Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install a5c-ai-babysitter-library-specializations-domains-science-nanotechnology-skills-dlgit clone https://github.com/a5c-ai/babysitter.gitcp babysitter/SKILL.MD ~/.claude/skills/a5c-ai-babysitter-library-specializations-domains-science-nanotechnology-skills-dl/SKILL.md---
name: dls-particle-sizer
description: Dynamic Light Scattering skill for hydrodynamic size distribution and polydispersity analysis
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: nanotechnology
domain: science
category: microscopy-characterization
priority: high
phase: 6
tools-libraries:
- Malvern Zetasizer software
- ALV correlator
- CONTIN algorithm
---
# DLS Particle Sizer
## Purpose
The DLS Particle Sizer skill provides dynamic light scattering analysis for nanoparticle hydrodynamic size determination, enabling rapid, non-destructive measurement of size distributions and stability assessment.
## Capabilities
- Hydrodynamic diameter measurement
- Polydispersity index (PDI) calculation
- Size distribution analysis (intensity, volume, number)
- Temperature-dependent measurements
- Multi-angle DLS analysis
- Particle concentration estimation
## Usage Guidelines
### DLS Measurement
1. **Sample Preparation**
- Dilute to appropriate concentration
- Filter to remove dust
- Equilibrate temperature
2. **Data Analysis**
- Use cumulants for monomodal samples
- Apply CONTIN for multimodal
- Report intensity-weighted Z-average
3. **Quality Metrics**
- PDI < 0.1: Monodisperse
- PDI 0.1-0.3: Narrow distribution
- PDI > 0.3: Broad distribution
## Process Integration
- Statistical Particle Size Distribution Analysis
- Nanoparticle Synthesis Protocol Development
- Nanoparticle Drug Delivery System Development
## Input Schema
```json
{
"sample_id": "string",
"solvent": "string",
"temperature": "number (C)",
"refractive_index": "number",
"viscosity": "number (cP)"
}
```
## Output Schema
```json
{
"z_average": "number (nm)",
"pdi": "number",
"distribution": {
"intensity": {"peaks": [{"size": "number", "percent": "number"}]},
"volume": {"peaks": [{"size": "number", "percent": "number"}]},
"number": {"peaks": [{"size": "number", "percent": "number"}]}
},
"quality_metrics": {
"intercept": "number",
"baseline": "number"
}
}
```