首页|Findings on Machine Learning Detailed by Investigators at IMDEA Materials Instit ute (A Novel Benchmarking Approach To Assess Fire Safety of Liquid Electrolytes In Lithium-ion Batteries)
Findings on Machine Learning Detailed by Investigators at IMDEA Materials Instit ute (A Novel Benchmarking Approach To Assess Fire Safety of Liquid Electrolytes In Lithium-ion Batteries)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting from Madrid, Spain, by NewsRx jour nalists, research stated, "Establishing authoritative electrolyte safety assessm ent methods at laboratory levels is crucial for addressing conflicts from therma l runaway of lithiumion batteries. However, self-extinguishing time (SET), as t he most widely used evaluation method now, lacks benchmarks and heavily relies o n the specific implementation of test procedures." Funders for this research include China Scholarship Council, BIOFIRESAFE Project-Ministerio De Ciencia E Innovacion (MINECO), Spain.
MadridSpainEuropeCyborgsElectrol ytesEmerging TechnologiesInorganic ChemicalsMachine LearningIMDEA Materi als Institute
NETL
NSTL
