journal article·2023-03Open access

Correlation between the developed layer's color and crystallographic orientation of pure copper during long-term color etching with Beraha˗I

József Bálint Renkó, Péter János Szabó, Attila Bonyár

Abstract

In situ optical microscopy investigation was performed on a Cu99.9 copper sample during color etching with Beraha˗I etchant for approximately 48 min in a microfluidic cell. The color change of the individual grains was analyzed by measuring light intensity change for different (RGB) wavelengths. Using these values, the luminance was calculated and visualized as a function of time. Crystallographic orientations of the examined grains were also determined by electron backscatter diffraction so that the layer-developing mechanisms could have been assigned to specific directions. Our experiment showed that not only the resulting color depends heavily on the orientation, but the different grains' planar density also affects the etching characteristics. It was shown that besides the cyclic color change originating from thin film interference, a significant contribution of the developed film's color comes from the absorption properties of the layer. Relying on these characteristics, a method was proposed to differentiate grains based on their planar density. Our experiments showed that grains close to the more dense orientations, like (100) and (111) developed a bright white color and kept it during the whole etching process. In contrast, grains that were close to sparse orientations (i.e., farthest from (100) orientation), like (122) or (133) developed a dark brown color. Grains with more general directions demonstrated a similar cyclic color change as previously examined on other materials, such as ferrite in the case of low-carbon steel and cast iron.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Anodic Oxide Films and Nanostructures · Corrosion Behavior and Inhibition · Copper Interconnects and Reliability

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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