🧲 NMR-Project

This project provides a comprehensive pipeline for parsing, analyzing, and visualizing Nuclear Magnetic Resonance (NMR) spectroscopy data, with a focus on 1H-NMR.
It includes data import, Fourier transformation, peak detection, integration, functional group identification, spin-spin coupling analysis, and quantum mechanical simulation of spin systems.

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✨ Features

• 📥 Data Import & Visualization
  Reads JEOL ASCII FID files and visualizes the raw time-domain signal. (ASCII reccommended)

• 🔄 Fourier Transform
  Converts the time-domain FID to the frequency domain using FFT, producing the NMR spectrum.

• 📈➕ Peak Detection & Integration
  Detects significant peaks using customizable thresholds and integrates peak areas to estimate relative proton counts.

• 🧬 Functional Group Identification
  Maps detected peaks to chemical functional groups based on their chemical shift (δ, ppm) ranges.

• 🔗 Spin-Spin Coupling (J-Coupling) Analysis
  Detects multiplets, estimates J-coupling constants ($J$), and visualizes multiplet structures with annotated J values.

• ⚛️ Quantum Mechanical Simulation
  Simulates the NMR Hamiltonian for coupled spin systems, computes eigenstates, and animates wavefunction evolution in a potential.

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📁 File Structure

NMR-Project/
│
├── data/
│   └── 13_03_11_indst_1H fid.asc        # Raw JEOL FID ASCII data files
│
├── notebooks/
│   ├── project_1_spring_2025.ipynb      # Main analysis notebook    
│   ├── testing_functions.ipynb          # Notebook for testing/refactoring functions  
│   ├── project_2_fall_2025.ipynb        # project presented in fall
│
├── nmr/
│   ├── __init__.py                      # Makes this a Python package  
│   ├── nmr_functions.py                 # All reusable NMR analysis functions/classes  
│   └── quantum_sim.py                   # Quantum simulation utilities (optional)  
│
├── outputs/
│   └── pen.gif                          # Example animation output  
│
├── README.md                            # Project overview and usage  
├── requirements.txt                     # List of dependencies (for pip install -r)  
└── .gitignore                           # Ignore data, outputs, etc. as needed  

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🚀 Usage

1. Open parsing_nmr_data.ipynb in Jupyter, VS Code, or Colab (Colab recommended for beginners).
2. Edit the file path in the data import cell to point to your JEOL FID ASCII file.
3. Run all cells sequentially to:
   • 📥 Import and plot raw data
   • 🔄 Perform Fourier transform and plot the spectrum
   • 📈➕ Detect and integrate peaks
   • 🧬 Identify functional groups
   • 🔗 Analyze spin-spin coupling and visualize multiplets
   • ⚛️ Simulate and animate quantum wavefunction evolution

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🛠️ Requirements

• Python 3.7+
• numpy
• pandas
• matplotlib
• seaborn
• scipy
• pillow (for GIF animation)

Install dependencies with:

pip install numpy pandas matplotlib seaborn scipy pillow

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🧩 Key Functions & Notebooks

• Data Import & FFT:
  See the initial code cells in parsing_nmr_data.ipynb.

• Peak Detection & Integration:
  Uses scipy.signal.find_peaks and scipy.integrate.simpson.

• Functional Group Mapping:
  See identify_functional_groups and auto_zoom_functional_groups_with_integration.

• Spin-Spin Coupling:
  See detect_and_plot_multiplet for multiplet and J-coupling analysis.

• Quantum Simulation:
  See the final section for Hamiltonian construction, eigenstate computation, and animation.

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🖼️ Example Output

• NMR Spectrum:
  Plots of the frequency-domain spectrum with detected peaks and functional group annotations.

• Integration Table:
  Printed output of relative proton counts for each peak.

• Multiplet Visualization:
  Zoomed-in plots of multiplets with J-coupling constants annotated.

• Quantum Animation:
  Animated GIF (pen.gif) showing the time evolution of a quantum wavefunction in a potential.

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📝 Notes

• The code is modular and can be adapted for other NMR datasets or extended for more advanced analyses.
• For best results, use high-quality FID data and adjust thresholds as needed for your instrument and sample.

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📜 License

This project is for educational and research purposes.

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👤 Author

Created by Quintinlf For questions, open an issue or contact via GitHub.

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See parsing_nmr_data.ipynb for full code and documentation.