Experimental and Computational Study Toward Identifying Active Sites of Supported SnO_x Nanoparticles for...

Area of Science:

• Materials Science
• Electrochemistry
• Catalysis

Background:

• Tin oxide (SnOₓ) is a promising electrocatalyst for carbon dioxide reduction reaction (CO₂RR).
• Current SnOₓ catalysts suffer from low activity and ambiguous active site structures under electrochemical conditions.

Purpose of the Study:

• To enhance CO₂RR performance of SnO₂ nanoparticles by supporting them on common materials.
• To investigate the structure-activity relationship of SnOₓ electrocatalysts using computational methods.
• To identify optimal operating conditions for SnOₓ-based CO₂RR.

Main Methods:

• Synthesis of SnO₂ nanoparticles supported on vulcan carbon and TiO₂.
• Electrochemical CO₂ reduction reaction (CO₂RR) testing at various temperatures.
• Atomistic simulations using machine learning interatomic potentials and density functional theory (DFT).

Main Results:

• Supported SnO₂ nanoparticles showed enhanced CO₂RR activity.
• Optimal operating temperature window for the catalyst was determined to be 12–30 °C.
• Machine learning and DFT simulations established correlations between SnOₓ structure, oxygen presence, and CO₂RR performance, distinguishing between *H and *CO₂⁻ binding.

Conclusions:

• Supporting SnO₂ nanoparticles on vulcan carbon or TiO₂ significantly improves CO₂RR activity.
• Computational modeling provides crucial insights into the atomic-level mechanisms governing SnOₓ electrocatalyst performance.
• This study facilitates the rational design of advanced SnOₓ-based electrocatalysts for efficient CO₂ conversion.