Multicomponent Adsorption Systems Research Articles

Competitive sorption of low and high molecular weight proteins in model mixtures by Q HyperZ chromatographic medium. Part II: Mass transfer mechanisms

The kinetic uptake of Bovine Serum Albumin (BSA) and ferritin in mixtures by the composite anion exchanger Q HyperZ was studied. Transient adsorption experiments were performed to investigate the dominant resistance between external and internal mass transfer in simultaneous and sequential adsorption experiments. From the evolution of protein solution concentration with time, the external mass transfer coefficients determined were very low in simultaneous (7.1 10−7 and 1.1 10−7 m/s for BSA and ferritin respectively) and sequential (4.6 10−7 and 2.5 10−7 m/s for BSA and ferritin respectively) adsorption systems which is in agreement with the low agitation speed used. From the transient protein uptakes, the internal mass transfer was studied and the homogenous diffusion model applied provides a good predictability in single as well as in simultaneous and sequential adsorption experiments. The effective diffusion coefficients were determined in sequential (6.4 10−14 m2/s and 3.8 10−14 m2/s for BSA and ferritin respectively) and simultaneous (4.2 10−14 m2/s for both proteins) systems. In multi-component adsorption system, it was found that BSA was slowed down upon the presence of ferritin on mixture solutions contrarily to ferritin protein. This phenomenon, known as electrostatic coupling effect, indicates that diffusion of charged proteins in ion exchangers are not independent.

Blighia sapida Waste Biochar in Batch and Fixed-Bed Adsorption of Chloroquine Phosphate: Efficacy Validation Using Artificial Neural Networks.

The present study investigated the potency of biochar prepared from Blighia sapida seedpods (BSSPs) in the uptake of chloroquine phosphate (CQP) from single-component batch and multicomponent fixed-bed adsorption systems. BSSPs presented a highly porous structure with a BET surface area of 1122.05 m2/g, to which adsorption efficiency correlated. The Dubinin-Radushkevich isotherm energy was obtained as 129.09 kJ/mol, confirming the chemisorption nature of the BSSP-CQP adsorption system. The efficiency of the artificial neural network (ANN) was evaluated using the lowest mean square error (MSE = 7.27) and highest correlation coefficient (R2 = 0.9910). A good agreement between the experimental results and the ANN-predicted data indicated the efficiency of the model. The percentage removal of 95.78% obtained for the column adsorption studies indicated the effectiveness of BSSPs in a multicomponent system. The mechanism of the interaction proceeded via hydrogen bonding and electrostatic attraction. This was confirmed by the high desorption efficiency (69.11%) with a HCl eluent. The degree of reversibility was found to be 2.95, indicating the reusability potential of BSSPs. BSSPs are therefore considered multilayered adsorbents with potential applications in pharmaceutical wastewater treatment.

Revealing the interface chemistry of polyaniline grafted biomass via statistical modeling of multi-component dye systems: optimization, kinetics, thermodynamics, and adsorption mechanism.

The growing need to examine the adsorption capabilities of innovative materials in real-world water samples has encouraged a shift from single to multicomponent adsorption systems. In this study, a novel composite, PANI-g-SM was synthesized by covalently grafting a lignocellulosic biomass, Saccharum munja (SM) with polyaniline (PANI). The as-synthesized composite was investigated for the simultaneous adsorption of cationic (Methylene Blue (MB); Crystal Violet (CV)) and anionic dyes (Reactive Red 35 (RR); Fast Green FCF (FG)) from four single components and two binary systems, MB + RR and CV + FG. Further, the effect and interaction of pH (2-11), dosage (0.01-0.04g/10mL), and initial concentration (0.0313 to 0.1563mmol/L) on the elimination of dyes by PANI-g-SM were studied through a novel design of Box-Behnken of Response Surface Methodology (RSM) technique which was found to be highly useful for revealing the chemistry of interfaces in multi-component systems. The extended Langmuir model for the binary system indicated the presence of synergism, as result the maximum monolayer adsorption capacity increased by 44.44%, 645.83%, 67.88%, and 441.07% for MB, RR, CV, and FG dye, respectively. Further, the adsorption process mainly followed a pseudo-second-order kinetic model, and the thermodynamic studies revealed the exothermic nature of adsorption for RR and FG dye while endothermic for MB and CV dye, respectively with varying from - 1.68 to - 6.12kJ/mol indicating the spontaneity of the process. Importantly, the efficacy of the composite was evaluated for the treatment of textile industry effluent highlighting its potential as an adsorbent for wastewater treatment.

Single and multicomponent adsorption of amoxicillin, ciprofloxacin, and sulfamethoxazole on chitosan-carbon nanotubes hydrogel beads from aqueous solutions: Kinetics, isotherms, and thermodynamic parameters

The removal of antibiotics in water receiving bodies is an integral part in eradicating antimicrobial resistance which has become a major threat to public health. Solid-liquid adsorption has demonstrated to be an effective technique in the removal of antibiotics from aqueous environments. Herein, chitosan-carbon nanotube (chitosan-CNT) hydrogel beads were synthesised for the adsorption of amoxicillin (AMX), ciprofloxacin (CIP) and sulfamethoxazole (SMX) from aqueous solution. Adsorption kinetics, isotherms and thermodynamic parameters were systematically investigated at a solution pH of 7. Single adsorption kinetics findings suggest that experimental data for AMX, CIP and SMX was better fitted by the nonlinear pseudo-first order model with calculated maximum adsorption capacities of 23.1 mg.g−1, 23.7 mg.g−1 and 25.17 mg.g−1, respectively. Moreover, findings from the Weber-Morris kinetic model suggest that multiple processes were limiting the overall adsorption rate of AMX, CIP and SMX on chitosan-CNT. Adsorption isotherm results indicated that single adsorption experimental data was better fitted by the nonlinear Freundlich isotherm model, while binary and ternary system experimental data were better fitted by the nonlinear competitive extended Sips adsorption isotherm models. Moreover, results for binary and ternary adsorption showed that multicomponent adsorption systems exhibited both antagonistic and synergistic adsorption of AMX, CIP and SMX. From the thermodynamics fundings, it was evident that the adsorption of AMX, CIP and SMX from solution is an endothermic process governed by both physical and chemical adsorption mechanisms. Based on the findings of the current study, it was concluded that chitosan-CNT has potential as a green technology for the removal of antibiotics from solution.

Development of a Multicomponent Adsorption Isotherm Equation and Its Validation by Modeling.

Researchers have made significant efforts over the past few decades to understand adsorption by developing various simple adsorption isotherm models. However, though many contaminants usually occur as multicomponent mixtures in nature, multicomponent adsorption isotherms have received limited attention and remain an area of inadequate research. We have presented here in a new multicomponent adsorption isotherm model, named the Jeppu Amrutha Manipal Multicomponent (JAMM) isotherm, that can alleviate this problem. We first developed the JAMM multicomponent isotherm using our experimental data sets of arsenic and fluoride competitive adsorption on activated carbon. We then tested the JAMM multicomponent isotherm for a case study of cadmium and zinc competitive adsorption. Next, we further assessed the JAMM isotherm using another competitive adsorption case study of copper and chromium. Through extensive validation studies and error analysis, the JAMM isotherm was able to demonstrate its efficacy in predicting the adsorption behavior in several multicomponent adsorption systems accurately. The main advantage of JAMM isotherm over other multicomponent isotherms is that it utilizes and leverages the single-component adsorption parameters to simulate multicomponent isotherms. The proposed JAMM analytical isotherm model furthermore incorporates the interaction between the components, a mole fraction parameter, and a heterogeneity index, providing a more comprehensive modeling framework for multicomponent adsorption. The mole fraction term was introduced for the distribution of adsorption sites based on the relative number of molecules of each component. An additional term for interaction coefficient was introduced for the representation of interactions. During the validation of JAMM with three experimental case studies with negligible, small, and high competition systems of adsorbates, impressive predictions were exhibited, with the average normalized absolute percentage error as 6.05% and average R2 as 0.86, highlighting the model's robustness, versatility, and reliability. We propose that the new JAMM isotherm modeling framework might profoundly help in chemical engineering, environmental engineering, and materials science applications by providing a potent tool for analyzing and predicting multicomponent adsorption systems.

Exploring the simultaneous mass transport of nimesulide and paracetamol adsorption on activated carbon: A PVSDM approach

Pore Volume and Surface Diffusion Model (PVSDM) was advanced to Extended PVSDM for modeling multicomponent adsorption systems. The dynamic adsorption of nimesulide and paracetamol on activated carbon was investigated through single and binary adsorption experiments. Langmuir and Extended Langmuir isotherms were used as local equilibrium functions, respectively. The results reveal that single and binary adsorption were affected by both external mass transport and intraparticle diffusion. The coexistence of nimesulide and paracetamol led to a competitive adsorption phenomenon, wherein nimesulide exhibited a higher affinity for the activated carbon surface, primarily occupying its surface active sites, while paracetamol diffuse into the pore volume to be adsorbed, especially at higher initial pharmaceutical concentrations. These findings emphasize the necessity of employing the robust Extended PVSDM for predicting the complex dynamics of binary adsorption. The findings also provide valuable insights that can significantly contribute to the development of efficient adsorption processes, addressing urgent environmental challenges.

Multi-component Adsorption Isotherms: Review and Modeling Studies

Adsorption is an important phenomenon widely used for the removal of contaminants. Several drinking water contaminants such as arsenic and fluoride, vanadium and chromium, nickel, cadmium and cobalt are found to coexist in nature as multi-component mixtures in water. Hence, the modeling of multi-component adsorption isotherms for designing water treatment systems has gained importance recently. However, review studies of multi-component adsorption and competitive adsorption modeling are limited. The current review paper summarizes twenty-six multi-component adsorption isotherm models. Also, case studies of several common multi-component adsorption systems and the mechanisms of multi-component adsorption are discussed. Furthermore, a modeling analysis of four multi-component isotherms models for three commonly found two-component adsorption systems, i.e., cadmium-nickel, nickel–cobalt, and cadmium-cobalt, is reported. The Extended Langmuir isotherm, Competitive Langmuir isotherm, Extended Langmuir–Freundlich isotherm and Extended Freundlich isotherm models were applied in the modeling study for the competitive adsorption of Cd, Ni, and Co. The goodness of fit parameters and adsorption isotherm constants were estimated for these models. The factors influencing competitive adsorption, mechanisms of adsorption, various single and multi-component isotherm models, their significance, and limitations are also discussed in this review article.Highlights• Twenty-six multi-component and ten single-component isotherm models are compiled• Factors affecting multi-component competitive adsorption isotherms are discussed in this review paper• The applications of four multi-component isotherm models for three binary contaminant systems are presented.Graphical

Storing carbon dioxide in deep unmineable coal seams for centuries following underground coal gasification

Underground coal gasification (UCG) has a huge potential in extracting energy from deep coal seams with a low environmental footprint. A vast void space created in a UCG operation serves as an effective sink to anthropogenic CO2 storage and sequestration. To advance the knowledge base regarding CO2 storage in post-UCG cavities, a 3D commercial-scale 990m × 60m × 24 m multi-cavity scenario was constructed to model the transport and fate of the stored CO2 plume at around 1000 m depth for centuries using a coalbed methane (CBM) and CO2 storage dedicated simulator. The effects of the import multiphysics were analyzed. It was revealed that transport phenomena entered a stabilized steady state in 50 years in a multicomponent adsorption system. In addition, the matrix-cleat diffusion exhibited a substantially strong trapping mechanism with an at-equilibrium spread-out speed of 0.24 m/year. Dynamic changes in a cleat system and an injection process were shown to play a minor role. Furthermore, two effective means were proposed for a protracted thousands-of-year simulation of CO2 storage in post-UCG multiple cavities. The relevant findings in this paper would promote the utility and applicability of UCG in the world's deep coal seams for the transition of the coal industry in a carbon-conscious world.

Simulation of Adsorption Process of l-Tryptophan on Mixed-Mode Resin HD-1 with Combined Physical Adsorption and Ion Exchange.

The mass-transfer process of l-tryptophan (l-Trp) in the hydrophobic interaction/ion-exchange mixed-mode resin HD-1 particles and fixed bed was studied experimentally and theoretically. The adsorption kinetics of l-Trp in single-component and multicomponent adsorption systems was investigated under different pH conditions. The co-adsorption of sodium ions (Na+) and l-Trp anions was found to be negligible. A modified liquid-film linear driving force model considering the physical adsorption of l-Trp zwitterions and anions as well as ion exchange of l-Trp cations was proposed. The dissociation equilibria of l-Trp molecules and functional groups on the resin were introduced in the model. The model could well fit the kinetic adsorption curves of l-Trp at different pH values. The presence of Na+ and the impurity amino acid l-glutamic acid (l-Glu) did not significantly affect the mass-transfer rate of l-Trp. The dynamic adsorption processes of l-Trp under different pH and concentration conditions were studied. A modified transport-dispersive model considering axial diffusion, liquid-film mass transfer, and a combined physical adsorption and ion-exchange equilibrium was established, which could predict the adsorption breakthrough curves of l-Trp well. During the dynamic adsorption process, the pH of mobile phase in the fixed bed changed with changing the l-Trp concentration in the mobile phase. l-Trp was well separated from Na+ and l-Glu with the purity of l-Trp higher than 99%, the recovery rate higher than 95%, and a concentration of 4.69 × 10–3 mol/L. The elution chromatographic peaks of l-Trp, l-Glu, and Na+ and the pH of the outlet solution were predicted satisfactorily.

Competitive adsorption analysis of antibiotics removal from multi-component systems using chemically activated spent tea waste: effect of operational parameters, kinetics, and equilibrium study.

In this study, spent tea powder waste was chemically treated for the synthesis of adsorbent using two activating agents, i.e., sulfuric acid and phosphoric acid, to obtain sulfuric acid activated carbon (SAC) and phosphoric acid activated carbon (PAC). The performance of PAC and SAC for the sorption of tetracycline (TCY) and sulfadiazine (SDZ) antibiotics from mono-component (SDZ/TCY) and multi-component (SDZ + TCY) adsorption systems was investigated. Synergistic and antagonistic effects were studied in removing target pollutants in SDZ + TCY systems. Kinetic and equilibrium studies were modeled by different kinetic and isotherm models. The adsorption capacity was assessed using Langmuir's competitive model in a [Formula: see text]. Pseudo-first-order kinetic and Langmuir isotherm models best fit the experimental kinetic and equilibrium data to remove antibiotics. The Langmuir's maximum adsorption capacity (qm) of PAC for the removal of SDZ and TCY in a [Formula: see text] was found to be 16.75 and 10.87mg/g, and qm of SAC for the removal of SDZ and TCY was found to be 24.69 and 23.20mg/g, respectively. In SDZ + TCY multi-component system, adsorption of TCY was synergistic in nature for both PAC and SAC. Sorption of SDZ displayed an antagonistic effect in the SDZ + TCY system for both SAC and PAC. In conclusion, the activated carbons synthesized from spent tea waste could be effectively adopted for the simultaneous adsorption of SDZ and TCY from multi-component systems.

A Review of the Modeling of Adsorption of Organic and Inorganic Pollutants from Water Using Artificial Neural Networks

The application of artificial neural networks on adsorption modeling has significantly increased during the last decades. These artificial intelligence models have been utilized to correlate and predict kinetics, isotherms, and breakthrough curves of a wide spectrum of adsorbents and adsorbates in the context of water purification. Artificial neural networks allow to overcome some drawbacks of traditional adsorption models especially in terms of providing better predictions at different operating conditions. However, these surrogate models have been applied mainly in adsorption systems with only one pollutant thus indicating the importance of extending their application for the prediction and simulation of adsorption systems with several adsorbates (i.e., multicomponent adsorption). This review analyzes and describes the data modeling of adsorption of organic and inorganic pollutants from water with artificial neural networks. The main developments and contributions on this topic have been discussed considering the results of a detailed search and interpretation of more than 250 papers published on Web of Science ® database. Therefore, a general overview of the training methods, input and output data, and numerical performance of artificial neural networks and related models utilized for adsorption data simulation is provided in this document. Some remarks for the reliable application and implementation of artificial neural networks on the adsorption modeling are also discussed. Overall, the studies on adsorption modeling with artificial neural networks have focused mainly on the analysis of batch processes (87%) in comparison to dynamic systems (13%) like packed bed columns. Multicomponent adsorption has not been extensively analyzed with artificial neural network models where this literature review indicated that 87% of references published on this topic covered adsorption systems with only one adsorbate. Results reported in several studies indicated that this artificial intelligence tool has a significant potential to develop reliable models for multicomponent adsorption systems where antagonistic, synergistic, and noninteraction adsorption behaviors can occur simultaneously. The development of reliable artificial neural networks for the modeling of multicomponent adsorption in batch and dynamic systems is fundamental to improve the process engineering in water treatment and purification.

Simultaneous adsorption of methylene blue and heavy metals from water using Zr-MOF having free carboxylic group

Industrial effluents contain multiple pollutants, which affect the quality of water remediation operations. Hence, it is important to understand the outcome of the multicomponent adsorption system to develop efficient decontamination process. In this work, acid assisted hydrothermal method (reflux temperature at atmospheric pressure) was employed to synthesize zirconium based metal-organic framework (MOF) and utilized for the adsorptive removal of methylene blue (MB) dye and heavy metals (lead and cadmium) from aqueous solution. The adsorbent was characterized by powder X-ray diffraction (PXRD), which confirms the face centered cubic (FCC) crystal structure similar to previously reported UiO-66. Brunauer–Emmett–Teller (BET) and surface area analysis shows that, the MOF has surface area of 505 m2.g−1 and micropores ranging from 0.4 to 0.7 nm. Fourier transform infrared spectroscopy (FTIR) analysis corroborate the presence of free carboxylic groups at 1710 cm−1, apart from this FTIR confirms the presence of regular bands of metal-carboxylic bonds. X-ray photoelectron spectroscopy (XPS) analysis of the adsorbent was conducted to understand the nature of adsorbate-adsorbent interaction and to confirm the loading of metal ions on adsorbent after adsorption. The morphological nature of the MOF was analyzed by scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDX). Effects of various parameters such as pH, adsorbent dosage, adsorption time and effect of initial concentration of adsorbates on adsorption were evaluated. Kinetics and isotherm studies were conducted to understand the nature and extent of adsorption. Langmuir monolayer adsorption capacity of the adsorbent for cadmium, lead and methylene blue were found to be 37 mg.g−1, 100 mg.g−1 and 169 mg.g−1 respectively.

Batch adsorption isotherm models applied in single and multicomponent adsorption systems – a review

The advancement in urbanization and industrialization in recent times due to increase in population has led to generation of huge quantities of pollutants which are discharged into the biota without proper treatment leading to environmental pollution. This situation is causing a lot of concern to environmental conservationists. It has been proven that adsorption is superior to most of the conventional treatment techniques due to the fact that it is easy to design, insensitive to toxic pollutants, cheap and very efficient in removing pollutants at low solution concentrations. An adsorption isotherm relates the concentration of adsorbed adsorbate in the adsorbent to that in the bulk solution at constant pH and temperature. Hence isotherm modeling can predict the amount of adsorbate a given quantity of adsorbent can remove from solution under given conditions. This article reviewed various isotherm models used to describe adsorption systems whether singular or multiple-component. The applications, advantages and disadvantages are discussed. Error functions which bring out the closeness of predicted results to experimental data are discussed. The difficulty in predicting physisorption with isotherm models is mentioned suggesting that researches should be carried out applying IUPAC type VI Isotherms to resolve the problem.

Antagonistic and synergistic analysis of antibiotic adsorption on Prosopis juliflora activated carbon in multicomponent systems

The synergistic and antagonistic adsorption involved in the removal of antibiotics in multicomponent systems was investigated. In this study, potassium hydroxide (KOH) activated Prosopis juliflora activated carbon (KPAC) was prepared, characterized and used for the removal of sulfadiazine (SDZ), metronidazole (MET) and tetracycline (TET) antibiotics from single, binary and ternary adsorption systems. The effects of experimental parameters i.e. contact time, adsorbent dose, pH and initial adsorbate concentration was investigated. Traditional kinetic and isotherm models were utilized to model experimental kinetic and equilibrium data. Meanwhile, Langmuir’s competitive model was used to investigate adsorption capacity in multicomponent systems. Subsequently, kinetics and equilibrium data were better represented by pseudo-second-order and Langmuir isotherm models, respectively. The results showed that maximum sorption capacity of KPAC was 18.48, 25.06 and 28.81 mg/g for removal of SDZ, MET and TET, respectively, in single-component adsorption system. Moreover, total adsorption yield of single-component system was higher in comparison with multicomponent adsorption systems. Furthermore, the results showed that multicomponent systems exhibited both antagonistic and synergistic adsorption of antibiotics. Desorption study showed that maximum desorption of SDZ, MET and TET was 11.7%, 22.5% and 13.9%, respectively. In conclusion, KPAC has potential to be used as an adsorbent for removal of antibiotic(s).

Application of Kinetic Models for Heavy Metal Adsorption in the Single and Multicomponent Adsorption System

The overall rate of heavy metal adsorption on the porous sorbent consists of three separate steps: external mass transport, intraparticle diffusion, and adsorption on active sites. The pseudo-first-order model, pseudo-second-order model, and film-pore volume diffusion model are three types of kinetic models that have developed based on these steps. In this research, studies for predicting these kinetic models from the concentration decay curves of Pb2+, Cd2+, Ni2+, and Zn2+ were done on a batch adsorption process. Evaluation of the models prediction was performed by two separate reported experimental data. There is limited literature on the application of film-pore volume diffusion model for multicomponent adsorption systems in previous modeling studies; hence, the performance of this kinetic model was evaluated in this study using data from concentration decay curves of multicomponent adsorption systems. Investigation showed that for different adsorption systems, the application of the film-pore volume diffusion model has decreased the average relative error between 1–83% and 1–40% in comparison to the pseudo-first-order and pseudo-second-order model, respectively. More accurate prediction of the film-pore volume diffusion model is related to consideration of external mass transfer resistance on prediction. Effective pore volume diffusivity of different metal ions was calculated between 0.004 × 10−6 cm2 s−1 and 2.2 × 10−6 cm2 s−1 for a different adsorption system.

Modeling of milk lactose removal by column adsorption using artificial neural networks: MLP and RBF

Artificial neural network (ANN) techniques are effective in modeling nonlinear processes, are simple to implement and require low computational time. In this work, the lactose adsorption process for continuous flow in a fixed-bed column with a molecularly imprinted polymer (MIP) adsorbent was modeled using an ANN technique. The neural models allowed predicting the relative lactose concentration (C/C0) from the interactions between the variables of contact time (min), temperature (?C), granulometry (mesh), bed height (cm) and flow rate (mL min-1). The ANN models were developed in MATLAB using multilayer perceptrons (MLP) and a radial basis function network (RBF). The MLP model was developed using a three-layer feed forward backpropagation network with 5, 8 and 4 neurons in the first, second and third layer, respectively. The function (RBF) network is also proposed and its performance is compared to a traditional network type. The best architecture configuration RBF model was developed using 5, 14 and 1 neurons in the first, second and third layer, respectively. The proposal of development of mathematical models applied to multi-component adsorption system for milk using these approaches is innovative. The resulting breakthrough curve models for lactose adsorption were in good agreement with the experimental results. Performance indices, such as R?, MSE, RMSE, SSE, MAE and RME were used to evaluate the reliabilities and accuracies of the models. A comparison between the ANN models shows the ability to predict the breakthrough curves of lactose removal in the milk adsorption process. Though, the MLP network model shows more accurately a higher correlation coefficient (R2 = 0.9751) and lower values for the obtained error indices. The accuracy of the model is confirmed by the comparison between the predicted and experimental data. The results showed that both neural models efficiently described the non-linear process of lactose adsorption in a fixed-bed column.

Individual and simultaneous adsorption of Ni (II), Cd (II), and Zn (II) ions over polyamide resin: Equilibrium, kinetic and thermodynamic studies

Heavy metal pollution is a serious environmental issue worldwide with rapid increase in global industrial activities (Podder and Majumder [2016]: Water Conserv Sci Eng 1, 103–125). In this study, aromatic polyamide (PA) containing the azomethine group (Vidhyadevi et al. [2012]: Sep Sci Technol 48, 1450–1458) was used as an adsorbent for the individual and simultaneous adsorption of Ni (II), Cd (II), and Zn (II) ions from their aqueous solutions. Equilibrium, kinetic, and thermodynamic analyses of Ni (II), Cd (II), and Zn (II) ions adsorption were also carried out. The kinetic study on heavy metal ions adsorption suggests that the adsorption follows pseudo‐second‐order kinetic model. The thermodynamic study results revealed that the process is spontaneous and exothermic in nature. In the multicomponent adsorption system, adsorption of one metal ion was considerably reduced by the presence of other ions in the solution due to competition for the active sites on PA. The adsorption of heavy metal ions over PA was confirmed through FT‐IR, SEM, and EDX analyses. The adsorption capacity of PA was found significantly higher than other adsorbents. The PA could be regenerated and reused even after five cycles for the Ni (II), Cd (II), and Zn (II) ions suggesting that adsorption using the PA is a reversible process. Significance of the present work Polyamide resin (PA) is an effective adsorbent for the individual and simultaneous removal of Ni (II), Cd (II), and Zn (II). Maximum adsorption capacity of PA for Ni (II), Cd (II), and Zn (II) ions were found to be better than other commonly used adsorbents. Repeated desorption studies indicate that the PA may be reused and the adsorption is a reversible process. Adsorption mechanism of metal ions over PA is explained. © 2018 American Institute of Chemical Engineers Environ Prog, 38: S340–S351, 2019

Evaluation of single-component and multi-component adsorption of metronidazole, phosphate and nitrate on activated carbon from Prosopıs julıflora

In this investigation, activated carbon was prepared from Prosopis juliflora (PJAC) and characterized using porosimetry, scanning electron microscope (SEM-EDX), Elemental analysis (CHNS), Fourier Transmission-Infrared Radiation (FTIR) and X-ray Diffraction (XRD) analysis. Subsequently, PJAC was used in single-component (metronidazole (MNZ), phosphate (PO43−) and nitrate (NO3−)) and multi-component (MNZ:P:N) adsorption systems. As a first step, single-component batch adsorption experiments, i.e. kinetic and equilibrium studies, were conducted at controlled conditions (30 °C) and outcomes were used to find out the rate constant and maximum adsorption capacity (qm). The pseudo-second-order kinetic model was found to well represent the removals of MNZ, PO43− and NO3− on PJAC. Among the five isotherm models used, Langmuir isotherm model has predicted qm of PJAC for MNZ (17.33 mg/g), PO43− (13.55 mg/g) and NO3− (10.99 mg/g) with good correlation. In addition, the thermodynamic parameters have shown that adsorption of MNZ, PO43− and NO3− was non-spontaneous, endothermic and increased randomness in nature. In order to quantify the competitive adsorption of the multi-component system, i.e. MNZ, PO43− and NO3−, the batch experiments were conducted in the presence of all three compounds at a ratio of 1:2.5:5 at three different MNZ:P:N concentrations levels (0.1:0.25:0.5, 1:2.5:5 and 10:25:50 mg/L). The modified Langmuir competitive adsorption isotherm model was used to predict the effect of competitive adsorption. In the multi-component system, the maximum adsorption capacities of MNZ and NO3− were decreased by ∼34 and ∼2 times, respectively than single compound system; however, it was increased by ∼1.12 times for PO43−. Overall, the results indicate that PJAC could be used as a potential adsorbent for the removal of emerging pollutants and nutrients.

Insights and pitfalls of artificial neural network modeling of competitive multi-metallic adsorption data

This manuscript discusses the advantages and limitations of ANNs models for modeling and predicting multi-component adsorption of heavy metal ions on bone char. In particular, the simultaneous adsorption of cadmium, nickel, zinc and copper ions in binary, ternary and quaternary mixtures on bone char has been used as a case study to analyze the problems associated with the training variables, activation function and architecture used in the ANNs modeling of multi-metallic adsorption data. The results of this study demonstrated that a proper ANNs training variable was fundamental for a reliable fitting and for the prediction of the complex adsorption behavior of metallic mixtures. In particular, the use of equilibrium concentrations as output data for the training of ANNs model may cause incorrect predictions of the multi-metallic adsorption on bone char. These pitfalls of ANNs models could prevail for multi-component systems with an antagonistic adsorption if extensive variables, such as equilibrium concentrations or removal percentages, were used in the training stage. These findings are valuable and can be used as guidelines for the application of ANNs models in the simulation and prediction of multi-component adsorption systems involved in water treatment and purification.

Antagonistic binary adsorption of heavy metals using stratified bone char columns

This manuscript introduces the application of reverse stratified bone char adsorbers for the binary adsorption of copper and zinc from aqueous solution. The impact of adsorbent bed layering on the antagonistic adsorption of these heavy metals ions using bone char has been studied. Breakthrough parameters of stratified columns have been calculated and analyzed for the removal of tested heavy metals. Results showed that the stratified adsorption columns have better breakthrough parameters for the antagonistic adsorption of these heavy metals in comparison to conventional packed bed columns. The competitive adsorption effect caused by co-ion can be reduced in stratified packed columns in contrast to the conventional bed configuration enhancing the bed utilization and adsorption capacities besides a reduction in the selectivity (i.e., the adsorbent preference for the adsorption of a specific adsorbate) for heavy metal removal. The improvements in the adsorption process were more evident for Zn2+ removal, which was very sensitive to the presence of Cu2+ ions. These benefits have been obtained even operating at column conditions where the presence of axial dispersion and mass transfer resistances has a significant impact on adsorption effectiveness. On the other hand, an artificial neural network (ANNs) model was used for correlating the breakthrough curves of stratified bone char adsorbers. The modeling of the binary adsorption breakthrough curves of these metals with stratified columns was challenging even for the ANNs approach, which has been recognized as an effective intelligent algorithm for data processing. In particular, ANNs model displayed the highest modeling errors in the breakthrough zone of Ct/C0 patterns. This finding highlighted the importance of developing alternative and robust modeling approaches for simulating and predicting the performance of multicomponent adsorption systems using intensified processes such as stratified packed bed columns. In summary, results of this study contribute to the understanding and application of intensified adsorption processes for facing water pollution problems caused by heavy metals and other priority pollutants.