Islamic Azad University Mahshahr

Soil contamination by lead, zinc, iron, manganese, and copper is a widespread environmental issue associated with the mining industry. Primary sources include mining activities, production and processing operations, waste disposal and management practices, and atmospheric sediments. Soil contamination and degradation, water pollution impacting aquatic ecosystems, plant absorption leading to agricultural product contamination, health risks associated with exposure to lead, zinc, iron, manganese, and copper, along with effects on fauna and biodiversity, constitute the primary environmental and health impacts of contamination. In this study, diverse sampling and analysis methods, geographic information systems, and remote sensing techniques are investigated for monitoring and assessing soil contamination with these metals. Soil modification techniques, phytoremediation, and other strategies for reduction and modification are considered among the most crucial, alongside health protection and risk management strategies. Finally, the article explores innovative methods and solutions for mineral waste management and remediation, the application of green chemistry and sustainable practices in the mining industry, and the utilization of artificial intelligence for controlling heavy metal ion pollution.

In this work, the effects of the presence of a heat sink and a heat source and their lengths and locations and the entropy generation on MHD mixed convection flow and heat transfer in a porous enclosure filled with a Cu-water nanofluid in the presence of partial slip effect are investigated numerically. Both the lid driven vertical walls of the cavity are thermally insulated and are moving with constant and equal speeds in their own plane and the effect of partial slip is imposed on these walls. A segment of the bottom wall is considered as a heat source meanwhile a heat sink is placed on the upper wall of cavity. There are heated and cold parts placed on the bottom and upper walls, respectively, while the remaining parts are thermally insulated. Entropy generation and local heat transfer according to different values of the governing parameters are presented in detail. It is found that the addition of nanoparticles decreases the convective heat transfer inside the porous cavity at all ranges of the heat sink and source lengths. The results for the effects of the magnetic field show that the average Nusselt number decreases considerably upon the enhancement of the Hartmann number. Also, adding nanoparticles to a pure fluid leads to increasing the entropy generation for all values of D for λl=−λr= 1.

This study was allocated to synthesis Bi_xZn_1−xO (0.00 ≤ <italic>x</italic> ≤ 0.06) nanoparticles. In addition, to study the microstructural properties, crystal imperfections and the morphology for these samples.

Nowadays, epoxy composites are elements of engineering materials and systems. Although they are known as versatile materials, epoxy resins suffer from high flammability. In this sense, flame retardancy analysis has been recognized as an undeniable requirement for developing future generations of epoxy-based systems. A considerable proportion of the literature on epoxy composites has been devoted to the use of phosphorus-based additives. Nevertheless, innovative flame retardants have coincidentally been under investigation to meet market requirements. This review paper attempts to give an overview of the research on flame retardant epoxy composites by classification of literature in terms of phosphorus (P), non-phosphorus (NP), and combinations of P/NP additives. A comprehensive set of data on cone calorimetry measurements applied on P-, NP-, and P/NP-incorporated epoxy systems was collected and treated. The performance of epoxy composites was qualitatively discussed as Poor, Good, and Excellent cases identified and distinguished by the use of the universal Flame Retardancy Index (FRI). Moreover, evaluations were rechecked by considering the UL-94 test data in four groups as V0, V1, V2, and nonrated (NR). The dimensionless FRI allowed for comparison between flame retardancy performances of epoxy composites. The results of this survey can pave the way for future innovations in developing flame-retardant additives for epoxy.

This paper investigates the entropy generation and natural convection inside a C-shaped cavity filled with CuO-water nanofluid and subjected to a uniform magnetic field. The Brownian motion effect is considered in predicting the nanofluid properties. The governing equations are solved using the finite volume method with the SIMPLE (Semi-Implicit Method for Pressure Linked Equations) algorithm. The studied parameters are the Rayleigh number (1000 ≤ Ra ≤ 15,000), Hartman number (0 ≤ Ha ≤ 45), nanofluid volume fraction (0 ≤ φ ≤ 0.06), and the cavity aspect ratio (0.1 ≤ AR ≤ 0.7). The results have shown that the nanoparticles volume fraction enhances the natural convection but undesirably increases the entropy generation rate. It is also found that the applied magnetic field can suppress both the natural convection and the entropy generation rate, where for Ra = 1000 and φ = 0.04, the percentage reductions in total entropy generation decreases from 96.27% to 48.17% for Ha = 45 compared to zero magnetic field when the aspect ratio is increased from 0.1 to 0.7. The results of performance criterion have shown that the nanoparticles addition can be useful if a compromised magnetic field value represented by a Hartman number of 30 is applied.

Abstract Epoxy resins (EPs) exhibit various extraordinary properties, including significant mechanical and thermal properties, low shrinkage, and high chemical resistance, opening a wide window of different applications such as adhesives, paints, coatings, etc. By contrast, EPs also have the undesirable behavior of being brittle and cannot sufficiently resist against the initiation and growth of cracks. Efforts are being made to enhance the toughening of EPs without sacrificing their other desirable properties. With the advent of nanotechnology, improving the toughening of EPs has gained momentum by incorporating different modified and unmodified nanofillers into these polymers. Since the discovery of carbonaceous nanofillers, especially carbon nanotubes (CNTs) and graphene (Gr), significant progress has been made in the development of EP‐based composites incorporating these nanofillers and their hybrids. The current review presents research progress during the last six years on the toughening of EPs using CNTs, Gr, and CNT‐Gr hybrids. Special attention is given to the chemical functionalization of these nanofillers, which has been demonstrated over and over again to significantly affect nanofiller dispersion in the EP matrix and subsequently its fracture properties. Details on the various toughening mechanisms of EP‐based composites are further provided.

The effect of source/sink heat location and size on Magneto-hydrodynamic mixed convection in hybrid nanofluid of Al2O3-Cu/Water within the L-shaped cavity is studied in this paper. Two uniform heat sources are put at the corners of the bottom walls of enclosure and the beginning and the end of L-shape enclosure set to be at the cold temperature. The other parts of enclosure’s walls are supposed to be insulated. The finite difference method and Boussinesq approximation is utilized to discrete the governing equations. The fundamental flow physics and thermal behavior are explored in terms of pertinent parameters such as the effects of sink/source heat generation, magnetic field and angle, Hartmann number, cavity length ratio, and hybrid volume fraction on average and surface Nusselt number, streamlines, isotherms, and entropy generation are studied. The results demonstrate that maximum amount of the sink power causes the best heat transfer performance.

Sustainable polymers are emerging fast and have received much more attention in recent years compared to petro-sourced polymers. However, they inherently have low-quality properties, such as poor mechanical properties, and inadequate performance, such as high flammability. In general, two methods have been considered to tackle such drawbacks: (i) reinforcement of sustainable polymers with additives; and (ii) modification of chemical structure by architectural manipulation so as to modify polymers for advanced applications. Development and management of bio-based polyurethanes with flame-retardant properties have been at the core of attention in recent years. Bio-based polyurethanes are currently prepared from renewable, bio-based sources such as vegetable oils. They are used in a wide range of applications including coatings and foams. However, they are highly flammable, and their further development is dependent on their flame retardancy. The aim of the present review is to investigate recent advances in the development of flame-retardant bio-based polyurethanes. Chemical structures of bio-based flame-retardant polyurethanes have been studied and explained from the point of view of flame retardancy. Moreover, various strategies for improving the flame retardancy of bio-based polyurethanes as well as reactive and additive flame-retardant solutions are discussed.

Investigation of MWCNTs localization and its impact on rheological, electrical, and thermal properties of PC/ABS(75/25)/MWCNTs blend nanocomposites.

The micro-sized nanoporous Y-type zeolites were silylated and incorporated into a homogeneous cellulose acetate membrane which resulted in an improvement in the morphology and CO2/N2 separation properties of the corresponding mixed matrix membranes.

A novel mixed matrix membrane (MMM) was fabricated by incorporating micro-sized nano-porous sodium zeolite-Y (NaY zeolite) into Matrimid®5218 matrix.

This study proposes a Modified Honey Bee Mating Optimisation (MHBMO) to solve the dynamic optimal power flow (DOPF) problem of power system considering the valve-point effects. DOPF is a complicated non-linear problem that occupies an important role in the economic operation of power system. It has non-smooth and non-convex characteristics when generation unit valve-point effects are taken into account. Non-linear characteristics of the power generators and practical constraints, such as ramp rate constraint, transmission constraints and non-linear cost functions, are all considered for the realistic operation and they cause more complication of the proposed problem. Recently, evolutionary algorithms are devoted to solve compliment problems like the OPF problem. HBMO is one of the evolutionary algorithms considered as a typical swarm-based approach to optimisation, in which the search algorithm is inspired by the process of real honey-bee mating. Besides the privileges of HBMO, it has some drawbacks such as probability of trapped in local optima and converge to global optima in long time. Therefore this study proposes an algorithm profit from a mutation to overcome the above drawbacks. In order to validate the proposed algorithm, it has been tested on the 14, 30 and 118-bus test systems. The proposed algorithm provides better results in comparison with original HBMO and other methods in the literature as demonstrated by simulation results.

This article is allocated to synthesizing pure ZnO and Rb-doped ZnO nanoparticles, Rb x Zn 1− x O-NPs via the sol–gel technique and then studying the effect of Rb doping ZnO on the crystal structure, microstructure parameters and morphology of the host lattice.

Carbon dioxide enhanced shale gas recovery depends strongly on adsorption properties of carbon dioxide and methane. In this work, Least Squares Support Vector Machine (LSSVM) optimized by Particle Swarm Optimization, has been proposed to learn and then predict adsorption capacity of methane and carbon dioxide from pure and binary gas mixtures in Jurassic shale samples from the Qaidam Basin in China based on input parameters pressure, temperature, gas composition and TOC. A literature dataset of 348 points was applied to train and validate the model. The predicted values were compared with the experimental data by statistical and graphical approaches. The coefficients of determination of carbon dioxide adsorption were calculated to 0.9990 and 0.9982 for training and validation datasets, respectively. For CH4 the numbers are 0.9980 and 0.9966. The model was extrapolating reasonable trends beyond measurement ranges. More extensive datasets are needed to properly parameterize the role of shale properties.

Polypropylene (PP) is a commodity plastic known for high rigidity and crystallinity, which is suitable for a wide range of applications. However, high flammability of PP has always been noticed by users as a constraint; therefore, a variety of additives has been examined to make PP flame-retardant. In this work, research papers on the flame retardancy of PP have been comprehensively reviewed, classified in terms of flame retardancy, and evaluated based on the universal dimensionless criterion of Flame Retardancy Index (FRI). The classification of additives of well-known families, i.e., phosphorus-based, nitrogen-based, mineral, carbon-based, bio-based, and hybrid flame retardants composed of two or more additives, was reflected in FRI mirror calculated from cone calorimetry data, whatever heat flux and sample thickness in a given series of samples. PP composites were categorized in terms of flame retardancy performance as Poor, Good, or Excellent cases. It also attempted to correlate other criteria like UL-94 and limiting oxygen index (LOI) with FRI values, giving a broad view of flame retardancy performance of PP composites. The collected data and the conclusions presented in this survey should help researchers working in the field to select the best additives among possibilities for making the PP sufficiently flame-retardant for advanced applications.

The entropy generation due to magnetohydrodynamic mixed convection flow and heat transfer in a Gamma-shaped porous cavity is explored in this research by the finite volume technique. There exists an internal heating generation inside the cavity and the top and bottom walls are moving by constant velocities to induce forced convection. The cavity is filled with copper/water nanofluid and subjected to an inclined uniform magnetic field. A numerical simulation is performed to study the effects of several key parameters such as the Hartmann number, nanoparticle volume fraction, and the length and location of a heat source inside the Gamma-shaped cavity on the heat transfer performance. The numerical results are presented graphically in the forms of isotherm, streamline contour plots and changing Nusselt numbers and entropy generation. The increase of the Nusselt number with the volume fraction is more pronounced for the smallest heat source, a heat source placed at the lowest height from the bottom side, the lowest volumetric heat generation, the lowest imposed magnetic field, the lowest Darcy number, and for a porous media with the lowest solid to fluid thermal conductivity ratio. Increasing the nanoparticle volume fraction has a higher impact on the production of entropy than the enhancement in the heat transfer rate.

This contribution simulates the impact of partial slip on entropy generation due to magnetohydrodynamic, mixed convection of nanofluids in a lid-driven U-shaped cavity with discrete heating. The influence of the partial slip effect is proposed along the lid-driven vertical walls. A uniform heat flux source on the bottom wall is proposed; meanwhile, the two portions of the outer-upper horizontal walls are cooled isothermally. The remainder cavity walls are taken adiabatic. The governing equations are solved using the finite volume approach, and the outcomes are successfully validated against previous studies. Simulation results are presented and discussed for several cases with the impacts of the governing parameters on the heat transfer rate. Inspection of the results in mixed convective and entropy generation environments demonstrate that the average Nusselt number increases with the increase in the volume fraction of nanoparticles at AR = 0.1. For all values of D (heat source location), the Nusselt number increases by crossing the heat source and reaches its maximum value at the end of the source. Also, for all values of the aspect ratio, addition of nanoparticles into the base fluid leads to a loss in the thermal performance. Moreover, for all states of movement, addition of nanoparticles into the base fluid leads to an increase in the entropy.

Accurate prediction of mercury content emitted from fossil-fueled power stations is of the utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations’ boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model included coal characteristics and the operational parameters of the boilers. The dataset was collected from 82 sample points in power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of the ANFIS-PSO, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively. Furthermore, relative errors between the acquired data and predicted values were between −0.25% and 0.1%, which confirm the accuracy of the model to deal non-linearity and represent the dependency of flue gas mercury content into the specifications of coal and the boiler type.

Citric acid (CA)–modified hydrogels from corn starch and chitosan were synthesized using a semidry condition. This strategy has great benefits of friendly environment because of the absence of organic solvents and compatible with the industrial process. The hydrogel blends were prepared with starch/chitosan ratios of 75/25, 50/50, and 25/75. The thermal stability, morphology, water absorption, weight loss in water, and methylene blue absorption were determined. Multi‐carboxyl structure of CA could result in a chemical cross‐linking reaction between starch, chitosan, and CA. The cross‐linking reaction between free hydroxyl groups of starch, amino groups of chitosan, and carboxyl groups of CA has been confirmed by attenuated total reflectance infrared (ATR‐IR) spectroscopy, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA) analysis. The water absorption properties of CA‐modified hydrogel blends were increased significantly compared with the native starch and chitosan. Moreover, the hydrogel blends modified with CA showed good water resistance and gel content. The morphology study confirmed the complete chemical cross‐linking and porous structure of hydrogel blends. The hydrogel blend with the starch/chitosan ratio of 50/50 presented powerful absorption of methylene blue as well as chemical cross‐linking reaction and dense structure. In sum, the hydrogel blend comprising 50% starch and 50% chitosan has the potential to be applied for water maintaining at large areas, for example, in agriculture.

Multiple sclerosis is a complex autoimmune disorder which characterized by demyelination and axonal loss in the central nervous system (CNS). Several evidences indicate that some new drugs and stem cell therapy have opened a new horizon for multiple sclerosis treatment, but current therapies are partially effective or not safe in the long term. Recently, herbal therapies represent a promising therapeutic approach for multiple sclerosis disease. Here, we consider the potential benefits of some herbal compounds on different aspects of multiple sclerosis disease. The medicinal plants and their derivatives; Ginkgo biloba, Zingiber officinale, Curcuma longa, Hypericum perforatum, Valeriana officinalis, Vaccinium macrocarpon, Nigella sativa,Piper methysticum, Crocus sativus, Panax ginseng, Boswellia papyrifera, Vitis vinifera, Gastrodia elata, Camellia sinensis, Oenothera biennis, MS14 and Cannabis sativa have been informed to have several therapeutic effects in MS patients.