Machine learning-derived reaction statistics for 3D spectroimaging of copper sulfidation in heterogeneous rubber/brass composites

Abstract

Abstract The sulfidation of copper derived from copper-zinc alloy (brass) in sulfur-containing rubber, used for plating steel-cord-reinforced rubber tires, is suggested to be the key reaction for the adhesive behavior between brass and rubber in tires. However, the heterogeneous structures of rubber/brass interfaces have prevented us from understanding the sulfidation of metallic copper in brass and the formation of copper sulfides at the brass surface and buried rubber interface. Here, we visualize the 3D spatial location and chemical states of copper species in a rubber/brass composite during its aging process by 3D X-ray spectroimaging with X-ray absorption fine structure-computed tomography. Machine learning-derived reaction statistics of the 3D spectroimaging data reveal the reaction mechanism of copper sulfidation in the heterogeneous rubber/brass composite.