首页|Reports Summarize Machine Learning Findings from Hefei University of Technology (Interpretable Machine Learning for Accelerating Reverse Design and Optimizing C o2 Methanation Catalysts With High Activity At Low Temperatures)
Reports Summarize Machine Learning Findings from Hefei University of Technology (Interpretable Machine Learning for Accelerating Reverse Design and Optimizing C o2 Methanation Catalysts With High Activity At Low Temperatures)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsreporting from Hefei, People’s Republi c of China, by NewsRx journalists, research stated, “CO2 methanationrepresents a promising technological pathway for achieving efficient carbon dioxide resourc e utilizationand mitigation of greenhouse gas emissions. However, the developme nt of CO2 methanation catalystswith high activity at low temperatures (<250 degrees C) remains a formidable challenge.”
HefeiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHefei University of Technolog y
NETL
NSTL
