Rice Husk Ash–Derived Silica Particles for the Adsorptive Removal of Acetylsalicylic Acid From Water: Synthesis, Characterization, Isotherm, Kinetic, and Thermodynamic Studies

Response surface methodology (RSM) was used for optimization of the adsorbent dosage, initial solution pH, initial ion concentration, and contact time in removal of Cr (III) with local nanoclay. The adsorption process was modeled by RSM and artificial neural network (ANN). The process was done in batch mode by central composite design (CCD) and the same design was applied for training ANN. The optimum condition was determined to be 500mg/L for adsorbent dosage, initial pH of 5, initial chromium concentration of 180mg/L and 20 min of contact time. In these conditions qRSM = 238.7780mg/g and qANN = 237.5152mg/g which indicate removal percentage of 72.45% and 72.07%, respectively. and indicate that the two models can predict the adsorption of Cr3+ properly. The two parameter Langmuir, Freundlich, Dubinin‐Radushkevich (D‐R), Temkin and three parameter Redlich‐Peterson (R‐PT), Sips and Toth isotherm models were applied to equilibrium data by minimizing the sum of squared errors (SSE), sum of the absolute errors (SAE), average relative errors (ARE), Hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), and nonlinear chi‐square test error functions. The results showed that the HYBRID error function gives the lowest value and the R‐PT model fits the data better than other isotherm models.

Removal of cadmium(II) and zinc(II) metal ions from binary aqueous solution by rice husk ash

Sorption of distillery spent wash onto fly ash: Kinetics, mechanism, process design and factorial design

This investigation reports the synthesis of a new adsorbent material (ZrPA), from Zr(IV) and propanolamine (PA), synthesized by sol−gel technique at room temperature following the green chemistry principle. The suitability of ZrPA as a potential adsorbent is assessed for the removal of fluoride following the batch mode of operation. The isotherm, kinetics, and thermodynamics of fluoride adsorption on ZrPA have been studied at various experimental conditions (initial fluoride concentration, adsorption time, adsorbent dose, and temperature). The characteristic of the adsorbent, before and after fluoride adsorption, was examined using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), coupled with energy dispersive spectrum (EDS) techniques. Further measurement of surface area, pore volume, and pore diameter using N2 intrusion automated gas sorption system shows the microporous nature of the prepared material. Adsorption of fluoride was found to be strongly affected by pH. Mathematically, pseudosecond-order kinetic model was found to best describe the reaction rate, which was consistent with the actual measurement. Applications of Freundlich, Langmuir, Temkin, and Dubinin−Radushkevich (D−R) isotherm models for the adsorption process were evaluated, and the data were also compared for six different error functions, that is, the sum of the squares of errors (SSE), sum of the absolute errors (SAE), the average relative error (ARE), the hybrid fractional error function (HYBRID), the Marquardt’s percent standard deviation (MPSD), and regression coefficient (R2), to test the adequacy and accuracy of the model equations. Thermodynamic parameters such as enthalpy, entropy, and free energy were calculated using van’t Hoff equations, which shows that fluoride adsorption on ZrPA indicates the spontaneous and endothermic nature of adsorption. The reusability of the ZrPA adsorbent material was tested up to 10 consecutive cycles for a sustainable commercial application purpose. Quantitative desorption of fluoride from ZrPA was found to be more than 95% at pH 12. To test the efficacy, the performance of the adsorbent material was studied with water samples collected from a fluorosis endemic region.

Multivariate modeling and optimization of Cr(VI) adsorption onto carbonaceous material via response surface models assisted with multiple regression analysis and particle swarm embedded neural network

Sorption of distillery spent wash onto fly ash: Kinetics and mass transfer studies

The choice of adsorption model to use when accounting for gas adsorption in shale gas reservoirs is critical especially for Gas in Place (OGIP) calculations since inaccurate predictions can affect reporting of overall gas reserves. To that end, different adsorption models would have to be compared and evaluated in order to select the model that fits experimental data accurately. In examining the effect of using different error criteria for determining parameters for shale gas adsorption models, a statistically robust error analysis has been performed based on the sum of normalised error (SNE). Most shale gas adsorption modelling are conducted without finding out the most appropriate error function to use which introduces adsorption prediction errors in calculations. Five different error analysis were used including Sum of squared error (SSE), average relative error (ARE), the sum of absolute error (SAE), Marquardt’s Percent standard Deviation (MPSD), and Hybrid fractional error (HYBRID). To account for the influence of temperature in adsorption capacities, the study also compares the use of temperature dependent models, such as Exponential and Bi-Langmuir models for gas adsorption. These models can be conducted at multiple temperatures and ensure adsorption data can be obtained at any temperature beyond laboratory conditions. This is particularly useful when conducting thermal stimulation as an enhanced gas recovery in both coal/shale gas reservoirs.

Comparison of various error functions in predicting the optimum isotherm by linear and non-linear regression analysis for the sorption of basic red 9 by activated carbon

Isotherms and thermodynamics by linear and non-linear regression analysis for the sorption of methylene blue onto activated carbon: Comparison of various error functions

Radioactive barium discharge into the environment is a big problem due to its toxicity and mobility. This paper describes the characterization of sulphonated polystyrene pellets (SPSP) using Fourier transform infrared (FTIR) and energy-dispersive X-ray spectroscopy (EDX). Batch studies were conducted to study the sorption of Ba(II) onto sulphonated polystyrene pellets (SPSP), and the adsorption efficiency (S%) was found to be 96% at pH 4.0 and contact period of 120 min. Experimental thermodynamic studies support the exothermic character of the SPSP/Ba system and the negative value of ∆S, indicating a non-random interaction of Ba(II) on the surface of SPSP during the adsorption process. Nonlinear isotherm models such as Langmuir, Freundlich, and Temkin were used to fit the equilibrium data. The kinetic data were fitted using nonlinear kinetic models such as pseudo first order, pseudo second order, intraparticle diffusion and Elovich. The adsorption process of Ba(II) onto SPSP was fitted to the pseudo first order kinetic model and with the Langmuir adsorption isotherm model, with a maximum adsorption capacity of 12.79 mg/g. Nonlinear isotherm and kinetic models results were interpreted using the coefficient of determination (R2), Marquardt's percent standard deviation (MPSD), Hybrid fractional error function (HYBRID), Sum of absolute error (EABS), Sum square error (SSE) and Average relative error (ARE) functions for error calculation and goodness of fit. This study demonstrates the effectiveness of sulfonated polystyrene pellets (SPSP) as an efficient and low-cost adsorbent for barium uptake from contaminated wastewater.

In this work, a new spherical magnetic silicon-substituted poly (N,N’-methylenebisacrylamide) (NSM) nanocomposite was synthesized, examined by various known instruments and applied as an adsorbent to eliminate copper (Cu2+) from its water solution using batch method experiment. The particles size of NSM composite was ranged from around 24.74 to 28.27 nm. The magnetic NSM nanocomposite are mesoporous, with specific surface area of 63.675 m2 g–1 and an average pore diameter of 7.6239 nm. The adsorption of Cu2+ ions was most efficient at a solution pH 5. The removal process using NSM nanocomposite has been studied in various settings, including initial Cu2+ ion concentration, initial pH, and temperature. Using an initial Cu2+ ions concentration (50 mg L–1) and NSM nanocomposite dose (2.0 g L–1), the maximum percent clearance of Cu2+ ions was 96.47%. The NSM’s maximum adsorption capacity (Qm) was 30.30 mg g–1. Experimental data were discussed using the Langmuir (LIM), Freundlich (FIM), and Tempkin (TIM) isotherm models. The experimental data from NSM aligns effectively with the LIM model. Several error functions, such as Chi-Squared Error (X2), Average Percent Error (APE), Root Mean Square (RMS), Sum of Absolute Errors (EABS), Hybrid Error Function (HYBRID), and Marquardt’s Percent Standard Deviation (MPSD), were applied to validate the isotherm model data. Calculations of the error function suggest that the LIM is the most appropriate for characterizing the adsorption process. Kinetic data were analyzed by fitting pseudo-first-order (PFOM), pseudo-second-order (PSOM), intraparticle diffusion (IPDM) and film diffusion (FDM) models. The PSOM rate model exhibited a robust correlation (R2 > 0.998) and predominantly governed the adsorption rate. The results show that NSM effectively removes the Cu2+ ions from water. Utilizing a response surface methodology analysis to optimize the degradation parameters revealed that a maximum degradation percentage of 52.56 ppm of Cu2+ solution and 3.79 g of NSM could be achieved.

The emergent occurrence of sulfonamide species involving sulfadiazine (SDZ) and sulfamethazine (SMZ) in aquatic systems can cause a wide range of potential risks; hence, remediation strategies need to be necessary. Here, we develop the novel metal-organic framework-derived nanocomposite, and apply for the adsorption of SDZ and SMZ antibiotics. To assess the best-fitting kinetic (pseudo first-order, pseudo second-order) and isotherm (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Redlich-Peterson, Sips, Toth, and Khan) models, a series of numerous statistical analysis was performed. Numerous error functions including squares of the errors (SSE), hybrid fractional error function (HYBRID), Marquardt's percent standard deviation (MPSD), and mean relative error (MRE) were also analyzed to assess the linear and nonlinear models. The results indicated that both linear and nonlinear kinetic models were mostly fitted well with pseudo second-order models (Radj)2 > 0.97. Although linear kinetics gave better (Radj)2, error functions (MRE, SSE, HYBRID, and MPSD) were mostly higher than those of nonlinear kinetics. For adsorption isotherm, nonlinear Redlich-Peterson was the most compatible model with extremely high adjusted coefficients of determination (Radj)2 ~ 1.0000. While nonlinear Langmuir model gave relatively high (Radj)2 (0.9898-0.9960) and acceptable error functions, we found the considerable difference of error functions and parameters among four types of linear Langmuir (Types I, II, III, IV). The findings indicate potential errors as selecting one of linearized Langmuir types in equilibrium study. It is suggested that nonlinear models should be applied for better fitness.

A green approach for the removal of Sr(II) from aqueous media: Kinetics, isotherms and thermodynamic studies

Kinetics and thermodynamics of fluoride removal using cerium-impregnated chitosan

A comprehensive methodology for analysis of coagulation performance: Dosing approach, isotherm modelling, FTIR spectroscopy and floc characterization