首页|Study Data from Chinese Academy of Sciences Provide New Insights into Machine Le arning (Unveiling the Structure-surface Energy Relationship of Zeolites Through Machine Learning)
Study Data from Chinese Academy of Sciences Provide New Insights into Machine Le arning (Unveiling the Structure-surface Energy Relationship of Zeolites Through Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting from Taiyuan, People's Republic of China, by NewsRx journalists, research stated, "Understanding the intricate rela tionship between structure and surface energy is essential for a thorough compre hension of the external surface structure and crystal morphology of zeolites. In this study, we evaluated the surface energies of various zeolite surfaces acros s multiple representative frameworks with DFT calculations." Funders for this research include National Science Fund for Distinguished Young Scholars, National Key R&D Program of China, National Natural Scien ce Foundation of China (NSFC), CAS Project for Young Scientists in Basic Researc h, Key Research Program of Frontier Sciences CAS, National Natural Science Found ation of China (NSFC), Informatization Plan of the Chinese Academy of Sciences, Youth Innovation Promotion Association CAS, Beijing Advanced Innovation Center f or Materials Genome Engineering, Synfuels China Co., Ltd., Chinese Academy of Sc iences.
TaiyuanPeople's Republic of ChinaAsiaAluminum SilicatesCyborgsEmerging TechnologiesInorganic ChemicalsMach ine LearningOxidesOxygen CompoundsSilicic AcidSilicon CompoundsSilicon DioxideZeolitesChinese Academy of Sciences