Microstructure and Mechanical Properties of Titanium–Equine Bone Biocomposites

Investigation of tribo-mechanical performance of alkali treated rice-husk and polypropylene-random-copolymer based biocomposites

This study was based on the experimental performance evaluation of a wood polymer composite (WPC) that was synthesized by incorporating untreated and treated rice husk (RH) fibers into a polypropylene random copolymer matrix. The submicron-scale RH fibers were alkali-treated to modify the surface and introduce new functional groups in the WPC. A compatibilizer (maleic anhydride) and a thermos-mechanical properties modifier (polypropylene grafted with 30 % glass fiber) were used in the WPC. The effects of untreated and treated RH on the WPC panels were studied using FESEM, FTIR, and microscope images. A pin-on-disk setup was used to investigate the bulk tribological properties of PPRC and WPC. The complex relationship between the friction coefficient of different loading of RH fibers in the WPC, as a function of sliding distance, was analyzed along with the temperature and morphology of the surface. It was observed that untreated RH acted as a friction modifier, while treated RH acted as a solid lubricant. Microhardness was calculated using the QCSM module on nanoindentation. It was found that untreated RH led to an increase in microhardness, while treated RH caused a decrease in hardness compared to PPRC.

Smart Web Service of Ti-Based Alloy’s Quality Evaluation for Medical Implants Manufacturing

The production of biocompatible medical implants is accompanied by technological and time costs. As a result, to be used in the human body, such a product must be of the highest quality. Assessing the quality of biomedical implants made of titanium alloys is relevant given their impact on the health and life of their wearer. In the case of the production of such implants by additive technologies, an important task is to evaluate the properties of the alloys from which it is made. The modern development of Artificial Intelligence allows replacing traditional assessment methods with machine learning methods for such assessment. Existing machine learning methods demonstrate very low classification accuracy, and existing hybrid systems, although increasing classification accuracy, are not sufficient to apply such schemes in practice. The authors improved the hybrid PNN-SVM system to solve this problem in this paper. It is based on the combining use of PNN, Ito Decomposition, and SVM. The PNN’s summation layer outputs were used as additional attributes to an initial dataset. Ito decomposition was used to nonlinearly model relationships between features of an extended dataset. Further classification is carried out using SVM with a linear kernel. The proposed approach’s modeling is performed based on a real-world dataset using the smart web service designed by the authors. Experimentally found an increase in the classification accuracy by 6% of the proposed system compared to existing ones. It makes it possible to use it in practice. Designed smart web service, in which the authors implemented both improved and existing hybrid classification schemes allows to quickly, easily, and without high qualification of the user to implement and explore in more detail chosen classification scheme when classification tasks in various fields of industry.

The Pressure Compaction of Zr-Nb Powder Mixtures and Selected Properties of Sintered and KOBO-Extruded Zr-xNb Materials

Materials were obtained from commercial zirconium powders. 1 mass%, 2.5 mass% and 16 mass% of niobium powders were used as the reinforcing phase. The SPS method and the extrusion method classified as the SPD method were used. Relative density materials of up to 98% were obtained. The microstructure of the sintered Zr-xNb materials differs from that of the extruded materials. Due to the flammability of zirconium powders, no mechanical alloying was used; only mixing of zirconium and niobium powders in water and isopropyl alcohol. Niobium was grouped in clusters with an average niobium particle size of about 10 μm up to 20 μm. According to the Zr-Nb phase equilibrium system, the stable phase at RT was the hexagonal α-phase. The tests were carried out for materials without the additional annealing process. The effect of niobium as a β-Zr phase stabilizer is confirmed by XRD. Materials differed in their phase composition, and for both methods the β-Zr phase was present in obtained materials. A very favorable effect of niobium on the increase in corrosion resistance was observed, compared to the material obtained from the powder without the addition of niobium.