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基于纳米成像的锂离子电池机械退化的量化和建模。

Quantification and modeling of mechanical degradation in lithium-ion batteries based on nanoscale imaging.

机构信息

Department of Information Technology and Electrical Engineering, ETH, Zurich, 8092, Switzerland.

Advanced Photon Source, Argonne National Laboratory, Lemont, 60439, USA.

出版信息

Nat Commun. 2018 Jun 14;9(1):2340. doi: 10.1038/s41467-018-04477-1.

DOI:10.1038/s41467-018-04477-1
PMID:29904154
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6002379/
Abstract

Capacity fade in lithium-ion battery electrodes can result from a degradation mechanism in which the carbon black-binder network detaches from the active material. Here we present two approaches to visualize and quantify this detachment and use the experimental results to develop and validate a model that considers how the active particle size, the viscoelastic parameters of the composite electrode, the adhesion between the active particle and the carbon black-binder domain, and the solid electrolyte interphase growth rate impact detachment and capacity fade. Using carbon-silicon composite electrodes as a model system, we demonstrate X-ray nano-tomography and backscatter scanning electron microscopy with sufficient resolution and contrast to segment the pore space, active particles, and carbon black-binder domain and quantify delamination as a function of cycle number. The validated model is further used to discuss how detachment and capacity fade in high-capacity materials can be minimized through materials engineering.

摘要

锂离子电池电极的容量衰减可能源于一种降解机制,其中碳黑-粘合剂网络从活性材料上脱落。在这里,我们提出了两种可视化和量化这种脱落的方法,并利用实验结果开发和验证了一个模型,该模型考虑了活性颗粒尺寸、复合电极的黏弹性参数、活性颗粒与碳黑-粘合剂域之间的附着力以及固体电解质相界面生长速率如何影响脱落和容量衰减。我们使用碳-硅复合材料电极作为模型系统,证明了 X 射线纳米断层扫描和背散射扫描电子显微镜具有足够的分辨率和对比度,可以分割孔空间、活性颗粒和碳黑-粘合剂域,并定量分层作为循环数的函数。经过验证的模型进一步用于讨论如何通过材料工程最小化高容量材料的脱落和容量衰减。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/aa88a8f84511/41467_2018_4477_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/996f67ef56c3/41467_2018_4477_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/6a6784c0c9be/41467_2018_4477_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/f67c1f22d923/41467_2018_4477_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/aa88a8f84511/41467_2018_4477_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/996f67ef56c3/41467_2018_4477_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/6a6784c0c9be/41467_2018_4477_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/f67c1f22d923/41467_2018_4477_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c6c/6002379/aa88a8f84511/41467_2018_4477_Fig4_HTML.jpg

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