首页|Data on Machine Learning Described by Researchers at Shanghai University (Discovery and verification of two-dimensional organic- inorganic hybrid perovskites via diagrammatic machine learning model)
Data on Machine Learning Described by Researchers at Shanghai University (Discovery and verification of two-dimensional organic- inorganic hybrid perovskites via diagrammatic machine learning model)
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Elsevier
2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artificial intelligence. According to news reporting out of Shanghai, People’s Republic of China, by NewsRx editors, research stated, “Two-dimensional (2D) organic-inorganic hybrid perovskites (OIHPs) have drawn increased attention due to rich physical properties such as ferroelectricity and photovoltaic properties.” The news journalists obtained a quote from the research from Shanghai University: “Nevertheless, it is challenging to discover novel 2D OIHPs within the vast chemical composition space. Herein, a diagrammatic machine learning model was employed to improve this issue. We collected 179 OIHPs with a variety of organic cations and screened out 6 features from 10,622 descriptors. Subsequently, a decision tree model was created to predict the dimensionality of OIHPs, achieving a LOOCV accuracy of 0.94 and a test accuracy of 0.89, respectively. Then, one candidate from a virtual space with 8256 samples was successfully synthesized, which was consistent with the prediction of the model. Finally, three rules were produced by visualization of the tree structure to generally discriminate 2D from non-2D OIHPs.”
Shanghai UniversityShanghaiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
Elsevier
