With the consolidation of online shopping, there is a need to gain insight into consumer decision-making within the digital sphere. The purpose of this study was to investigate factors that influence online shopping intention of fashion products, among female Millennials. By means of a proposed conceptual model, seven hypotheses were tested and data was collected from three hundred young females in South Africa. The data analysis was conducted using SEM in SPSS 23 and AMOS 23, and the results indicated that four of the seven hypotheses were supported. The results from this study provide online fashion retailers with insight into how they can utilise online shopping platforms to reap the financial results from this concept.

Marketers and retailers are increasingly interested in grabbing the opportunity to reach the consumer at the right time and place with a smart phone. Depending on Location Based Advertising (LBA) and associated sensors with the IBeacon technology, marketers can determined the consumer’s favorite products through his search history and previous purchase activities furthermore his location in-store. So, marketers and retailers pay more attention to in-store mobile LBA. In this work, the modified LBA in-store framework are constructed. This model proposed that the temporal time, type of information and the variety of receiver of mobile in-store LBA affect the Purchase intention in retail stores.

The purpose of this paper is to investigate factors driving parasocial relationships and their effect on brand equity. A conceptual model including the following variables is proposed: opinion leader attributes, parasocial relationship, brand equity and the moderating effect of endorser-brand congruency. The proposed research model is analyzed using a survey of 301 Chinese consumers. Structural equation modelling is employed to examine the hypothesized relationships among all variables. The findings show that the opinion leader attributes of expertise and exploration positively affect the parasocial relationship between consumers and the endorser, and the parasocial relationship and brand equity are positively associated. Furthermore, endorser-brand congruency acts as a moderator on the relationship between opinion leader attributes and the parasocial relationship. The implications, limitations, and discussions are provided.

In this paper, graphene-coated Al powders prepared by in situ reduction method were directly used for cold spraying, obtaining a graphene-reinforced Al matrix composite coating with more compact structure and better performance. Cross-sectional analysis revealed that compared with the pure Al powders, the graphene-coated Al powders were more severely deformed, and the resulting coating was denser and its porosity was reduced by over 80%. The hardness of the graphene-coated Al coating was increased by 40%, and its brine immersion time was prolonged by nearly three times. However, the graphene increases the pitting sensitivity of the Al coating; so, the enhanced corrosion resistance of the graphene-coated Al coating is mainly attributed to the improvement of its structure densification.

Although flame synthesis promises economic benefit and rapid synthesis of carbon nanotube (CNT), the lack of control and understanding of the effects of flame parameters (e.g., temperature and precursor composition) impose some challenges in modelling and identifying CNT growth region for obtaining better throughput. The present study presents an investigation on the types of carbon precursor that affect CNT growth region on nickel catalyst particles in an ethylene inverse diffusion flame. An established CNT growth rate model that describes physical growth of CNT is utilised to predict CNT length and growth region using empirical inputs of flame temperature and species composition from the literature. Two variations of the model are employed to determine the dominant precursor for CNT growth which are the constant adsorption activation energy (CAAE) model and the varying adsorption activation energy (VAAE) model. The carbon precursors investigated include ethylene, acetylene, and carbon monoxide as base precursors and all possible combinations of the base precursors. In the CAAE model, the activation energy for adsorption of carbon precursor species on catalyst surface E a,1 is held constant whereas in the VAAE model, E a,1 is varied based on the investigated precursor. The sensitivity of the growth rate model is demonstrated by comparing the shifting of predicted growth regions between the CAAE model and the VAAE model where the CAAE model serves as a control case. Midpoint-based and threshold-based techniques are employed within each model to quantify the predicted CNT growth region. Growth region prediction based on the midpoint-VAAE approach demonstrates the importance of acetylene and carbon monoxide to some extent towards CNT growth. Ultimately, the threshold-VAAE model shows that the dominant precursor for CNT growth is the mixture of acetylene and carbon monoxide. A simplified reaction mechanism is proposed to describe the surface chemistry for precursor reactions with nickel catalyst where decomposition of the ethylene fuel source into acetylene and carbon monoxide is accounted for by chemisorption.

This work reports the syntheses of an inexpensive and efficient asphalt-derived mesoporous carbon (AdMC) as an adsorbent. The adsorbent was activated with potassium hydroxide to increase its surface area and then characterized by SEM–EDS, FT-IR, and BET. The adsorption properties of AdMC were evaluated for the adsorptive removal of eleven Poly Aromatic Hydrocarbons (PAHs) and diesel from water samples. The prepared AdMC showed very high surface areas and high micropore volumes equal to 2316 m2/g and 1.2 cm3/g, respectively. Various experimental conditions influencing the adsorption capacity of eleven PAHs and diesel were investigated. At high concentrations, PAHs and diesel solubility in water is very low. Hence, samples were emulsified with a surfactant, and then maximum adsorption capacity was investigated. Adsorption profile of individual PAHs was examined using gas chromatography/mass spectrometry analysis followed by liquid–liquid extraction. Total hydrocarbon removal was studied using a total organic analyzer. Asphalt-derived mesoporous sorbent showed an extreme ability to remove PAHs and diesel (average adsorption capacity of 166 mg/g for individual PAHs and diesel (maximum capacity of 1600 mg/g). The experimental results fitted the Langmuir model with a correlation efficiency of 0.9853. The results obtained for both adsorbents also matched to pseudo-second-order kinetics, suggesting that the adsorption of PAHs and diesel is chemical, monolayer, and homogeneous process.

The present work focused on the determination of texture, morphology, crystallinity, and gas adsorption characteristics of porous graphene prepared from rice husks ashes at different stabilization temperature. The stabilization temperature applied in this work is 100 °C, 200 °C, 300 °C, and 400 °C to convert rice husk into rice husk ashes (RHA). Chemical activation was adopted at temperature 800 °C using potassium hydroxide (KOH) as dehydrating agent at (1:5) impregnation ratio to convert RHA into rice husk ashes-derived graphene (GRHA). The resultant GRHA were characterized in terms of their morphological changes, SSA, crystallinity, and functional group with TEM, the BET method, Raman spectroscopy, and XRD analysis, respectively. Results from this study showed that the SSA of the GRHA at stabilization temperature 200 °C (1556.3 m2/g) is the highest compared to the other stabilization temperature. Raman spectroscopy analysis revealed that all GRHA samples possess D, G, and 2D bands, which confirm the successful synthesis of the rice husks into porous graphene-like materials, known as GRHA. Appearance of diffraction peak in XRD at 44.7° indicating the graphitic structure of all the GRHA samples. Meanwhile, the TEM images of GRHA200 exhibited wrinkled structures due to the intercalation of oxygen and a few layers of graphene flakes. These wrinkled structures and graphene layers are the other factors that lead to the highest SSA of GRHA200 compared to other prepared samples GRHA. Furthermore, the adsorption capacity of CH4 for GRHA200 is up to 43 cm3/g at 35 bar and ambient temperature, almost double the adsorption capacity performance of GRHA400 at the same operating pressure and temperature.

The aim of this work is to investigate the ability of a new functionalized graphene oxide 3-amino-5-phenylpyrazole (F-GO) in the adsorption and removal of Hg2+ from aqueous solution. Both untreated graphene oxide (GO) and F-GO were characterized using FT-IR, EDX, FE-SEM, XRD and TGA analysis. The effects of three operational variables (pH, adsorbent dose and initial metal ion concentrations) on Hg2+ adsorption capacity of F-GO were investigated by central composite design. This technique aims to find a simple way to optimize the adsorption process and to analyze the interaction between the significant parameters. A quadratic model suggested for the analysis of variance found that the adsorption of metal ions heavily depend upon pH of the solution. The adsorption mechanism has been determined by pseudo-first-order kinetic models and the adsorption behavior was modeled by Freundlich isotherm. Results demonstrated that the adsorption capacities of F-GO for removal of Hg2+ were generally higher than those of GO, which is attributed to a decrease in the agglomeration of graphene layers due to the presence of amino-functional moieties with their bulky phenyl groups. Thermodynamic data indicated that the functionalization significantly affects the thermostability of the GO precursor materials. The desorption study demonstrated favorable regenerability of the F-GO adsorbent, even after three adsorption–desorption cycles.