Nanomaterials have demonstrated significant potential in enhancing the performance and functionality of composite materials across various industrial applications. This review delves into the unique properties of nanomaterials, with a particular focus on carbon-based nanomaterials, and presents key findings on their effectiveness in improving composite performance. The study emphasizes specific nano-based composite materials, highlighting their substantial promise in advancing the field of nanocomposites. Additionally, it addresses the challenges associated with the production and utilization of nanocomposite materials and discusses potential solutions to overcome these obstacles. The review concludes with recommendations for further research and innovation in nanocomposites to fully harness the advantages of these advanced materials for broader future applications.

This study explored the use of coir fibers extracted from coconut husks, an agro-waste material that constitutes sanitation and environmental pollution problems, as a reinforcing element in the production of metakaolin-based geopolymer composites with improved properties. A series of sample formulations were produced with varying coir fiber content (0.5, 1.0, 1.5, and 2.0 percent weight of metakaolin powder). The investigation was conducted using a 10 M NaOH alkaline solution with a 0.24 NaOH:Na₂SiO₃ mass ratio. Samples were cured for 28 days and tested for bulk density, ultrasonic pulse velocity (UPV), and compressive and flexural strength. Microstructural examinations such as X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM) were also performed on samples. Compressive strength values up to 21.25 N/mm² at 0.5% fiber content and flexural strength values up to 10.39 N/mm² at 1% fiber content were achieved in this study. The results obtained showed a decreasing bulk density of geopolymer samples (2113 kg/m³ to 2045 kg/m³) with increasing coir fiber content. The geopolymer samples had UPV values varying from 2315 m/s to 2717 m/s. Coir fiber with 0.5–1.0% fiber content can be incorporated into metakaolin-based geopolymers to produce eco-friendly composite materials with improved mechanical properties for sustainable development.

In this work, African maize cobs (AMC) were used as a rich biomass precursor to synthesize carbon material through a chemical activation process for application in electrochemical energy storage devices. The carbonization and activation were carried out with concentrated Sulphuric acid at three different temperatures of 600, 700 and 800 °C, respectively. The activated carbon exhibited excellent microporous and mesoporous structure with a specific surface area that ranges between 30 and 254 m²·g⁻¹ as measured by BET analysis. The morphology and structure of the produced materials are analyzed through Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Boehm titration, X-ray Photoelectron Spectroscopy (XPS) and Raman Spectroscopy. X-ray photoelectron spectroscopy indicates that a considerable amount of oxygen is present in the materials. The functional groups in the activated carbon enhanced the electrochemical performance and improved the material’s double-layer capacitance. The carbonized composite activated at 700 °C exhibited excellent capacitance of 456 F g⁻¹ at a specific current of 0.25 A g⁻¹ in 6 M KOH electrolyte and showed excellent stability after 10,000 cycles. Besides being a low cost, the produced materials offer good stability and electrochemical properties, making them suitable for supercapacitor applications.

This paper explores the effects of cement stabilization (5, 10, 15 and 20 wt%) on the structural and mechanical properties (compressive/flexural strengths and fracture toughness) of abandoned termite mound soil. The crystal structures and crystallinity of the constituents were determined using X-ray diffraction (XRD), while the microstructure was characterized via scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). The functional groups were also identified using Fourier transform infra-red spectroscopy (FTIR). The compressive/flexural strengths of the stabilized and un-stabilized termite mound soil were also studied after curing for 7, 14 and 28 days. The fracture toughness mechanism was analyzed with the aid of the R-curve method. Additionally, the underlying deformation and cracking mechanisms are elucidated via in-situ/ex-situ optical and scanning electron microscopy. The stabilized termite mound soil displayed the highest mechanical properties of 13.91 MPa, 10.25 MPa and 3.52 kPa·m^1/2 for compressive strength, flexural strength and fracture toughness, respectively. Besides displaying good mechanical properties and being locally available at no cost, renewable and an eco-friendly material, the termite mound soil will contribute to lowering the cost of housing in Sub-Saharan Africa, particularly in Chad.

The bioenergy sector in Nigeria currently lacks a proper assessment of resource availability. In this study, we investigated the bioenergy potential of agricultural residues and municipal solid and liquid waste using data from 2008 to 2018, and we applied a computational and analytical approach with mild assumptions. The technical potential for the production of cellulosic ethanol and biogas was estimated from the available biomass. It was discovered that higher energy was generated from biogas than cellulosic ethanol for the same type of residue. The available crop residue technical potential of 84 Mt yielded cellulosic ethanol and biogas of 14,766 ML/yr (8 Mtoe) and 15,014 Mm³/yr (13 Mtoe), respectively. Biogas has diverse applications ranging from heat to electric power generation and therefore holds great potential in solving the current electricity crisis in Nigeria. It will also position the nation towards achieving the 7th sustainable development goal (SDG 7) on clean and affordable energy.

Ground vibration induced by rock blasting is an unavoidable effect that may generate severe damages to structures and living communities. Peak particle velocity (PPV) is the key predictor for ground vibration. This study aims to develop a model to predict PPV in opencast mines. Two machine-learning techniques, including multivariate adaptive regression splines (MARS) and classification and regression tree (CART), which are easy to implement by field engineers, were investigated. The models were developed using a record of 1001 real blast-induced ground vibrations, with ten (10) corresponding blasting parameters from 34 opencast mines/quarries from India and Benin. The suitability of one technique over the other was tested by comparing the outcomes with the support vector regression (SVR) algorithm, multiple linear regression, and different empirical predictors using a Taylor diagram. The results showed that the MARS model outperformed other models in this study with lower error (RMSE = 0.227) and R² of 0.951, followed by SVR (R² = 0.87), CART (R² = 0.74) and empirical predictors. Based on the large-scale cases and input variables involved, the developed models should lead to better representative models of high generalization ability. The proposed MARS model can easily be implemented by field engineers for the prediction of blasting vibration with reasonable accuracy.