Boeing, a leading global aerospace company, partnered with IBM Quantum to explore how quantum computing could address two critical aerospace engineering challenges: the design of advanced composite materials and the prevention of metal corrosion. This collaboration leveraged IBM’s quantum computing expertise and Boeing’s deep aerospace industry knowledge to develop innovative approaches that could potentially transform aircraft design and manufacturing.

The Aerospace Engineering Challenges

Boeing faced two significant engineering challenges that traditional computing methods struggled to address efficiently:

Ply Composite Design Optimization
Aircraft manufacturers like Boeing use advanced materials known as ply composites to create lightweight, safe, and strong components for aircraft like the 787 Dreamliner. These composites consist of thousands of individual plies—long strands of strong material layered across one another like fabric. Each strand is strong in one direction, and building a component with the right properties requires careful arrangement of each strand at precisely the right angle . IBM
For a large aircraft component, these design decisions can involve up to 100,000 variables, creating an optimization problem of enormous complexity. Traditional computing approaches cannot solve such problems all at once, forcing engineers to break them into smaller pieces, which leads to suboptimal designs and longer development cycles . IBMIBM
Metal Corrosion Prevention
Corrosion represents a persistent challenge for the aerospace industry, affecting the longevity, safety, and maintenance costs of aircraft. Metal components exposed to humidity and environmental factors develop thin water films on their surfaces, initiating chemical reactions that lead to corrosion . HPCwire
Understanding and preventing these reactions requires modeling complex quantum-scale interactions between water molecules and metal surfaces—a task that classical computing methods can only approximate with significant limitations. More precise simulations could lead to the development of better corrosion-resistant materials and protective coatings . IBMIotworldtoday

Quantum Solutions

The IBM-Boeing partnership developed two distinct quantum computing approaches to address these aerospace engineering challenges:

Quantum Optimization for Ply Composite Design
For the ply composite design problem, the teams developed a quantum optimization approach that could potentially handle the massive number of variables involved in designing composite materials. They created a streamlined model of the ply composite problem, focusing on finding the optimal way to stack layers of material . IBM
However, existing quantum optimization methods were inefficient, using just one binary variable per qubit. Through their collaboration, Boeing and IBM researchers developed more efficient encoding techniques that made better use of limited quantum resources. This breakthrough allowed them to run what was, at the time, the largest binary optimization problem ever handled by a quantum computer: a small version of Boeing’s ply composite problem with 40 variables . IBMIBM
Quantum Simulation of Corrosion Processes
For the corrosion challenge, IBM and Boeing researchers developed new techniques to perform quantum simulations of a key step in the corrosion process known as water reduction—the splitting of a water molecule on a magnesium surface, which initiates a chain of corrosion reactions . IBMIotworldtoday
The team created two innovative approaches:

A new embedding method specifically designed for simulating reactions of molecules on surfaces
A circuit simplification technique that significantly reduced the quantum resources required to run their simulations

Implementation

The implementation of these quantum solutions involved close collaboration between Boeing’s aerospace engineering teams and IBM’s quantum computing experts.
Ply Composite Design Implementation
For the ply composite challenge, the teams implemented a phased approach. They first identified a simplified version of the problem that could be tackled with current quantum hardware while still representing the essential characteristics of the full design challenge. This allowed them to test and validate their quantum optimization approach on existing quantum computers . IBM
The implementation required developing new quantum algorithms that could encode the complex constraints of aerospace material design into a format compatible with quantum processing. The researchers created specialized techniques to map the material properties and structural requirements onto quantum states, allowing the quantum computer to explore the vast solution space more efficiently than classical approaches . IBMIBM
While current quantum computers weren’t yet large enough to design a complete airplane wing, the successful implementation of a 40-variable model demonstrated that the approach was viable and could scale as quantum hardware capabilities improved . IBM
Corrosion Process Simulation Implementation
For the corrosion prevention challenge, the teams implemented a quantum simulation workflow that integrated both classical and quantum computing elements. They developed a hybrid approach that used classical computing for preprocessing and then employed quantum computing for the most computationally intensive aspects of the molecular simulation . HPCwire
The implementation included the development of an embedding method specifically designed for simulating reactions of molecules on surfaces, allowing them to focus quantum resources on the most critical aspects of the water reduction process. Additionally, their circuit simplification technique significantly reduced the quantum resources required, making it feasible to run meaningful simulations on current quantum hardware . IotworldtodayIBM
This implementation allowed them to compute the energies involved in the water reduction reaction with greater accuracy than leading classical methods like Density Functional Theory (DFT), which has been used to study this same reaction in hundreds of other papers but requires significant approximations . HPCwireIotworldtoday
Results and Business Impact
The collaboration between IBM and Boeing delivered several significant outcomes with potential long-term business implications.
Results of Ply Composite Design Project
The teams successfully ran a 40-variable model of Boeing’s ply composite problem on a quantum computer, which was, at the time, the largest execution of its kind ever performed. This represented a significant milestone in applying quantum computing to real-world aerospace engineering challenges . IBM
As Jay Lowell, Chief Scientist for Boeing’s Disruptive Computing and Networks team, noted, this achievement demonstrated that “it’s not if quantum computers will be relevant to our business problems, but when” . IBM The project showed that quantum solutions for complex optimization problems were more achievable than previously thought, potentially bringing quantum-enhanced aerospace design closer to reality.
While current quantum computers aren’t yet capable of handling the full 100,000-variable problems involved in actual aircraft design, the techniques developed through this collaboration laid important groundwork for scaling up the approach as quantum hardware improves . IBMIBM
Results of Corrosion Prevention Project
In the corrosion prevention project, the researchers demonstrated that quantum computing could model the water reduction reaction more accurately than leading classical methods. By computing the energies involved in this fundamental quantum process, they achieved a level of precision that classical approximation methods simply couldn’t match . Iotworldtoday
This enhanced accuracy could potentially lead to better understanding of corrosion mechanisms and the development of more effective corrosion-resistant materials. Given that corrosion represents a significant maintenance and safety challenge for the aerospace industry, even incremental improvements in corrosion prevention could translate to substantial economic benefits and safety enhancements.

The circuit simplification method developed during this project also has potential applications beyond corrosion studies, potentially enhancing the efficiency of quantum simulations across various domains.

Future Directions

Building on their successful collaboration, IBM and Boeing have outlined several directions for future research and development:

Scaling Up Ply Composite Design

As quantum computers continue to increase in capacity and reliability, Boeing aims to scale up their quantum optimization approach to handle progressively larger and more complex design problems. This could eventually enable the optimization of full-scale aerospace components with tens of thousands of variables, potentially revolutionizing aircraft design and manufacturing.

The techniques developed for efficient encoding of optimization problems on quantum hardware will likely find applications in other areas of aerospace design and manufacturing, extending beyond ply composites to other complex optimization challenges.

Expanding Corrosion Simulation Capabilities

For the corrosion prevention work, the researchers plan to continue their collaboration to investigate how quantum computing may shed light on additional chemical reactions involved in material degradation across different environments. This expanded focus could lead to comprehensive models of corrosion processes and more effective prevention strategies . IotworldtodayIBM

Boeing is also exploring the application of their quantum simulation approach to the development of advanced corrosion-resistant chemicals for coating airplanes, potentially leading to more durable and environmentally friendly protective solutions . IBM

Building Quantum Capabilities and Workforce

Through this partnership, Boeing has established a quantum-literate workforce and capabilities that position the company to take advantage of quantum computing as the technology matures. The skills and expertise developed during these projects will enable Boeing to apply quantum approaches to other aerospace challenges as quantum hardware continues to improve . IBMSpringerLink
As Jennifer Glick, Technical Lead for Quantum Prototypes at IBM Quantum, observed, these collaborations are “helping us push the frontier of quantum research” and “beginning to see what a future where quantum computers solve real, practical problems looks like” . IBM This pioneering work is establishing a foundation for the broader adoption of quantum computing in the aerospace industry and beyond.