Overview

• The new method uses AI to analyze images of printed semiconducting samples, estimating band gap and stability quickly.
• Traditional manual characterization processes are significantly slower, handling only 20 samples per hour compared to the new method's rapid pace.
• Researchers plan to integrate this technique into an autonomous lab system for continuous material discovery and characterization.
• The technique has shown 98.5% accuracy for band gap and 96.9% accuracy for stability compared to manual benchmarks.
• The development could benefit a wide range of applications, including solar energy, transparent electronics, and transistors.