首页|New Machine Learning Study Results from Chulalongkorn University Described (Scre ening of Cu-mn-ni-zn High-entropy Alloy Catalysts for Co2 Reduction Reaction By Machine-learning-accelerated Density Functional Theory)
New Machine Learning Study Results from Chulalongkorn University Described (Scre ening of Cu-mn-ni-zn High-entropy Alloy Catalysts for Co2 Reduction Reaction By Machine-learning-accelerated Density Functional Theory)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in Machine Learning. According to news originatingfrom Bangkok, Thailand, by NewsR x correspondents, research stated, “High-entropy-alloy (HEA) catalystshave been used in many challenging electrocatalytic reactions, e.g., CO2 reduction reacti on (CO2RR) dueto their promising properties. For CO2RR catalysts, tuning metal compositions in Cu-based catalysts isone of the techniques to control the desir ed products.”
BangkokThailandAsiaCyborgsEmergi ng TechnologiesMachine LearningChulalongkorn University
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