Data-integrated scale bridging for batteries

All-Solid State Lithium Ion Batteries (ASSLIBs)

Major progress in battery technology is a key to the decarbonization of industry and everyday life. In All-Solid State Lithium Ion Batteries (ASSLIBs) the liquid electrolyte of conventional Lithium ion batteries is replaced by a polycrystalline solid-state electrolyte. It seems promising that ASSLIBs might outperform conventional Lithium ion batteries with respect to capacity, operational safety and charging performance. Therefore, an in-depth understanding of the multiphysical multiscale effects within the solid-state electrolyte is subject of ongoing research across various disciplines.

Our focus

From atoms to microstructures: identifying what matters

Atomistic simulations offer promising insights into relevant effects and mechanisms within polycrystalline materials. However, they go along with massive computational demands, thereby limiting the size of the studied cells considerably. We aim to build continuum models on microscale that account for the observed effects on smaller scale in order to obtain meaningful results. This yields models that are consistent with atomistic results by construction.

Inside grain boundaries: where the magic happens

Studies on smaller scale suggest the relevance of grain boundary effects for the overall effective material response. Hence, grain boundary mechanisms are at the core of our models. Gaining a better understanding of how their existence and properties impact the effective diffusion behavior is among our research questions. The complex variety of grain boundary types and configurations arising from atomistic investigations also poses challenges on continuum models.

Beyond classical simulations: towards real time-capable surrogate models

The enormous computational cost arising from atomistic simulation causes a significant data sparsity in a very high-dimensional space of potential configurations. Exploitation of the material and structural features that govern the effective behavior in this model enables the application of data-integrated techniques and the design of meaningful surrogate models. This will allow for an on-the-fly identification of parameter space segments of high uncertainty and a meaningful selection of configurations to be chosen for high-fidelity simulations - both on atomistic and continuum scale.

Cross-disciplinary insights: making research accessible across fields

By means of meaningful metrics and visualizations we aim to develop a joint understanding of relevant mechanisms and regimes across scales. This is facilitated by a demonstrator for paramter space exploration that allows experts from different fields to investigate the behavior interactively and in real-time. In silico explorations of microstructures and their implications on larger scales become possible.

Funding information and acknowledgement

 SimTech Logo  Funded by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2075 - 390740016. We acknowledge the support by the Stuttgart Center for Simulation Science (SC SimTech).
This image shows Lena Scholz

Lena Scholz

M. Sc.

Doctoral Researcher

This image shows Felix Fritzen

Felix Fritzen

Prof. Dr.-Ing. Dipl.-Math. techn.

Head of department

 

Prof. Dr. Blazej Grabowski

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