Studies of the corrosion evaluation of SS-304 stainless steel exposed in lithium bromide aqueous solution have been carried out applying the electrochemical noise technique and polarization curves, as well as the weight loss method. The test temperatures were ambient to 80 °C, and the exposure time was during 15 days. The main objective was to determine the corrosion rates and the type of corrosion that SS-304 suffers under the mentioned conditions, with the purpose of evaluating its application to heat pumps/transformers. Polarization curves revealed the formation of a passive film, which under increased temperature changed its protective properties. The electrochemical noise results suggested that at the test temperatures the type of corrosion was mixed or pitting corrosion. The noise resistance was calculated through statistical analysis, and then, the Stern-Geary equation and Faraday law were applied to determine mass loss, which was compared to that obtained from weight loss method. Two localized corrosion indicators were also obtained: pitting index (PI) and the coefficient of variation of current (CV), which were compared each other and interrelated with the noise signals and visual observations. To support the type of corrosion process, scanning electron microscopy (SEM) coupled with energy dispersive X-ray analyzer (EDX) was used to study the surface morphology of the corroded specimens and for determining qualitative analyses.
Bibliographical noteFunding Information:
This work was supported by PROMEP program from the Education Secretary of Mexico, through the number project: UAEMOR-EXB-01with reference no. 103.5/04/1360 granted to the first author, who thanks for this enormous support. Also, thanks are given to Carlos Limon from the Electrical Research Institute for his help in the preparation of the photos and for the spot welded of 80Cr–20Ni wire to the working electrodes. The authors acknowledge the support of Guadalupe Rodríguez and Georgina Blass from the IIE, for their support in atomic absorption analysis.
- Current time series
- Electrochemical noise
- Resistance noise