Application of MIPAR Software in the Quantitative Analysis of Corroded Surfaces

Corrosion is a common failure mechanism in steel and its structural components, often compromising their mechanical integrity and service life. One widely used method of protection is the application of functional coatings (organic, inorganic, or hybrid) that are tailored to perform specific roles under various environmental conditions. This study investigates the use of MIPAR, a powerful image analysis software, in the quantitative evaluation of corroded surfaces to assess the performance of such coatings. Composite coatings were prepared by incorporating 5 wt.% of polyaniline into a commercial alkyd-based paint and applied onto carbon steel substrates. The polyaniline emeraldine salt was synthesized following the IUPAC-recommended procedure, involving deprotonation with ammonium hydroxide and subsequent reprotonation with sulfamic, succinic, citric, and acetic acids. The base coating and four composite coatings were then exposed to a corrosive environment (3% NaCl solution), and surface degradation was monitored through digital imaging. MIPAR analysis was employed to quantify surface corrosion coverage, enabling a detailed evaluation of coating performance and corrosion progression. This approach demonstrates how digital image analysis enhances the accuracy and efficiency of corrosion studies by providing measurable, reproducible data on coating performance. The results highlight the potential of integrating digital imaging and advanced software tools like MIPAR in the development of next-generation functional coatings, including those with self-healing properties. Furthermore, future applications of MIPAR may involve leveraging its machine learning capabilities and multi-layer imaging to analyze complex coating systems, corroded and healed surfaces. This integration can significantly streamline research workflows and accelerate the discovery of more effective corrosion protection technologies.