The authors introduce DD2D, a physics-guided deep learning method that predicts 2D structures directly from diffraction patterns using a twin-tower framework. The method demonstrates high anti-interference, robust recognition, and up to 99.0% prediction accuracy, showing promise for future 2D materials discoveries.
- Rong Fu
- Tianhao Su
- Zhongming Ren
