Create README.md

README.md

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+---
+license: cc-by-nc-4.0
+tags:
+- emmi-ai
+- physics-simulation
+- dem
+- cfd-dem
+- neural-operator
+pretty_name: NeuralDEM Dataset
+---
+
+# NeuralDEM Dataset
+
+Dataset repository for **NeuralDEM**, containing simulation data for training and evaluating deep learning surrogates for industrial particulate flows and particle-fluid coupled systems.
+
+## Dataset Summary
+
+The NeuralDEM dataset covers two primary physics benchmarks:
+
+1. **Hopper Simulations (Particle Systems)**
+   * **Setup**: Hopper domain with a bottom outlet initially loaded with ~250,000 particles discharging over time.
+   * **Physics**: Discrete Element Method (DEM) dynamics across diverse hopper geometry angles and particle friction regimes.
+2. **Fluidized Bed Reactor (Particle-Fluid Coupled Systems)**
+   * **Setup**: Reactor containing ~500,000 particles with uniform fluid (air) injection from the bottom grid.
+   * **Physics**: Coupled CFD-DEM multi-physics system over ~160,000 hexahedral CFD grid cells across varying fluid inlet velocities.
+
+
+For inference scripts, model checkpoints, and simulation rollouts, visit the [NeuralDEM GitHub Repository](https://github.com/Emmi-AI/NeuralDEM).
+
+## License
+
+This dataset is distributed under the [CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) license.
+
+## Citation instructions
+```
+@article{alkin2024neuraldem,
+  title={{NeuralDEM} for real time simulations of industrial particular flows},
+  author={Benedikt Alkin and Tobias Kronlachner and Samuele Papa and Stefan Pirker and Thomas Lichtenegger and Johannes Brandstetter},
+  journal={Nature Communications Physics},
+  year={2025}
+  doi={10.1038/s42005-025-02342-4},
+}
+```