a5c-ai/dls-particle-sizer
library/specializations/domains/science/nanotechnology/skills/dls-particle-sizer/SKILL.md
Dynamic Light Scattering skill for hydrodynamic size distribution and polydispersity analysis
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter dls-particle-sizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- dls-particle-sizer
- description:
- Dynamic Light Scattering skill for hydrodynamic size distribution and polydispersity analysis
- specialization:
- nanotechnology
- domain:
- science
- category:
- microscopy-characterization
- priority:
- high
- phase:
- 6
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
-
Sample Preparation
- Dilute to appropriate concentration
- Filter to remove dust
- Equilibrate temperature
-
Data Analysis
- Use cumulants for monomodal samples
- Apply CONTIN for multimodal
- Report intensity-weighted Z-average
-
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
{
"sample_id": "string",
"solvent": "string",
"temperature": "number (C)",
"refractive_index": "number",
"viscosity": "number (cP)"
}
Output Schema
{
"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"
}
}
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