Surface Characteristics and Bone Biocompatibility of Cold-Sprayed Porous Titanium on Polydimethylsiloxane Substrates.

A variant of the cold spray (CS) technique was applied for the functionalization of polymer-based materials such as polydimethylsiloxane (PDMS) to improve the extent of mammalian cell interactions with these substrates. This was demonstrated by the embedment of porous titanium (pTi) into PDMS substrates using a single-step CS technique. CS processing parameters such as gas pressure and temperature were optimized to achieve the mechanical interlocking of pTi in the compressed PDMS to fabricate a unique hierarchical morphology possessing micro-roughness. As evidenced by the preserved porous structure, the pTi particles did not undergo any significant plastic deformation upon impact with the polymer substrate. The thickness of the particle embedment layer was determined, by cross-sectional analysis, ranging from 120 µm to over 200 µm. The behavior of osteoblast-like cells MG63 coming into contact with the pTi-embedded PDMS was examined. The results showed that the pTi-embedded PDMS samples promoted 80-96% of cell adhesion and proliferation during the early stages of incubation. The low cytotoxicity of the pTi-embedded PDMS was confirmed, with cell viability of the MG63 cells being above 90%. Furthermore, the pTi-embedded PDMS facilitated the production of alkaline phosphatase and calcium deposition in the MG63 cells, as demonstrated by the higher amount of alkaline phosphatase (2.6 times) and calcium (10.6 times) on the pTi-embedded PDMS sample fabricated at 250 °C, 3 MPa. Overall, the work demonstrated that the CS process provided flexibility in the parameters used for the production of the modified PDMS substrates and is highly efficient for the fabrication of coated polymer products. The results obtained in this study suggest that a tailorable porous and rough architecture could be achieved that promoted osteoblast function, indicating that the method has promise in the design of titanium-polymer composite materials applied to biomaterials used in musculoskeletal applications.

Neural Network Modelling of Track Profile in Cold Spray Additive Manufacturing.

Cold spray additive manufacturing is an emerging technology that offers the ability to deposit oxygen-sensitive materials and to manufacture large components in the solid state. For further development of the technology, the geometric control of cold sprayed components is fundamental but not yet fully matured. This study presents a neural network predictive modelling of a single-track profile in cold spray additive manufacturing to address the problem. In contrast to previous studies focusing only on key geometric feature predictions, the neural network model was employed to demonstrate its capability of predicting complete track profiles at both normal and off-normal spray angles, resulting in a mean absolute error of 8.3%. We also compared the track profile modelling results against the previously proposed Gaussian model and showed that the neural network model provided comparable predictive accuracy, even outperforming in the predictions at cold spray profile edges. The results indicate that a neural network modelling approach is well suited to cold spray profile prediction and may be used to improve geometric control during additive manufacturing with an appropriate process planning algorithm.