This paper discusses the influence of fiber reinforcement on the properties of geopolymer concrete composites, based on fly ash, ground granulated blast furnace slag and metakaolin. Traditional concrete composites are brittle in nature due to low tensile strength. The inclusion of fibrous material alters brittle behavior of concrete along with a significant improvement in mechanical properties i.e., toughness, strain and flexural strength. Ordinary Portland cement (OPC) is mainly used as a binding agent in concrete composites. However, current environmental awareness promotes the use of alternative binders i.e., geopolymers, to replace OPC because in OPC production, significant quantity of CO₂ is released that creates environmental pollution. Geopolymer concrete composites have been characterized using a wide range of analytical tools including scanning electron microscopy (SEM) and elemental detection X-ray spectroscopy (EDX). Insight into the physicochemical behavior of geopolymers, their constituents and reinforcement with natural polymeric fibers for the making of concrete composites has been gained. Focus has been given to the use of sisal, jute, basalt and glass fibers.

The photocatalytic activity of eco-friendly zinc oxide doped silica nanocomposites, synthesized via a co-precipitation method followed by heat-treatment at 300, 600, and 900 °C is investigated. The samples have been characterized by employing X-ray diffraction method, and further analyzed using the Rietveld Refinement method. The samples show a space group P63mc with hexagonal structure. The prepared composites are tested for their photocatalytic activities for the degradation of methyl orange-based water pollutants under ultra-violet (UV) irradiation using a 125 W mercury lamp. A systematic analysis of parameters such as the irradiation time, pH value, annealing temperatures, and the concentration of sodium hydroxide impacting the degradation of the methyl orange (MO) is carried out using UV-visible spectroscopy. The ZnO.SiO₂ nanocomposite annealed at 300 °C at a pH value of seven shows a maximum photo-degradation ability (~98.1%) towards methyl orange, while the photo-degradation ability of ZnO.SiO₂ nanocomposites decreases with annealing temperature (i.e., for 600 and 900 °C) due to the aspect ratio. Moreover, it is seen that with increment in the concentration of the NaOH (i.e., from 1 to 3 g), the photo-degradation of the dye component is enhanced from 20.9 to 53.8%, whereas a reverse trend of degradation ability is observed for higher concentrations.

Zinc oxide (ZnO) in various nano forms (nanoparticles, nanorods, nanosheets, nanowires and nanoflowers) has received remarkable attention worldwide for its functional diversity in different fields i.e., paints, cosmetics, coatings, rubber and composites. The purpose of this article is to investigate the role of photocatalytic activity (role of photogenerated radical scavengers) of nano ZnO (nZnO) for the surface activation of polymeric natural fibres especially cotton and their combined effect in photocatalytic applications. Photocatalytic behaviour is a crucial property that enables nZnO as a potential and competitive candidate for commercial applications. The confirmed features of nZnO were characterised by different analytical tools, i.e., scanning electron microscopy (SEM), field emission SEM (FESEM) and elemental detection spectroscopy (EDX). These techniques confirm the size, morphology, structure, crystallinity, shape and dimensions of nZnO. The morphology and size play a crucial role in surface activation of polymeric fibres. In addition, synthesis methods, variables and some of the critical aspects of nZnO that significantly affect the photocatalytic activity are also discussed in detail. This paper delineates a vivid picture to new comers about the significance of nZnO in photocatalytic applications.

The term aerogel is used for unique solid-state structures composed of three-dimensional (3D) interconnected networks filled with a huge amount of air. These air-filled pores enhance the physicochemical properties and the structural characteristics in macroscale as well as integrate typical characteristics of aerogels, e.g., low density, high porosity and some specific properties of their constituents. These characteristics equip aerogels for highly sensitive and highly selective sensing and energy materials, e.g., biosensors, gas sensors, pressure and strain sensors, supercapacitors, catalysts and ion batteries, etc. In recent years, considerable research efforts are devoted towards the applications of aerogels and promising results have been achieved and reported. In this thematic issue, ground-breaking and recent advances in the field of biomedical, energy and sensing are presented and discussed in detail. In addition, some other perspectives and recent challenges for the synthesis of high performance and low-cost aerogels and their applications are also summarized.

Polymer based textile composites have gained much attention in recent years and gradually transformed the growth of industries especially automobiles, construction, aerospace and composites. The inclusion of natural polymeric fibres as reinforcement in carbon fibre reinforced composites manufacturing delineates an economic way, enhances their surface, structural and mechanical properties by providing better bonding conditions. Almost all textile-based products are associated with quality, price and consumer’s satisfaction. Therefore, classification of textiles products and fibre reinforced polymer composites is a challenging task. This paper focuses on the classification of various problems in textile processes and fibre reinforced polymer composites by artificial neural networks, genetic algorithm and fuzzy logic. Moreover, their limitations associated with state-of-the-art processes and some relatively new and sequential classification methods are also proposed and discussed in detail in this paper.

This paper presents a novel meta-heuristic approach based on the crow search algorithm (CSA) for solving the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a nonlinear optimization problem designed to minimize power losses while satisfying the required constraints. The CSA is a recent efficient approach that depends on the intelligent behavior of crows. Nowadays, it has been used to solve many complex engineering optimization problems where it has proven its power and effectiveness. Motivated by the high ability in solving complex optimization problems and faster convergence of CSA, this paper proposes a novel approach to solve the ORPD problem. Furthermore, the settings of control variables such as generator terminal voltage, tap changer positions, and capacitor banks are determined to achieve the minimum total power loss while satisfying a set of nonlinear constraints. The accuracy and the performance of the proposed algorithm were performed and compared to other meta-heuristic algorithms reported in the literature. Several tests are applied on two standard test systems, including IEEE 14-bus and IEEE 30-bus as well as on the large-scale Tunisian 86-bus system. In addition, a sensitivity analysis has been performed to valid the performance of the CSA in solving the ORPD problem. We demonstrate that the proposed CSA provides a supremacy results and statistically significant in solving ORPD problems (for IEEE-14 bus $p<0.0006$ , for IEEE-30 bus $p<0.006$ , and for Tunisian 86-bus $p<0.0000001$ ).