- PII
- 10.31857/S0044453723060110-1
- DOI
- 10.31857/S0044453723060110
- Publication type
- Status
- Published
- Authors
- Volume/ Edition
- Volume 97 / Issue number 6
- Pages
- 821-826
- Abstract
- Graphite intercalated compounds (GICs) with different stage numbers are prepared chemically from highly oriented pyrolytic graphite (HOPG), natural flaked graphite (FG) and nitric acid. Exfoliated graphite samples (EG-T) are synthesized from GICs via water treatment followed by thermal shock. The aim of this work is to investigate the dependence of the inner EG-T pore structure on the extent of oxidation and type of graphite by processing scanning electron microscopy (SEM) micrographs of EG-T cross sections. A procedure is developed on the basis of a deep convolutional neural network that speeds up image processing with no appreciable loss of accuracy. A strong correlation is found between EG-T pore structure parameters, the depth of oxidation, and the type of graphite.
- Keywords
- терморасширенный графит пористая структура сегментация нейронные сети
- Date of publication
- 12.09.2025
- Year of publication
- 2025
- Number of purchasers
- 0
- Views
- 13
References
- 1. Chung D.D.L. // J. Mater. Sci. 2016. V. 51. P. 554. https://doi.org/10.1007/s10853-015-9284-6
- 2. Nayak S.K., Mohanty S., Nayak S.K. // High Perform. Polym. 2019. V. 32. P. 506. https://doi.org/10.1177/0954008319884616
- 3. Sorokina N.E., Redchitz A.V., Ionov S.G. et al. // J. Phys. Chem. Solids. 2006. V. 67. P. 1202. https://doi.org/10.1016/j.jpcs.2006.01.048
- 4. Inagaki M., Kang F., Toyoda M. et al. // Advanced Materials Science and Engineering of Carbon, Butterworth-Heinemann. 2014. P. 313. https://doi.org/10.1016/B978-0-12-407789-8.00014-4
- 5. Wang Z., Han E., Ke W. // Corros. Sci. 2007. V. 49. P. 2237. https://doi.org/10.1016/j.corsci.2006.10.024
- 6. Inagaki M., Suwa T. // Carbon. 2001. V. 39. P. 915. https://doi.org/10.1016/S0008-6223 (00)00199-8
- 7. Inagaki M., Tashiro R., Washino Y. et al. // J. Phys. Chem. Solids. 2004. V. 65. P. 133. https://doi.org/10.1016/j.jpcs.2003.10.007
- 8. Inagaki M., Saji N., Zheng Y.-P. et al. // TANSO. 2004. V. 2004. P. 258. https://doi.org/10.7209/tanso.2004.258
- 9. Bellens S., Vandewalle P., Dewulf W. // Procedia CIRP. 2020. V. 96. P. 336. https://doi.org/10.1016/j.procir.2021.01.157
- 10. Varfolomeev I., Yakimchuk I., Safonov I. // Computers. 2019. V. 8. № 4. P. 72. https://doi.org/10.3390/computers8040072
- 11. Li X., Lai T., Wang S. et al. // 2019 IEEE Intl. Conf. Parallel Distrib. Process. with Appl. Big Data Cloud Comput. Sustain. Comput. Commun. Soc. Comput. Networking. 2019. P. 1500. https://doi.org/10.1109/ISPA-BDCloud-SustainCom-SocialCom48970.2019.00217
- 12. Kang F., Zheng Y.-P., Wang H.-N. et al. // Carbon. 2002. V. 40. № 9. P. 1575. https://doi.org/10.1016/S0008-6223 (02)00023-4
