首页|New Machine Learning Study Results from University of JinanDescribed (Elevating Perovskite Efficiency Via Machine Learningassisted Screening of Passivators)
New Machine Learning Study Results from University of JinanDescribed (Elevating Perovskite Efficiency Via Machine Learningassisted Screening of Passivators)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news reportingoriginating from Guangzhou, People ’s Republic of China, by NewsRx correspondents, research stated,“The swift iden tification of effective passivation materials for MAPbI3-based perovskite solar cells (PSCs)remains a formidable challenge, we employ the power of machine lear ning to discern the complex correlationbetween the molecular characteristics of passivation materials and the power conversion efficiency (PCE)of PSCs. Our re sults show that molecular characteristics such as complexity, molecular weight, O atoms,and hydrogen bond receptors are associated with PCE in MAPbI3-based PSC s.”
GuangzhouPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningUniversity of Jinan
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