{"id":105446,"date":"2019-12-16T09:50:37","date_gmt":"2019-12-16T14:50:37","guid":{"rendered":"https:\/\/www.ucf.edu\/news\/?p=105446"},"modified":"2023-03-16T13:58:55","modified_gmt":"2023-03-16T17:58:55","slug":"artificial-intelligence-may-help-scientists-make-spray-on-solar-cells","status":"publish","type":"post","link":"https:\/\/www.ucf.edu\/news\/artificial-intelligence-may-help-scientists-make-spray-on-solar-cells\/","title":{"rendered":"Artificial Intelligence May Help Scientists Make Spray-on Solar Cells"},"content":{"rendered":"

Artificial Intelligence may be just the thing to accelerate spray-on solar cell technology, which could revolutionize how consumers use energy.<\/p>\n

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.<\/p>\n

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\u2019s 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 \u2013 flexibility, stability, efficiency and low cost. That\u2019s where artificial intelligence comes in.<\/p>\n

The team\u2019s work is so promising that its findings are the cover story Friday, Dec. 13 in the Advanced Energy Materials<\/em> journal.<\/p>\n

The team reviewed more than 2,000 peer-reviewed publications about perovskites and collected more than 300 data points then fed into the AI system they created. The system was able to analyze the information and predict which perovskites recipe would work best.<\/p>\n

\u201cOur results demonstrate that machine learning tools can be used for crafting perovskite materials and investigating the physics behind developing highly efficient PSCs,\u201d says Jayan Thomas, the study\u2019s lead author and an associate professor at the NanoScience Technology Center<\/a> with multiple affiliations. \u201cThis can be a guide to design new materials as evidenced by our experimental demonstration.\u201d<\/p>\n

If this model bears out, it means researchers could identify the best formula to create a world standard. Then spray-on solar cells may happen in our lifetime, the researchers say.<\/p>\n

\u201cThis is a promising finding because we use data from real experiments to predict and obtain a similar trend from the theoretical calculation, which is new for PSCs. We also predicted the best recipe to make PSC with different bandgap perovskites,\u201d says Thomas and his graduate student, Jinxin Li, who is the first author of this paper. \u201cPerovskites have been a hot research topic for the past 10 years, but we think we really have something here that can move us forward.\u201d<\/p>\n

Others on the research team include: Basudev Pradhan from the NanoScience Technology Center and Surya Gaur from the College of Engineering and Computer Science. Pradhan is currently a faculty member at Centre of Excellence in Green and Efficient Energy Technology, at the Central University of Jharkhand in India<\/p>\n

Thomas joined UCF in 2011 and is a part of the NanoScience Technology Center with a joint appointment in the College of Optics and Photonics and the Department of Materials Science and Engineering in the College of Engineering. His previous work resulted in a variety of innovations, including material that could help keep pilots and sensitive equipment safe from destructive lasers, a way to both transmit and store electricity in a lightweight copper wire, and filaments that harvest and store the sun’s energy and can be woven into textiles.<\/p>\n

Previously, Thomas was at the University of Arizona in its College of Optical Sciences. He has several degrees including a doctorate in chemistry\/materials science from Cochin University of Science and Technology in India. He\u2019s published dozens of studies and earned several grants and awards including a National Science Foundation CAREER Grant and an R&D 100 award.<\/p>\n","protected":false},"excerpt":{"rendered":"

UCF researchers have developed an AI system that can identify formulas for creating liquid solar cells, which potentially could allow them to be painted on bridges, houses and skyscrapers.<\/p>\n","protected":false},"author":16,"featured_media":105447,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"lazy_load_responsive_images_disabled":false,"footnotes":"","_links_to":"","_links_to_target":"","_wp_rev_ctl_limit":""},"categories":[5,23,24],"tags":[54138,973,981,3279,15761,14916],"tu_author":[],"class_list":["post-105446","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-colleges","category-research","category-science-technology","tag-artificial-intelligence","tag-college-of-engineering-and-computer-science","tag-college-of-optics-and-photonics","tag-nanoscience-technology-center","tag-pegasus-briefs","tag-research"],"yoast_head":"\nArtificial Intelligence May Help Scientists Make Spray-on Solar Cells | University of Central Florida News<\/title>\n<meta name=\"description\" content=\"Artificial Intelligence may be just the thing to accelerate spray-on solar cell technology, which could revolutionize how consumers use energy. 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