Data analytics approach to predict the hardness of copper matrix composites

Copper matrix composite materials have exhibited a high potential in applications where excellent conductivity and mechanical properties are required. In this study, the machine learning models have been applied to predict the hardness of the copper matrix composite materials (CuMCs) produced via the powder metallurgy technique. Six different machine learning regression models were employed. The observed CuMCs were reinforced with two different volume fractions (2 vol.% and 7vol.%) of ZrB2 particles. Based on experimental work, we extracted the independent variables (features) like the milling time (MT, Hours), dislocation density (DD, m-2), average particle size (PS, μm), density (ρ, g/cm3), and yield stress (σ, MPa) while the Vickers hardness (MPa) was used as the dependent variable. Feature selection was performed by calculation the Pearson correlation coefficient (PCC) between the independent and dependent variables. The predictive accuracy higher than 80% was achieved for Cu-7vol.% ZrB2 and lower for the Cu-2vol.% ZrB2

Innovative processing routes in manufacturing of metal matrix composite materials

Metal matrix composites (MMCs) belong to a group of modern materials owing to their excellent technological, mechanical, and physical properties such as excellent wear and corrosion resistance, high electrical and thermal conductivity, improved strength and hardness. Final properties of MMCs are affected equally by all steps of its manufacturing process. It is shown that by using adequate process parameters to obtain starting materials (reaching the specific size, shape, and reactivity) the control of volume fraction and distribution of reinforcements within the matrix can be achieved. For this purpose, mechanical alloying has been appointed as a good approach. MMCs can be produced using powder metallurgy, ingot metallurgy, and additive manufacturing techniques. Combining high-energy ball milling with these techniques enables the design of an innovative processing route for MMCs manufacturing. Mechanochemical process (achieved using high-energy ball milling) was employed in three manufacturing procedures: hot pressing, compocasting, and laser melting/sintering for obtaining of the suitable powder. These production routes for MMCs manufacturing were the subject of this work. The aim of MMCs design is to establish an optimal combination of production techniques merged into the cost-effective fabrication route for obtaining MMCs with required properties

Predicting the modulus of elasticity of biocompatible titanium alloys using machine learning

Titanium alloys are widely employed in various fields, particularly in biomedical engineering, due to their mechanical and corrosion resistance properties combined with good biocompatibility. The modulus of elasticity is a distinguishing feature of this group of materials compared to others used for similar purposes. A database of approximately 238 titanium alloys free of toxic elements was compiled for this study. The influence of different factors (such as alloy element proportions, density, and specific heat) on the modulus of elasticity was predicted using four methods: support vector machine, XGBoost, Neural Network, and Random Forest. The Random Forest mean absolute error (MAE) of 7.33 GPa, falls within the range of experimentally obtained absolute errors in the literature (up to about 11 GPa). A strong correlation (R2 = 0.72) was observed between experimental and predicted data. Lastly, specific alloying element regions were identified for the modulus of elasticity, which can be used to design new biocompatible titanium alloys in the future

X-Ray analysis by Williamson-Hall and stereological analysis of mechanically alloyed Cu-Zr-B alloys

Ternary Cu-2.71Zr-2.27B (wt.%) alloys were fabricated using powder metallurgy, i.e., mechanical alloying followed by cold pressing and sintering. Influence of the mechanical alloying parameters on microstructural and morphological changes of Cu-Zr-B powder mixture was investigated using scanning electron microscopy and X-ray diffraction. Stereological analysis was employed to determine changes in size and shape of copper particles during 40 hours of mechanical alloying. It was shown that with an increase in mechanical alloying time, the size of copper powder decreases. Williamson-Hall analysis was used to calculate crystallite sizes (D, nm), lattice parameter (nm), lattice strain (ε, %), and dislocation density (ρ, m-2). It was shown that with increasing mechanical allo ying time, lattice parameter as well as lattice strain both increases. Particles undergo high forces through ball-particle-ball and wall-particle-ball collisions during mechanical alloying. These collisions induce accumulation of dislocations in copper matrix and a decreasing in its crystallite size due to dominant plastic deformation mechanisms. Dislocation densities reach its maximum value at around 30 hours of mechanical alloying, after which they decrease owing to the recrystallization of copper matrix

Effect of process parameters on the phase transformation kinetics in copper-based alloys and composites

Copper-based alloys and composites, owing to their convenient properties, are being considered essential materials in various industries. Since copper possesses an ability to develop high corrosion resistance, putting it in the domain of a desirable material in the manufacturing of valves, pipes, and also systems that carry industrial gases and aqueous fluids. Its usage is also invaluable for cables and electrical wires. This review paper describes diversity in copper alloy processing techniques (powder and ingot metallurgy) which are alongside the phase transformation kinetics interpreted and explained in detail. Furthermore, the focus is put on the copper alloys, as well as the kinetics present in these systems, with the application being highlighted. Correlation between physical properties and phase transformation kinetics in copper alloys is made. It is shown that if certain alloying elements are to be added, different properties could be improved. The effect of phase precipitation on phase transformation kinetics of copper alloys is shown by studying the Cu-15Ni-8Sn alloy

Transformation of Cs-exchanged clinoptilolite to CsAlSi5O12 by hot-pressing

Dense CsAlSi5O12 was successfully obtained by hot pressing of Cs-exchanged clinoptilolite at 900 degrees C. Simultaneous application of high temperature and mechanical pressure allowed formation of CsAlSi5O12 at temperature considerably lower than 1150 degrees C which was the lowest reported temperature of CsAlSi5O12 formation in pressureless sintered Cs-exchanged clinoptilolite. CsAlSi5O12 formation was preceded by complete amorphisation of Cs-exchanged clinoptilolite in temperature range between 700 and 900 degrees C. Bearing in mind that clinoptilolite possesses high affinity for Cs cation it is believed that hot pressing of Cs-exchanged clinoptilolite might be an efficient way to immobilize radioactive Cs by its incorporation into crystal lattice of stable CsAlSi5O12. The samples sintered at 950 degrees C had relative density about 84% of theoretical density and open porosity of only 6% which is expected to result in low Cs leaching rate