Towards More Efficient Batteries

Using X-ray diffraction tomography supported by machine learning, an international team of researchers screened screened a key degradation process in battery cathodes.

Dr Anatoliy Senyshyn carried out measurements on the SPODI structural powder diffractometer, which provided important insights into the degradation processes in battery cathodes. © Bernhard Ludewig, FRM II / TUM

Dr Anatoliy Senyshyn carried out measurements on the SPODI structural powder diffractometer, which provided important insights into the degradation processes in battery cathodes. © Bernhard Ludewig, FRM II / TUM

The rechargeable lithium-ion battery is a revolutionary technological solution that already provides elec­tric power to many types of mobile devices for a reasonable length of time. Nevertheless, there is room for improvement, including lifetime, safety, and cost.

Cathode loses charge capacity

International researchers precisely determined the exact mechanisms behind the deterioration of the batteries’ performance during use. To find out why the commonly used cathodes lose their charge capacity upon continuous operation, characterization of the cathode material with the desired accuracy, depth, and length scale was required, which led to a highly advanced experimental approach.

Measurements were carried out simultaneously using micro-focused X-ray diffraction and fluorescence tomography, supported by neutron powder diffraction. The crucial feature of this approach is the involvement of machine learning in handling and analysing the resulting extremely large data sets.

Artistic interpretation of a new battery technology improving the batteries in smartphones. © generiert mit KI, ChatGPT, bearbeitet von Reiner Müller (FRM II)

Artistic interpretation of a new battery technology improving the batteries in smartphones. © generiert mit KI, ChatGPT, bearbeitet von Reiner Müller (FRM II)

Insights into degradation mechanisms

The team monitored various changes induced by the operation of the cathode for 100 charge/recharge cycles, using an extremely high 3D spatial resolution of one micrometre. The fine details observed provided unique insights into the elemental composition variations, chemical phase transformations, and morphological alterations. This made it possible to define degradation mechanisms specific to the selected cathode material, the role of the carbon matrix, and the binder in the battery aging. The conclusions pave the way for optimising the composite cathode materials towards higher efficiency and sustainability.

Publication

W. B. Hua, J. N. Chen, D. F. Sanchez, B. Schwarz, Y. Yang, A. Senyshyn, Z. G. Wu, C. H. Shen, M. Knapp, H. Ehrenberg, S. Indris, X. D. Guo, X.P. Ouyang, Probing Particle-Carbon / Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning Aided Diffraction Tomog-raphy, Angew. Chem. Int. Ed. 63, e202403189 (2024) DOI: 10.1002/anie.202403189

Further information

Experiments were carried out at MSPD, ALBA, Spain; P02.1, PETRA III / DESY, Germany; X05LA, SLS / PSI, Switzerland and SPODI, MLZ