📅 Day 1: Principles of SECM and Microelectrode Behavior
Core Objective: Master the theoretical foundations of ultra-microelectrodes, SECM hardware configuration, and fundamental mass-transport dynamics.
- Introduction to Scanning Electrochemical Microscopy and its applications
- SECM hardware setup, bipotentiostat operation, and probe geometries
- Principles and behavior of ultra-microelectrodes (UMEs)
- Steady-state diffusion at UMEs compared with planar electrodes
- Mass-transport dynamics around microelectrode probes
- Understanding and quantifying the RG tip ratio
- Determining diffusion-limited currents, IL
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Hands-on Lab: Simulate steady-state microelectrode diffusion profiles and examine how probe geometry influences mass transport using Google Colab.
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Tools Covered: Python, NumPy, Matplotlib, Google Colab
📅 Day 2: Operational Modes and Quantitative Kinetics Fitting
Core Objective: Quantify heterogeneous electron-transfer kinetics by analyzing feedback mechanisms, operational modes, and experimental approach curves.
- Introduction to major SECM operational modes
- Positive feedback over conductive and reactive surfaces
- Negative feedback over insulating and inactive surfaces
- Substrate-Generator/Tip-Collector (SG-TC) operating mode
- Mapping localized catalytic activity for OER, HER, and ORR reactions
- Approach-curve analysis for extracting kinetic parameters
- Determining heterogeneous electron-transfer rate constants, k0
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Hands-on Lab: Perform nonlinear least-squares fitting on experimental SECM approach curves to extract heterogeneous electron-transfer kinetic constants using Google Colab.
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Tools Covered: SciPy, SymPy, Pandas, Google Colab
📅 Day 3: High-Resolution Spatial Mapping and Advanced Data Analytics
Core Objective: Process, correct, and transform raw SECM spatial-grid scans into publication-ready 2D and 3D electrochemical activity maps.
- Distance-control mechanisms in high-resolution SECM measurements
- Shear-force feedback, contact modes, and probe-positioning strategies
- Understanding spatial-resolution limits and scanning parameters
- Building structured data-processing pipelines for SECM grid scans
- Automated plane-subtraction algorithms for surface-tilt correction
- Spatial noise reduction, filtering, and interpolation strategies
- Converting raw spatial coordinates into interpretable kinetic maps
- Generating publication-ready 2D heatmaps and interactive 3D surfaces
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Hands-on Lab: Build an automated pipeline to process raw 2D and 3D spatial-grid scans, remove surface tilt, reduce noise, and generate interactive electrochemical activity heatmaps using Google Colab.
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Tools Covered: Plotly, Scikit-image, Python, Google Colab
