New computer vision method helps speed up screening of electronic materials

The new computer vision technique developed by MIT engineers significantly speeds up the characterization of newly synthesized electronic materials. It automatically analyzes images of printed semiconducting samples and quickly estimates two key electronic properties for each sample: band gap (a measure of electron activation energy) and stability (a measure of longevity). This technique is 85 times faster compared to the standard benchmark approach and has the potential to clear the bottleneck in the pipeline of advanced materials screening.

The integration of this technique into the process of discovering and characterizing new materials for electronic applications involves the following steps:

1. Scientists use AI tools to identify promising materials from hundreds of millions of chemical formulations.
2. Engineers build machines that can print hundreds of material samples at a time based on chemical compositions tagged by AI search algorithms.
3. The newly developed computer vision technique automatically analyzes images of printed semiconducting samples and estimates their electronic properties.
4. The technique can be incorporated into a fully automated materials screening system, allowing for an autonomous lab of the future where a computer can predict potential compounds and run experiments 24/7 to arrive at the desired solution5.

This new technique has the potential to accelerate the search for promising electronic materials, including those for solar cells, transistors, LEDs, and batteries, and could lead to faster and more efficient development of advanced electronic applications.

The new computer vision technique developed by MIT engineers estimates two key electronic properties for each sample of electronic materials: band gap (a measure of electron activation energy) and stability (a measure of longevity).