首页|Reports from University of Science and Technology China Provide New Insights into Machine Learning (A Comprehensive Pyrolysis Study of Sorghum and Reed Stalk: Tg/ir/ms Analysis and Machine Learning-assisted Kinetic Prediction)
Reports from University of Science and Technology China Provide New Insights into Machine Learning (A Comprehensive Pyrolysis Study of Sorghum and Reed Stalk: Tg/ir/ms Analysis and Machine Learning-assisted Kinetic Prediction)
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 – A new study on Machine Learning is now available. According to news reportingfrom Hefei, People’s Republic of China, by NewsRx journalists, research stated, “This work focused oninvestigating the pyrolysis characteristics of sorghum stalk (SS) and reed stalk (RS), whose potentialityas value-added feedstocks for thermochemical conversion is largely unexplored. The experimental method,thermogravimetric-infrared-mass spectrometry, was applied to reveal the thermal decomposition process,evaluate the kinetic and thermodynamic parameters, and identify the gaseous products, which could providefundamental data and valuable information for bioenergy utilization and optimization of reactors.”
HefeiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningUniversity of Science and Technology China
NETL
NSTL
