# Dls Particle Sizer

> Dynamic Light Scattering skill for hydrodynamic size distribution and polydispersity analysis

- Skill: `a5c-ai/dls-particle-sizer` (Agent Skill)
- Install (CLI): `npx skillmds@latest add a5c-ai/dls-particle-sizer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/dls-particle-sizer/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/dls-particle-sizer

---


# 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"
  }
}
```