📡 SAXS Synthetic Scattering Curves Dataset

Thousands of physically accurate Small Angle X-ray Scattering (SAXS) curves, generated from rigorous physical models.

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🔬 What is this dataset?

This dataset provides synthetic SAXS intensity curves I(q) generated using validated physical scattering models (via SASmodels), covering a wide range of nanoparticle shapes, materials, sizes, and concentrations.

Each curve is fully labelled with its physical parameters, making it immediately usable for:

• Training ML models to predict nanoparticle parameters from experimental curves
• Benchmarking fitting algorithms
• Data augmentation for experimental datasets
• Developing automated analysis pipelines

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📊 Sample Visualization

(See attached figures in the dataset repository)

💼 Versions & Pricing

This page hosts a free sample (~100 curves).
Full commercial versions are available on Gumroad →

Tier	Curves	Shape	Material	Price
Sample (this page)	100	sphere	ag	Free
ag_sphere	100k	Sphere	Ag	49€
au_sphere	100k	Sphere	Au	49€
sio2_sphere	100k	Sphere	SiO2	49€
latex_sphere	100k	Sphere	Latex	49€
ag_cylinder	100k	Cylinder	Ag	79€
au_cylinder	100k	Cylinder	Au	79€
sio2_cylinder	100k	Cylinder	SiO2	79€
latex_cylinder	100k	Cylinder	Latex	79€
Custom	Unlimited	Custom	Custom	On request

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🚀 Ploting function exemple

import h5py
import numpy as np
import matplotlib.pyplot as plt

def plotSaxs(h5_path, index_to_plot=0):
    with h5py.File(h5_path, 'r') as f:
        # Extract Data
        q = f.attrs['q']
        intensities = f['intensities'][index_to_plot]
        material = f.attrs.get('material', 'Unknown').upper()
        shape = f.attrs.get('shape', 'Unknown').capitalize()

        # Extract specific metadata for the legend
        params_str = ""
        for k in f.keys():
            if k == 'intensities':
                continue
            val = f[k][index_to_plot]
            params_str += f"{k}: {val:.2f} | "

    # Plotting Setup
    plt.rcParams.update({
        'font.size': 12,
        'axes.labelsize': 14,
        'xtick.labelsize': 12,
        'ytick.labelsize': 12,
        'legend.fontsize': 10,
        'lines.linewidth': 2,
        'figure.dpi': 200
    })

    fig, ax = plt.subplots(figsize=(9, 5))

    # main curve
    ax.loglog(q, intensities, color='#1f77b4', label=f"{material} {shape}")

    ax.set_xlabel(r'Scattering Vector $q$ ($\mathring{A}^{-1}$)')
    ax.set_ylabel(r'Intensity $I(q)$ ($cm^{-1}$)')
    ax.set_title(f'Simulated SAXS Profile: {material} {shape}', pad=15)

    # Styling the Grid and Spines
    ax.grid(True, which="both", ls="-", alpha=0.2)
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)

    # Adding metadata info as a text box or legend
    props = dict(boxstyle='round', facecolor='white', alpha=0.5)
    ax.text(0.05, 0.05, params_str.rstrip(' | '), transform=ax.transAxes,
            fontsize=9, verticalalignment='bottom', bbox=props)

    ax.legend(frameon=False)

    plt.tight_layout()

    # Save as PDF or TIFF
    save_path = h5_path.replace('.h5', '.tiff')
    plt.savefig(save_path)
    print(f"Plot saved to: {save_path}")
    plt.show()

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📄 License

This dataset is released under a Commercial Restricted License.

• ✅ Academic and research use: free
• ✅ Internal ML training: free for non-commercial entities
• ❌ Commercial use (products, services, APIs): requires a paid license

See LICENSE for full terms.

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📬 Contact & Custom Orders

Need a specific material, shape, q-range, or instrument noise model?
→ Contact via Gumroad or open a Discussion on this page.

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📖 Citation

If you use this dataset in academic work, please cite:

@dataset{saxs_2026,
  author    = {Thevenon, Esteban},
  title     = {SAXS Synthetic Scattering Curves Dataset},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Venon28/SAXS}
}