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This study aims to minimize pollution and enhance the mechanical properties of SiC- reinforced aluminum- based composite by utilizing waste eggshell. Pollution is increasing at an exponential rate across the globe. Every nation is struggling to have strong control over the rise in pollution. Many countries are even successful in this regard, but only up to a certain extent; also, a lot of capital investment is required just to make arrangements for making and taking care of dedicated dump yards. An alternative approach in this regard could be using the unwanted wastes in some constructive works by recycling them. Novel strategies and dedicated cells for the research and development regarding the recycling of various kinds of wastes are continuously being developed by various nations.

This study attempts to make a hybrid composite of AA6101 alloy through the friction stir process (FSP) technique in which waste eggshells and SiC have been used as reinforcement particles. As the densities of eggshells, SiC show different values of densities to make them a single entity, they were subjected to ball milling for around 75 h. After ball milling, the reinforcement particles (eggshells and SiC) were distributed uniformly in the metal matrix (Al), and they appear as a single entity in the metal matrix composite.

The main objective of this study is to obtain an enhanced value of tensile strength of the final composite. Concerning this, the parameters of FSP, i.e. rotational speed and transverse speed, have been optimized through the Box–Behnken design approach. The optimized values of FSP parameters came out to be as 935.92 rpm of rotational speed and 22.48 mm/min as transverse speed value.

The results showed that the tensile strength and hardness of the composite developed at an optimum combination of FSP parameters enhanced by about 47.14 and 45.45%, respectively.

This study aims to attempt to make an aluminum-based composite using reinforcement such as graphite and fly ash. Pollution is an enhanced serious issue of concern for global. Industries play a major role in disturbing the balance of the environment system. Composite is made by using the stir casting technique. The waste that is generated by the industries if left untreated or left to be rotten at some place may prove fatal to invite various types of diseases. Proper treatment of these wastes is the need of the hour, the best way to get rid of such kinds of hazardous wastes is to use them by recycling.

Stir casting technique was used to make a composite. Graphite and fly ash were mixed with equal amounts of 2.5% to 15% in aluminum. The microstructure of composite formed after composite was noticed. After seeing the microstructure it was understood that reinforcement particles are very well-mixed in aluminum.

When graphite was mixed with 3.75% and 3.75% fly ash in aluminum, the strength of the composite came to about 171.12 MPa. As a result, the strength of the composite increased by about 16.10% with respect to the base material. In the same way, when 3.75% graphite and 3.75% fly ash were added to aluminum, the hardness of the composite increased by about 26.60%.

In this work, graphite and fly ash have been used to develop green metal matrix composite to support the green revolution as promoted/suggested by United Nations, thus reducing the environmental pollution. The addition of graphite and fly ash to aluminum reduced toughness. The thermal expansion of the composite has also been observed to know whether the composite made is worth using in higher temperatures.

Aluminium metal matrix composite (AMMC) is most popular in various industrial applications such as aerospace, automobile, marine, sports and many others. In common practice, silicon carbide, aluminum oxides, magnesium oxide, graphene and carbon nano tubes are the major reinforcing elements to prepare the AMMC. The purpose of this paper is to develop AMMCs reinforce with eggshell (ES) and rice husk ash (RHA).

Stir casting process is used for preparation of AMMC. From past few years, more emphasis is given to prepare the AMMCs using agro waste such as rice husk and/or ES as reinforcing materials. In this method, after the Al-matrix material is melted; it is stirred vigorously to form vortex at the surface of the melt, and the reinforcement material is then introduced at the side of the vortex. Stir casting process is a vortex and vigorous method to prepare the AMMCs. First, aluminum alloy (AA3105) is melted in the furnace when metal is in semisolid form. Reinforcement, i.e. ES and RHA are preheated at temperature 220°C and 260°C, respectively.

The result of AMMC shows that the tensile strength and hardness increased by using 22.41% and 45.5%, respectively, at 4.75 Wt.% each reinforcement, i.e. ES and RHA, and 1% Cr. The toughness and ductility of metal matrix composite (MMCs) have decreased up to 23.31% and 19.23% respectively by using 1% Cr, 4.75 wt. % ES and by 4.75 wt. % RHA of composite material.

In this work, Cr, waste ES and RHA have been used to develop green MMC to support the green revolution as promoted/suggested by United Nations, thus reducing the environmental pollution.

The purpose of this paper is to study Al-based green composite. To make composite samples of aluminium alloy (AA3105) with different weight percentages of rice husk ash (RHA) and eggshell (ES) particles as reinforcement, stir casting method was used.

Several other aspects, including the weight percent of reinforcing agent particles, the applied stress and the sliding speed, were taken into consideration. During the course of the wear test, the sliding distance that was recorded varied from a minimum of 1,000 m all the way up to a maximum of 3,135 m (10, 15, 20, 25 and 30 min). The typical range for normal loads is 8–24 N, and their speed is 1.58 m/s.

With the AA/ES/RHA composite, the wear rates decreases when the grain size of the reinforcing particles enhanced. Scanning electron microscopy images of worn surfaces show that at low speeds, delaminating and ploughing are the main causes of wear. At high speeds, ploughing is major cause of wear. Composites with better wear-resistant properties can be used in wide range of tribological applications, especially in the automotive industry. It was found that hardness increases at the same time as the weight of the reinforcement increases. Tensile and hardness were maximized at 10% reinforcement mix in Al3105.

In this work, ES and RHA has been used to develop green metal matrix composite to support green revolution as promoted/suggested by United Nations thus reducing the environmental pollution.

The purpose of this study to find an alternate method to minimize waste i.e., eggshell and rice husk ash. In this paper, eggshell (ES) and rice husk ash (RHA) particles are used as reinforcements for examining their effect on the coefficient of thermal expansion (CTE), grain size (GS) and corrosion behavior for developed composite material.

In this investigation, 5 Wt.% each of ES and RHA reinforcement particles have been introduced. To investigate the microstructures of the developed composite material, scanning electron microscope was used. Physical and mechanical properties of composite material are tensile strength and hardness that have been examined.

The result of this paper shows that number of grains per square inch for composition Al/5% ES/5% RHA composite was found to be 1,243. Minimum value of the volume CTE was found to be 6.67 × 10–6/°C for Al/5% ES/5% RHA composite. The distribution of hard phases of ES particles in metal matrix is responsible for improvements in tensile strength and hardness. These findings demonstrated that using carbonized ES as reinforcement provides superior mechanical and physical properties than using uncarbonized ES particles.

There are several articles examining the impact of varying Wt.% of carbonized ES and rice husk reinforcement on the microstructures and mechanical characteristics of metal composites. CTE, GS and corrosion behavior are among of the features that are examined in this paper.

This paper aims to extract the Cr from chrome containing leather waste (CCLW) in order to develop composite at optimum casting parameters using RSM technique. Chrome containing leather wastes (CCLW) is one of the significant cause of pollution that is exhaled by the leather industries. One of the technique to address the problem of pollution that is created by CCLW is to recycle it and produce some fruitful results from it. This will not only minimize the levels of harmful emissions to some extent but also give some befitting results.

The current work is all about exploring the ways by which CCLW could be used as a reinforcing material with aluminum. In this work, alumina has been used as a secondary reinforcement particle together with CCLW as with the help of stir casting process. The parameters of stir casting have been optimized by using “Response Surface Methodology.”

To maximize the hardness and tensile strength the values of optimal input casting parameters as found by the experimental results (response surface methodology) are as follows: the pre-heating temperature of collagen and alumina must be 166 °C and 300 °C, respectively, while the wt.% of collagen and alumina present in the matrix must be 2.45% and 5% sequentially 180 s of stirring time.

The hardness of the finally tested composite is 67.12 BHN (approx) which has been enhanced by 52.54% as compared to the base material. Tensile strength of composite also enhanced about 18% with respect to base material developed at the optimum combination of casting parameters.

The purpose of this study is to investigate and evaluate the impact of varying proportions of reinforcement on the mechanical properties of a modified Al₂O₃-LM6 cast composite under self-pouring temperature conditions. This study aims to determine the optimal mixture proportion of fine powders of Al, Si and xAl₂O₃ (with x values of 2%, 3% and 4%) through the application of design of experiment (DoE) and statistical analysis using the Minitab software. This study also involved evaluating the microstructural estimation and other physical properties of the cast composite to understand the combined effect of the reinforcement proportion on the material’s properties.

The researchers initially mixed the powders through ball milling and then compacted the moisture-free powder mix in a closed steel die. The resulting preforms were heated at the self-pouring temperature in an inert environment to fabricate the final cast composite. By applying DoE and performing an analysis of variance (ANOVA), the researchers sought to optimize the mixture proportion that would yield the best mechanical properties.

The experimental results indicated that a mixture combination of 83.5% Al blended with 12.5% Si and 4% Al₂O₃ led to the greatest improvement in mechanical properties, specifically in terms of increased density, hardness and impact strength. The ANOVA further supported the interaction effect of each processing parameter on the observed results. The results of this study offer valuable insights for the fabrication of modified Al₂O₃-LM6 cast composites under self-pouring temperature conditions. The identified optimal mixture proportion provides guidance for manufacturing processes and material selection to achieve improved mechanical properties in similar applications.

This study focuses on a specific composite material consisting of modified Al₂O₃ and LM6. Although Al₂O₃ and LM6 have been studied individually in various contexts, the combination of these materials and their impact on mechanical properties under self-pouring temperature conditions is a novel aspect of this research. The researchers use DoE methodology, along with statistical analysis using Minitab software, to optimize the mixture proportion and analyze the data. This systematic approach allows for a comprehensive exploration of the parameter space and the identification of significant factors that influence the mechanical properties of the composite.

The purpose of this paper is related with the comparative study between graphene-based glass fiber–reinforced polymer composites and without graphene composite on polymer matrix. The current study explains the result of amalgamation of 4 Wt.% graphene oxide (GO), in comparison to without graphene, on the mechanical strength of glass fiber/epoxy (GE).

A hand layup technique is used for the experimental study. For this, chemical synthesis process is approached based on Hummer’s theory. For mechanical testing of glass fiber–reinforced graphene composites and without graphene composites, American Society for Testing and Materials-3039 (ASTM3039) standards was adopted. Furthermore, comparatively, composites were characterized by field emission scanning electron microscopy.

Reinforcement of 4.0 Wt.% GO in epoxy matrix material showed 7.46% and 12.31% improvement in mechanical strength and elongation, respectively. Scanning electron microscopy results showed the influence of graphene cumulations in the failure of GO-reinforced GE (GO-GE) composites.

The inimitable things of graphene grounded nanofillers have encouraged in the world of material for their thinkable manipulation in glass fiber polymeric composites. In this work, for the first time, graphene is used as nanofiller in glass fiber epoxy coatings, and their fractography study is investigated.

The purpose of this paper is to understand the integrated impact of the application of protection measures against identity theft on consumers’ synergistic perception of trust, the cost of products/services and operational performance (OP) – all of which in turn is postulated to contribute to purchase intention (PI) when shopping online.

In order to accomplish the specified aim, this study first conducted an experiment by involving the students from a university in Bangladesh. Then a survey was conducted to capture their opinion based on the previous experiment.

The study identified that in e-commerce, OP and trust have potential impact on pursuing consumers’ PI. Traditionally, price is always an issue in marketing; however, for e-commerce, this issue does not have direct impact on PI.

The main limitation of this study is that a less established e-commerce example was utilized to conduct the experiment and survey for validating the model. Also, the study was conducted only in the context of Bangladesh and a student sample was utilized. Future studies can test the model in different contexts (particularly to verify the impact of privacy) by utilizing data from consumers.

This study has resolved a controversial issue by generating clear guidelines that the overall conjoint effect of OP, trust, and price on PI is neither negative nor neutral. Synergistically, the application of these controlling tools of identity theft can substantially enhance consumers’ trust, which is the single most predictor to pursue consumer PI.

This study has provided in-depth insight into the impact of different controlling measures in e-commerce PI. Practitioners have potential learning from this study that if consumers find the application of different controlling mechanisms against cybercrimes, particularly identity theft, enhancing the reliability, authenticity and security of transactions in this virtual medium, they do not mind paying a higher price. Such insights have not been provided by existing studies on this topic. Developing trust on e-commerce purchase is the driving force, not the price.

This research investigates students’ information-seeking behaviours at the Indian Maritime University (IMU) and assesses the impact of AI chatbots on their marine science knowledge and awareness. The study aims to provide insights into the role of AI-driven solutions in enhancing knowledge sharing and the challenges faced in using AI tools for marine information retrieval.

The study used a stratified random sampling method, encompassing 152 respondents from IMU’s B.Sc. in Nautical Science and B. Tech in Marine Engineering programs. Data collection involved a structured electronic survey questionnaire. The analysis encompassed descriptive statistics using SPSS.

Information needs were met through diverse channels, with 57.9% of respondents using AI-driven chatbots for marine information retrieval. AI significantly recommended research papers (61.8%). The chatbot positively impacted marine science awareness and knowledge, with a mean satisfaction rating of approximately 3.3. Challenges included insufficient access to AI tools, data privacy concerns and accuracy issues.

This study contributes original insights into the information-seeking behaviours of marine students at IMU and the impact of AI chatbots on their knowledge and awareness. It highlights the multifaceted nature of marine information retrieval, the effectiveness of AI-driven solutions in enhancing knowledge sharing and the challenges that need to be addressed for the broader adoption of AI tools in this context.