AFM-SPM Analyzer
SkillDev toolsAtomic Force Microscopy and Scanning Probe Microscopy skill for nanoscale topography, mechanical, and electrical property mapping
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the AFM-SPM Analyzer skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/afm-spm-analyzer/SKILL.md and read by ahel’s review.
Purpose
The AFM-SPM Analyzer skill provides comprehensive atomic force and scanning probe microscopy data analysis for nanoscale surface characterization, including topography, mechanical properties, and electrical measurements.
Capabilities
- Topography imaging and analysis
- Surface roughness calculation (Ra, RMS)
- Force-distance curve analysis
- Nanoindentation and mechanical mapping
- Kelvin probe force microscopy (KPFM)
- Conductive AFM measurements
Usage Guidelines
AFM Analysis Workflow
-
Topography Analysis
- Apply plane leveling corrections
- Remove artifacts and noise
- Calculate roughness parameters
-
Mechanical Mapping
- Calibrate cantilever spring constant
- Apply contact mechanics models
- Generate modulus maps
-
Electrical Measurements
- Calibrate work function reference
- Map surface potential
- Measure local conductivity
Process Integration
- Multi-Modal Nanomaterial Characterization Pipeline
- In-Situ Characterization Experiment Design
- Thin Film Deposition Process Optimization
Input Schema
{
"data_file": "string",
"analysis_type": "topography|force_curves|mechanical|electrical",
"cantilever_specs": {
"spring_constant": "number (N/m)",
"tip_radius": "number (nm)"
}
}
Output Schema
{
"topography": {
"Ra": "number (nm)",
"RMS": "number (nm)",
"Rmax": "number (nm)",
"image_path": "string"
},
"mechanical": {
"modulus": "number (GPa)",
"adhesion": "number (nN)",
"deformation": "number (nm)"
},
"electrical": {
"surface_potential": "number (mV)",
"work_function": "number (eV)"
}
}
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
afm-spm-analyzer- Source
- github.com/a5c-ai/babysitter