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Over the years, engineering materials are being developed due to the need for better service performance. Wear, a common phenomenon in applications requiring surface interaction, leads to catastrophic failure of materials in the industry. Hence, preventing this form of degradation requires the selection of an appropriate surface modification technique. Laser surface modification techniques have been established by researchers to improve mechanical and tribological properties of materials. In this chapter, adequate knowledge about laser surface cladding and its processing parameters coupled with the oxidation, wear and corrosion performances of laser-modified titanium has been reviewed.

Quenching is one of the major processes of heat treatment of medium carbon steel that aims at improving its mechanical properties. However, the effectiveness of this process is dependent on several control factors that must be maximized to obtain optimum results in terms of hardness, yield strength, ultimate tensile strength among others. This study aims at optimizing the process of improving the mechanical properties of medium carbon steel by varying some key factors like the quenchant used (A), heat treatment temperature (B), and soaking time (C). The measured responses in this study were the hardness, yield strength (YS), and ultimate tensile strength (UTS). Optimization was conducted in two stages. The first stage dealt with the mono-optimization of process parameters using Taguchi's Signal-to-Noise (S/N) ratio. A total of nine (9) experiments were performed based on standard L9 orthogonal array because each of the three control factors has three (3) levels. The second stage was multi-objective optimization using Taguchi-based grey relational analysis (GRA). The optimal conditions for hardness, YS, and UTS were obtained at A 2 B 3 C 3 , A 3 B 2 C 3 , and A 3 B 3 C 3 , respectively. Using ANOVA as statistical analysis, it was observed that the soaking time was the main control factor for all three measured responses (31.95% contribution ratio for hardness, 62.46%, and 66.76% for YS and UTS, respectively), while the quenchant had the least contribution. Analysis of the Taguchi-based GRA revealed that the results obtained are in total conformance to that of the Taguchi method, with soaking time having the highest contribution ratio of 69.41%.

The quality and performance of composite-based materials are functions of their mechanical properties. Hence, a scientific basis is needed for the determination of the feasible combination of process parameters that will bring about excellent mechanical properties. This study examines the potential of artificial neural network (ANN) for the prediction of mechanical properties, namely density and hardness of graphene nanoplatelet (GNP)/polylactic acid (PLA) nanocomposite developed under various operating conditions of spark plasma sintering (SPS) technique. A back-propagation having a 2-12-2 architecture and Levenberg-Marquardt algorithm was developed to predict the mechanical performance in terms of density and hardness property of GNP/PLA nanocomposites. The predictions of the modelled results were compared with those of the experimental value obtained. The model gave a low rootmean-squared error and performed well with the correlation coefficient (R) for both outputs; density (0.95497) and hardness (0.9832) found to be close to 1. The results of the predicted data were discovered to be very consistent with the values obtained

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To enhance the energy security and promote energy diversity, biomass sources of energy are viable resources worldwide. Bioenergy is an organic source of power derived from various feedstock including fuel wood, energy crops, solid wastes, and residues of plants. This book chapter explores the use of biomass in Africa and the technical and economic potential of these resources for energy supply in the continent. Findings of literature revealed that the potential of biomass is high in Africa due to availability of land, its preference due to limited electricity supply and the exorbitant nature of fossil fuels, the assorted variety of energy crops suitable for growth in the continent and the green nature associated with the resource. The chapter also established that bioenergy is renewable and not carbon neutral. As such, accurate computation of its resultant greenhouse gas emissions based on their sequestration and emission rates is strongly advised to optimize biomass for energy utility and sustainability compared to conventional energy sources.

Bamboo fibers (BF) treated in 1.3 Molar NaOH and particulate coconut shell (PCS) sieved to − 45 µm were incorporated into polyvinyl chloride (PVC) matrix towards improving the properties of PVC composite for ceiling boards and insulating pipes which sags and degrade with time needing improvement in properties. The process was carried out via compression moulding applying 0.2 kPa pressure and carried out at a temperature of 170 °C. Composites developed were grouped according to their composition. Groups A, B, C, and D were infused with 2, 4, 6 and 8 wt% PCS at constant amount, respectively. Each group was intermixed with a varying proportions of BF (0–30 wt% at 5% interval). Tests carried out on the samples produced revealed that the yield strength, modulus of elasticity, flexural strength, modulus of rupture were enhanced with increasing BF proportion from 0 to 30 wt% BF at 2 wt% constant PCS input. Thermal and electrical properties trended downward as the fiber content reduced even as the hardness was enhanced with PCS/BF intermix which was also reflected in the wear loss index. Impact strength was highest on the infix of 4 wt% PCS and 15 wt% BF. Compressive strength was better boasted with increasing fiber and PCS amount but 8 wt% PCS amounted to depreciation in trend. It was generally observed that PCS performed optimally at 2 wt% incorporation while beyond that resulted in lowering of strength. Blending of the two variable inputs; 0–30 wt% BF and 2 wt% PCS presented better enhancement in properties.