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Estimating pitting descriptors of 316 L stainless steel by machine learning and statistical analysis - npj Materials Degradation
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A hybrid rule-based/ML approach using linear regression and artificial neural networks (ANNs) determined pitting corrosion descriptors from high-throughput data obtained with Scanning Electrochemical Cell Microscopy (SECCM) on 316 L stainless steel. Non-parametric density estimation determined the central tendencies of the Epit/log(jpit) and Epass/log(jpass) distributions.
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