POLiS – Post Lithium Storage Cluster of Excellence
Post-lithium batteries are the next frontier in energy storage technology, aiming to overcome the limitations of current lithium-ion batteries in terms of energy density, cost, safety, and environmental impact across various applications, from portable electronics to electric vehicles and grid storage. However, significant research and development are still needed to overcome technical challenges and bring these technologies to commercial viability. As part of the Cluster of Excellence, POLiS, our group is doing research on improved electrode materials and battery design with computational methods such as simulation, machine learning and research data management.
POLiS – Post Lithium Storage Cluster of Excellence
- Contact:
see below
- Project Group:
- Funding:
DFG
- Startdate:
2019
Microstructure simulations
Contact: Britta Nestler, Daniel Schneider
The development of microstructure models and their application to battery materials is one pillar for the accelerated discovery of new battery electrode compounds and optimization of battery lifetime and performance. Our research work focuses on the influence of microstructure on the overall battery performance i.e. it operates at the interface between an atomistic view and the homogenized cell scale.
By including information from ab-initio simulations and close-to-equilibrium experiments, the phase-field method can describe the complex multi-physics on the material level.
We investigate
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Charging rates depending on diffusion, mechanical deformation, electro-chemical insertion and phase transitions
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The influence of microstructure on battery performance
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Degradation phenomena
Research data management and machine learning
Contact: Michael Selzer, Arnd Koeppe
We thrive to improve post-Li batteries by employing modern research data management tools and machine learning and AI techniques. This includes:
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Development of digital twins for multiscale high throughput simulations
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Develop a comprehensive ontology covering all major research topics within POLIS. Transform developed ontologies to adapt the Kadi4mat platform to facilitate storage and data structure.
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Data-driven concepts to establish computational screening, optimization, and design techniques for Post-Lithium battery systems.