Colloidal Stability Analyzer
SkillDev toolsColloidal stability assessment skill for evaluating nanoparticle dispersion stability through zeta potential, aggregation kinetics, and shelf-life prediction
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 Colloidal Stability 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/colloidal-stability-analyzer/SKILL.md and read by ahel’s review.
Purpose
The Colloidal Stability Analyzer skill provides comprehensive assessment of nanoparticle dispersion stability, enabling prediction of aggregation behavior, shelf-life estimation, and optimization of stabilization strategies through DLVO theory and experimental validation.
Capabilities
- Zeta potential analysis
- DLVO theory-based stability prediction
- Aggregation kinetics modeling
- pH and ionic strength effects
- Steric stabilization assessment
- Shelf-life prediction algorithms
Usage Guidelines
Stability Assessment
-
Zeta Potential Analysis
- Measure at multiple pH values
- Determine isoelectric point
- Assess stability window (|zeta| > 30 mV)
-
DLVO Theory Application
- Calculate van der Waals attraction
- Estimate electrostatic repulsion
- Determine energy barrier height
-
Shelf-Life Prediction
- Monitor size over time
- Apply accelerated aging protocols
- Predict long-term stability
Process Integration
- Nanoparticle Synthesis Protocol Development
- Nanomaterial Surface Functionalization Pipeline
- Nanoparticle Drug Delivery System Development
Input Schema
{
"nanoparticle_type": "string",
"size": "number (nm)",
"surface_chemistry": "string",
"dispersion_medium": "string",
"pH_range": {"min": "number", "max": "number"},
"ionic_strength": "number (mM)"
}
Output Schema
{
"zeta_potential": "number (mV)",
"stability_classification": "stable|marginally_stable|unstable",
"aggregation_rate": "number (nm/day)",
"predicted_shelf_life": "number (days)",
"optimization_recommendations": ["string"]
}
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
colloidal-stability-analyzer- Source
- github.com/a5c-ai/babysitter