Robotics & Machine Learning Daily News2024,Issue(Dec.6) :156-157.

Recent Findings from Henan University Provides New Insights into Machine Learnin g (Machine Learning Quantification of Grain Boundary Defects for High Efficiency Perovskite Solar Cells)

河南大学最近的研究成果为机器学习(高效钙钛矿太阳能电池晶界缺陷的机器学习量化)提供了新的见解

Robotics & Machine Learning Daily News2024,Issue(Dec.6) :156-157.

Recent Findings from Henan University Provides New Insights into Machine Learnin g (Machine Learning Quantification of Grain Boundary Defects for High Efficiency Perovskite Solar Cells)

河南大学最近的研究成果为机器学习(高效钙钛矿太阳能电池晶界缺陷的机器学习量化)提供了新的见解

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。根据消息来源来自中华人民共和国河南,由NewsRx记者报道,研究称,“权力”钙钛矿型太阳能电池的转换效率近年来有了显著提高。在e处导致这种变化的关键因素是pe罗纹石层及其邻近层的显微结构层可以控制。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news originatingfrom Henan, People’s Republic of China, by NewsRx correspondents, research stated, “The powerconversion efficien cy of perovskite solar cells has been significantly improved in recent years. On e of thekey factors leading to this change is that the microstructure of the pe rovskite layer and its neighboringlayers can be controlled.”

Key words

Henan/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Henan University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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