Surface properties of titanium obtained by different printing parameters - Microstructural, microbiological and biological behavior

Abstract

Understanding the effect of the microstructural characteristics of titanium implants obtained by the additive manufacturing (AM) technique, at different angles and post-processing, on their osteogenic potential and microbial profile will guide the development of precision, individualized devices for specific applications. With the advances that have been made in titanium surface engineering and medical/dental AM techniques, the time has come to integrate the various areas of knowledge through multi-, inter- and transdisciplinarity, in order to understand the effects generated by the AM process at an atomic, molecular and structural level. While most current studies are based on the development of different surface treatments, the boldness of this project lies in using technologies to determine which titanium microstructure parameters, generated by the laser sintering process, are capable of favoring bone biology and preventing microbial contamination. In view of this, the aim of this study will be to correlate the microstructural characteristics of Ti6Al4V samples, obtained using the MA technique by selective laser melting (SLM), with their osteogenic potential and microbial profile. The SLM surface will be analyzed in the form of discs and characterized using quantum tunneling techniques such as scanning tunneling microscopy (STM), atomic force microscopy (AFM), 3D laser confocal microscopy and scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), electron backscatter diffraction (EBSD), wettability and surface free energy. The osteogenic potential will be assessed by analyzing cell proliferation, adhesion and morphology, alkaline phosphatase activity, expression of osteogenic genes by real-time PCR and mineralization of the extracellular matrix. The quantification, diversity and relative abundance of microorganisms will be determined using 16S rRNA-based PCR gene sequencing, as well as microbial adhesion analysis. The results obtained will be subjected to parametric or non-parametric tests, depending on the distribution of the data (±=0.05). (AU)