Babysitter colloidal-stability-analyzer

Colloidal stability assessment skill for evaluating nanoparticle dispersion stability through zeta potential, aggregation kinetics, and shelf-life prediction

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/nanotechnology/skills/colloidal-stability-analyzer" ~/.claude/skills/a5c-ai-babysitter-colloidal-stability-analyzer && rm -rf "$T"

manifest: library/specializations/domains/science/nanotechnology/skills/colloidal-stability-analyzer/SKILL.md

Colloidal Stability Analyzer

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"]
}