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MrPlow writes:

Submitted via IRC for SoyCow4408

A research team at the University of Central Florida used Machine Learning, aka Artificial Intelligence to optimize the materials used to make perovskite solar cells (PSC). The Organic-Inorganic halide perovskites material used in PSC converts photovoltaic power into consumable energy.

These perovskites can be processed in solid or liquid state, offering a lot of flexibility. Imagine being able to spray or paint bridges, houses and skyscrapers with the material, which would then capture light, turn it into energy and feed it into the electrical grid. Until now, the solar cell industry has relied on silicon because of its efficiency. But that's old technology with limits. Using perovskites, however, has one big barrier. They are difficult to make in a usable and stable material. Scientists spend a lot of time trying to find just the right recipe to make them with all the benefits -- flexibility, stability, efficiency and low cost. That's where artificial intelligence comes in.

The team's work is so promising that its findings are the cover story Dec. 13 in the Advanced Energy Materials journal

Source: https://www.ucf.edu/news/artificial-intelligence-may-help-scientists-make-spray-on-solar-cells/

Jinxin Li, Basudev Pradhan, Surya Gaur, Jayan Thomas. Perovskite Solar Cells: Predictions and Strategies Learned from Machine Learning to Develop High‐Performing Perovskite Solar Cells (Adv. Energy Mater. 46/2019). Advanced Energy Materials, 2019; 9 (46): 1970181 DOI: 10.1002/aenm.201970181

Original Submission