首页|New Findings in Machine Learning Described from Southern University of Science a nd Technology (SUSTech) (Optimization of Porous Structures Via Machine Learning for Solar Thermochemical Fuel Production)
New Findings in Machine Learning Described from Southern University of Science a nd Technology (SUSTech) (Optimization of Porous Structures Via Machine Learning for Solar Thermochemical Fuel Production)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According tonews originating from Shenzhen, People’s R epublic of China, by NewsRx correspondents, research stated,“Porous reactant is the key component in solar thermochemical reactions, significantly affecting th e solarenergy conversion and fuel production performance. Triply periodic minim al surface (TPMS) structures,with analytical expressions and predictable struct ure-property relationships, can facilitate the design andoptimization of such s tructures.”
ShenzhenPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningSouthern University of Sci ence and Technology (SUSTech)
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