首页|ShanghaiTech University Reports Findings in Machine Learning (Machine Learning on Microstructure-Property Relationship of Lithium-Ion Conducting Oxide Solid Ele ctrolytes)
ShanghaiTech University Reports Findings in Machine Learning (Machine Learning on Microstructure-Property Relationship of Lithium-Ion Conducting Oxide Solid Ele ctrolytes)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsoriginating from Shanghai, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Understandingthe st ructure-property relationship of lithium-ion conducting solid oxide electrolytes is essentialto accelerate their development and commercialization. However, th e structural complexity of nonidealmaterials increases the difficulty of study. ”Our news journalists obtained a quote from the research from ShanghaiTech Univer sity, “Here, wedevelop an algorithmic framework to understand the effect of mic rostructure on the properties by linkingthe microscopic morphology images to th eir ionic conductivities. We adopt garnet and perovskite polycrystallineoxides as examples and quantify the microscopic morphologies via extracting determined physicalparameters from the images. It directly visualizes the effect of physic al parameters on their correspondingionic conductivities. As a result, we can d etermine the microstructural features of a Li-ion conductor withhigh ionic cond uctivity, which can guide the synthesis of highly conductive solid electrolytes.”
ShanghaiPeople’s Republic of ChinaAsiaCyborgsElectrolytesEmerging TechnologiesInorganic ChemicalsMachine Learning
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