Python for SECM: Simulation, Approach-Curve Kinetic Fitting, and Interactive 3D Mapping

To develop practical skills in SECM theory, electrochemical kinetic analysis, spatial-data processing, and scientific visualization using free and open-source computational tools.

• Understand SECM instrumentation, probe geometries, and operating principles.
• Study ultra-microelectrode diffusion and diffusion-limited current.
• Analyse positive, negative, and SG-TC feedback modes.
• Fit approach curves and estimate electron-transfer rate constants.
• Process raw SECM scans using tilt correction, filtering, and interpolation.
• Generate publication-ready 2D and 3D electrochemical activity maps.

📅 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, I_L

🛠️ Hands-on Lab: Simulate steady-state microelectrode diffusion profiles and examine how probe geometry influences mass transport using Google Colab.

🧰 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

🛠️ Hands-on Lab: Perform nonlinear least-squares fitting on experimental SECM approach curves to extract heterogeneous electron-transfer kinetic constants using Google Colab.

🧰 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

🛠️ 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.

🧰 Tools Covered: Plotly, Scikit-image, Python, Google Colab

• PhD scholars and postdoctoral researchers
• Electrochemists and analytical chemists
• Materials and nanotechnology researchers
• Battery, fuel-cell, and electrocatalysis researchers
• Corrosion and coatings professionals
• Sensor and biosensor researchers
• Scientists interested in Python-based electrochemical data analysis

After completing the workshop, participants will be able to:

• Interpret microelectrode and SECM current responses.
• Simulate diffusion and probe-geometry effects.
• Analyse experimental approach curves.
• Extract heterogeneous electron-transfer kinetics.
• Clean and process spatial electrochemical datasets.
• Create interactive heatmaps and surface-activity visualizations.
• Apply SECM analysis to catalysis, corrosion, energy storage, sensors, coatings, and biological interfaces.