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Why do materials fail? Quantum will finally give us answers 

Дата публикации: 26-06-2026 06:32:37

Explore how quantum insights transform aerospace coatings by analyzing chemical interactions and predicting degradation.

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From the start, materials science has always relied on a simple model: test, fail, iterate. Quantum-informed modeling changes that. Where once we were limited to macro effects, we can now understand what’s happening at the level of the molecule. 

To see this approach in action, we can look at the case of advanced aerospace coatings, where harsh conditions degrade the surface in ways that are hard to predict. Rather than treating materials as uniform systems, researchers are able to zoom in on specific chemical interactions –how radiation affects particular bonds, how local structures respond, and how those changes cascade into real-world failure. This makes it possible to explain the degradation in precise, physical terms. This is what we’re achieving at QPolyDeg, and the implications for material sciences are almost unlimited. 

The challenge of aerospace coatings 

In aerospace, the durability of external coatings directly affects maintenance cycles, operational cost, and component lifetime. Modern aircraft coatings, typically based on polyurethane polymer systems, are continuously exposed to intense UV radiation at altitude. Over time, this leads to embrittlement and degradation.  

Predicting this degradation remains difficult. The underlying mechanisms occur at the molecular level, where UV radiation interacts with specific functional groups and triggers complex chemical pathways. These processes are highly localized, sensitive to chemical composition and crosslinking structure, and challenging to capture using conventional simulation approaches. So, what if we could see these processes up close?  

Advances in computational methods 

Traditional simulations rely on approximations that miss key localized quantum effects. Hybrid approaches combine classical and quantum methods to focus on the interactions that matter most to material behavior. For polymer coatings, this enables a more accurate view of the specific chemistry driving degradation – moving beyond rough trends to more physically grounded insight. By improving how these local interactions are represented, computational models can move beyond approximate trends towards more physically grounded insight into material behavior.  

Introducing QPolyDeg 

The QPolyDeg project uses advanced computer modeling to study UV-driven degradation in polyurethane coatings. It enables us to understand the behavior of functional groups, and their interaction with radiation. 

In practice, this involves combining multiple levels of modelling within a single workflow. Classical molecular dynamics and force-field approaches enable the exploration of larger-scale polymer structures, while higher-accuracy quantum chemistry methods are used to analyze specific chemical processes. As a result, QPolyDeg makes it possible to: 

  • identify which functional groups drive radiation absorption, 
  • understand the mechanisms leading to degradation, and 
  • link these processes to measurable outcomes such as embrittlement or loss of coating performance.  

By connecting molecular-scale processes to macroscopic effects, the workflow provides a more direct path from material design to performance prediction. 

Zooming out: implications and takeaways for leaders 

This approach goes beyond coatings – it changes the way new materials are designed. Modern methods that combine classical, data-driven and quantum approaches, material discovery could be less costly and more effective than anything we’ve seen before. Projects such as QPolyDeg illustrate how this transition can be grounded in concrete industrial challenges, delivering measurable improvements in understanding, prediction, and ultimate performance. Most of all, they bring us a step closer to a world where materials can be designed from the bottom up. We’re looking at a whole new era of material science, made possible by quantum research.

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