Solid-state batteries replace the flammable liquid inside a conventional battery with a solid material, but ions move too slowly across the interfaces where different solids meet, limiting performance. This project uses computer simulations—combining classical physics, quantum mechanics, and machine learning—to understand and redesign those interfaces so that ions can travel faster and more efficiently. Current lithium-ion batteries are nearing their performance limits, and incremental improvements will not deliver the energy density, safety, or charging speed needed to electrify transport and store renewable energy at grid scale. If the simulations succeed, they could guide the development of solid-state batteries that charge faster, last longer, and do not catch fire. The project also aims to shift from lithium to sodium, a far more abundant and cheaper material, making large-scale battery production more sustainable. This is fundamental computational science: it will not produce a working battery in the lab, but it will give experimentalists a blueprint for which materials and interfaces to build and test.
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Building better batteries is one of the major scientific and societal challenges of the 21st century. However, incremental improvements to current batteries cannot meet the requirements necessary for Europe to reach its net-zero goals by 2050. Next-generation batteries are therefore essential for the transformational improvements in performance required for the electrification of transport and grid-scale storage of energy from renewable resources. Nevertheless, the full potential of such batteries is severely hindered by numerous underlying challenges, many of which centre on the ion transport and interfaces in their constituent materials. Building upon my expertise and proven track record in the atomistic simulation of materials and connecting such simulations to the macroscale, AMPed will revolutionise the understanding and design of the ion transport and interfaces within solid-state battery architectures. AMPed will utilise state-of-the-art classical, quantum mechanical, structure prediction and machine learning approaches to develop battery materials with improved performance, stability and sustainability by achieving the following four key objectives: (1) Establish a new time-domain paradigm for understanding ion transport in solid electrolytes (2) Explore nanostructured solid electrolytes for optimised performance (3) Mitigate resistance and instability at heterointerfaces in solid-state batteries (4) Drive transition to sustainable solid-state sodium batteries These novel and exploratory models will be experimentally validated in partnership with my close network of interdisciplinary experts in battery materials and devices. AMPed will provide transformative opportunities for the design of energy materials and push the boundaries of computational energy materials design, thereby advancing the excellence of energy research in Europe and further consolidating my research at the frontier of computational materials science.
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