streamlines

Nanotechnology

Deep learning streamlines 2D material identification

Illustration of the DDPM-based data augmentation and classification framework for Raman spectra of 2D materials. Credit: Applied Materials Today (2024). DOI: 10.1016/j.apmt.2024.102499 Researchers have developed a deep learning-based approach that greatly streamlines the accurate identification and classification of two-dimensional (2D) materials using Raman spectroscopy. In comparison, traditional Raman analysis methods are time-consuming and require manual and subjective interpretation. This new…