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Machine learning models offer improved accuracy over traditional empirical relations for predicting corrosion rates and identifying corrosion types, though achieving generalizability across new electrochemical regimes requires hybrid approaches that incorporate physics-informed parameters. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

Machine learning in corrosion electrochemistry: A critical review of prediction and corrosion-type identification

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