Computational modeling of the Nb -CO chemisorption process

Area of Science:

• Computational Chemistry
• Materials Science
• Surface Science

Background:

• Niobium (Nb) clusters exhibit unique electronic properties relevant to catalysis.
• Investigating atmospheric pollutant adsorption on metal clusters is crucial for environmental applications.

Purpose of the Study:

• To investigate the adsorption of carbon monoxide (CO) on niobium clusters (Nb$$).
• To elucidate the reactive nature and stability of Nb$$ and Nb$$-CO systems.
• To explore potential technological applications of Nb$$ clusters in catalysis.

Main Methods:

• Employed Coupled-Cluster (CC) and Density Functional Theory (DFT) with HSE06 functional.
• Utilized def2-QZVP and Def2-TZVP/C auxiliary basis sets for calculations.
• Performed geometry optimization, electronic structure analysis, and IR vibrational spectra calculations.

Main Results:

• Both Nb$$ and Nb$$-CO clusters were found to be stable.
• Evidence of chemisorption of CO onto the Nb$$ cluster was observed.
• Analysis of binding energies, charge distribution, and molecular orbitals provided insights into the interaction.

Conclusions:

• The Nb$$ cluster demonstrates a strong interaction with CO, suggesting chemisorption.
• The findings support the potential of Nb$$ clusters for use in automotive catalytic converters.
• Further theoretical and experimental studies are recommended to validate these findings.