Predicting the parabolic growth rate constant for high-temperature oxidation of steels using machine learning models

The parabolic growth rate constant (k_p) of high-temperature oxidation of steels is predicted via a data analytics approach. Four machine learning models including Artificial Neural Networks, Random Forest, k-Nearest Neighbors, and Support Vector Regression are trained to establish the relations between the input features ...

Simplistic correlations between molecular electronic properties and inhibition efficiencies: Do they really exist?

The often used simplistic correlations between molecular electronic parameters and experimentally determined corrosion inhibition efficiencies are critically evaluated for a set of 24 heterocyclic organic compounds, tested as corrosion inhibitors for copper in 3 wt.% NaCl aqueous solution. Twelve different molecular electronic descriptors...