Taylor658/SiN-photonic-waveguide-loss-efficiency

SiN Photonic Waveguide Loss & Efficiency Dataset

Description
This dataset provides 90,000 synthetic rows of silicon nitride (Si₃N₄) photonic waveguide parameters, with a focus on waveguide loss and efficiency metrics. The data is useful for modeling, simulation, or LLM fine tuning to predict and understand the relationship between fabrication/design parameters and optical performance.

Key Highlights ✨

• Material Focus: Silicon Nitride (Si₃N₄)
• Columns: 25 structured columns capturing waveguide geometry, fabrication method, operation conditions, and measured synthetic performance metrics.
• Size: 90,000 rows (ideal for both training and validation splits)
• Use Cases:
  • Straight and Bent Waveguide loss prediction
  • Process control and optimization
  • Photonic design parameter review and study
  • Synthetic data augmentation for AI/ML tasks

Dataset Structure 🏗️

Each row corresponds to a single waveguide configuration or measurement instance, including:

1. Waveguide Geometry

   • `waveguide_width (µm)
   • `waveguide_height (nm or µm)
   • `bend_radius (µm)
   • `device_length (mm)

2. Material & Fabrication

   • cladding_material
   • cladding_thickness (µm)
   • deposition_method
   • etch_method
   • sidewall_roughness (nm)
   • annealing_params

3. Operational Parameters

   • wavelength (nm)
   • polarization (TE/TM)
   • input_power (dBm)
   • temperature (°C)

4. Performance Metrics

   • insertion_loss (dB)
   • propagation_loss (dB/cm)
   • coupling_efficiency_input (%)
   • coupling_efficiency_output (%)
   • scattering_loss (dB/cm)
   • effective_index
   • mode_confinement_factor (0–1)

5. Metadata

   • batch_id (fabrication batch/wafer ID)
   • data_source (Synthetic or Measurement)
   • measurement_method (cut-back, ring_resonance, etc)
   • uncertainty (± dB or %)

Example Row

waveguide_width = 1.212
waveguide_height = 400.00
cladding_material = SiO2
cladding_thickness = 2.50
deposition_method = LPCVD
etch_method = RIE
sidewall_roughness = 2.05
annealing_params = 900C_3hr
wavelength = 1452.23
polarization = TE
input_power = 0.00
temperature = 25.00
bend_radius = 50.00
device_length = 10.00
insertion_loss = 3.50
propagation_loss = 0.300
coupling_efficiency_input = 72.00
coupling_efficiency_output = 68.00
scattering_loss = 0.15
effective_index = 1.800
mode_confinement_factor = 0.80
batch_id = BATCH_12
data_source = Synthetic
measurement_method = cut-back uncertainty = 0.05

How to Use 💡

1. Download/Clone

   • You can download the CSV file manually or use Hugging Face’s datasets library:

     from datasets import load_dataset
     
     dataset = load_dataset("username/SiN_Photonic_Waveguide_Loss_Efficiency")
     

2. Loading & Exploration

   • Load into your favorite Python environment (pandas, polars, etc.) to quickly explore the data distribution:

     import pandas as pd
     
     df = pd.read_csv("SiN_Photonic_Waveguide_Loss_Efficiency.csv")
     print(df.head())
     

3. Model Training

   • For tasks like waveguide loss prediction, treat the waveguide geometry/fabrication columns as input features, and the insertion_loss or propagation_loss columns as the labels or targets.
   • Example ML scenario:

     features = df[[
         "waveguide_width", "waveguide_height", "sidewall_roughness", 
         "wavelength", "polarization", "temperature"
     ]]
     target = df["propagation_loss"]
     
     # Then train a regression model, e.g., scikit-learn, XGBoost, etc.
     

4. Synthetic Data Augmentation

   • Use this synthetic dataset to supplement smaller real world datasets

Caveats & Limitations ⚠️

• Synthetic Nature: While ranges are inspired by real world photonic designs, actual values may differ based on specific foundries, tools, and processes.
• Statistical Simplifications: Not all real world correlations or distributions (e.g., non uniform doping profiles, advanced thermal effects) are captured.
• Measurement Noise: The uncertainty column does not fully replicate complex measurement artifacts.

License 📄

This dataset is available under the MIT License. You are free to modify, distribute, and use it for commercial or non-commercial purposes, just provide attribution.

Citation & Acknowledgments 🙌

If you use this dataset in your research or applications, please cite it as follows (example citation):

Author: https://huggingface.co/Taylor658
Title: SiN Photonic Waveguide Loss & Efficiency (Synthetic)
Year: 2025

@misc{sin_waveguide_loss_efficiency_2025,
  title  = {SiN Photonic Waveguide Loss & Efficiency (Synthetic)},
  author = {atayloraeropsace},
  year   = {2025},
  howpublished = {\url{https://huggingface.co/datasets/username/SiN_Photonic_Waveguide_Loss_Efficiency}}
}

Contributing 🧑‍💻

We welcome community contributions, ideas, and corrections: