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NANO2021-Nanoteknologi og nye materiale

Neutron Scattering and Atomistic Simulations for a SUPERior Understanding of SUPERionic Conduction

Alternative title: Nøytronspredning og atomistiske simuleringer for en bedre forståelse av superionisk ledning

Awarded: NOK 8.5 mill.

Over the last decade battery technology has become an integral part of our lives, powering devices from mobile phones to electric cars, and helping to drive the shift to a greener society. But how do batteries work, and how can they be made cheaper, safer, and more efficient? Many of you probably know the answer to the first question: that the flow of electricity is caused by motion of particles called ions - charged versions of chemical elements like lithium - from one side of the battery to the other. This phenomenon is called ionic conduction, and is also used in devices like fuel cells and thermoelectrics, which convert chemical and heat energy to electricity, respectively. Materials that conduct ions especially well - in other words, that allow ions to flow freely through them - are called superionic conductors, and are crucial to all of these technologies. This brings us to the second question, now slightly reformulated: how can devices based on superionic conductors be made cheaper, safer, and more efficient? An important step to answering this lies in understanding what the conduction mechanism is, or, in other words, how the ions move through the structure of the material. Achieving this is far from easy, since it requires a “camera” that can make videos of objects that are less than a millionth of a hair’s breadth in size and that make up to one trillion moves per second. In SUPER^2, this extraordinary “camera” is provided by experimental technique called neutron scattering, where a beam of neutrons hits a sample of superionic materials and bounces off the atoms inside, producing a pattern in a detector. By carefully analysing this pattern, the conduction mechanism can be deduced. More crucial information is supplied by AI-powered computer simulations that can generate videos of the ions in the material from the material structure. By comparing our simulations with experiments, we aim to pave the way for superionic materials and devices of the future.

Ionic conduction – the transport of ions through a material – is the fundamental mechanism behind green technologies ranging from batteries to fuel cells. One of the most promising material classes for these applications are superionic conductors, solid-state materials that have an exceptionally high ionic conductivity at room or elevated temperature. Despite their importance, there is a lack of detailed experimental information on how ions diffuse through these materials, and simulations of these diffusion processes are both difficult to run and prone to systematic errors. SUPER^2 aims to address both challenges by combining some of the most powerful experimental and computational techniques available to generate a detailed picture of the atomic-scale diffusion mechanism in several technologically relevant materials. In particular, polarized quasi-elastic and inelastic neutron scattering will provide spatially and temporally resolved information on the diffusion and lattice vibrations, respectively, while ab initio-based atomistic dynamics simulations will complement these with mechanistic details and calculations of experimental observables. Beyond providing a better understanding of the selected materials, the project will permit the benchmarking of several ab initio approaches against experiment and generate a new and automated software workflow for data analysis and simulations. These developments will have significant implications for the development of new high-performance and sustainable superionic materials. The project will be executed by three partners: University of Stavanger (UiS) in Norway and Science and Technology Facilities Council (STFC) and University College London (UCL) in the UK.

Funding scheme:

NANO2021-Nanoteknologi og nye materiale