Corrosion, AI and additive manufacturing: the challenges of the industry
Corrosion remains one of the major challenges to the reliability of industrial infrastructure and components, especially in a scenario where assets are aging while new materials and increasingly demanding operating conditions are emerging.
Dr. Brendy Rincón Troconis, a materials science specialist and founder of the Corrosion Research Laboratory at the University of Texas at San Antonio (UTSA), discussed in an interview with INSPENET some of the challenges that will shape the future of materials integrity, from the development of accelerated testing to the use of artificial intelligence (AI) and additive manufacturing.
Aging infrastructure versus new materials
One of the central problems for the industry is to increase the reliability and durability of materials while they work in progressively more complex and aggressive environments.
For Rincón Troconis, there is also a particularly challenging combination: much of the infrastructure continues to age at the same time as the industry incorporates different materials and technologies.
This reality necessitates understanding the mechanisms behind corrosion , rather than limiting the analysis to its consequences. This knowledge is essential for developing material integrity solutions capable of responding to real-world operating conditions.
From the laboratory to real-world service conditions
Another challenge lies in the difference between controlled experiments and what actually happens in the field.
Accelerated tests can provide valuable information, but they must reproduce the degradation mechanisms observed under real-world conditions. The specialist points out that ensuring this correspondence is one of the areas requiring special attention in corrosion research.
Closing that gap would allow for the generation of more representative data and improve the tools used to assess the integrity of materials and anticipate problems in components and infrastructure.
Artificial intelligence for proactive decisions
The growth in the capacity to collect and analyze information opens up another opportunity: integrating artificial intelligence with data obtained directly in the field.
Rincón Troconis proposes a scenario in which information can be collected on-site and analyzed with AI support to offer alternatives that facilitate proactive decision-making.
The goal is to provide organizations with tools capable of transforming corrosion data into timely and useful information. This could help them make decisions before degradation processes progress to more serious consequences.
Additive manufacturing and layered engineered materials
Additive manufacturing introduces particularly interesting possibilities for component design. This technology allows for the fabrication of complex structures and the adaptation of a material's properties to specific needs.
One application proposed by the researcher involves developing functionally graded materials. Through layer-by-layer fabrication , one surface could be optimized for a specific corrosive environment, while the interior of the component is designed to provide mechanical strength, and another area is adapted to different environmental conditions.
However, additive manufacturing also generates heterogeneities and new degradation pathways. Therefore, harnessing its potential requires understanding the relationship between processing, microstructure , performance, and material integrity.
New generations facing the challenge of corrosion
The training of specialists will be equally crucial. Rincón Troconis points out that young researchers are combining materials science, electrochemistry, data science and advanced characterization techniques to study complex corrosion problems.
His career also reflects this multidisciplinary vision, from his early research on corrosion rates at the General Rafael Urdaneta Bridge in Lake Maracaibo, to later work on microbiologically induced corrosion , atmospheric corrosion, galvanic coupling, coatings and environmentally assisted cracking, his career has progressively broadened the scope of this research.
At UTSA, this journey also resulted in the development of infrastructure, academic training, and educational activities aimed at bringing the science of corrosion closer to students of different ages.
The convergence of research, AI, additive manufacturing, and specialized training thus points to a new stage for material integrity: a better understanding of how materials degrade in order to intervene earlier, design them with greater precision, and increase the reliability of the systems that support modern infrastructure.