Completed Chemistry Clean Energy

New Phase Field Models for Unravelling Multi-Physics Material Degradation Challenges (NEWPHASE)

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AI plain-English summary

Corrosion costs the UK £46 billion each year, and lithium-ion batteries still fail unpredictably—both problems stem from the same blind spot in materials science. Engineers can model how materials deform under stress, and chemists can track reactions on a surface, but no one can reliably predict what happens when mechanical loads and corrosive environments act together. This fellowship aims to close that gap by developing a new class of computer models that simulate how material interfaces—the boundaries where corrosion pits form or battery electrodes degrade—evolve over time. The key innovation is a mathematical trick called the phase field method, which replaces the sharp, hard-to-track interface with a diffuse region that computers can handle. If successful, the models will be validated against 3D X-ray scans and then tested on real-world problems: extending the life of the world’s oldest large offshore wind farm, improving battery safety, and guiding maintenance decisions for water pipes and nuclear reactors. The ultimate goal is to make simulation-based “digital twins” a routine part of engineering, so that infrastructure operators can spot hidden damage before it leads to collapse.

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The biggest scientific and engineering challenges often lie in between disciplines. Through the years, we have gained a good understanding of how materials behave when subjected to mechanical loads (solid mechanics). We also understand the nature of the chemical reactions occurring when materials are exposed to a given environment (electrochemistry). However, predicting material behaviour due to combined exposure to mechanical loads and a degrading environment continues to be an elusive goal. Not being able to understand and predict electro-chemo-mechanics phenomena comes at a great cost since materials are very sensitive to environmental and mechanical degradation in many applications. The value of the fundamental science conducted in this fellowship will be demonstrated on two of these applications: (1) corrosion damage, and (2) Li-Ion batteries. Their importance cannot be emphasised enough. Solely in the UK, failure of structures and industrial components due to corrosion entails a staggering cost of £46 billion per annum. Li-Ion batteries are key enablers in achieving universal access to reliable, clean, sustainable energy. Now, there is an opportunity to develop models that can prevent corrosion failures and significantly enhance progress in battery technology. Larger computer resources and new algorithms enable simulating concurrent (coupled) physical processes such as chemical reactions, diffusion of species and mechanical deformation; so-called multi-physics modelling. However, the opportunity of building upon the success of multi-physics simulations to predict material degradation is held back due to our inability to model how the boundary between two different phases develops over time. For example, corrosion is often non-uniform, leading to small defects (pits) that grow and act as crack initiators. Preventing the associated catastrophic failures, such as the Morandi Bridge collapse, requires capturing how these defects will nucleate at the electrolyte-material interface and grow. But the modelling of morphological changes in an evolving interface has been long considered a mathematical and computational challenge. I will overcome this longstanding obstacle by smearing the "sharp" interface over a small diffuse region using an auxiliary "phase field" variable - a paradigm change that will make tracking of evolving interfaces amenable to numerical computations. A new generation of models will be developed and validated with powerful 3D techniques such as X-ray Computed Tomography, which have timely experienced notable improvements in spatial resolution and image reconstruction times. By explicitly capturing the damage process, this fellowship will not only open new horizons in the understanding of multi-physics material degradation phenomena but also set the basis for the introduction of simulation-based assessment in engineering practice; model predictions can be compared with inspection data, introducing the "Digital Twins" and "Virtual Testing" paradigms into engineering applications involving demanding environments. The near-term societal impact will be demonstrated by addressing salient technological problems in offshore energy, batteries, water supply networks and nuclear fission. Efforts will be guided by the fellowship advisory board, which includes leading firms in each of these sectors: EDF Energy, Rolls-Royce, SUEZ, PA Consulting, Vattenfall and Subsea7. For example, the new generation of models developed will be used to assist in the life extension decision of the oldest large-scale wind farm in the world, Horns Rev 1. The lessons learned in this world-first engineering assessment will set an example for the entire sector and demonstrate the potential of computer simulations in enhancing the economic viability of the leading renewable energy source. The successful fellowship will lay scientific foundations for new engineering solutions that will improve UK's competitiveness and our quality of life.

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Researchers

Emilio Martinez-Paneda (Principal Investigator)

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Original classification

Fellowship

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