This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

Solar cells generate electricity by absorbing sunlight in a thin layer of perovskite, a light-absorbing material. This layer is made with a liquid solution that dries and crystallizes into a solid film, but small changes in temperature, humidity and other conditions can affect the film and the performance of the solar cell.

Now, recent research combining a robot system with machine learning may overcome this challenge. Researchers from the University of Osaka have published their findings on a newly developed automated platform for fabricating perovskite films. The system coordinates film deposition with optical imaging and environmental measurements. The findings were published in ACS Nano.

The team used the platform to investigate the transformation of the liquid coating to a crystalline film, focusing on changes in film color and the behavior of antisolvent droplets. As these changes can occur rapidly, the researchers needed measurements that could capture the process on very short timescales. The resulting observations provided detailed information about how events during film formation influence the final material.

"We want to move beyond trial and error by measuring what happens to the film while it is actually forming," says lead author Ryosuke Kado. "Our system allows us to connect these real-time changes with the quality of the perovskite film and identify the factors that matter most."

The system can capture changes in film color on a subsecond timescale and resolve the motion and impact of antisolvent droplets within just a few milliseconds.

Source link