Durability and Corrosion

Sustainability is defined as meeting present needs without compromising future generations' ability to meet their own needs. Its principles focus on reducing wastefulness, enhancing the quality of processes and products, and implementing efficient systems inspired by natural ecosystems. During the last decade, sustainability has become an emergent critical focus within the field of engineering, driven by the need to reduce environmental impact, optimize resource use, and develop durable, efficient systems across various industries. A sustainable material is defined as one that minimizes its environmental impact throughout its life cycle, from raw material extraction to processing, usage, and eventual recycling or disposal. Such materials are characterized by their durability, resource efficiency, recyclability, and the ability to reduce waste and greenhouse gas emissions. They play an important role in addressing environmental challenges, particularly in sectors such as construction, transportation, and energy, where resource consumption and emissions are significant concerns.

The intersection of corrosion science and sustainability is increasingly important as the global demand for metals and engineered materials continues to rise. Corrosion directly impacts the durability of these materials by reducing their lifespan, necessitating frequent replacements that involve further energy-intensive mining and production processes. In fact, corrosion plays a significant role in sustainability as it leads to the depletion of natural resources and increases carbon emissions. When materials corrode, the energy invested in their extraction, processing, and manufacturing is wasted, resulting in substantial financial losses and harmful environmental impacts. Developing advanced corrosion control techniques and more durable materials is essential for achieving sustainability goals. Adopting circular economy principles, such as the "reduce-reuse-recycle" framework, further enhances these efforts by promoting recycling and extending the lifespan of materials.

For a deeper understanding of the sustainability challenges related to corrosion, see "Challenges for the Corrosion Science, Engineering, and Technology Community as a Consequence of Growing Demand and Consumption of Materials: A Sustainability Issue" by Ingrid Milošev and John R. Scully, two of the best corrosion scientists. Their work explores the broader implications of material consumption, corrosion management, and sustainability-driven innovations [1].

Corrosion affects a wide range of metallic materials, from structural carbon steels to high-performance alloys such as stainless steels, titanium alloys, and superalloys. Even these expensive and corrosion-resistant materials are susceptible to degradation under certain environmental conditions. Moreover, industries that require complex and customized metallic components, particularly those adopting sustainable additive manufacturing (AM), must account for corrosion concerns to ensure the long-term durability of printed parts. Additionally, photovoltaic (PV) modules, widely considered a sustainable energy resource, are also prone to corrosion-related degradation, especially flexible solar panels used in marine environments, where exposure to saltwater accelerates material deterioration.

Hence, the control of corrosion is very important. Different practices can be used for corrosion control, including corrosion examination, corrosion protection, and corrosion prediction, which are elaborated in the subsequent subsections.

Electrochemical techniques, such as potentiodynamic polarization and electrochemical impedance spectroscopy (EIS), are widely used for assessing corrosion behavior. These methods provide insights into corrosion kinetics, passive film stability, and electrochemical reactions at the metal surface. Accelerated tests, including salt spray and cyclic exposure corrosion testing, simulate harsh environments to predict material durability.  For comparing the corrosion resistance of metallic components, including additively manufactured (AM) parts, potentiodynamic polarization and EIS are commonly used. In contrast, for photovoltaic (PV) modules, cyclic salt spray tests are widely applied to evaluate their durability in corrosive environments. There are well-established standards for each of these assessments, depending on the purpose, sample type, and environmental conditions.

• Potentiodynamic Polarization – Most well-known standards: ASTM G5, ASTM G61, ASTM G59
• Photovoltaic Modules – Relevant standards: IEC 61701, IEC 60068-2-52

Corrosion protection methods are essential for extending the lifespan of metallic materials by reducing their susceptibility to environmental degradation. Different approaches are used depending on the material, environment, and application. Below are some common corrosion protection strategies.

• Cathodic Protection: This technique prevents corrosion by making the metal surface a cathode in an electrochemical cell. It is commonly applied in underground pipelines, marine structures, and storage tanks using sacrificial anodes (galvanic protection) or impressed current systems.
• Anodic Protection: This method applies a small anodic current to maintain the metal in a passive state, reducing corrosion rates significantly. It is primarily used for highly corrosion-resistant metals like stainless steel in aggressive environments such as chemical processing industries.
• Organic Coatings: Epoxy-based coatings act as a barrier layer to prevent moisture, oxygen, and corrosive ions from reaching the metal surface. They are widely used in marine, automotive, and industrial applications due to their excellent adhesion and chemical resistance.
• Anodization: Anodization is an electrochemical process that enhances the corrosion resistance, surface hardness, and wear resistance of metals by forming a controlled oxide layer. It is particularly effective for aluminum and titanium, making it a widely used method for aerospace, biomedical, and industrial applications. For titanium, anodization not only improves corrosion protection but also allows for color customization and enhanced biocompatibility, making it valuable for medical implants and aerospace components. The thickness and properties of the anodized layer can be tailored by adjusting the electrolyte composition, voltage, and process duration, ensuring optimized performance for specific applications.

Corrosion prediction is crucial for assessing material longevity and preventing unexpected failures in various industries. Advanced simulation methods, such as those using COMSOL Multiphysics, enable the modeling of corrosion processes by solving electrochemical and mass transport equations, allowing for the prediction of corrosion rates, localized attack, and environmental effects on different materials. Additionally, machine learning (ML) is emerging as a powerful tool for corrosion prediction by analyzing large datasets from experimental and field studies to identify patterns and forecast corrosion behavior under varying conditions. ML models can integrate real-time sensor data, environmental parameters, and material properties to improve accuracy in corrosion risk assessment, offering a more data-driven and proactive approach to corrosion management.

The following research examples focus on corrosion studies that address sustainability and material durability challenges.

Titanium alloys are known for their corrosion resistance; however, they remain susceptible to localized corrosion in harsh environments. This study evaluated the corrosion properties of additively manufactured (AM) titanium parts, which are rarely used in their as-built condition due to their high surface roughness. Most AM parts require surface treatments to enhance performance, and electropolishing is among the most effective options, particularly for complex and inaccessible geometries that cannot be treated with mechanical methods.  However, conventional electrochemical and chemical treatments for titanium alloys commonly rely on hydrofluoric acid, which poses significant environmental and safety concerns. This research explored an ethylene glycol-based electrolyte as a more eco-friendly alternative. Additionally, the treatment conditions were optimized by incorporating an anodization step to further improve surface roughness and corrosion resistance. This study has been published as an open-access article and provides a reference for selecting sustainable treatment methods that enhance the corrosion resistance of AM titanium alloy surfaces.

Although some non-destructive methods exist for corrosion examination, most conventional techniques are destructive, time-consuming, and require manual analysis. However, numerous valuable databases contain corrosion behavior parameters for specific environments and exposure conditions. By employing machine learning (ML) techniques, these databases can be used for training models to predict corrosion behavior in different conditions and materials, reducing the need for additional testing and resource consumption.  These researchs specifically utilized a steel manufacturer's database, which contains corrosion behavior data for various steels in acidic and basic environments. By training ML models on this dataset, the corrosion behavior of stainless steels was predicted with over 90% accuracy. Furthermore, the proposed model was generalized to work even when detailed information about the exposed environment or exact elemental composition of stainless steel was unavailable. The study found that even with basic inputs, such as hydrogen and sulfide concentrations in the corrosive environment and the sum of alloying elements, up to 77.8% of corrosion behavior could be accurately predicted.  The code and dataset related to these works are publicly available on GitHub for further research and application.