XQueryer

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[Natl. Sci. Rev.] An integrated software-hardware smart system for material synthesis, characterization, crystal structure analysis, and visualization.

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<a href="README.md">English</a> ·
 <a href="README_CN.md">中文</a> ·
 <a href="README_JA.md">日本語</a> ·
 <a href="README_KO.md">한국어</a>

An AI framework for real-time crystal-structure identification from powder X-ray diffraction (PXRD) patterns.

> **Explore the article website → [bin-cao.github.io/XQueryer](https://bin-cao.github.io/XQueryer/)**
>
> The multilingual project page introduces the paper, simulation pipeline, model architecture, benchmark results, and real-time diffractometer integration.

> [!TIP]
> **Need a smaller model? Try [XQueryer Lightweight](https://github.com/Asterbin/Asterbin-XQueryer-Lightweight) →** A lightweight implementation is available in its dedicated repository.

## XQueryer at a glance

XQueryer combines high-fidelity, physics-guided PXRD simulation with a neural structure-identification model. It is designed for AI-driven laboratories where diffraction data should become useful crystal information quickly and automatically.

| Dataset | Model | Validation | Deployment |
| --- | --- | --- | --- |
| 2.3M+ simulated PXRD patterns from 100,315 Materials Project structures | FFT filtering, CNN features and cross-attention | +28.9% accuracy over the next-best model; 70.3% accuracy on 1,003 RRUFF patterns | Integrated with a PANalytical Aeris benchtop diffractometer for real-time analysis |

## Highlights

- **Physics-guided data synthesis** — models intrinsic sample factors and extrinsic diffractometer effects to create diverse PXRD patterns.
- **Robust pattern understanding** — frequency-domain filtering helps reduce noise and peak overlap before classification.
- **Real-time workflow** — automatically parses fresh diffractometer output and returns identified structures with Materials Project information.
- **Open research resources** — source code, simulation tools, tutorials, matching utilities, and benchmark code are linked below.

## Resources

| <img src="https://cdn.simpleicons.org/github/24292f" width="15" alt=""> Code & data | <img src="https://cdn.simpleicons.org/bookstack/24292f" width="15" alt=""> Learning | <img src="https://cdn.simpleicons.org/link/24292f" width="15" alt=""> Related |
| --- | --- | --- |
| [Source code](./src) · [Simulation](./sim) · [RRUFF–MP matching](./match) · [Dataset](https://onedrive.live.com/?redeem=aHR0cHM6Ly8xZHJ2Lm1zL2YvYy81ZDg2MjYyMzg0NzBiNDllL0V1d09VMTNQM2JoSHNiU2lEMTRON3hZQmZCTEdCYTFjX0VhVkhrbGZUajRxZXc%5FZT0xa3liaFg&id=5D8626238470B49E%21s5d530eecddcf47b8b1b4a20f5e0def16) | [Model tutorial](./src/Tutorial.ipynb) · [Simulation tutorial](./sim/XRD.ipynb) · [High-throughput simulation](./sim/tutorial_sim.ipynb) | [XqueryerBench](https://github.com/WPEM/XqueryerBench) · [Lightweight version](https://github.com/Asterbin/Asterbin-XQueryer-Lightweight) · [Video demo](https://www.youtube.com/watch?v=OYPoh7K5uM0) |

## Paper

Bin Cao, Zinan Zheng, Yang Liu, Longhan Zhang, Lawrence W-Y Wong, Lu-Tao Weng, Jia Li, Haoxiang Li and Tong-Yi Zhang. **XQueryer: an intelligent crystal structure identifier for powder X-ray diffraction.** *National Science Review* 12, nwaf421 (2025). [Read the article](https://doi.org/10.1093/nsr/nwaf421)

## Contact

Maintained by Bin Cao. For questions, suggestions, or issues, please [open an issue](https://github.com/Bin-Cao/XQueryer/issues) or contact [bcao686@connect.hkust-gz.edu.cn](mailto:bcao686@connect.hkust-gz.edu.cn).

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