tof-sims-analyzer

name	tof-sims-analyzer
description	Time-of-Flight Secondary Ion Mass Spectrometry skill for molecular surface analysis and imaging
allowed-tools	["Read","Write","Glob","Grep","Bash"]
metadata	{"specialization":"nanotechnology","domain":"science","category":"surface-analysis","priority":"medium","phase":6,"tools-libraries":["ION-TOF software","SurfaceLab","NESAC/BIO tools"]}
graph	{"domains":["domain:nanotechnology"],"skillAreas":["skill-area:mathematical-reasoning","skill-area:physics-simulation","skill-area:data-analysis"],"workflows":["workflow:experiment-design"],"roles":["role:research-engineer"]}

ToF-SIMS Analyzer

Purpose

The ToF-SIMS Analyzer skill provides molecular-level surface analysis capabilities for nanomaterials, enabling identification of surface species, chemical imaging, and depth profiling with high sensitivity.

Capabilities

• Molecular ion identification
• Surface contamination analysis
• 2D and 3D chemical imaging
• Isotope labeling detection
• Depth profiling
• Principal component analysis of spectra

Usage Guidelines

ToF-SIMS Analysis

1. Spectral Analysis

   • Identify characteristic fragments
   • Build peak lists for materials
   • Apply multivariate analysis

2. Imaging Mode

   • Optimize spatial resolution
   • Generate chemical maps
   • Correlate with topography

3. Depth Profiling

   • Select appropriate sputter source
   • Monitor interface sharpness
   • Account for matrix effects

Process Integration

• Multi-Modal Nanomaterial Characterization Pipeline
• Nanomaterial Surface Functionalization Pipeline

Input Schema

{
  "sample_id": "string",
  "analysis_mode": "spectral|imaging|depth_profile",
  "primary_ion": "Bi3+|Bi1+|C60+",
  "polarity": "positive|negative",
  "area_of_interest": {"x": "number", "y": "number"}
}

Output Schema

{
  "identified_species": [{
    "mass": "number (amu)",
    "assignment": "string",
    "intensity": "number"
  }],
  "chemical_maps": [{
    "species": "string",
    "image_path": "string"
  }],
  "pca_results": {
    "principal_components": "number",
    "variance_explained": ["number"]
  }
}