Early quantum technology case studies (non-exhaustive) in product design and R&D CASE STUDY 1 Computational simulation of corrosion for materials durability Corrosion in aircraft materials poses a major challenge, weakening structural components, shortening lifespan and increasing maintenance costs. The ability to simulate material behaviour at the atomic level with very high accuracy enables researchers to rapidly evaluate potential materials for corrosion resistance, accelerating the discovery process by focusing on the most promising candidates of new alloys and coatings. This not only extends the lifespan of aircraft components but also enhances safety and reduces maintenance costs. To improve the durability and safety of aerospace materials, Boeing needed to simulate corrosion reactions in them. Classical computing methods were slow and limited in accuracy to identify the specific properties that make certain materials more resistant to corrosion. To overcome these limitations, Boeing used variational quantum algorithms to simulate how water molecules interact with magnesium surfaces, a key reaction that triggers corrosion in lightweight aerospace metals. These models, which were run on commercially available cloud-based quantum computers, allowed for more precise energy calculations and reaction dynamics. Boeing’s research team focused on reducing the complexity of the quantum models by up to 85%.13 The study highlights how quantum computing can accelerate material discovery for aerospace platforms. Additionally, the findings could benefit steel-intensive industries like maritime transport, automotive and industrial machinery. We are investing time now to learn how quantum computers can help us model these complex reactions in the future. We expect this investment will enable us to find better material systems faster and reduce the cost to develop high- performing aerospace materials. John Lowell, Principal Senior Tech Fellow, Boeing Research and Technology CASE STUDY 2 Accelerated R&D cycles of drug discovery for pharmaceutical manufacturing Messenger RNA (mRNA) therapeutics are a new way to help the body make its own medicines. Instead of giving a drug directly, scientists design mRNA molecules that tell our cells how to make helpful proteins. mRNA is made up of building blocks called nucleotides. These are small molecules that link together in long chains, forming the mRNA sequence. Designing effective mRNA drugs is challenging as it involves simulation of how long chains of nucleotides fold into functional shapes. The folding patterns affect drug effectiveness and safety. Imagine trying to fold a very long piece of paper into a tiny box – there are countless ways to fold it and finding the best way is extremely tricky. Regular computers struggle with this because there are many possible shapes to check, especially for longer mRNA sequences, slowing down R&D cycles.Quantum computers can look at many possible folding patterns at the same time. Recent advances by Moderna have shown that quantum computers can predict mRNA shapes up to 60 nucleotides. For mRNA sequences with 200 nucleotides, traditional methods can take hours or even days for comprehensive analysis, and to save time they often simplify the process by skipping over key details. While this approach is faster, it risks missing critical insights that could impact results. Quantum computing, on the other hand, can handle complexity without cutting corners, delivering deeper insights into folding patterns in a fraction of the time. Better understanding mRNA folding enables more effective drugs with fewer side effects and faster development during health emergencies. Reduced time-to-market means lower costs for developing new treatments. This technology helps bring new, life-saving medicines to people faster, supporting global health and well-being.14Quantum computing Quantum Technologies: Key Opportunities for Advanced Manufacturing and Supply Chains 10

Quantum Technologies Key Opportunities for Advanced Manufacturing and Supply Chains 2025