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The electrochemical behavior for different surface conditions and different degrees of deformation of metastable austenitic stainless steel AISI 304 UNS S30400 were studied using critical pitting potential and electrochemical noise measurements. The influence on corrosion resistance by using different abrasives (silicon carbide and corundum) for surface finish by grinding is illustrated. For the characterization of local defects and surface topography, scanning electron microscopy (SEM) and tactile measurements were used. An inverse correlation between occurrence of local defects on the surface and critical pitting potential was found by using image processing. Therefore, gray scale values of different surfaces were compared. The influence of mass content of α'-martensite on the corrosion resistance is shown by comparing different qualities of surface finish. For smooth machined surfaces it can be shown that an increasing numbers of strain induced martensite is decreasing the corrosion resistance lightly. For low abrasive machining an inverse correlation between the critical pitting potential and surface roughness is given. However, for higher abrasive machining parameters, this correlation could not be found.
The project aims for the development of a new material system from high tensile stainless steel wires as net material with environmentally compatible antifouling properties for off-shore fish farm cages. Therefore, current net materials from textiles (polyamide) shall be partially replaced by high strength stainless steel in order to have a more environmentally compatible system which meets the more severe mechanical loads (waves, storms, predators (sharks)). With a new antifouling strategy current issues like reduced ecological damage (e.g. due to copper disposal), lower maintenance costs (e.g. cleaning) and reduced durability shall be resolved.
The corrosion resistance of stainless steels is massively influenced by the condition of their surface. The surface quality includes the topography of the surface, the structure and composition of the passive layer, and the surface near structure of the base material. These factors are influenced by final physical/chemical surface treatments. The presented work shows significantly lower corrosion resistance for mechanical machined specimens than for etched specimens. It also turns out that the rougher the surface, the lower the corrosion resistance gets. However, there is no general finding which shows if blasted or grinded surfaces are more appropriate, but a dependency on process parameters and the characteristics on corrosive exposure in terms of corrosion behavior. The results show that not only the surface roughness Ra has an influence on corrosion behavior but also the shape of peaks and valleys which are evolved by surface treatments. Imperfections in the base material, like sulfidic inclusions lead to a weaker passive layer, respectively, to a decrease of the corrosion resistance. By using special passivating techniques the corrosion resistance of stainless steels can be increased to a higher level in comparison to common passivation.
This paper presents the current state of development and selected technological challenges in the application of ecologically and economically sustainable nets for aquaculture based on ongoing development projects. These aim at the development of a new material system of high-strength stainless steel wires as net material with environmentally compatible antifouling properties for nearshore and offshore aquacultures. Current plastic netting materials will be replaced with high-strength stainless steel to provide a more environmentally friendly system that can withstand more severe mechanical stresses (waves, storms, tides and predators). A new antifouling strategy is expected to solve current challenges, such as ecological damage (e.g., due to pollution from copper-containing antifouling substances or microplastics), high maintenance costs (e.g., cleaning and repairs), and shorter service life. Approaches for the next development steps are presented based on previous experience as well as calculation models based on this experience.