Evaluation and analysis of the adsorption mechanism of three emerging pharmaceutical pollutants on a phosphorised carbon-based adsorbent: Application of advanced analytical models to overcome the limitation of classical models.

The double layer adsorption of sulfamethoxazole, ketoprofen and carbamazepine on a phosphorus carbon-based adsorbent was analyzed using statistical physics models. The objective of this research was to provide a physicochemical analysis of the adsorption mechanism of these organic compounds via the calculation of both steric and energetic parameters. Results showed that the adsorption mechanism of these pharmaceuticals was multimolecular where the presence of molecular aggregates (mainly dimers) could be expected in the aqueous solution. This adsorbent showed adsorption capacities at saturation from 15 to 36 mg/g for tested pharmaceutical molecules. The ketoprofen adsorption was exothermic, while the adsorption of sulfamethoxazole and carbamazepine was endothermic. The adsorption mechanism of these molecules involved physical interaction forces with interaction energies from 5.95 to 19.66 kJ/mol. These results contribute with insights on the adsorption mechanisms of pharmaceutical pollutants. The identification of molecular aggregates, the calculation of maximum adsorption capacities and the characterization of thermodynamic behavior provide crucial information for the understanding of these adsorption systems and to optimize their removal operating conditions. These findings have direct implications for wastewater treatment and environmental remediation associated with pharmaceutical pollution where advanced adsorption technologies are required.

Removal of textile pollutants from aqueous medium using biosynthesized CuO nanoparticles: Theoretical comparative investigation via analytical model.

The work deals with the removal of two dyes, namely methylene blue (MB) and methyl orange (MO), from polluted water by adsorption onto CuO nanoparticles synthesized with a green synthesis procedure, starting from plant resources. Adsorption isotherms are determined at different temperatures aiming at investigating the adsorption mechanisms of the two dyes. The experimental results indicate that, for both MB and MO, the adsorption capacity increases with increasing temperature, with slight differences in the case of MO. Comparatively, the CuO nanoparticles show a higher MB adsorption capacity with respect to MO. A modelling analysis is carried out with a multilayer model derived from statistical physics, selected among a group of models, each hypothesizing a different number of adsorbed molecules layers. The analysis of model parameters allows determining that the adsorbate molecules exhibit a non-parallel orientation on the surface of biosynthesized CuO nanoparticles and each functional group of the adsorbent binds multiple molecules, simultaneously.The model also allows determining the number of dye molecule layers formed on adsorbent surface, in all the cases resulting higher than three, also confirming the effect of temperature on the maximum adsorption capacity.Specifically, the total number of dye layers formed on biosynthesized CuO nanoparticles surface exhibited a range of 4.17-4.55 for MB dye and of 3.01-3.51 for MO dye.Finally, the adsorption energies reveal that adsorption likely involves physical forces (all resulting all below 22 kJ/mol), i.e. hydrogen bonding and van der Waals forces. The adsorption energies for the interactions between dye molecules are lower than those calculated for the interactions between the dye molecules and the adsorbent surface.

Physicochemical assessment of ammonium adsorption using a palm shell-based adsorbent activated with acetic acid: experimental and theoretical studies.

The adsorption of ammonium from water was studied on an activated carbon obtained using raw oil palm shell and activated with acetic acid. The performance of this adsorbent was tested at different operating conditions including the solution pH, adsorbent dosage, and initial ammonium concentration. Kinetic and equilibrium studies were carried out, and their results were analyzed with different models. For the adsorption kinetics, the pseudo-first order equation was the best model to correlate this system. Calculated adsorption rate constants ranged from 0.071 to 0.074 g/mg min. The ammonium removal was 70-80% at pH 6-8, and it was significantly affected by electrostatic interaction forces. Ammonium removal (%) increased with the adsorbent dosage, and neutral pH condition favored the adsorption of this pollutant. The best ammonium adsorption conditions were identified with a response surface methodology model where the maximum removal was 91.49% with 2.27 g/L of adsorbent at pH 8.11 for an initial ammonium concentration of 36.90 mg/L. The application of a physical monolayer model developed by statistical physics theory indicated that the removal mechanism of ammonium was multi-ionic and involved physical interactions with adsorption energy of 29 kJ/mol. This activated carbon treated with acetic acid is promising to depollute aqueous solutions containing ammonium.

Elimination of aspirin and paracetamol from aqueous media using Fe/N-CNT/ß-cyclodextrin nanocomposite polymers: theoretical comparative survey via advanced physical models.

The main purpose of this research is to theoretically investigate the adsorption of two pharmaceutical molecules, i.e. aspirin and paracetamol, using two composite adsorbents, i.e. N-CNT/ß-CD and Fe/N-CNT/ß-CD nanocomposite polymers. A multilayer model developed by statistical physics is implemented to explain the experimental adsorption isotherms at the molecular scale, so as to overpass some limitations of the classical adsorption models. The modelling results indicate that the adsorption of these molecules is almost accomplished by the formation of 3 to 5 adsorbate layers, depending on the operating temperature. A general survey of the number of adsorbate molecules captured by the adsorption site (npm) suggested that the adsorption process of pharmaceutical pollutants is multimolecular and that each adsorption site can capture several molecules simultaneously. Furthermore, the npm values demonstrated the presence of aggregation phenomena of aspirin and paracetamol molecules during adsorption. The evolution of the adsorbed quantity at saturation confirmed that the presence of Fe in the adsorbent enhanced the removal performance of the investigated pharmaceutical molecules. In addition, the adsorption of the pharmaceutical molecules aspirin and paracetamol on the N-CNT/ß-CD and Fe/N-CNT/ß-CD nanocomposite polymer surface involved weak physical type interactions, since the interaction energies do not overcome the threshold of 25 000 J mol-1.

Explaining the adsorption mechanism of the herbicide 2,4-D and the drug ketoprofen onto wheat husks Fagopyrum esculentum treated with H2SO4.

In this paper, the adsorption of the herbicide 2,4-D and the drug ketoprofen on wheat husks Fagopyrum esculentum treated with H2SO4 is experimentally and analytically analyzed. The adsorbent is fully characterized through some techniques such as FT-IR, SEM, and XRD. Adsorption tests are carried out to optimize the performances in terms of adsorbent dosage and solution pH. Subsequently, the impact of temperature is determined through the realization of adsorption isotherms. A multilayer model is employed to microscopically interpret the adsorption mechanism of both the investigated compounds. The modelling analysis shows that the number of molecules bound per adsorption site varied from 0.68 to 2.77 and from 2.23 to 3.59 for ketoprofen and herbicide 2,4-D, respectively. These estimated values testify that an aggregation process occurs during adsorption. The global number of formed layers of each adsorbate is also determined, showing a significant reduction from 5.73 to 2.61 for ketoprofen and from 1.79 to 1.5 for herbicide 2,4-D with the temperature. For a complete understanding of the adsorption mechanism, the saturation adsorption capacity and adsorption energy were calculated and interpreted. Overall, it may be inferred that physical interactions govern how these contaminants adsorb on the tested adsorbent.

Adsorption of perfluorooctanoic carboxylic and heptadecafluorooctane sulfonic acids via magnetic chitosan: isotherms and modeling.

This paper evaluates the adsorption mechanism of perfluorooctanoic carboxylic acid (PFCA) and heptadecafluorooctane sulfonic acid (HFOSA) on magnetic chitosan for the first time via a statistical physics modeling. Magnetic chitosan (MC-CoFe2O4) was produced from shrimp wastes and used in standard batch adsorption systems to remove PFCA and HFOSA. The experimental isotherms indicated that the maximum adsorption capacities ranged from 14 to 27.12 mg/g and from 19.16 to 45.12 mg/g for PFCA and HFOSA, respectively, where an exothermic behavior was observed for both compounds. The adsorption data were studied via an advanced model hypothesizing that a multilayer process occurred for these adsorption systems. This theoretical approach indicated that the total number of formed layers of PFCA and HFOSA adsorbates is about 3 (Nt = 2.83) at high temperatures (328 K) where a molecular aggregation process was noted during the adsorption. The maximum saturation-multilayer adsorption of PFCA and HFOSA on magnetic chitosan was 30.77 and 50.26 mg/g, respectively, and the corresponding adsorption mechanisms were successfully investigated. Two energies were responsible for the formed adsorbate layer directly on the surface and the vertical layers were computed and interpreted, reflecting that physical interactions were involved to bind these molecules on the adsorbent surface at different temperatures where the calculated adsorption energies ranged from 14 to 31 kJ/mol. Overall, this work provides theoretical insights to understand the adsorption mechanism of PFCA and HFOSA using the statistical physics modeling and its results can be used to improve the adsorbent performance for engineering applications.

Using an enhanced multilayer model to analyze the performance of nickel alginate/graphene oxide aerogel, nickel alginate aerogel/activated carbon, and activated carbon in the adsorption of a textile dye pollutant.

This work describes the modeling and analysis of methylene blue molecule on different adsorbents, namely, nickel alginate/graphene oxide (NA/GO) aerogel, nickel alginate/activated carbon (NA/AC) aerogel, and Trichosanthes kirilowii maxim shell activated carbon (TKAC). A multilayer statistical physics model was used to calculate the energetic and steric parameters of the adsorption of methylene blue on these adsorbents. Based on the modeling investigation, it was concluded that the formation of multiple dye adsorbed layers on these adsorbents could be feasible where physical adsorption interactions could be involved. Adsorption capacities at saturation of these adsorbents ranged from 542.97 to 470.03 mg/g, 790.66 to 684.47 mg/g, and 401.11 to 1236.24 mg/g for NA-GO aerogel, NA-AC aerogel, and TKAC, respectively. This research contributes with new findings for the understanding of dye adsorption on novel materials, which can be used in water pollution control.

Adaptation of advanced physical models to interpret the adsorption isotherms of lead and cadmium ions onto activated carbon in single-compound and binary systems.

The work reports a modeling analysis of single-compound and binary adsorption of Pb2+ and Cd2+ ions from polluted water onto the activated carbon at room temperature. The homogeneous model for single adsorption (HM) and the exclusive extended monolayer model for binary adsorption (EEMM) are applied for the interpretation of the experimental data set. The adopted models correlate the entire set of adsorption data, allowing a thorough description of the occurring phenomena. The overall objective of the study is to determine the adsorption mechanisms, also through a comparative analysis between the single-compound and binary modeling data. The parameters of both models are used for to retrieve useful indications about the adsorption of these two ions. In particular, the number of ions adsorbed per single functional groups changed from single-compound to binary adsorption, allowing to explain the competitive behavior of the investigated system. The adsorption energy values vary between 21.39 (Pb2+) and 24.06 kJ/mol (Cd2+), and 27.17 (Pb2+) and 32.59 kJ/mol (Cd2+) in single-compound and binary systems, respectively, indicating that adsorption is a physisorption process.

Application of a multilayer physical model for the critical analysis of the adsorption of nicotinamide and propranolol on magnetic-activated carbon.

The paper describes a theoretical analysis of the adsorption of nicotinamide and propranolol onto a magnetic-activated carbon (MAC). For a better evaluation of the adsorption mechanism, adsorption isotherms expressing the variation of the adsorption capacity as function of adsorbate concentration were determined at different temperatures ranging from 20 to 45 °C. For both the analytes, experimental tests reveal that adsorption capacity increases with temperature. An advanced multi-layer model derived from the statistical physics is set for the interpretation of the entire adsorption data set. The modelling results show that the propranolol molecules change their adsorption orientation from a mixed (parallel and non-parallel) orientation to a multimolecular process. For nicotinamide, the aggregation of molecules is practically absent, except for the data at lower temperatures. The model allows stating that the adsorption of both the pharmaceutical compounds occurs via the formation of one or two layers on MAC adsorbent, the propranolol showing a higher tendency to form multiple layers. Finally, adsorption energy is estimated suggesting that the adsorption is endothermic and physical interactions are the responsible of the adsorption of both the compounds onto MAC adsorbent.

Understanding the Cu2+ adsorption mechanism on activated carbon using advanced statistical physics modelling.

Adsorption modeling via statistical physics theory allows to understand the adsorption mechanism of heavy metal ions. Therefore, this paper reports the analysis of the mechanism of copper ion (Cu2+) adsorption on four activated carbons using statistical physics models. These models contain parameters that were utilized to provide new insights into the possible adsorption mechanism at the molecular scale. In particular, a monolayer adsorption model was the best alternative to correlate the Cu2+ adsorption data at 25-55 °C and pH 5.5. Furthermore, the application of this model for copper adsorption data analysis showed that the removal of this heavy metal ion was a multi-cationic process. This theoretical finding indicated that Cu2+ ions interacted via one functional group of activated carbon surface during adsorption. In this direction, the adsorption energy was calculated thus showing that Cu2+ removal was endothermic and associated with physical interaction forces. Furthermore, these activated carbons showed saturation adsorption capacities from 54.6 to 87.0 mg/g for Cu2+ removal, and their performances outperformed other adsorbents available in the literature. Overall, these results provide new insights of the adsorption mechanism of this water pollutant using activated carbons.

Physicochemical assessment of anionic dye adsorption on bone char using a multilayer statistical physics model.

The statistical physics modeling is a reliable approach to interpret and understand the adsorption mechanism of both organic and inorganic adsorbates. Herein, a theoretical study of the adsorption mechanism of anionic dyes, namely reactive blue 4 (RB4), acid blue 74 (AB74), and acid blue 25 (AB25), on bone char was performed with a multilayer statistical physics model. This model was applied to fit the equilibrium adsorption data of these dyes at 298-313 K and pH 4. Results indicated that the global number of formed dye layers on the bone char varied from 1.62 to 2.24 for RB4, AB74, and AB25 dyes depending on the solution temperature where the saturation adsorption capacities ranged from 0.08 to 0.12 mmol/g. Dye molecular aggregation was also identified for these dyes where dimers and trimers prevailed at different operating conditions especially for adsorbates RB4 and AB74. Adsorption mechanism of these dyes was multimolecular and endothermic with adsorption energies from 10.6 to 20.8 kJ/mol where van der Waals interactions and hydrogen bonding could be present. This investigation contributes to understand the physicochemical variables associated to dye adsorption using low-cost adsorbents as bone char.

Adsorption mechanism of Zn2+, Ni2+, Cd2+, and Cu2+ ions by carbon-based adsorbents: interpretation of the adsorption isotherms via physical modelling.

A theoretical physicochemical and thermodynamic investigation of the adsorption of heavy metals Zn2+, Cd2+, Ni2+, and Cu2+on carbon-based adsorbents was performed with statistical physics fundaments. Particularly, the experimental adsorption isotherms of heavy metal removal, at 30°C and pH 5, using adsorbents obtained from the pyrolysis of three biomasses (cauliflower cores, broccoli stalks, and coconut shell) were modelled and interpreted with a homogeneous statistical physics adsorption model. Calculations indicated that the heavy metal adsorption with these carbon-based materials was a multi-ionic process where several ions interact simultaneously with the same carboxylic functional group on the adsorbent surface. Adsorption capacities for these metal ions and adsorbents were correlated with electronegativity theory, which established that the adsorbate with the highest electronegativity was more readily adsorbed by the carboxylic functional groups available on the adsorbent surfaces. Also, the chemical compositions of biomass precursors explained achieved adsorption capacities for these metallic ions. The best adsorbent for heavy metal removal was obtained from CC biomass pyrolysis. Calculated adsorption energies for heavy metal removal could be associated with physisorption-type forces. Finally, the adsorption mechanism analysis was complemented with the determination of adsorption thermodynamic functions using the statistical physics.