Resolving Spin State Discrepancies of Small Cationic Iron Clusters by Far-Infrared Vibrational Spectroscopy
Kevin Anthony Kaw1, Ozan Lacinbala1, Deepak Pradeep2
1KU Leuven, Quantum Solid-State Physics, Department of Physics and Astronomy, Celestijnenlaan 200d - box 2414, BE 3001 Leuven, Belgium.
Determining the structure and spin states of iron clusters is crucial for understanding their properties. This study uses infrared spectroscopy and DFT calculations to accurately assign geometries and spin states for iron clusters, aiding future research.
Area of Science:
- Physical Chemistry
- Atomic and Molecular Physics
- Materials Science
Background:
- The properties of atomic clusters are strongly linked to their geometry and electronic structure.
- Transition-metal clusters present challenges due to multiple low-lying spin and geometric isomers, complicating theoretical predictions.
Purpose of the Study:
- To conclusively assign geometries and spin states for cationic iron clusters (3-12 atoms).
- To reduce uncertainties in spin magnetic moments derived from experimental techniques.
- To establish a reliable method for benchmarking theoretical calculations of transition-metal clusters.
Main Methods:
- Infrared multiple photon dissociation (IRMPD) spectroscopy using Argon as a messenger atom.
- Measurement of vibrational spectra of cationic iron clusters in the 110-400 cm⁻¹ range.
- Comparison of experimental spectra with density functional theory (DFT) calculations.
Main Results:
- Vibrational spectra provided direct structural information for iron clusters.
- Spectra accurately determined spin multiplicities, complementing X-ray magnetic circular dichroism (XMCD) experiments.
- The combined approach successfully assigned geometries and spin states for Fe₃-₁₂⁺ clusters.
Conclusions:
- Infrared multiple photon dissociation spectroscopy combined with DFT is a powerful tool for characterizing transition-metal clusters.
- This methodology offers a general route for accurate determination of cluster geometries and spin states.
- The findings provide benchmark data for theoretical models and reduce experimental uncertainties.
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