Abstract

The paper presents new results of manufacturing coatings by magnetron sputtering to improve the functional properties of joint endoprostheses. The antibacterial properties of Ti-Cu and Ta-Cu coatings deposited by DC multi-magnetron sputtering on Ti6Al4V alloy substrates subjected of gas-abrasive treatment have been investigated. The roughness of the substrate was measured by optical profilometry. The coating hardness and elastic modulus were estimated by nanoindentation methods; the adhesion characteristics were assessed by Rockwell test. Scanning electron microscopy with energy-dispersive X-ray analysis verified the application of coatings with 25 at.% Cu, at thicknesses of 2 μm and 10 μm to roughened Ti6Al4V alloy. All coatings demonstrated sufficient adhesion, whereas Ta-Cu coatings generally revealed higher hardness, while the elastic modulus decreased with increasing coating thickness. Staphylococcus aureus strains were used for in vitro study of the antibacterial properties of Ti-Cu and Ta-Cu coatings. The largest zones of inhibition of bacteria S. aureus 23 mm were observed for 10 µm Ta-Cu coating thickness. The release dynamics of Cu ions from Ta-Cu and Ti-Cu coatings into physiological solution analyzed over seven days via inductively coupled plasma mass spectrometry, matched the inhibition zone growth. The Ti-Cu and Ta-Cu coatings of 2 µm thickness provided weaker antibacterial effect. The optimal parameters of magnetron sputtering of antibacterial Ti-Cu and Ta-Cu coatings on Ti6Al4 alloy substrates were selected. These findings support the potential of these coatings in developing endoprosthesis implants with enhanced antimicrobial and wear-resistant properties

Details

Title
Antibacterial Ti-Cu and Ta-Cu Coatings for Endoprostheses Applied by Magnetron Sputtering onto Ti6Al4V Alloy
Author
Alontseva, Darya 1 ; Azamatov, Bagdat 2 ; Borisov, Alexander 3 ; Maratuly, Bauyrzhan 3 ; Yantsen, Yuliya Safarova 4 ; Voinarovych, Sergii 5 ; Dzhes, Alexey 3 ; Łatka, Leszek 6 

 School of Digital Technologies and Artificial Intelligence, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan 
 School of Digital Technologies and Artificial Intelligence, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan; Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan 
 Smart Engineering Competence Centre, D. Serikbayev East Kazakhstan Technical University, Ust-Kamenogorsk, Kazakhstan 
 Laboratory of Bioengineering and Regenerative Medicine, National Laboratory Astana, Nazarbayev University, Astana, Kazakhstan 
 E.O. Paton Electric Welding Institute of NAS of Ukraine, Kyiv, Ukraine 
 Department of Metal Forming, Welding and Metrology, Faculty of Mechanical Engineering, University of Science and Technology, Wrocław, Poland 
Pages
23-41
Publication year
2024
Publication date
2024
Publisher
De Gruyter Poland
ISSN
17302439
e-ISSN
20834799
Source type
Scholarly Journal
Language of publication
English; Polish
ProQuest document ID
3149068663
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/3.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.