An assessment of biomedical CoCrMo alloy fabricated by direct metal laser sintering technique for implant applications.

CoCrMo alloys have been used for several decades in implantable devices due to their favourable mechanical properties, low wear rate in addition to good biocompatibility and high corrosion resistance. These alloys are conventionally produced via casting and/or forging route, however additive manufacturing techniques being recently employed in their fabrication. In this work, CoCrMo samples were produced by direct metal laser sintering additive manufacturing process. The microstructure and surface composition were examined employing scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy (XPS). The corrosion resistance was measured in 0.14 M sodium chloride solution and in phosphate buffered solution (PBS) both with and without addition of albumin at pH 7.4 and 37 °C. For this, potentiodynamic tests in addition to electrochemical impedance spectroscopy were employed. The studied CoCrMo alloy exhibits a good corrosion resistance in solutions tested being the highest in PBS solution without albumin addition. The XPS analysis showed that the passive film composition and its thickness are not modified by the adsorbed layer. Microstructural analysis revealed occurrence of strain-induced martensitic transformation.

Automatic evaluation of nickel alloy secondary phases from SEM images.

Quantitative metallography is a technique to determine and correlate the microstructures of materials with their properties and behavior. Generic commercial image processing and analysis software packages have been used to quantify material phases from metallographic images. However, these all-purpose solutions also have some drawbacks, particularly when applied to segmentation of material phases. To overcome such limitations, this work presents a new solution to automatically segment and quantify material phases from SEM metallographic images. The solution is based on a neuronal network and in this work was used to identify the secondary phase precipitated in the gamma matrix of a Nickel base alloy. The results obtained by the new solution were validated by visual inspection and compared with the ones obtained by a commonly used commercial software. The conclusion is that the new solution is precise, reliable and more accurate and faster than the commercial software.