Micro-scale potentiodynamic polarisation (log(j)) curves of 316L stainless steel

This database comprises 5 Potentiodynamic Polarisation (PP) datasets. Each dataset consists of a pair of CSVs: 1 file containing the values of the applied potential E (Vs Ag/AgCl); and 1 containing the corresponding log of the current density log(j) (µA/cm²) values.

This database was deployed as the source dataset in the following scientific article, accepted for publication in npj Materials Degradation journal on 25 September 2023:
"Estimating pitting descriptors of 316L stainless steel by machine learning and statistical analysis".
Leonardo Bertolucci Coelho1,2,∗, Daniel Torres1, Vincent Vangrunderbeek2, Miguel Bernal1, Gian Marco Paldino3, Gianluca Bontempi3, Jon Ustarroz 1,2
1 ChemSIN – Chemistry of Surfaces, Interfaces and Nanomaterials, Université libre de Bruxelles (ULB), Brussels, Belgium
2 Research Group Electrochemical and Surface Engineering (SURF), Vrije Universiteit Brussel, Brussels, Belgium
3 Machine Learning Group (MLG), Université libre de Bruxelles (ULB), Brussels, Belgium
*[e-mail]

These datasets are almost identical to the ones available at https://data.mendeley.com/datasets/78rz8vw46x/2
The only difference is that eventual missing j values were filled with an iterative imputer (Python 3.7 language). The IterativeImputer class (from sklearn.impute) models each feature with missing values as a function of other features and uses that estimate for imputation.