NO3)3 with a terpyridine ligand and Nd(NO3)3 in acetonitrile.
• Compared theoretical EXAFS spectra from NWPEsSe-identified structures with experimental and AIMD-derived spectra.

Main Results:

• NWPEsSe successfully identified correct solvation structures for both Eu(NO3)3(terpyNO2) and Nd(NO3)3(acetonitrile)3.
• Calculated EXAFS signals closely matched experimental spectra for the Eu-ligand complex and showed good similarity for the Nd salt.
• The algorithm reduced structure identification time from weeks/months to within a week.

Conclusions:

• NWPEsSe provides an efficient and versatile approach for characterizing lanthanide ion structures in solution.
• The method significantly reduces computational time compared to traditional AIMD simulations.
• This global optimization strategy is adaptable for characterizing main-group metal complexes as well.