Perovskite solar cells already achieve efficiencies of over 26% and are light, flexible and inexpensive to produce. They are considered a promising alternative to conventional silicon modules. However, challenges such as long-term stability and scalability still stand in the way of industrial utilisation.<\/p>\n\n\n\n\n\n
AI as the key to optimising production Detecting errors before they occur Simulations for maximum efficiency The path to market maturity Perovskite solar cells could revolutionise photovoltaics. Their high efficiency and flexible application possibilities make them very promising. However, production hurdles are slowing market maturity. A new study by KIT shows how artificial intelligence optimises processes through machine learning and accelerates the commercialisation of this technology. <\/p>\n","protected":false},"author":2,"featured_media":124513,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"pmpro_default_level":"","inline_featured_image":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[12482,12476,12483,22433],"tags":[16580,12575,41549,12564,12525,12526,30358,13861,51720,16748,51721,12529,51722,19754],"class_list":["post-124580","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-energy","category-immonews","category-proptech-en","category-trends-en","tag-effizienz-en","tag-forschung-en","tag-herstellung-en","tag-immobilien-en","tag-immoinvest-en","tag-immonews-en","tag-ki-en","tag-kuenstliche-intelligenz-en","tag-langzeitstabilitaet-en","tag-materialien-en","tag-perowskit-en","tag-photovoltaik-en","tag-solarenergiemarkt-en","tag-weiterentwicklung-en","pmpro-has-access"],"acf":{"bild_mit_ki_erstellt_worden":[],"lead":"Perovskite solar cells could revolutionise photovoltaics. Their high efficiency and flexible application possibilities make them very promising. However, production hurdles are slowing market maturity. A new study by KIT shows how artificial intelligence optimises processes through machine learning and accelerates the commercialisation of this technology. ","autor":"Quelle: KIT","ort":"","bildunterschrift":"","bild_im_grid":false,"gallerie":"","newsim":""},"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t
<\/strong>The Karlsruhe Institute of Technology (KIT) is researching how machine learning can improve the manufacturing process for perovskite cells. Deep learning models analyse material properties in real time and optimise the parameters for maximum efficiency.<\/p>\n\n\n\n\n\n
<\/strong>AI uses in-situ imaging techniques to monitor thin-film formation and detect errors at an early stage. This allows process deviations to be corrected immediately and expensive rejects to be avoided.<\/p>\n\n\n\n\n\n
<\/strong>AI-supported simulations allow production conditions to be precisely adapted. The control of the vacuum quenching time in particular plays a decisive role. AI optimises this process to ensure the best possible material structure.<\/p>\n\n\n\n\n\n
<\/strong>The KIT study shows that AI is a key driver for the further development of perovskite photovoltaics. The technology could revolutionise the solar energy market and become industrially usable faster than ever with AI.<\/p>\n\n","protected":false},"excerpt":{"rendered":"