Acoustic emission characteristics and CT-Based mesoscopic features of damage evolution in cathode carbon blocks under varying electrolysis durations
Source abstract
Abstract
This study investigated the damage characteristics of graphitised cathode carbon blocks under different electrolysis durations (0 h, 1 h, 2 h, and 3 h). By integrating high-temperature mechanical loading, acoustic emission (AE) monitoring, and three-dimensional (3D) X-ray micro-computed tomography (micro-CT), the mechanical response, AE signal evolution, and microstructural porosity changes of the blocks were systematically examined. The results demonstrated that prolonged electrolysis significantly reduced the peak compressive strength of the cathode blocks. The number of AE events decreased with increasing electrolysis duration, declining from 1,571 in the control group to 299 in the 3-hour group, representing an 80.97% reduction. Distinct variation trends were observed in both b-values and S-values, while the RA-AF distribution indicated that electrolysis reduced the proportion of shear cracks from 70.53% to 20.07%. Micro-CT analysis revealed that after 3 hours of electrolysis, the total porosity decreased from 13.84% to 8.16%, and the proportion of interconnected pores decreased from 87.65% to 82.13%. Meanwhile, the electrolyte permeability increased from 17.26% to 49.32%. Similar changes were observed in the contact area. These findings elucidate the damage evolution of graphitised cathode carbon blocks during electrolysis and provide a basis for online condition monitoring and service life prediction.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Corrosion Behavior and Inhibition · Earthquake Detection and Analysis · Hydrogen embrittlement and corrosion behaviors in metals
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Jiangxi University of Science and Technology
Ganzhou Chenguang Rare Earths New Material Co., Ltd
Funding
National Natural Science Foundation of China General Project · Supercomputing Platform of Jiangxi University of Science and Technology
References (31)
Show source-provided references
1. 10.1007/s11663-019-01731-910.1007/s11663-019-01731-9 ↗
2. 10.1007/s11837-019-03717-z10.1007/s11837-019-03717-z ↗
3. 10.24425/amm.2022.13781810.24425/amm.2022.137818 ↗
4. 10.1016/j.cscm.2023.e0202110.1016/j.cscm.2023.e02021 ↗
5. 10.1016/j.measurement.2024.11508810.1016/j.measurement.2024.115088 ↗
6. 10.2113/2023/277379510.2113/2023/2773795 ↗
7. 10.1016/j.compositesa.2011.07.01510.1016/j.compositesa.2011.07.015 ↗
8. 10.1016/j.compositesa.2016.10.01310.1016/j.compositesa.2016.10.013 ↗
9. Nghi QN, Mahoor M, Ilya S, et al. Micro-CT measurement of fibre misalignment: application to carbon/epoxy laminates manufactured in autoclave and by vacuum assisted resin transfer moulding. Compos Part A-Appl Sci Manuf. 2018;104:14–23.10.1016/j.compositesa.2017.10.018 ↗
10. 10.1016/j.compstruct.2019.11119610.1016/j.compstruct.2019.111196 ↗
11. 10.1016/j.geothermics.2016.09.00810.1016/j.geothermics.2016.09.008 ↗
12. 10.1016/j.matchar.2019.05.03310.1016/j.matchar.2019.05.033 ↗
13. 10.1007/s00603-021-02589-710.1007/s00603-021-02589-7 ↗
14. 10.1016/j.conbuildmat.2024.13972610.1016/j.conbuildmat.2024.139726 ↗
15. 10.1016/j.conbuildmat.2025.14241610.1016/j.conbuildmat.2025.142416 ↗
16. 10.1016/j.conbuildmat.2025.14276110.1016/j.conbuildmat.2025.142761 ↗
17. 10.1016/j.jobe.2025.11329810.1016/j.jobe.2025.113298 ↗
18. 10.1016/j.compositesb.2025.11317210.1016/j.compositesb.2025.113172 ↗
19. Fan N, Qiao YG, Wang HY, et al. Computed tomography imaging-based quantification of microstructural heterogeneity in coal under uniaxial loading: insights into pore-scale gas flow behavior. Energy. 2025;338:138876.10.1016/j.energy.2025.138876 ↗
20. 10.1016/j.tafmec.2025.10505310.1016/j.tafmec.2025.105053 ↗
21. Li H, Cai YD, Liu DM, et al. Full-scale pore structure and its impact on methane adsorption in deep coal reservoirs of the Zijinshan area, eastern Ordos Basin. Phys Fluids. 2025;37(8):086618.10.1063/5.0284039 ↗
22. Chen DL, Xia CG, Liu HN, et al. Research on b value estimation based on apparent amplitude-frequency distribution in rock acoustic emission tests. Mathematics. 2022;10:3202.10.3390/math10173202 ↗
23. 10.1016/j.coldregions.2015.08.00510.1016/j.coldregions.2015.08.005 ↗
24. 10.1016/j.mtcomm.2024.10885610.1016/j.mtcomm.2024.108856 ↗
25. Dong LJ, Zhang LY. Error analysis of the b-value in rock fracture acoustic emission. Yangtze River Sci Res Inst Bull. 2020;37(8):75–81.
26. Gu JC, Wei FS. On the quantification of seismic activity: seismic activity level. China Earthquake. 1987;S1:14–24.
27. 10.1016/j.tafmec.2022.10335910.1016/j.tafmec.2022.103359 ↗
28. Dong LJ, Zhang YH, Bi SJ, et al. Uncertainty investigation for the classification of rock micro-fracture types using acoustic emission parameters. Int J Rock Mech Min Sci. 2023;162:105292.10.1016/j.ijrmms.2022.105292 ↗
29. 10.1016/j.conbuildmat.2024.13732110.1016/j.conbuildmat.2024.137321 ↗
30. 10.1016/j.conbuildmat.2010.05.00410.1016/j.conbuildmat.2010.05.004 ↗
31. 10.1016/j.ijrmms.2020.10432310.1016/j.ijrmms.2020.104323 ↗