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The textile industry's waste often contains excessive amounts of crystal violet (CV), leading to environmental concerns. Graphene oxide has been studied as a promising adsorbent for removing crystal violet, a cationic dye, from aqueous solutions. The study involved a comprehensive analysis of various experimental parameters, including initial concentration, pH, adsorbent mass, contact time, and temperature. Graphene oxide underwent thorough analysis using Fourier‐transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), scanning electron microscopy (SEM), and specific surface area determination via the Brunauer–Emmett–Teller (BET) method. Energy‐dispersive X‐ray spectroscopy (EDS) was also employed. This study aimed to optimize the synthesis yield of graphene oxide from graphite using the Hummers method and response surface methodology (RSM), achieving a yield of 106.14% with 5 g of KMnO4 and 1 g of NaNO3 for 8 hours. The graphene oxide was analyzed via FTIR, XRD, SEM, BET, pHpzc, and EDS. Optimal conditions for maximal adsorption included 0.016 g of graphene oxide, 18 minutes of contact time, pH 10, and a temperature of 25°C, resulting in a 97.38% reduction in crystal violet with a monolayer adsorption capacity of 470.78 mg/g. Kinetic data were best fitted by the pseudosecond‐order model, and the Langmuir isotherm accurately depicted adsorption. Thermodynamic analysis indicated spontaneous (ΔG° < 0) and exothermic (ΔH° < 0) crystal violet adsorption. Density functional theory (DFT) explored interactions between graphene oxide and crystal violet, supporting experimental findings and confirming graphene oxide's efficacy as an adsorbent for crystal violet removal from aqueous solutions. [ABSTRACT FROM AUTHOR]

Geographical origin and environmental factors have a significant impact on the constituents and the biological properties of medicinal and aromatic plants. Herein, the Inula viscosa plant grown in El Menzel - Morocco were investigated with a focus on the impact of geographical province and solvent type on the mass yield and the biological activities of plant extracts. Chemical composition was characterized by gas chromatography/mass spectrometry (GC/MS). Antimicrobial activity was determined using the disk diffusion method and the microdilution test against eight clinical fungal, Gram-positive and Gram-negative bacterial isolates. The chemical composition results showed that the plant has good nutritional quality in terms of protein, carbohydrates, lipids and dietary fiber. In fact, alkaloids and saponisides are the most predominant chemical compounds in Inula vuscosa. Meanwhile, eighty volatile compounds were identified, representing 95% of the total essential oil content, the main component of which is tetra-pentacontane (11.26%). Furthermore, results showed high antioxidant activity, with efficacy increasing in the order: essential oil > chloroform extract > ethereal extract > ethanolic extract. In addition, both chloroformic extract and essential oil demonstrated significant antibacterial activity against all strains tested. This study highlights the influence of geographical variations and extraction solvents on the bioactivity of Inula viscosa, offering insights into its potential applications in pharmacology and nutraceuticals. [ABSTRACT FROM AUTHOR]

This study is based on the use of a natural material in the adsorption process to remove organic pollutants. The objective is to assess its effectiveness in adsorbing the organic pollutant MB from an aqueous solution, while operating in an open system. The DP bioadsorbent was characterized using FTIR and SEM. To determine their effect on adsorption efficiency, a number of variables were examined, including contact time, concentration of pollutant MB, adsorbent mass, pH, temperature, and adsorbent particle size. The effect of these variables on adsorption efficiency shows that a removal rate of 92.66% is achieved under optimum conditions, including a contact time of 35 minutes, a concentration of pollutant MB of 22.5 mg·l-1, an adsorbent mass (mDP) of 1.1 g·l-1 and a solution pH of 5.6. In addition, a progressive decrease in adsorption efficiency is observed with increasing temperature and adsorbent mass. On the other hand, this efficiency increases with increasing a concentration of pollutant MB. Three popular models, the Freundlich, Langmuir, and Dubin-Radushkevich models, have been used to examine the adsorption isotherms of the MB dye on DP. With a correlation factor of 0.98, it was discovered that MB adsorption monitored by the Freundlich isotherm. The Langmuir and Dubinin-Radushkevich models, however, do not adequately describe the data. The kinetic results were studied using the pseudo-first-order and pseudo-secondorder equations, and show that MB dye adsorption on DP (adsorbent) follows the pseudo-second-order model. Also estimated were thermodynamic parameters such as (ΔH°), (ΔS°), (ΔG°), enthalpy, entropy, Gibbs free energy respectively to anticipate the character of adsorption. The results indicate that the adsorption process of MB on the bioadsorbent is exothermic. The results derived from the ΔG° values lead to the conclusion that the adsorption of MB occurs spontaneously. [ABSTRACT FROM AUTHOR]

In the present review article, a soil from the region of Fez-Sefrou Morocco was screened for some physicochemical characteristics using the Plackett-Burman model in order to determine the most important factors that promote its fertility. Five independent variables were selected: pH, electrical conductivity, humidity, organic matter, and C/N ratio. These variables were evaluated by statistical analysis, based on their significance, the value of the coefficient of determination and the Pareto chart. The results suggest that humidity and C/N ratio have an influence with a high level of confidence, while the other three show no significant effect on the content of nutrients in the soil. The analysis of the R² variance value also showed that the models used for prediction were large and significant factors (p less than 0.05). Pareto chart plots for each response and its characteristics provided accurate data to select well-fitting variables for further optimization. [ABSTRACT FROM AUTHOR]