首页|Studies from Chinese Academy of Sciences in the Area of Machine Learning Described (Machine learning insights into catalyst composition and structural effects on CH4 selectivity in iron-based fischer tropsch synthesis)
Studies from Chinese Academy of Sciences in the Area of Machine Learning Described (Machine learning insights into catalyst composition and structural effects on CH4 selectivity in iron-based fischer tropsch synthesis)
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 Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news originating from Taiyuan, Pe ople’s Republic of China, by NewsRx correspondents, research stated, “Fe-based F ischer-Tropsch Synthesis (FTS) enables the selective conversion of syngas intolong-chain hydrocarbons, which can be further refined to produce highly demanded liquid fuels and high-value chemical products.”
Chinese Academy of SciencesTaiyuanPeople’s Republic of ChinaAsiaAlkanesCyborgsEmerging TechnologiesMachine LearningMethane
NETL
NSTL
