In the current aera of rapid development in the field of electric vehicles and electrochemical energy storage,solid-state battery technology is attracting much research and ***-state electrolytes,as the key component ...
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In the current aera of rapid development in the field of electric vehicles and electrochemical energy storage,solid-state battery technology is attracting much research and ***-state electrolytes,as the key component of next-generation battery technology,are favored for their high safety,high energy density,and long ***,finding high-performance solid-state electrolytes is the primary challenge for solid-state battery *** on inorganic solid-state electrolytes,this work highlights the need for ideal solid-state electrolytes to have low electronic conductivity,good thermal stability,and structural and phase *** experimental and theoretical computational methods suffer from inefficiency,thus machine learning methods become a novel path to intelligently predict material properties by analyzing a large number of inorganic structural properties and *** the gradient descent-based XGBoost algorithm,we successfully predicted the energy band structure and stability of the materials,and screened out only 194 ideal solid-state electrolyte structures from more than 6000 structures that satisfy the requirements of low electronic conductivity and stability simultaneously,which greatly accelerated the development of solid-state batteries.
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