Hybrid scanning electrochemical cell microscopy-interference reflection microscopy (SECCM-IRM): tracking phase
Dimitrios Valavanis1, Paolo Ciocci2, Gabriel N Meloni1
1Department of Chemistry, University of Warwick, Coventry CV4 7AL, UK. p.r.unwin@warwick.ac.uk.
This study combines scanning electrochemical cell microscopy (SECCM) and interference reflection microscopy (IRM) to visualize interfacial processes. The new technique tracks the SECCM meniscus in real-time, enabling detailed study of surface reactions and material formation.
Area of Science:
- Surface Science and Electrochemistry
- Advanced Microscopy Techniques
- Materials Science and Nanotechnology
Background:
- Studying interfacial processes requires techniques with high spatial and temporal resolution.
- Scanning Electrochemical Cell Microscopy (SECCM) confines reactions to small areas.
- Interference Reflection Microscopy (IRM) offers high surface sensitivity near substrates.
Purpose of the Study:
- To combine SECCM and IRM for real-time, in situ monitoring of interfacial electrochemical processes.
- To track the status of the SECCM meniscus during experiments.
- To investigate surface changes and material precipitation at electrode/electrolyte interfaces.
Main Methods:
- Coupling SECCM with IRM using transparent conductive substrates (e.g., ITO on glass).
- Real-time optical monitoring of the SECCM meniscus and interfacial phenomena.
- Voltammetry, electrowetting quantification, and CaCO3 precipitation studies.
Main Results:
- Demonstrated stability and reproducibility of the SECCM meniscus over a wide potential window (ca. 5% variation).
- Detected and quantified subtle electrowetting at high cathodic potentials.
- Observed surface changes possibly due to indium nanoparticle formation and characterized CaCO3 precipitation patterns.
Conclusions:
- The combined SECCM-IRM technique provides high spatiotemporal resolution for studying interfacial processes.
- This method allows for in situ or in operando visualization and tracking of solid phase formation.
- The high-throughput nature of SECCM-IRM facilitates large dataset generation for exploring experimental parameter landscapes.
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