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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 HighâPerforming Perovskite Solar Cells (Adv. Energy Mater. 46/2019). Advanced Energy Materials, 2019; 9 (46): 1970181 DOI: 10.1002/aenm.201970181
(Score: 4, Interesting) by DeathMonkey on Thursday December 19 2019, @06:47PM
This is true and those halogens are even worse than plain old lead by itself! [nih.gov]
However, the entire purpose of this AI is to find DIFFERENT materials that can be used to create the peroskite structure. So to assume that they're to be using the lead based ones that already exist is the opposite of what they;re doing.