A new computer vision technique developed by MIT engineers significantly speeds the characterization of newly synthesized electronic materials that could be used in solar cells, transistors, LEDs, and batteries.
Boosting the performance of solar cells, transistors, LEDs, and batteries will require better electronic materials, made from novel compositions that have yet to be discovered. To speed up the search for advanced functional materials, scientists are using AI tools to identify promising materials from hundreds of millions of chemical formulations. In tandem, engineers are building machines that can print hundreds of material samples at a time based on chemical compositions tagged by AI search algorithms. But to date, there's been no similarly speedy way to confirm that these printed materials actually perform as expected. This last step of material characterization has been a major bottleneck in the pipeline of advanced materials screening. Now, a new computer vision technique developed by MIT engineers significantly speeds up the characterization of newly synthesized electronic materials. The technique 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). The new technique accurately characterizes electronic materials 85 times faster compared to the standard benchmark approach. The researchers intend to use the technique to speed up the search for promising solar cell materials. They also plan to incorporate the technique into a fully automated materials screening system. "Ultimately, we envision fitting this technique into an autonomous lab of the future," says MIT graduate student Eunice Aissi. "The whole system would allow us to give a computer a materials problem, have it predict potential compounds, and then run 24-7 making and characterizing those predicted materials until it arrives at the desired solution." "The application space for these techniques ranges from improving solar energy to transparent electronics and transistors," adds MIT graduate student Alexander (Aleks) Siemenn.…