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 ...

Insights into the high-sulphur aging of sintered silver nanoparticles: An experimental and ReaxFF study

In high power electronics packaging, sintered silver nanoparticle joints suffer from thermal-humidity- electrical-chemical joint driven corrosion in extreme environments. In this paper, we conducted aging tests on sintered silver nanoparticles under high-temperature, high-humidity, and high-sulphur conditions. The results show that: (1) the...