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Researchers at Osaka University have developed an automated measurement system that can significantly speed up research on solar materials, according to a study published in JACS Au. The system automates experimental and analytical processes, making it easier and faster to discover new and more efficient solar cell materials.

To meet the requirements for large-scale use, solar cell materials need to be highly efficient, made from common chemical elements, and have low toxicity. The current manual research process is time-consuming and costly, hindering the discovery of suitable materials.

The newly developed robotic measurement system can perform photoabsorption spectroscopy, optical microscopy, and time-resolved microwave conductivity analyses. It was used to evaluate 576 thin-film semiconductor samples. The researchers used machine learning techniques to analyze the data and characterize the material properties.

The study focused on cesium-bismuth-tin-iodine blends, which were treated with different organic salt additives and annealed at varying temperatures. The automated system proved to be accurate and reduced the time needed for the measurement process by one-sixth of the usual time.

Lead author Chisato Nishikawa emphasized that the method is ideal for exploring areas with limited existing data. The researchers hope to automate more of the process in the future, making it easier to study completely new materials.

By combining robotic systems and artificial intelligence, researchers are making significant progress in finding efficient and non-toxic solar materials. This research brings us one step closer to a future powered by solar energy.

Source:
Title: How Robots Can Help Find Better Solar Materials
Website: Science X

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