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Eco-friendly corrosion protective coatings based on smart nanotechnology platforms for a circular economy

Periodic Reporting for period 2 - COAT4LIFE (Eco-friendly corrosion protective coatings based on smart nanotechnology platforms for a circular economy)

Período documentado: 2023-05-01 hasta 2025-04-30

The Circular Industrial Economy (CIE) focuses on managing stocks of manufactured assets—such as infrastructure, buildings, vehicles, equipment, and consumer goods—to preserve their value and utility at the highest possible level for the longest possible time. It also aims to maintain resource stocks at their highest purity and value.

The primary objective of the COAT4LIFE project was to develop innovative anticorrosion and corrosion-sensing platforms in the form of multifunctional coatings. These were designed to detect and prevent corrosion in metallic structures used in high-performance sectors—particularly aeronautics and offshore—while adhering to sustainable and eco-friendly principles throughout their life cycle. In doing so, COAT4LIFE contributed to extending the service life of metallic structures and infrastructures across various applications, through the development of novel materials and components. This aligns closely with key R&D innovation areas associated with the CIE and the United Nations 2030 Agenda for Sustainable Development.

COAT4LIFE’s main goals were achieved through the following technical objectives:

Integration of emerging corrosion-sensing technologies (TRL 3–4) with advanced anticorrosion nanoadditive systems based on controlled chemical release (TRL >5);
Application of machine learning techniques to identify optimal corrosion inhibitors for specific use cases;
Modeling and correlating substrate degradation with sensor signal outputs;
Formulation and optimization of coatings and pre-treatments, followed by scale-up of the most promising technologies;
Environmental assessment of coating components.
Additional objectives aligned with the scope of the call were also successfully met, including: 6. Staff exchange and knowledge transfer between research institutions and industry;

Training and mobility of researchers;
Development of innovation-oriented and entrepreneurial skills among seconded staff.
Key outcomes of the project include the development of several coating formulations that combine corrosion detection with active protection additives, tailored for aluminum, magnesium, and steel substrates. The most promising formulations were scaled up, validated, and assessed for environmental impact and life cycle analysis (LCA). Furthermore, machine learning models were created to support the development of anticorrosion additives, and analytical and numerical methods were employed to model coating degradation.

In terms of staff exchange, 56 individuals from both academia and industry—including early-stage and experienced researchers—participated in over 124 person-months of secondments. This significantly contributed to effective knowledge transfer among partners and the successful realization of the project’s objectives.
Within WP2 – Functional Nanoadditives, various compositions of layered double hydroxides (LDHs) based on Zn-Al and Mg-Al intercalated with nitrates were synthesized by SMT and characterized by UAVR. Additionally, LDHs intercalated with corrosion detection species were successfully prepared by UAVR. Magnetic nanoparticles (MNPs) based on iron oxides were also synthesized and characterized by UAVR.

In WP3 – Surface Pre-treatment and Characterization, procedures for the surface pre-treatment of metal alloys intended for subsequent coating applications were developed by HEREON and UAVR. Sol-gel formulations incorporating polyhedral oligomeric silsesquioxanes (POSS) and/or organosilanes were also developed. LDH-based corrosion inhibitors and sensing additives were integrated into these formulations. Sol-gel layers were applied to both aluminum alloys and steel (SMT/SINTEF), and electrochemical assessments were conducted (SMT/UT/TLB).

Under WP4 – Coating Development, extensive studies on the dispersion of SiNCs, LDHs, and MNPs were carried out through collaboration between academic partners (UAVR, HEREON) and industrial partners (SYNPO, COL). The stability of two polymeric systems in saltwater environments was evaluated. Coating/inhibitor/indicator combinations were tested for corrosion protection on AA2024, AZ31 magnesium alloy, and steel substrates.

In WP5 – Modelling of Structures with Corrosion-Protective Coatings, a predictive machine learning (ML) model for evaluating the performance of anticorrosion additives was developed (UAVR, HZG/HEREON). A comprehensive experimental database of tested chemicals was compiled, and an ML model based on artificial neural networks was implemented. Mechanical properties of coatings and substrate systems were assessed (LU, KTU, SYNPO, COL), and degradation modeling under freshwater and seawater conditions was performed using both analytical and finite element methods.

For WP6 – Environmental Behavior, Toxicity, and Life-Cycle Assessment, synthesis procedures for engineered nanomaterials (WP2) and coating preparation (WP4) were developed following safe-by-design principles. Environmental risks associated with the materials and compounds used in coating production were systematically analyzed as part of an eco-conscious design strategy. Life cycle assessments (LCA) were conducted for three different coatings (UAVR).

In WP7 – Upscaling and Demonstration, the most promising additives and coating components were scaled up (SMT, SYNPO, COL) and made available for further testing. Various coating formulations were developed by combining these components and applied to different substrates for validation (COL, SYNPO). The new coatings demonstrated improved performance compared to existing materials.

Within WP8 – Dissemination and Exploitation, the project resulted in 12 peer-reviewed scientific publications and one MSc thesis. Findings were presented at over 30 international conferences. Several coating formulations showed strong potential for commercialization. The next steps include co-development of enhanced coatings among partners and implementation of a market entry strategy outlined in the final exploitation plan.
The project achieved significant progress beyond the state of the art by developing novel coating systems with integrated corrosion sensing functionalities, evaluating the ecotoxicity of newly synthesized nanomaterials, and applying Machine Learning to optimize corrosion inhibitor selection for advanced anti-corrosion coatings. These innovations have been disseminated through 12 scientific publications and 36 international conferences.

It also played a key role in training young researchers and company staff in interdisciplinary, cutting-edge research areas, fostering the development of more durable and environmentally friendly multifunctional coatings and accelerating the societal uptake of new technologies.

The project strengthened collaboration among partners, leading to participation in new European initiatives such as SURE2COAT (GA ID: 101091982), VIPCOAT (GA ID: 952903), MIRACLES (GA ID: 101182521), and SAFERCOAT (GA ID: 101182588).

Finally, the two SME partners benefited significantly from the staff exchange scheme, advancing their technologies and strengthening collaboration with larger industrial players for future product co-development. Conversely, the two large companies involved in the project gained access to innovative technologies that are expected to contribute to a new generation of products—more durable, environmentally friendly, and aligned with sustainability goals.
Machine Learning for design of corrosion inhibitors
Fate, behaviour, ecotoxicity and life cycle assessment in COAT4LIFE
Ecotoxicity Results in COAT4LIFE
Mechanisms of magnetic sensing coatings
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