**4. Discussion**

Mooring chain steel samples were exposed to artificial seawater and artificial seawater with bacteria for different durations. Different techniques were used to study the localized corrosion phenomena associated with these conditions.

PDP curve measurements show that the fresh steel surface has an average corrosion rate of 0.3 mm/y in seawater (open to air). However, the corrosion rate changes with time because of the surface condition changes over time.

In the presence of micro-organisms, OCP showed a large scatter during the first period (a few days) of exposure. This has to be attributed to irregular attachment of the organisms at the surface and formation of biofilm which disturbs the balance of electrochemical reactions. After 2 to 3 weeks all samples reached a stable value of circa −0.6 VAg/AgCl which is usually measured for this steel in seawater.

The LPR (Rp) measured (in closed vessels) was relatively stable during exposure to SW in the absence of microorganisms. In the closed system the corrosion rate measured using LPR was one third of that measured using PDP curves in an open system. The Rp value 3.6 k Ω·cm<sup>2</sup> corresponds with circa 0.1 mm/y corrosion rate for this steel in seawater, in case general corrosion is assumed. On the other hand, in the presence of microorganisms the Rp decreased over time. In all cases good reproducibility was found, but questions were raised about the meaning of the Rp in the case of local corrosion, the subject of this study. This parameter and the way to measure it is completely based on the theory of uniform corrosion. In fact, pits were found in all samples, and that means localized corrosion. The local corrosion rate cannot be established via Rp since the representative area is not clear. If only one third of the surface area is corroding, the real corrosion rate will be three times the measured average corrosion rate.

The reason for applying OCP and LPR in this investigation was that these techniques are relatively easy to perform and therefore suitable to be used for in situ monitoring. However, LPR creates errors due to the non-linearity when biofilms are present at steel surface. EIS gives not only information of polarization resistance, but also information of capacitive behaviour of the surface layers. The polarization resistance measured by EIS was approaching 3.5 k Ω·cm<sup>2</sup> in 28 days. The capacitance for the steel in the SW with bacteria was larger than in SW without bacteria, which could be attributable to a larger charged surface area in the presence of biofilm. Thus, EIS gives more information about the surface conditions, although more data fitting is needed. Next to EIS measurements, a detailed pit analysis is also required.

In all cases pits were found in the exposed steel surfaces. A distinction can be made between two different types of pits:


relatively large corrosion spots initiate from small pits and grow in depth and laterally due to high local driving forces such as local metallic inclusions. Relatively large inclusions are found in the steel (MnS and TiVCr, 5–20 μm, see Figures 18 and 19); inclusions are known to have different potentials with regard to the matrix and cause local galvanic corrosion. Therefore, it is obvious that a link exists between the inclusions found and the large pits.

The exposure of coupons without bacteria indicated the aforementioned formation of pits. The steel was fine-grain treated. It contains Al, Ti, V, Cr, Ni and Mo alloy elements, apart from Mn. The microstructure was composed of martensite and bainite. A tiny difference in local chemical difference can initiate small pits as demonstrated in Figure 11. The large pits and the underlying corrosion mechanism is attributed to the exists of inclusions. The pit size depends on the geometry and orientation of the inclusions. The inclusions were not uniformly distributed. The number of inclusions per unit area was not determined in this work. The correlation between the locations of the localized corrosion and inclusions deserves further investigation.

The important question is if the "large" pits will propagate because of MIC or other local causes such as, for example, oxygen depletion ("crevice corrosion"). In the presence of microorganisms, biofilms are formed on the surface. Biofilms can include elements which contribute to the corrosion mechanism but can also function as a barrier to oxygen. One mechanism of MIC is the oxygen differential cell formed under the biofilm which accelerates the local corrosion. Results of epi-fluorescence microscopy showed local concentrations of active organisms (near pits), which implies also local activity. Thus, it is evidence that active organisms preferentially settle in the neighbourhood of pits indicating their possible role in the corrosion process.

Concerning the mechanisms of MIC, a number of theories and models are reported, such as cathodic depolarization theory (CDT), iron sulphide mechanism, anodic depolarization, biomineralization, Romero's mechanism etc. [31]. However, Blackwood examined the CDT theory and reported that both the CDT and direct electron transfer from the metal into the cell for the role of SRB in the corrosion of carbon steel were incorrect [32]. The MIC process is so complicated that to understand the mechanism needs more effort by materials scientists, electrochemists and biologists working together [32,33].

Results of this study, in particular those of the surface investigation after exposure, prove that surface properties of the steel have an essential role in starting a local corrosion attack. The microstructure and composition heterogeneities at the matrix such as grain boundary (which will be investigated in future) and inclusions generate local corrosion cells because a small difference in composition or microstructures generates an electrochemical difference (e.g., potential difference). These local corrosion cells are likely onsets of local corrosion.
