首页|Study Findings from University of Science and Technology Beijing Broaden Understanding of Machine Learning (Knowledge-driven Ex- perimental Discovery of Ce-based Metal Oxide Composites for Se- lective Catalytic Reduction of Nox ...)
Study Findings from University of Science and Technology Beijing Broaden Understanding of Machine Learning (Knowledge-driven Ex- perimental Discovery of Ce-based Metal Oxide Composites for Se- lective Catalytic Reduction of Nox ...)
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NETL
NSTL
Amer Chemical Soc
Data detailed on Machine Learning have been presented. According to news originating from Beijing, People's Republic of China, by NewsRx correspondents, research stated, "Mining the scientific literature, combined with data-driven methods, may assist in the identification of optimized catalysts. In this paper, we employed interpretable machine learning to discover ternary metal oxides capable of selective catalytic reduction of nitrogen oxides with ammonia (NH3-SCR)." Financial supporters for this research include National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central Universities, University of Science and Technology Beijing, China Scholarship Council.
BeijingPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningUniversity of Science and Technology Beijing
NETL
NSTL
Amer Chemical Soc
