The Ti-19Nb-2.5Fe-6Sn alloy subjected to proper heat treatments is a promising material to be applied in orthopedic implants. This type of Ti alloy presents relatively low cost, good biocompatibility, and reasonable mechanical strength combined with low elastic modulus. In such an alloy, Fe improves mechanical strength while ω phase precipitation can be controlled by Sn addition. In this work, samples of the Ti-19Nb-2.5Fe-6Sn (wt.%) alloy were prepared by arc melting, hot swaging, and solution heat treatment. Results from the literature combined with thermodynamic simulations, differential scanning calorimetry (DSC), and heating/cooling experiments coupled with microstructural analyses were applied to determine the β transus temperature of this alloy. Following, the samples were solution heat treated in the β field and continuously cooled to room temperature at different rates. The effects of cooling rates on intergranular and intragranular α phase precipitation were evaluated. It was found that low cooling rates lead to intergranular precipitation while moderate cooling rates provide more expressive intragranular precipitation.

Additive Manufacturing technology has continually advanced, allowing microstructure and property optimization. In recent years, several studies have been carried out with the aim of understanding mechanisms of formation and evolution of the microstructure and, consequently, their influence on mechanical properties. However, correlations between microstructure and corrosion properties are not completely understood, making more systematic investigations necessary. In this work, samples of the Ti-6Al-4V alloy were produced by combining different laser powers and scanning speeds in order to generate different energy density values (VED) with subsequent microstructures and properties. The samples were characterized by optical and scanning electron microscopy, hardness and relative density. Complementarily, corrosion tests were carried out. For the entire set of parameters used, the processed samples showed the formation of acicular martensite α´, followed by different levels of porosity depending on the applied energy density. VED proved to be an important control parameter, and the best combinations of hardness and corrosion resistance were obtained for the parameter ratio that generated energy densities greater than 100 J/mm3.

The mechanical behavior of metastable β Ti alloys can be controlled through heat treatments. Thus, the relationship between the precipitation of α phase and the mechanical properties of these alloys is of special interest. In this work, the microstructure evolution of Ti-30Nb-3Fe alloy during aging heat treatments was evaluated using optical microscopy, scanning electron microscopy and X-ray diffraction. Moreover, Vickers hardness and elastic modulus were measured as a function of aging time. Finally, the ultimate strength and ductility of the alloy aged at 500 °C was assessed by tensile tests. In comparison to a Ti-30Nb alloy, the addition of Fe lowered the β-transus temperature, decreased the martensite start temperature to a value below room temperature, increased the precipitation temperature and reduced the dissolution temperature of ω phase, and lastly, decreased the α phase precipitation temperature. Low heating rates enabled isothermal ω phase precipitation and growth, providing favorable conditions for α phase precipitation and increasing the amount of α phase precipitates. Compared to the solution heat-treated and water-quenched condition, aging heat-treated Ti-30Nb-3Fe alloy presented higher Vickers hardness and mechanical strength, without significant loss of ductility.

The application of cellular automata in materials science requires the conversion of the automata's rules and abstract general properties to rules and properties associated with the material and phenomena under study. In this paper we propose a model which uses cellular automata to simulate recrystallization and grain growth during isothermal and non-isothermal treatments of cold worked polycrystalline materials. The algorithm's spatial and temporal scaling is based on known experimental results for recrystallization and grain growth in highly cold-worked commercially pure titanium grade 2. In the recrystallization, the best agreement between experimental and computational results in terms of the process kinetics and the average diameter of recrystallized grains is obtained from a nucleation model that considers the temperature-dependent nuclei formation rate. In the simulation of grain growth after primary recrystallization, the results indicate the normal growth of an equiaxed grain structure whose kinetics and dimensions are comparable to those observed experimentally.