Construction of a Predictive Model for Assessing the Porosity of TiNi Materials Based on Sintering Parameters of Samples
Yury V. Kistenev
(Login required)
Tomsk State University, Russian Federation
DOI: 10.18287/JBPE25.11.030305
Abstract
Additive manufacturing of TiNi alloys has developed significantly in recent years. Such growth is due to the unique properties of the resulting designs − superelasticity, bending strength − stretching, corrosion, chemical and thermodynamic stability. In addition, three-dimensional (3D) printing technology significantly expanded the scope of use of this material in various applied areas from biomedicine (for printing implants and bone tissue engineering), to, for example, the automotive and aerospace industries. Despite the fact that 3D printing technology already has commercial solutions that allows producing complex-shaped structures, this area is in the stage of development. Of a particular interest is the optimization of printing process and the development of a quality control system (achieving the required parameters of porosity, roughness, minimizing defects such as cracks, contamination, delamination, surface and subsurface heterogeneities, surface quality, shrinkage, etc.). In this paper, an original non-destructive method for assessing the sintering temperature as an indirect measure of porosity of a material using optical coherence tomography (OCT) and machine learning methods is proposed. Random Forest Regression approach was used to predict depth maps and spatial statistics from the sintering temperature. The Random Forest model based on the first- and the second-order texture metrics of OCT images provided R² of about 0.95 for sintering temperature prediction.
Keywords
Full Text:
PDFReferences
1. V. E. Gunter, V. N. Khodorenko, and T. L. Chekalkin, “Medical materials and shape memory implants”, Publishing House of MIT, Tomsk (2011). ISBN:9785985890365.
2. J. Zhu, Q. Zeng, and T. Fu, “An updated review on TiNi alloy for biomedical applications,” Corrosion Reviews 37(6), 539–552 (2019).
3. W. Cai, Y. F. Zheng, X. Meng, and L. C. Zhao, “Superelasticity in TiNi alloys and its applications in smart systems,” Materials Science Forum 475, 1915–1920 (2005).
4. S. H. Mohammed, S. H. Shahatha, “Shape memory alloys, properties and applications: a review,” AIP Conference Proceedings, AIP Publishing 2593(1), 020008 (2023).
5. V. Shishkovsky, L. T. Volova, M. V. Kuznetsov, Yu. G. Morozov, and I. P. Parkin, “Porous biocompatible implants and tissue scaffolds synthesized by selective laser sintering from Ti and NiTi,” Journal of Materials Chemistry 18(12), 1309–1317 (2008).
6. Z. Wang, Y. Tan, and N. Li, “Powder metallurgy of titanium alloys: a brief review,” Journal of Alloys and Compounds 965, 171030 (2023).
7. S. G. Anikeev, N. V. Artyukhova, M. I. Kaftaranova, V. N. Khodorenko, E. V. Yakovlev, A. B. Markov, V. V. Promakhov, and O. R. Mamazakirov, “The influence of electron-beam treatment on the structure of a TiNi powder alloy obtained by calcium-hydride reduction,” Journal of Surface Investigation: X-ray, Synchrotron and Neutron Techniques 15, 1067–1071 (2021).
8. N. V. Artyukhova, Yu. F. Yasenchuk, K. Ji-Soon, and V. É. Gunther, “Reaction sintering of porous shape-memory Titanium−Nickelide-based alloys,” Russian Physics Journal 57, 1313–1320 (2015).
9. I. А. Drozdov, “Formation of intermetallics in a porous powder Titanium-Nickel diffusion couple,” Powder Metallurgy and Metal Ceramics 34(5,6), 62–70 (1995).
10. C. Velmurugan, V. Senthilkumar, and P. S. Kamala, “Microstructure and corrosion behavior of niti shape memory alloys sintered in the SPS process,” International Journal of Minerals, Metallurgy, and Materials 26(10), 1311–1321 (2019).
11. T. Miao, S. Zhan, X. Chen, and L. Hu, “Effect of sintering temperature on microstructure characteristics of porous NiTi alloy fabricated via elemental powder sintering,” Materials 17(3), 743 (2024).
12. D. Zhao, Y. Yang, J. Liu, G. Yang, Y. Qin, and D. Yin, “Effect of soaking time on the preparation of porous NiTi alloy during fields-activated micro-sintering and forming technology,” in 4th International Conference on New Forming Technology (ICNFT 2015), MATEC Web of Conferences 21, 10007 (2015).
13. D. F. Williams, “On the mechanisms of biocompatibility”, Biomaterials 29(20), 2941–2953 (2008).
14. N. Viknianshchuk, A. I. Mishanin, S. I. Tverdokhlebov, and A.S. Golovkin, “Approaches to biomaterials testing according to modern biocompatibility paradigm,” Translational Medicine 4(1), 29–40 (2017).
15. M. Bahraminasab, B. B. Sahari, “NiTi shape memory alloys, promising materials in orthopedic applications,” in Shape Memory Alloys − Processing, Characterization and Applications, F. M. B. Fernandes (Ed.), 262–278 (2013).
16. J. L. Hernandez, K. A. Woodrow, “Medical applications of porous biomaterials: features of porosity and tissue-specific implications for biocompatibility,” Advanced Healthcare Materials 11(9), 2102087 (2022).
17. H. J. Haugen, S. Bertoldi, “Characterization of morphology—3D and porous structure,” Characterization of Polymeric Biomaterials, 21–53 (2017).
18. Y. Yasenchuk, E. Marchenko, V. Gunther, A. Radkevich, O. Kokorev, S. Gunther, G. Baigonakova, V. Hodorenko, T. Chekalkin, J. Kang, S. Weiss, and A. Obrosov “Biocompatibility and clinical application of porous TiNi alloys made by self-propagating high-temperature synthesis (SHS),” Materials 12(15), 2405 (2019).
19. S. J. Hollister, “Porous scaffold design for tissue engineering,” Nature Materials 4(7), 518–524 (2005).
20. F. S. L. Bobbert, A. A. Zadpoor, “Effects of bone substitute architecture and surface properties on cell response, angiogenesis, and structure of new bone,” Journal of Materials Chemistry B 5(31), 6175–6192 (2017).
21. C. Torres-Sanchez, F. R. A. Al Mushref, M. Norrito, K. Yendall, Y. Liu, and P. P. Conway, “The effect of pore size and porosity on mechanical properties and biological response of porous titanium scaffolds,” Materials Science and Engineering: C 77, 219–228 (2017).
22. Y. Zhang, N. Sun, M. Zhu, Q. Qiu, P. Zhao, C. Zheng, Q. Bai, Q. Zeng, and T. Lu, “The contribution of pore size and porosity of 3D printed porous titanium scaffolds to osteogenesis,” Biomaterials Advances 133, 112651 (2022).
23. Q. S. Yan, “Prediction of porosity of porous NiTi alloy from processing parameters based on SVR,” Advanced Materials Research 393, 231–235 (2012).
24. V. Maitra, J. Shi, and C. Lu, “Robust prediction and validation of as-built density of Ti-6Al-4V parts manufactured via selective laser melting using a machine learning approach,” Journal of Manufacturing Processes 78, 183–201 (2022).
25. T. Kamal, A. Upadhyaya, and Gouthama, “Machine learning based sintered density prediction of bronze processed by powder metallurgy route,” Metals and Materials International 29(6), 1761–1774 (2023).
26. L. Mosser, O. Dubrule, and M. J. Blunt, “Reconstruction of three-dimensional porous media using generative adversarial neural networks,” Physical Review E 96(4), 043309 (2017).
27. V. V. Nikolaev, T. B. Lepekhina, G. V. Malkin, A. S. Garin, E. S. Marchenko, A. V. Dubrov, M. D. Khomenko, and Y. Kistenev, “Estimating the porosity of Nickel-Titanium (NiTi) implants using optical coherence tomography and machine learning”, Journal of Biomedical Photonics & Engineering 10(4), 112–120 (2024).
Сontact
34 Moskovskoe shosse, Samara, 443086, Russian Federation
Email: j-bpe@ssau.ru
Phone: +7-846-267-4550
© 2014-2025 J-BPE