Studies from Los Alamos National Laboratory Further Understanding of Machine Lea rning (Machine Learning-guided Design, Synthesis, and Characterization of Atomic ally Dispersed Electrocatalysts)
Los Alamos国家实验室的研究进一步理解机器学习（以机器学习为导向的原子分散电催化剂的设计、合成和表征）
Studies from Los Alamos National Laboratory Further Understanding of Machine Lea rning (Machine Learning-guided Design, Synthesis, and Characterization of Atomic ally Dispersed Electrocatalysts)
Los Alamos国家实验室的研究进一步理解机器学习（以机器学习为导向的原子分散电催化剂的设计、合成和表征）
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news originatingfrom Los Alamos, New Mexico, by N ewsRx correspondents, research stated, “The recent integrationof machine learni ng into materials design has revolutionized the understanding of structure-prope rtyrelationships and optimization of material properties beyond the trial-and-e rror paradigm. On one hand,machine learning has significantly accelerated the d evelopment of atomically dispersed metal-nitrogencarbon(M-N-C) electrocatalyst s, which traditionally heavily relied on heuristic approaches.”
Key words
Los Alamos/New Mexico/United States/N orth and Central America/Cyborgs/Emerging Technologies/Machine Learning/Los Alamos National Laboratory
NETL
NSTL