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- license: mit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # AutoMat Benchmark: STEM Image to Crystal Structure
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+
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+ The **AutoMat Benchmark** is a multimodal dataset designed to evaluate deep‑learning systems for iDPC-STEM‑based crystal‑structure reconstruction and property prediction.
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+
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  ---
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+
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+ ## 📁 Dataset Structure
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+
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+ The dataset is organized into three tiers of increasing difficulty:
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+
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+ ```text
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+ benchmark/
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+ ├── tier1/
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+ │ ├── img/ # STEM images (e.g., PNG, TIFF)
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+ │ ├── label/ # Atomic position labels (e.g., TXT, JSON)
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+ │ └── cif_file/ # Reconstructed or ground‑truth CIF files
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+ ├── tier2/
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+ │ └── ... # Same sub‑folders as tier1
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+ ├── tier3/
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+ │ └── ...
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+ └── property.csv # Material properties for all samples
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+ ````
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+
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  ---
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+
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+ ## 🔬 Tier Descriptions
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+
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+ | Tier | Characteristics |
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+ |--------|----------------------------------------------------------------|
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+ | Tier 1 | Simulated low-noise STEM images, light elements, low complexity |
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+ | Tier 2 | Moderate noise or multiple elements, more realistic patterns |
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+ | Tier 3 | Low dose, multi-elements, complex symmetry |
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+
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+ Each sample in the dataset includes:
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+ - A STEM image (`img/`)
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+ - Labeled atomic coordinates (`label/`)
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+ - A reconstructed or reference CIF file (`cif_file/`)
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+ - Associated material properties in `property.csv`
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+
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+ ---
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+
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+ ## 📊 Tasks Supported
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+
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+ - STEM-to-structure inference
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+ - CIF generation and comparison
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+ - Atomic position prediction
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+ - Property prediction (formation energy, energy_per_atom, bandgap, etc.)
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+
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+ ---
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+
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+ ## 🔗 Files Description
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+
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+ | File / Folder | Description |
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+ |--------------------|------------------------------------------------------------|
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+ | `img/` | STEM input images (grayscale microscopy) |
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+ | `label/` | Atomic position data (format: .txt / .json per sample) |
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+ | `cif_file/` | .cif crystal structure files for each sample |
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+ | `property.csv` | Global material properties table with `material_id` match |
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+
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+ ---
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+
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+ ## 📄 License
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+
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+ This dataset is released under the **MIT License**. You are free to use, modify, and distribute with attribution.
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+
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+ ---
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+
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+ ## ✉️ Citation
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+
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+ If you use this benchmark, please cite:
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+ ```bibtex
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+ @dataset{yang2025automat,
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+ author = {Yaotian Yang et al.},
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+ title = {AutoMat Benchmark for STEM Image-Based Crystal Structure Reconstruction},
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+ year = {2025},
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+ url = {https://huggingface.co/datasets/yaotianvector/STEM2Mat}
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+ }
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+ ```
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+
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+ ---
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+
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+ ## 🙋 Contact
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+
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+ For questions or collaborations, please contact: `yangyt22@gmail.com`
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+