Our goal is to optimize energy materials properties from the macro to the atomic scale. We established a comprehensive workflow using electrons, ions, X-rays, light and probes in 2D and 3D. All is connected so data can be analyzed using software powered by machine learning to help us create a digital twin and intelligently drive materials optimization.Silke Christiansen I Fraunhofer Institute for Ceramic Technologies and Systems IKTS, Forchheim, DE.
Energy systems like solar cells, fuel cells, and batteries contain many materials with varying properties, scales, and arrangements. Our goal is to control and optimize material and interface properties from macro to atomic scale with device manufacturers who optimize and control device performance. In our lab we established a comprehensive energy materials workflow which includes sample preparation, inert transfer, cryogenic environments, and full microscopic, spectroscopic, and bulk characterization using electrons, ions, x-rays, light, and probes in 2D and 3D. All this is connected so data can be analyzed correlatively and quantitatively using statistical tools and image recognition software powered by machine learning to help us create a digital twin and intelligently drive materials and device optimization.
For further reading: Wolz, BC, Jaremenko, C, Vollnhals, F, Kling, L, Wrege, J, Christiansen, S. X-ray microscopy and automatic detection of defects in through silicon vias in three-dimensional integrated circuits. Engineering Reports e12520, (2022): https://doi.org/10.1002/eng2.12520,
In The Electrochemical Innovation Lab at UCL, we help drive towards a Net Zero carbon future by studying electrochemical power systems including batteries, fuel cells, and super-capacitors in order to improve performance, durability, and safety, and lower cost.Prof. Paul Shearing I Royal Academy of Engineering Chair in Emerging Battery Technologies, Department of Chemical Engineering at University College London (UCL), UK.
Microscopy techniques are central to our research – we have spent the past decade building a library of data on materials, electrodes, and electrochemical devices with our microscopes running around the clock. This is a real exemplar of a multi-scale challenge and provides exciting opportunities for correlative microscopy. With increasingly sophisticated tools for in situ and operando microscopy, we believe that we can condense the time it takes from discovering exciting new materials, to their deployment in the real world.
Image courtesy of: Lu, X., Bertei, A., Finegan, D.P. et al. 3D microstructure design of lithium-ion battery electrodes assisted by X-ray nano-computed tomography and modelling. Nat Commun 11, 2079 (2020). Provided by Springer Nature. https://doi.org/10.1038/s41467-020-15811-x, licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/
In my group we focus on image-based material characterization and analysis in energy storage and microelectronics. To do this we develop and apply advanced imaging and analysis workflows leveraging artificial intelligence to characterize the structural and chemical properties across the cell- and microstructure-levels from mm to nm in 2D as well as 3D.P.D. Roland Brunner I Materials Center Leoben, AT
In batteries, for instance, the electrochemical properties and morphology of the materials directly impact performance. Therefore, a deep understanding of structure-property relationships across length scales is key to improving the devices and materials within. Silicon-based anode materials hold promise for next-generation Li-ion batteries due to the high theoretical capacity, but challenges remain around capacity fade and cell life expectancy. Proper material engineering is essential here and an accurate representation of the complex multi-phase microstructures helps guide materials synthesis and processing efforts.
To do this we develop and apply advanced imaging and analysis workflows leveraging artificial intelligence to characterize the structural and chemical properties across cell- and microstructure-levels from mm to nm in 2D as well as 3D.
Image courtesy of: Vorauer, T., Kumar, P., Berhaut, C.L. et al. Multi-scale quantification and modeling of aged nanostructured silicon-based composite anodes. Commun Chem 3, 141 (2020). Provided by Springer Nature. https://doi.org/10.1038/s42004-020-00386-x, licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/
In this 42-page WILEY ebook, get an overview of:
- Microscopy techniques & their benefits for energy materials research
- Microscopy-enabled accomplishments in energy materials research (11 short versions of selected peer-reviewed articles from various WILEY journals)
- Current challenges & future developments in microscopy applications for energy materials (Interview with Professor Paul Shearing from the University College London)
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