Detection and analysis of microbiologically influenced corrosion of 316 L stainless steel with electrochemical noise technique

• Shot noise parameters, fn and q were found to detect the MIC at an early stage.
• Probabilistic failure model for MIC was predicted using Weibull distribution.
• RN may not be a proper indicator to detect the MIC.

Microbiologically Influenced Corrosion (MIC) is a specific type of corrosion caused or promoted by microorganisms usually chemoautotrophs. In recent years, there has been growing interest in the exploitation of electrochemical noise technique to investigate and monitor biocorrosion. The advantages of Electrochemical Noise (EN) technique includes the possibility to detect and study the early stages of localized corrosion; however the comprehension of EN signals still remains very limited. In the present work an attempt has been made to analyze the current and potential noise records for type 316 L stainless steel (SS) specimen immersed in Iron oxidizing bacteria inoculated medium amended with different concentrations of NaCl. All the potential and current noise data collected in the time domain were transformed in the frequency domain, using MATLAB software. Shot noise parameters like frequency of corrosion events (fn), average charge in each event (q), true coefficient of variation and noise resistance (RN) were analyzed. Low frequency events and high charge were observed for the specimen after the exposure of 3 weeks in microbial medium with 1% NaCl when compared to control. It indicates that microbes can influence the pitting corrosion over the specimen which was also evidenced by Scanning Electron Microscope (SEM). In addition to this, the probabilistic failure model for MIC on 316 L SS was predicted using Weibull distribution.