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AI-driven robots could speed up next-gen solar development


AI-driven robots could speed up next-gen solar development

RoboMapper works almost 10x faster than previous techniques, lowering the cost and the carbon footprint of searching for new solar cell materials.
July 27, 2023

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Researchers at North Carolina State University have made a robot that can conduct experiments to identify materials for solar cells. The technology, called RoboMapper, has already found a new type of photovoltaic material called a perovskite that could lead to efficient and stable solar cells, the team reports in the journal Matter.

RoboMapper works almost 10 times faster than previous automated techniques, said Tonghui Wang, lead author of the paper said in a press release. “This makes searching for new materials far more efficient, more cost effective, and more sustainable in terms of our carbon footprint.”

Solar cells, batteries, and other important energy technologies all rely on the materials that go into them. Developing these materials is time-consuming and expensive. It involves making tiny tweaks to the recipes, from the elements and additives that go into the material to processing conditions such as heating temperatures and solution concentrations. This can result in millions of different combinations to make and test in a lab, taking countless hours and adding cost.

Materials scientists in recent years have turned to robots driven by artificial intelligence to speed up the process. Past work has led to robots that can perform experiments and analyze the results. The AI then uses the data to determine what to make for testing next.

The NCSU team has streamlined this process to make it more efficient with their new take on robotic technology. Previous efforts have used robots that work with one sample per chip. So each experimental step—which involves placing, aligning, and calibrating samples—was done on one sample at a time. While faster than manual experiments, having one sample on a chip is still time consuming and requires a lot of electricity to power the various instruments.


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“RoboMapper also automates this process, but places dozens of samples on each chip by miniaturizing the material samples with the help of modern printing,” said Aram Amassian, professor of materials science and engineering at NCSU in a press release.

The team focused on using RoboMapper to develop perovskites, materials that are more efficient than silicon at converting light to electricity. Perovskites are also cheaper and easier to make, and promise thinner, lighter solar panels.

In their proof-of-concept demonstration, the researchers instructed RoboMapper to make 150 perovskite alloys using a defined set of elements. The bot made the samples and tested them using various techniques to see whether it had the right crystalline structure and optical properties for solar cells. It also tested whether the samples were stable when exposed to light, which is one usual drawback of perovskites.

Next, RoboMapper used its experimental data to create a computer model, which predicted a new alloy composition that would have the best combination of perovskite solar cell properties. Finally, the researchers created this ideal alloy with both RoboMapper and using conventional laboratory techniques. The material turned out to be not only stable but also highly efficient at converting light to electricity.

Source: Tonghui Wang et al. Sustainable materials acceleration platform reveals stable and efficient wide-bandgap metal halide perovskite alloys. Matter, 2023.

Image: ©Anthropocene Magazine

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