Help & Documentation

Getting Started
  1. Insert your molecule: Paste SMILES/InChI strings or molecular data into the input field
  2. Select analysis options: Choose which analyses to perform
  3. Analyze: Click "Analyze Molecule" to evaluate COF and MOP formation potential
  4. Review results: Examine the comprehensive analysis results
  5. Export data: Download results in various formats
COF Chemistry Background
What are COFs?

Covalent Organic Frameworks (COFs) are crystalline porous materials constructed from organic building blocks linked by covalent bonds. They offer:

  • High surface areas (up to 2000+ m²/g)
  • Tunable pore sizes and shapes
  • Chemical stability
  • Design flexibility
Tripodal Molecules

Tripodal molecules have three-fold symmetry with a central core and three extending arms. They are ideal for COF formation because:

  • Provide structural rigidity
  • Enable predictable topology
  • Allow for systematic design
Analysis Types

Analyzes the 3D structure of your molecule:

  • Tripodal Detection: Identifies three-fold symmetry
  • Arm Angles: Measures angles between molecular arms
  • Planarity: Assesses molecular flatness
  • Flexibility: Evaluates conformational freedom

Identifies COF-forming functional groups:

  • Aldehydes: React with amines to form imines
  • Amines: React with aldehydes and acids
  • Boronic Acids: Form boronate esters
  • Carboxylic Acids: Form amides and esters
  • Phenols: Participate in condensation reactions

Predicts possible COF topologies:

  • STP (SrSi₂): 3D tetrahedral topology
  • DIA (Diamond): 3D diamond-like structure
  • HEX (Hexagonal): 2D hexagonal topology
  • SQL (Square): 2D square lattice

Analyzes synthetic feasibility:

  • Disconnection Sites: Identifies strategic bond breaks
  • Synthetic Routes: Suggests synthesis pathways
  • Building Blocks: Identifies required starting materials
  • Reaction Partners: Suggests suitable comonomers
COF Force Field Decision Tree

Advanced MD simulation with intelligent force field selection for COF analysis.

Step 1: Access the VR Viewer
  1. Go to your ChatCOF application
  2. Navigate to VR COF Viewer section
  3. Make sure you have a molecule analyzed first (enter SMILES and run analysis)
Step 2: Find the Force Field Controls
  1. Look for the "MD Simulation Controls" panel
  2. Find the "Force Field" dropdown (has a blue info icon next to it)
  3. You'll see it currently shows various options
Step 3: Choose Your Mode
Option A - AI Auto-Select (Recommended)
  1. Select 🤖 Auto-Select (Decision Tree) from dropdown
  2. Watch the green text below explain why it picked that force field
  3. The system automatically chooses based on your molecule's properties
Option B - Manual Selection

Pick any specific force field from the organized groups:

  • High-Throughput Screening: UFF, DREIDING
  • Adsorption & Host-Guest: COMPASS
  • Chemical Reactivity: ReaxFF
  • High-Accuracy: MMFF94, ML-DeePMD, ML-GAP
Step 4: Start MD Simulation
  1. Click "Start MD Simulation" button
  2. The console will show which force field is running (e.g., "Starting MD simulation with COMPASS at 325K")
  3. Watch the molecular dynamics animation
Step 5: Test Different Molecules
  1. Go back and analyze a different molecule (different SMILES)
  2. Return to VR viewer
  3. Notice how the auto-selection picks different force fields for different molecules
  4. The reasoning text updates to explain each choice
Step 6: Compare Results
  • Try the same molecule with different force fields
  • Observe how simulation behavior changes
  • Use manual override when you need specific accuracy/speed trade-offs

High-Throughput Screening
  • UFF (Universal): Fast, large databases, metal compatibility
  • DREIDING (Accuracy): Better accuracy for medium systems
Adsorption & Host-Guest
  • COMPASS: Accurate π-π stacking, H-bonding, gas separation
Chemical Reactivity
  • ReaxFF: Bond formation/breaking reactions
High-Accuracy
  • MMFF94: Standard organic molecules
  • ML-DeePMD: Near-quantum accuracy for small systems
  • ML-GAP: Large systems with high precision

The system analyzes your molecule and automatically decides based on:

Example Decision Logic:
  • High COF score (0.8+) + STP topology → COMPASS (for accurate adsorption studies)
  • Low stability + mechanical focus → DREIDING (for structural analysis)
  • Metal-containing COF → UFF (metal compatibility)
  • Large system (>200 atoms) → UFF (computational efficiency)
  • Reactive groups detected → ReaxFF (chemical reactivity)
Real-Time Feedback:
  • Green text below dropdown shows why that force field was chosen
  • Updates automatically when you change molecules
  • Manual selection overrides auto-mode

Advanced molecular dynamics trajectory generation and visualization controls.

Trajectory Generation
Generate Trajectory
  1. Set desired Duration (ps) - typically 10-100 picoseconds
  2. Adjust Time Step (fs) - usually 1.0 femtoseconds
  3. Click "Generate Trajectory" (green button)
  4. Wait for completion - progress shows in console
Play Trajectory
  1. After generation completes
  2. Click "Play Trajectory" (blue button)
  3. Watch molecular motion animation
  4. Frame counter shows current/total frames
Force Visualization Options
Force Vectors

Shows directional forces on each atom with colored arrows. Red = repulsive, Blue = attractive.

Electrostatic Surface

Displays electron density surface. Red = negative charge, Blue = positive charge regions.

Van der Waals Surface

Shows molecular contact surface based on atomic radii and non-bonded interactions.

Parameter Guidelines
Parameter Small Systems (<50 atoms) Medium Systems (50-200 atoms) Large Systems (>200 atoms)
Duration (ps) 50-100 ps 20-50 ps 10-20 ps
Time Step (fs) 0.5-1.0 fs 1.0 fs 1.0-2.0 fs
Expected Frames 50,000-100,000 20,000-50,000 5,000-20,000
Performance Tips:
  • Start small: Use 10ps duration for initial testing
  • Force visualizations: Turn off when not needed - they slow down playback
  • Large molecules: Increase time step to 2.0fs for faster generation
  • Frame counter: Shows progress - Frame: current/Total: maximum
What You'll See:
  • Thermal motion: Atoms vibrating due to temperature
  • Bond flexibility: Bonds stretching and bending realistically
  • Conformational changes: Molecular shape evolution over time
  • Force interactions: How atoms push and pull on each other
Topology Types
STP (SrSi₂)

3D tetrahedral topology with mesoporous structure. Typical pore size: 2.5 nm. Suitable for gas storage and separation.

DIA (Diamond)

3D diamond-like topology with interconnected pores. Typical pore size: 3.0 nm. Excellent mechanical properties.

HEX (Hexagonal)

2D hexagonal topology with planar structure. Typical pore size: 2.0 nm. Good for membrane applications.

SQL (Square)

2D square lattice topology. Typical pore size: 1.8 nm. Suitable for selective adsorption.

Input Formats
SMILES (Simplified Molecular Input Line Entry System)

A text-based notation for molecules. Examples:

  • c1ccc(cc1)C(=O)O - Benzoic acid
  • c1nc(nc(n1)N)N - Melamine
  • c1ccc(cc1)N(c2ccccc2)c3ccccc3 - Triphenylamine
InChI (International Chemical Identifier)

A standard identifier for chemical substances. More verbose than SMILES but provides unique identification.

Export Formats
JSON

Complete analysis results in JSON format for further processing.

CSV

Tabular data format for spreadsheet analysis.

CIF (Crystallographic Information File)

Standard format for crystallographic data, including predicted COF structures.

PDB (Protein Data Bank)

3D structure format for visualization in molecular viewers.

Troubleshooting
Common Issues

If you get an "Invalid molecule structure" error:

  • Check your SMILES syntax
  • Ensure all atoms have valid valencies
  • Verify ring closures are properly numbered

Analysis might be slow for large molecules:

  • Complex molecules take longer to analyze
  • Multiple analyses increase processing time
  • Consider disabling unnecessary analyses
Need More Help?

For additional support or questions about COF chemistry:

  • Check the analysis results for specific recommendations
  • Consult the literature for COF synthesis protocols
  • Consider experimental validation of predictions