Composition and state prediction of lithium-ion cathode via convolutional neural network trained on scanning electron microscopy images - Oh, Jimin; Yeom, Jiwon; Madika, Benediktus; Kim, Kwang Man; Liow, Chi Hao; Agar, Joshua C.; Hong, Seungbum (npj computational materials, 2024)
Keywords: 639/301/1034/1037; 639/301/299/891; Accuracy; Additives; Algorithms; Artificial intelligence; Artificial neural networks; Cathodes; Characterization and Evaluation of Materials; Chemistry and Materials Science; Composition; Computational Intelligence; Electric vehicles; Electrode materials; Electrodes; Electrolytes; Energy storage; Fourier transforms; Lithium; Lithium-ion batteries; Machine learning; Materials Science; Mathematical and Computational Engineering; Mathematical and Computational Physics; Mathematical Modeling and Industrial Mathematics; Mathematical models; Morphology; Neural networks; Prediction models; Rechargeable batteries; Scanning electron microscopy; Spectrum analysis; Subject specialists; Theoretical