首页|Researchers at Harbin University Have Reported New Data on Machine Learning (Pre diction, Interpretation and Extrapolation for Shear Modulus and Bulk Modulus of Solid-state Electrolytes Based On Machine Learning)
Researchers at Harbin University Have Reported New Data on Machine Learning (Pre diction, Interpretation and Extrapolation for Shear Modulus and Bulk Modulus of Solid-state Electrolytes Based On Machine Learning)
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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 from Heilongjiang, Peopl e's Republic of China, by NewsRx correspondents, research stated, “The dendrite growth is a major challenge in the metal battery applications, and solid-state e lectrolytes (SSEs) have a better dendrite suppression ability than liquid electr olytes. The shear modulus (G) and bulk modulus (K) are important indicators to m easure the suppression ability of SSEs.”
HeilongjiangPeople's Republic of ChinaAsiaCyborgsElectrolytesEmerging TechnologiesInorganic ChemicalsMachi ne LearningHarbin University
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