Fig. 2: The feature engineering result. | Nature Communications

Fig. 2: The feature engineering result.

From: Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning

Fig. 2

a For the charging process, 15 features are extracted from the voltage-capacity (left) and dQ/dV curve (right). b The same set of features are for the discharging process as F16 to F30. c Features are visualized by classes, following the format CxBn, indicating the nth battery from class x. The size of a circle maps the absolute feature value. Source data are provided as a Source Data file.

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