# Nanostructure Size Distribution Analyzer AI Agent Connect

> Calculates nanoparticle size distribution metrics from DLS and TEM data.

## Overview
- **Category:** science
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_hCWpm0Tq0DIo6SkyK7z4QhB2uol8dwzGjI3vmRox/ai-agent-connect
- **Tags:** nanoparticles, dls, tem, statistics, characterization

## Description

This MCP server provides specialized statistical tools for nanoparticle characterization. It allows AI agents to process Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM) data to determine critical metrics like mean size, polydispersity index (PDI), and distribution width. Use `analyze_dls_data` for hydrodynamic sizing from intensity moments, `analyze_tem_data` for physical diameter counts, and `compare_characterization` to identify the difference between hydrodynamic and physical sizes.

## Tools

### analyze_dls_data
Calculates size distribution metrics from DLS measurement sets

### analyze_tem_data
Calculates size distribution metrics from direct TEM measurements

### compare_characterization
Compares DLS and TEM results to identify differences

### get_distribution_summary
Provides a high-level descriptive summary of a specific distribution

## Prompt Examples

**Prompt:** 
```
Analyze these TEM diameters: [12.5, 13.2, 11.8, 12.9, 12.1]
```

**Response:** 
```
The average physical diameter is 12.5 nm with a Polydispersity Index of 0.04.
```

**Prompt:** 
```
What is the difference between my DLS and TEM results? DLS: {"meanSize": 25.0, "pdi": 0.1} TEM: {"meanSize": 18.0, "pdi": 0.05}
```

**Response:** 
```
The size difference is 7.0 nm, suggesting a surface layer thickness of approximately 7.0 nm.
```

**Prompt:** 
```
Get a summary for these sizes using a log-normal model: [5.0, 5.5, 6.0]
```

**Response:** 
```
For the log-normal distribution, the mode is 5.45, the median is 5.5, and the mean is 5.48.
```

## Frequently Asked Questions

**How do I analyze DLS data?**
Provide the intensity-weighted moments as a JSON string to the `analyze_dls_data` tool.

**Can I compare DLS and TEM results?**
Yes, use the `compare_characterization` tool by providing the output objects from both DLS and TEM analyses.

**What statistical models are supported?**
The server supports log-normal and normal distribution models via the `get_distribution_summary` tool.