Boeing is advancing a new approach to addressing aircraft corrosion through the application of quantum computing, targeting one of the most persistent and costly challenges in aerospace materials performance.

Aircraft corrosion remains a significant issue, with global costs estimated at $2.5 trillion annually. Improving how corrosion is modeled and predicted could enhance material durability, reduce safety risks and lower lifecycle costs across aerospace and related industries.

The company has been awarded $2.5 million to support its QUantum Innovation for Corrosion Kinetics (QUICK) project, which aims to optimize the full quantum computational stack, from applications to algorithms, while developing a hybrid quantum-classical workflow tailored to corrosion use cases.

The funding follows Boeing’s selection for the Advanced Research Projects Agency-Energy Quantum Computing for Computational Chemistry (QC3) program. The initiative is part of the U.S. Department of Energy and focuses on applying quantum algorithms to chemistry and materials problems that remain beyond the reach of classical computing systems.

QC3 is allocating $37 million across 10 projects centered on quantum-enabled solutions for chemistry and materials challenges. Boeing is the only aerospace company selected for funding under the program.

“We are excited to be part of QC3 and continue leading with anchored demonstrations to prove today’s capability and chart the path to scale for real-world impact,” said Jay Lowell, chief scientist for Boeing Disruptive Computing, Networks & Sensors.

The QUICK project focuses on demonstrating how next-generation quantum systems can outperform conventional computing approaches, including running corrosion-related simulations on quantum hardware.

Program goals include achieving performance improvements of up to 100x compared to current classical methods, with a focus on enabling transformative impact in materials and energy applications.

For Boeing, these advances could accelerate the discovery of corrosion-resistant materials and shorten development cycles for components used across aerospace and other industries. More accurate and faster corrosion modeling also has implications for coatings development, surface protection strategies and long-term asset performance.

The project will move into implementation and testing phases, with quantum algorithms deployed on hardware as required by the QC3 program. The broader objective is to enable faster and more precise corrosion modeling, with potential benefits spanning safety, durability and cost efficiency.

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