In this study, a multi-objective optimization regarding the tribological characteristics of the hybrid composite with a base material of aluminum alloy A356 as a constituent, reinforced with a 10 wt.% of silicon carbide (SiC), size 39 µm, and 1, 3, and 5 wt.% graphite (Gr), size 35 µm, was performed using the Taguchi method, gray relational analysis (GRA), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making methods. Tribological tests were carried out on a “block on disc” type tribometer with lubrication. Load, sliding speed, and graphite mass concentration were analyzed as input parameters. As output parameters, wear rate and coefficient of friction were calculated. An analysis of variance (ANOVA) was conducted to identify all parameters that have a significant influence on the output multi-response. It was found that the normal load has the highest influence of 41.86%, followed by sliding speed at 32.48% and graphite addition at 18.47%, on the tribological characteristics of composites. Multi-objective optimization determined that the minimal wear rate and coefficient of friction are obtained when the load is 40 N, the sliding speed is 1 m/s, and the composite contains 3 wt.% Gr. The optimal combination of parameters achieved by GRA was also confirmed by the TOPSIS method, which indicates that both methods can be used with high reliability to optimize the tribological characteristics. The analysis of worn surfaces using scanning electron microscopy revealed adhesive and delamination wear as dominant mechanisms.

Magnesium (Mg) has attracted considerable attention as a biodegradable material for medical implants owing to its excellent biocompatibility, mitigating long-term toxicity and stress shielding. Nevertheless, challenges arise from its rapid degradation and low corrosion resistance under physiological conditions. To overcome these challenges, titanium (biocompatibility and corrosion resistance) has been integrated into Mg. The incorporation of titanium significantly improves mechanical and corrosion resistance properties, thereby enhancing performance in biological settings. Mg–Ti alloys are produced through mechanical alloying and spark plasma sintering (SPS). The SPS technique transforms powder mixtures into bulk materials while preserving structural integrity, resulting in enhanced corrosion resistance, particularly Mg80-Ti20 alloy in simulated body fluids. Moreover, Mg–Ti alloy revealed no more toxicity when assessed on pre-osteoblastic cells. Furthermore, the ability of Mg–Ti-based alloy to create composites with polymers such as PLGA (polylactic-co-glycolic acid) widen their biomedical applications by regulating degradation and ensuring pH stability. These alloys promote temporary orthopaedic implants, offering initial load-bearing capacity during the healing process of fractures without requiring a second surgery for removal. To address scalability constraints, further research is necessary to investigate additional consolidation methods beyond SPS. It is essential to evaluate the relationship between corrosion and mechanical loading to confirm their adequacy in physiological environments. This review article highlights the importance of mechanical characterization and corrosion evaluation of Mg–Ti alloys, reinforcing their applicability in fracture fixation and various biomedical implants.

The demand for an improvement in the tribological properties of lubricants used in various industrial plants, the automotive industry, and other power transmissions has resulted in the development of a whole family of improved lubricants based on nanotechnology. Especially important are nanotube additives, which significantly improve the tribological properties of lubricants, primarily by reducing the friction coefficient and wear of the coupled elements but also by reducing the temperature load and increasing the stability of the oil film between the lubricated surfaces. The properties of nanotube-based additives were further improved using elements such as metal oxides and compounds based on titanium, molybdenum, aluminum, etc. This paper presents the results obtained in the field of research and application of nanocomposite lubricant additives. It also gives a partial comparative analysis of the research conducted in this field. The primary goal of this paper is to analyze the research results in the field of the application of nanotubes in lubricants and to indicate the importance of their application, such as improving the tribological properties of machines and reducing power losses. Furthermore, this paper shows the negative impact of nanoparticles on the environment and human health and the costs of applying some types of nanoparticles.

Three-dimensional printing, or additive manufacturing, represents one of the fastest growing branches of the industry, and fused deposition modeling (FDM) is one of most frequently used technologies. Three-dimensional printing does not provide high-quality surfaces, so finishing is required, and milling is one of the best methods for improving surface quality. The combination of 3D printing and traditional manufacturing technologies is known as hybrid manufacturing. In order to improve quality and determine optimal machining parameters, researchers increasingly use artificial intelligence methods. In the context of manufacturing technologies, both multiple regression analysis (MRA) and artificial neural networks (ANNs) have proven to be highly reliable in predicting and optimizing machining processes. This study focuses on the use of MRA and an ANN to analyze the influence of machining parameters such as feed rate, depth of cut, and spindle speed on the surface roughness of a 3D-printed part in a milling process. The study compares the measured results with the outcomes obtained through MRA and the ANN to assess their effectiveness in predicting and optimizing surface roughness. The results show that higher accuracy was obtained from the ANN method.

In recent years, man has become more aware of the fact that today’s approach to energy saving is unsustainable. It is believed that in the near future, biomass will increasingly become of interest as one of the most promising renewable energy sources. The paper describes one example of the use of biomass (corn cob) in the process of production of thermal energy, i.e. in the process of seedcorn drying. The purpose of the investigations reported in the paper was to define the use of corn cob as a fuel to increase energy efficiency. Additionally, energy efficiency was explained through hourly consumption of corn cob in thermogens, which was further compared with consumption of conventional fuels (natural gas).