X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level
Source abstract
Abstract
Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advancements in Battery Materials · Advanced Battery Materials and Technologies · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Pritzker School of Molecular Engineering
University of Chicago
Advanced Photon Source
Argonne National Laboratory
Aiiso Yufeng Li Family Department of NanoEngineering
University of California San Diego
Energy Storage Research Alliance
National Synchrotron Radiation Research Center
Sustainable Electrochemical Energy Development (SEED) Center
National Taiwan University of Science and Technology
Funding
U.S. Department of Energy · University of Chicago · LG Energy Solution
References (62)
Show source-provided references
1. 10.1016/j.joule.2022.07.00210.1016/j.joule.2022.07.002 ↗
2. 10.1038/s41560-023-01208-910.1038/s41560-023-01208-9 ↗
3. 10.1038/s41578-019-0157-510.1038/s41578-019-0157-5 ↗
4. 10.1021/acs.chemrev.0c0010110.1021/acs.chemrev.0c00101 ↗
5. 10.1016/j.ensm.2022.12.01310.1016/j.ensm.2022.12.013 ↗
6. 10.1021/acsenergylett.4c0280010.1021/acsenergylett.4c02800 ↗
7. 10.1038/s41563-020-00903-210.1038/s41563-020-00903-2 ↗
8. 10.1038/s41563-021-00967-810.1038/s41563-021-00967-8 ↗
9. 10.1016/j.matt.2020.09.01810.1016/j.matt.2020.09.018 ↗
10. 10.1016/j.joule.2022.12.00110.1016/j.joule.2022.12.001 ↗
11. 10.1002/aenm.20220201210.1002/aenm.202202012 ↗
12. 10.1038/s41560-021-00917-310.1038/s41560-021-00917-3 ↗
13. 10.1016/j.joule.2019.06.00810.1016/j.joule.2019.06.008 ↗
14. 10.1016/j.isci.2021.10339410.1016/j.isci.2021.103394 ↗
15. 10.1016/j.ultramic.2015.11.00110.1016/j.ultramic.2015.11.001 ↗
16. 10.1021/acsenergylett.8b0238110.1021/acsenergylett.8b02381 ↗
17. 10.1039/D2EE03840D10.1039/D2EE03840D ↗
18. 10.1016/j.jpowsour.2019.05.03910.1016/j.jpowsour.2019.05.039 ↗
19. 10.1039/C6CP04251A10.1039/C6CP04251A ↗
20. 10.1016/j.joule.2018.11.00210.1016/j.joule.2018.11.002 ↗
21. 10.1038/s41565-022-01081-910.1038/s41565-022-01081-9 ↗
22. Kastner J. · 2018 · 1
23. 10.1016/j.matdes.2020.10855310.1016/j.matdes.2020.108553 ↗
24. 10.1016/j.ndteint.2010.06.00410.1016/j.ndteint.2010.06.004 ↗
25. 10.1107/S160057752200309510.1107/S1600577522003095 ↗
26. 10.1038/s41524-023-01039-y10.1038/s41524-023-01039-y ↗
27. 10.1149/1945-7111/ad63d010.1149/1945-7111/ad63d0 ↗
28. 10.1126/science.abg599810.1126/science.abg5998 ↗
29. 10.1038/s41560-020-0575-z10.1038/s41560-020-0575-z ↗
30. 10.1002/aenm.20230432710.1002/aenm.202304327 ↗
31. 10.1016/j.est.2020.10134410.1016/j.est.2020.101344 ↗
32. 10.1149/1945-7111/ad5d2210.1149/1945-7111/ad5d22 ↗
33. 10.1002/adfm.20230134110.1002/adfm.202301341 ↗
34. 10.1021/acsenergylett.2c0193610.1021/acsenergylett.2c01936 ↗
35. 10.1021/acsenergylett.2c0213810.1021/acsenergylett.2c02138 ↗
36. 10.1039/C8EE00907D10.1039/C8EE00907D ↗
37. 10.1016/j.softx.2016.09.00210.1016/j.softx.2016.09.002 ↗
38. 10.1021/acsenergylett.2c0269910.1021/acsenergylett.2c02699 ↗
39. 10.1149/2.0601902jes10.1149/2.0601902jes ↗
40. 10.1093/nsr/nwac27210.1093/nsr/nwac272 ↗
41. 10.1016/j.jpowsour.2018.06.04110.1016/j.jpowsour.2018.06.041 ↗
42. 10.1149/2.0231803jes10.1149/2.0231803jes ↗
43. 10.1002/aenm.20130127810.1002/aenm.201301278 ↗
44. 10.1149/2.0731814jes10.1149/2.0731814jes ↗
45. 10.1126/science.abg721710.1126/science.abg7217 ↗
46. 10.1016/j.ensm.2024.10324610.1016/j.ensm.2024.103246 ↗
47. 10.1038/s41563-023-01792-x10.1038/s41563-023-01792-x ↗
48. 10.1149/1945-7111/ad09f510.1149/1945-7111/ad09f5 ↗
49. 10.1016/j.softx.2024.10169010.1016/j.softx.2024.101690 ↗
50. Owen, S. J. Sculpt: A new tool for automatic parallel hex meshing. Proposed for presentation at the 1500 External Review; USDOE, Albuquerque, NM, USA, 2013.
51. 10.1007/s00366-014-0368-810.1007/s00366-014-0368-8 ↗
52. 10.1038/ncomms1290910.1038/ncomms12909 ↗
53. 10.1002/smm2.100710.1002/smm2.1007 ↗
54. 10.1038/s41565-020-0657-x10.1038/s41565-020-0657-x ↗
55. 10.1021/acsenergylett.1c0275610.1021/acsenergylett.1c02756 ↗
56. 10.1038/s41524-022-00709-710.1038/s41524-022-00709-7 ↗
57. Jacobsen C. · 2019 · 32110.1017/9781139924542.009 ↗
58. 10.1107/S160057752400292310.1107/S1600577524002923 ↗
59. 10.1080/08940886.2023.224681610.1080/08940886.2023.2246816 ↗
60. 10.1038/s41467-021-26480-910.1038/s41467-021-26480-9 ↗
61. 10.1364/JOSAA.37559510.1364/JOSAA.375595 ↗
62. 10.1038/s43246-022-00313-810.1038/s43246-022-00313-8 ↗