首页|New Findings on Machine Learning from Northwestern Polytechnic University Summar ized (Machine-learning-assisted Design of Buried-interface Engineering Materials for High-efficiency and Stable Perovskite Solar Cells)
New Findings on Machine Learning from Northwestern Polytechnic University Summar ized (Machine-learning-assisted Design of Buried-interface Engineering Materials for High-efficiency and Stable Perovskite Solar Cells)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingfrom Xi’an, People’s Republic of Chi na, by NewsRx journalists, research stated, “Buried-interface engineeringis cru cial to the performance of perovskite solar cells. Self-assembled monolayers and buffer layersat the buried interface can optimize charge transfer and reduce r ecombination losses.”Funders for this research include National Natural Science Foundation of China ( NSFC), NationalNatural Science Foundation of China (NSFC).
Xi’anPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesEngineeringMachine LearningNorthwestern Pol ytechnic University
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