Fabrication and characterization of magnesium-based nanocomposites reinforced with Baghdadite and carbon nanotubes for orthopaedical applications

This study explores the potential of Mg/Carbon Nanotubes/Baghdadite composites as biomaterials for bone regeneration and repair while addressing the obstacles to their clinical application. BAG powder was synthesized using the sol-gel method to ensure a fine distribution within the Mg/CNTs matrix. Mg/1.5 wt.% CNT composites were reinforced with BAG at weight fractions of 0.5, 1.0, and 1.5 wt.% using spark plasma sintering at 450 degrees C and 50 MPa after homogenization via ball milling. The cellular bioactivity of these nanocomposites was evaluated using human osteoblast-like cells and adipose-derived mesenchymal stromal cells. The proliferation and attachment of MG-63 cells were assessed and visualized using the methylthiazol tetrazolium (MTT) assay and SEM, while AD-MSC differentiation was measured using alkaline phosphatase activity assays. Histograms were also generated to visualize the diameter distributions of particles in SEM images using image processing techniques. The Mg/CNTs/0.5 wt.% BAG composite demonstrated optimal mechanical properties, with compressive strength, yield strength, and fracture strain of 259.75 MPa, 180.25 MPa, and 31.65%, respectively. Machine learning models, including CNN, LSTM, and GRU, were employed to predict stress-strain relationships across varying BAG amounts, aiming to accurately model these curves without requiring extensive physical experiments. As shown by contact angle measurements, enhanced hydrophilicity promoted better cell adhesion and proliferation. Furthermore, corrosion resistance improved with a higher BAG content. This study concludes that Mg/CNTs composites reinforced with BAG concentrations below 1.0 wt.% offer promising biodegradable implant materials for orthopedic applications, featuring adequate load-bearing capacity and improved corrosion resistance. (c) 2024 Chongqing University. Publishing services provided by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )