首页|Report Summarizes Machine Learning Study Findings from State Key Laboratory of H eavy Oil Processing (Identifying Efficient and Inexpensive Hydrodesulfurization Catalysts Through Machine Learning-assisted Analysis of Metal-sulfur Bonds In .. .)
Report Summarizes Machine Learning Study Findings from State Key Laboratory of H eavy Oil Processing (Identifying Efficient and Inexpensive Hydrodesulfurization Catalysts Through Machine Learning-assisted Analysis of Metal-sulfur Bonds In .. .)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news reporting originating in Beijing, People's Rep ublic of China, by NewsRx journalists, research stated, "This paper investigates the potential of transition metal sulfides (TMSs) as hydrodesulfurization (HDS) catalysts through electronic structure and bonding analysis. The HDS mechanism focuses on breaking and regenerating metal-sulfur (M-S) bonds at sulfur vacancie s, known as active sites adhering to the Sabatier principle." Financial support for this research came from State Key Laboratory of Heavy Oil Processing Independent Innovation Project.
BeijingPeople's Republic of ChinaAsiaAnionsChalcogensCyborgsEmerging TechnologiesHydrogen SulfideMachine LearningSulfidesSulfurSulfur CompoundsState Key Laboratory of Heavy Oil Processing
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