Capture of I131 from medical-based wastewater using the highly effective and recyclable adsorbent of g-C3N4 assembled with Mg-Co-Al-layered double hydroxide

RSM and ANN methodologies in modeling the enhanced biodiesel production using novel protic ionic liquid anchored on g-C3N4@Fe3O4 nanohybrid

Herin, a new nanohybrid acid catalyst was fabricated for the efficient biodiesel production. At the first, magnetic porous nanosheets of graphitic carbon nitride (g-C3N4@Fe3O4) was prepared and then functionalized with sulfonic acid. Next, the preparation of the catalyst was completed by mixing this surface modified support with n-methyl imidazolium butyl sulfonate zwitterion to achieve non-covalent immobilized acidic ionic liquid on g-C3N4@Fe3O4 support. The catalyst underwent characterization through various techniques such as 1H and 13C NMR, FTIR, SEM, TEM, TGA, EDX and BET which revealing that the magnetic support loaded acidic ionic liquids via a robust charge interaction effect enabling the one-pot production of biodiesel from low-quality oils. Furthermore, the catalyst could be simply recovered using a permanent magnet and reused multiple times without a significant decline in catalytic activity. Consequently, the solid catalyst based on ionic liquids holds promise for the sustainable and eco-friendly production of biodiesel from low-quality oils. Furthermore, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were used to model the yield and various process parameters. The findings underscore the enhanced predictive capabilities of ANN in comparison to RSM.

Application of machine learning for antibiotic resistance in water and wastewater: A systematic review

Antibiotic resistance (AR) is considered one of the greatest global threats in the current century, which can only be overcome if all interconnected areas of humans, animals and the environment are taken into account as part of the One Health concept proposed by the World Health Organization (WHO). Water and wastewater are among the most important environmental media of AR sources, where the phenomena are generally non-linear. Therefore, the aim of this study was to investigate the application of machine learning-based methods (MLMs) to solve AR-induced problems in water and wastewater. For this purpose, most relevant databases were searched in the period between 1987 and 2023 to systematically analyze and categorize the applications. Accordingly, the results showed that out of 12 applications, 11 (91.6%) were for shallow learning and 1 (8.3%) for deep learning. In shallow learning category, n = 6, 50% of the applications were regression and n = 4, 33.3% were classification, mainly using artificial neural networks, decision trees and Bayesian methods for the following objectives: Predicting the survival of antibiotic-resistant bacteria (ARB), determining the order of influencing parameters on AR-based scores, and identifying the major sources of antibiotic resistance genes (ARGs). In addition, only one study (8.3%) was found for clustering and no study for association. Surprisingly, deep learning had been used in only one study (8.3%) to predict ARGs sequences. Therefore, working on the knowledge gaps of AR, especially using clustering, association and deep learning methods, would be a promising option to analyze more aspects of the related problems. However, there is still a long way to go to consider and apply MLMs as unique approaches to study different aspects of AR in water and wastewater.

Efficient removal of ciprofloxacin and ofloxacin from aqueous solutions using a novel nano-scale adsorbent: Modeling, optimization, and characterization

In the fascinating realm of water purification, our study unveils the remarkable potential of a cutting-edge nano-scale adsorbent-combining graphene oxide (GO), chitosan (CS), and polydopamine (PDA)-in efficiently remove ciprofloxacin (CPF) and ofloxacin (OFL) from aqueous solutions. Our exploration delves deep into the adsorbent's character, utilizing a range of analytical techniques including SEM, RAMAN, FTIR, TGA, BET, XRD, and Zeta potential analyses provided insights into the adsorbent's properties. Modeling the adsorption process with Response Surface Methodology (RSM), Artificial Neural Network (ANN) and General Regression Neural Network (GRNN) indicated excellent predictions by GRNN, with RMSE = 0.0200 and 0.0166, MAE = 0.0082 and 0.0092, as well as AAD = 0.0002 and 0.0006, highlighting its modeling power. Optimization using genetic algorithm (GA) revealed maximum CPF removal efficiency of approximately 95.20% under pH = 6.3, sonication time = 9.0 min, adsorbent dosage = 2.10 g L⁻1, temperature = 45 °C and initial CPF concentration = 90.0 mg L⁻1. Similarly, OFL removal reached about 95.50% under pH = 6.30, sonication time = 8.0 min, adsorbent dosage = 2.0 g L⁻1, temperature = 45 °C and OFL concentration = 115.0 mg L⁻1. RSM optimization closely aligned with GA results. Pseudo-second-order (PSO) kinetic model and Langmuir isotherm model best fitted the experimental data for both antibiotics. Thermodynamic analysis indicated a favorable and spontaneous adsorption process for CPF and OFL. The study concludes that the proposed adsorbents show effectiveness in removing CPF and OFL at lower doses and shorter sonication times compared to various reported adsorbents.

Evaluating the efficacy of recyclable nanostructured adsorbents for rapid removal of methylparaben from aqueous solutions

In this study, we evaluate the efficiency of two novel nanostructured adsorbents - chitosan-graphitic carbon nitride@magnetite (CS-g-CN@Fe3O4) and graphitic carbon nitride@copper/zinc nanocomposite (g-CN@Cu/Zn NC) - for the rapid removal of methylparaben (MPB) from water. Our characterization methods, aimed at understanding the adsorbents' structures and surface areas, informed our systematic examination of influential parameters including sonication time, adsorbent dosage, initial MPB concentration, and temperature. We applied advanced modeling techniques, such as response surface methodology (RSM), generalized regression neural network (GRNN), and radial basis function neural network (RBFNN), to evaluate the adsorption process. The adsorbents proved highly effective, achieving maximum adsorption capacities of 255 mg g-1 for CS-g-CN@Fe3O4 and 218 mg g-1 for g-CN@Cu/Zn NC. Through genetic algorithm (GA) optimization, we identified the optimal conditions for the highest MPB removal efficiency: a sonication period of 12.00 min and an adsorbent dose of 0.010 g for CS-g-CN@Fe3O4 NC, with an MPB concentration of 17.20 mg L-1 at 42.85 °C; and a sonication time of 10.25 min and a 0.011 g dose for g-CN@Cu/Zn NC, with an MPB concentration of 13.45 mg L-1 at 36.50 °C. The predictive accuracy of the RBFNN and GRNN models was confirmed to be satisfactory. Our findings demonstrate the significant capabilities of these synthesized adsorbents in effectively removing MPB from water, paving the way for optimized applications in water purification.

A new tannin-based adsorbent synthesized for rapid and selective recovery of palladium and gold: Optimization using central composite design

A tannin-based adsorbent was synthesized by pomegranate peel tannin powder modified with ethylenediamine (PT-ED) for the rapid and selective recovery of palladium and gold. To characterize PT-ED, field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS-Mapping), and Fourier transform infrared spectroscopy (FT-IR) were used. Central composite design (CCD) was used for optimization. The kinetic, isotherm, interference of coexisting metal ions, and thermodynamics were studied. The optimal conditions, including Au (III) concentration = 30 m g L - 1 , Pd (II) concentration = 30 m g L - 1 , adsorbent mass = 26 mg, pH = 2, and time = 26 min with the sorption percent more than 99 %, were anticipated for both metals using CCD. Freundlich model and pseudo-second-order expressed the isotherm and kinetic adsorption of the both metals. The inhomogeneity of the adsorbent surface and the multi-layer adsorption of gold and palladium ions on the PT-ED surface are depicted by the Freundlich model. The thermodynamic investigation showed that P d 2 + and A u 3 + ions adsorption via PT-ED was an endothermic, spontaneous, and feasible process. The maximum adsorption capacity of P d 2 + and A u 3 + ions on PT-ED was 261.189 m g g - 1 and 220.277 m g g - 1 , respectively. The probable adsorption mechanism of P d 2 + and A u 3 + ions can be ion exchange and chelation. PT-ED (26 mg) recovered gold and palladium rapidly from the co-existing metals in the printed circuit board (PCB) scrap, including Ca, Zn, Si, Cr, Pb, Ni, Cu, Ba, W, Co, Mn, and Mg with supreme selectivity toward gold and palladium. The results of this work suggest the use of PT-ED with high selectivity and efficiency to recover palladium and gold from secondary sources such as PCB scrap.

Double ionic liquid reinforced g-CN nanocomposite for an enhanced adsorption of methylparaben: Mechanism, modeling, and optimization

The efficient removal of organic pollutants, especially pharmaceuticals, from aquatic environments has attracted great attentions. Application of green, multipurpose, and inexpensive compounds is being extensively favorite as adsorbent instead of the traditional chemicals or materials. In this study, sulfonated graphitic carbon nitride was modified with two ionic liquids of polyethyleneimine and choline chloride to create a novel nanocomposite (Sg-CN@IL2 NC) and to use for removal of methylparaben (MeP) from aqueous media. After confirmation of the successful synthesized using different methods, the effective parameters for MeP removal, such as initial MeP concentration, adsorbent dose, sonication time, and temperature, as well as their interactions, were experimentally examined and modeled using response surface methodology (RSM), generalized regression neural network (GRNN), and radial basis function neural network (RBFNN). The models were then optimized using desirability function analysis (DF) and genetic algorithm (GA). The results showed that MeP adsorption: a) can be explained more accurate and reliable using GRNN (AARD% = 11.67, MAE = 15.31, RAE % = 45.42, RRSE % = 55.18, MSE = 435.86, RMSE = 20.70, and R2 = 0.995) than the others; b) reached equilibrium within 7.0 min with a maximum uptake of 267.2 mg/g at a temperature of 45 °C and a neutral pH; c) followed from Freundlich (R2 = 0.999) isotherm and PSO kinetic (R2 = 0.95) models; d) is endothermic and spontaneous; e) is mainly due to π-π stacking, electrostatic and hydrogen bonding interactions. Moreover, Sg-CN@IL2 NC showed an appropriate reusability for up to five cycles. These findings demonstrate the potential of as-prepared NC as an excellent adsorbent for removal of MeP from aqueous media.

Novel g-C3N4/PrFeO3 nanocomposites with Z-scheme structure and superior photocatalytic activity toward visible-light-driven removal of tetracycline antibiotics

In the presented work, heterostructured nanocomposites based on g-C3N4 and PrFeO3 with different mass content of PrFeO3 (0-10 wt%) were prepared by ultrasonic processing to study their photocatalytic activity in the process of antibiotic degradation under visible light. The study of phase composition, structural, morphological and textural characteristics carried out by powder X-ray diffraction, scanning electron microscopy and adsorption-structural analysis confirmed the presence of two phases - graphite-like C3N4 and orthorhombic PrFeO3 with average crystallite sizes of 5 and 21 nm and mesoporous structure with specific surface area of 57.2-68.6 m2/g and average pore size of 20 nm. The measured values of the forbidden bandwidth for the obtained nanocomposites were ∼3 eV, indicating potential activity under visible light irradiation. The efficiency of antibiotic removal under visible light was evaluated in the degradation of TCHCl. It was found that 5 % PrFeO3 content was optimal and increased the TOF by 5 times compared to pure g-C3N4. The results of photocatalytic test with absorbers showed that photocatalysis occurs by Z-scheme mechanism. The results obtained allow us to consider this nanocomposite as an effective and stable photocatalyst for pharmaceutical wastewater treatment.

Biological treatment of triclosan using a novel strain of Enterobacter cloacae and introducing naphthalene dioxygenase as an effective enzyme

In recent years, triclosan (TCS) has been widely used as an antibacterial agent in personal care products due to the spread of the Coronavirus. TSC is an emerging contaminant, and due to its stability and toxicity, it cannot be completely degraded through traditional wastewater treatment methods. In this study, a novel strain of Enterobacter cloacae was isolated and identified that can grow in high TCS concentrations. Also, we introduced naphthalene dioxygenase as an effective enzyme in TCS biodegradation, and its role during the removal process was investigated along with the laccase enzyme. The change of cell surface hydrophobicity during TCS removal revealed that a glycolipid biosurfactant called rhamnolipid was involved in TCS removal, leading to enhanced biodegradation of TCS. The independent variables, such as initial TCS concentration, pH, removal duration, and temperature, were optimized using the response surface method (RSM). As a result, the maximum TCS removal (97%) was detected at a pH value of 7 and a temperature of 32 °C after 9 days and 12 h of treatment. Gas chromatography-mass spectrometry (GC/MS) analysis showed five intermediate products and a newly proposed pathway for TCS degradation. Finally, the phytotoxicity experiment conducted on Cucumis sativus and Lens culinaris seeds demonstrated an increase in germination power and growth of stems and roots in comparison to untreated water. These results indicate that the final treated water was less toxic.

Efficient removal of levofloxacin by a magnetic NiFe-LDH/N-MWCNTs nanocomposite: Characterization, response surface methodology, and mechanism

Antibiotic pollutants in water bodies, was studied to remove using an oxidized, nitrogen-doped, and Fe₃O₄ and NiFe-LDH decorated MWCNT (magnetic NiFe-LDH/N-MWCNTs) nanocomposite (NC). The novel, engineered NC was characterized by different techniques of SEM, XRD, TEM, EDX, and XPS and then examined under different main effective parameters of NC dose, levofloxacin (LVX) concentration, pH, time, and temprature. The experimentally obtained data then evaluated using the modeling approaches of RSM, GRNN, and ANFIS. The as prepared adsorbent showed an excellent adsorption performance (removal efficiency = 95.28% and adsorption capacity = 344.83-454.55 mg/g) under the respective values of the mentioned parameters of 0.152 g, 23.01 mg/L, 12.00 min, and 37.5 °C, respectively. The comparison of the models showed that although all of them accurately predicted the removal efficiency, ANFIS presented the best capability with R², RMSE, MSE, MAE, as well as AAD of 0.9998, 0.0082, -0.0004, 0.0069, 0.1322, respectively. The adsorption by the NC followed Freundlich isotherm (R² = 0.9993) and PSO kinetic (>0.998) models, confirming a heterogenous chemisorption process. The thermodynamic parameters showed an endothermic and spontaneous nature for LVX removal by magnetic NiFe-LDH/N-MWCNTs NC. A high-performance efficiency, appropriate reusability (five times without loss of efficiency), as well as easy separation due to magnetic properties, makes the NC to a promising option in removing LVX from water.

Synthesis, characterization, and application of graphene oxide/layered double hydroxide /poly acrylic acid nanocomposite (LDH-rGO-PAA NC) for tetracycline removal: A comprehensive chemometric study

Tetracycline (TC), as the second produced and used antibiotic worldwide, is difficult to be entirely metabolized not only in the body, but also in the treatment processes of water and/or wastewater. Therefore, special attention needs to be paid on defining or developing new options for removing such contaminant. Herein, a reduced graphene oxide (GO) was integrated with Ni-Al layered double hydroxide (LDH) as well poly acrylic acid (LDH-rGO-PAA) and examined to reduce TC -as a model antibiotic-in water media under different operational parameters of TC initial concentration, pH, NC dose, and time. The governed behaviour in the adsorption process was investigated using three model methods of response surface methodology (RSM), artificial neural networks (ANN), and general regression neural network (GRNN) after confirming the physico-chemical properties of LDH-rGO-PAA nanocomposite (NC) using different techniques. The LDH-rGO-PAA NC displayed a good performance as either removal efficiency (R = 94.87 ± 0.25%) or adsorption capacity (q_e = 887.5 mg/g) with the respective values of 110 mg/L, 6.3, 20 mg, and 18.50 min for the mentioned factors (TC initial concentration, pH, NC dose, and time, respectively), which was higher than that of reported for the similar adsorbents until now.

Tetracycline capture from aqueous solutions by nanocomposite of MWCNTs reinforced with glutaraldehyde cross-linked poly (vinyl alcohol)/chitosan

The presence of pharmaceuticals as the emerging contaminates needs novel approaches and new materials to be remediated. This study aimed to develop and apply MWCNTs reinforced with glutaraldehyde cross-linked poly (vinyl alcohol)/chitosan nanocomposite (MWCNTs/CS-PVA/GA NC) for removal of tetracycline (TC) as a model of antibiotics from aqueous solutions. The successful synthesis of NC was supported by techniques of SEM, XRD, TGA, FTIR, and EDX. The prepared NC was then utilized for TC adsorption under the main effective parameters of TC concentration (25-125 mg/L), sonication time (0-8 min), NC dose (1-130 mg), and tempearure (5-45 °C). The process behavior was comparably explored with different methods of central composite design (CCD), artificial neural networks (ANN), and general regression neural network (GRNN). The results showed that under the optimum settings presented by desirability function (DA), in which the respective values for the factors were 125 mg/L, 6.8 min, 130 mg, and 45 °C, the efficiency and adsorption capacity of NC is supposed to be 99.07% and ∼525 mg/g, respectively. From the models studied, although all were able to express the process with satisfactory accuracy, ANN provided the best accuracy and reliability owning to the highest R² (0.999) and lowest RMSE, ADD, MAE. The kinetics, isotherms, and thermodynamic studies showed that the process is fast (over 4.5 min), chemisorption, heterogeneous with multilayer nature, spontaneous, feasible, and endothermic. In addition, the as prepared NC could be recycled for five times without significant fail in its performance. All in all, the developed MWCNTs/CS-PVA/GA NC can be considered as a promising candidate in dealing with aqueous solutions' pollution with antibiotic.

Enhanced removal of radioactive iodine anions from wastewater using modified bentonite: Experimental and theoretical study

Efficient and cost-effective removal of radioactive iodine anions from contaminated water has become a crucial task and a great challenge for waste treatment and environmental remediation. Herein, we present hexadecylpyridinium chloride monohydrate modified bentonite (HDPy-bent) for the efficient and selective removal of iodine anions (I^- and IO₃^-) from contaminated water. Batch experiments showed that HDPy-bent could remove more than 95% of I^- and IO₃^- within 10 min, and had maximum I^- and IO₃^- adsorption capacities of 80.0 and 50.2 mg/g, respectively. Competitive experiments indicated that HDPy-bent exhibited excellent I^- and IO₃^- selectivity in the excessive presence of common concomitant anions including PO₄^3-, SO₄^2-, HCO₃^-, NO₃^-, Cl^- (maximum mole ratio of anions vs iodine anions was ∼50,000). An anion exchange mechanism was proposed for the selective adsorption of iodine anions. Optimal adsorption structure of HDPy⁺/I^- (IO₃^-) at atomic level and driving forces of the I^- (IO₃^-) adsorption were calculated by density functional theory (DFT) simulations. Moreover, the good durability and reusability of the HDPy-bent has been demonstrated with 5 adsorption-desorption cycles. Dynamic column experiment also demonstrated that HDPy-bent exhibited excellent removal and fractional recovery capabilities towards I^- and IO₃^- from simulated groundwater and environmental water samples. In conclusion, this work presents a promising adsorbent material for the decontamination of radioactive iodine anions from wastewater on a large scale.

Application of response surface method in the separation of radioactive material: a review

Response Surface Method (RSM) is one of the most popular and powerful tools for experimental design and optimization. This paper first reviewed the research progress of RSM in the separation and recovery of various radioactive materials, and verified the application of RSM in adsorption isotherm analysis and thermodynamic calculation. The main advantage of RSM in radioactive material separation is the reduction in the number of experiments required, resulting in considerably less radioactive material consumption, secondary waste generation, workload and radiation dose, which is valuable for the research of radioactive material separation.

Enhanced melanoidin removal by amine-modified Phyllanthus emblica leaf powder

Melanoidins are classified as hazardous colouring and polluting biopolymers, which are generated in very large amounts in molasses-based distillery effluent. In this study, melanoidin was removed through adsorption using amine surface-modified Phyllanthus emblica leaf powder (PELP) as a low-cost natural adsorbent. The amine-modified adsorbents were prepared by forming self-assembled monolayers (SAMs). The pzc of melanoidin and anime-modified PELP were found to be 6.9 and 3.8, respectively. RSM-CCD was used to optimize the environmental conditions considering adsorbent doses (0.2-2 % w/v), pH (3-11) and temperature (25-55 °C). A complete decolourization of melanoidin (98.50 ± 1 %) was observed at the optimized conditions (44.0 °C, pH = 5.93 and dose = 1.34 % w/v) along with 93.4 ± 0.2 % of COD reduction. The surface modification enhanced the maximum adsorption capacity to 616.2 mg g^-1 i.e. 2.5 folds. The modified adsorbent also resulted in colour removal and COD reduction as 91 ± 3 and 84 ± 2 %, respectively from a real spentwash sample.

Synergistic adsorption-photocatalytic degradation of different antibiotics in seawater by a porous g-C3N4/calcined-LDH and its application in synthetic mariculture wastewater

In this work, a modified g-C₃N₄/MgZnAl-calcined layered double hydroxide composite (M-CN/cLDH) was successfully fabricated via a template method. The composite material is a hierarchical porous flower-like nanostructure self-assembled from stacked hybrid flakes. The 3D M-CN/cLDH architectures exhibit a synergistic effect of adsorption and photocatalysis for eliminating typical tetracycline antibiotics in seawater, i.e., oxytetracycline (OTC), tetracycline (TC), chlortetracycline (CTC), and doxycycline (DXC). The synergistic removal rate of OTC in seawater of M-CN/cLDH is 2.73 times higher than that of g-C₃N₄ after 120 min of visible-light illumination, and M-CN/cLDH also performs better adsorption-photocatalytic degradation on OTC in the continuous flow reaction process. The superior adsorption capability of the M-CN/cLDH is attributed to the open porous structures of cLDH, and its excellent photocatalytic degradation activity is ascribed to the closely bonded heterojunctions between g-C₃N₄ (CN) and cLDH double layers. The mass spectra reveals the degradation pathways of OTC, and its byproducts are less toxic after degradation for 120 min. The exploration of the M-CN/cLDH in synthetic mariculture wastewater suggested a huge potential for its practical application. With the assistance of magnesium ammonium phosphate (MAP) precipitation pretreatment, the material can effectively retain the high OTC removal rate in the synthetic mariculture wastewater circumstance.

Barbituric and thiobarbituric acid-based UiO-66-NH2 adsorbents for iodine gas capture: Characterization, efficiency and mechanisms

Efficient iodine gas capture is necessitated in many industries like spent nuclear fuel off-gas treatment in view of environmental protection and resource recycling. However, the adsorption efficiency and stability of the current adsorbents are limited. In the present work, efficient and stable barbituric and thiobarbituric acid-based UiO-66-NH₂ adsorbents (i.e., UiO-66-NH-B.D and UiO-66-NH-T.D, respectively) have been synthesized by post-synthetic covalent modification. Characterization approaches, including SEM-EDS, TEM, XRD, FTIR, XPS, ¹H NMR, TGA and BET, are used to obtain information on the properties and adsorption mechanisms of these metal-organic framework (MOF) adsorbents. The kinetics and mechanisms involved are studied in detail. The treatment efficiency and recyclability of the adsorbents are checked and compared with the adsorbents reported in previous works. The results show that the current adsorbents are potentially suitable for efficient iodine gas capture. High maximum iodine adsorption amount by UiO-66-NH-B.D and UiO-66-NH-T.D (1.17 and 1.33 g/g) was achieved under 75 °C. These new adsorbents are thermally stable for iodine adsorption and regenerated and reused with good performance. The adsorption mechanisms were revealed based on experimental results, indicating that iodine is adsorbed by both physisorption and chemisorption.

Development of a novel graphitic carbon nitride and multiwall carbon nanotube co-doped Ti/PbO2 anode for electrocatalytic degradation of acetaminophen

In this work, we have constructed a novel graphitic carbon nitride/multiwall carbon nanotube (GCN/CNT) doped Ti/PbO₂ as anode for highly effective degradation of acetaminophen (ACE) wastewater. The ACE removal efficiency of 83.2% and chemical oxygen demand removal efficiency of 76.3% are achieved under the optimal condition of temperature 25 °C, initial pH 7, current density 15 mA cm^-2 and Na₂SO₄ concentration 6.0 g L^-1. The excellent electrocatalytic activity of Ti/PbO₂-GCN-CNT anode for ACE oxidation is ascribed to the effective suppression of oxygen evolution and the enhanced electron transfer after introducing GCN and CNT. Furthermore, Ti/PbO₂-GCN-CNT electrode displays excellent stability and reusability. ACE degradation is accomplished by direct oxidation and indirect oxidation, and ∙OH radical plays primary role in the indirect oxidation of ACE wastewater. The intermediates of ACE degradation are detailly investigated using LC-MS analysis and a possible degradation mechanism is proposed.

Ultrasound-assisted solid phase microextraction-HPLC method based on Fe3O4@SiO2-NH2-molecularly imprinted polymer magnetic nano-sorbent for rapid and efficient extraction of harmaline from Peganum harmala extract

In the present study, a magnetic molecularly imprinted polymer (MMIP) was synthesized for the extraction of harmaline from Peganum harmala by dispersive solid-phase microextraction (DSPME). The MMIP for selective and intelligent extraction of harmaline with excellent functionality and high selectivity was synthesized using the sol-gel method with functionalized superparamagnetic core-shell nanoparticles, ethylene glycol dimethacrylate (EDMA) as a cross-linker, methacrylic acid (MAA) as a functional monomer, and 2,2-azobisisobutyronitrile (AIBN) as a porogen. To study the properties and morphology of the coated polymer, FT-IR spectroscopy, FESEM, TEM images, and VSM were used. The DSPME-HPLC-UV equipment was used to quantify and analyze the data obtained from harmaline extraction. In this research, the efficiency of the synthesized polymer in harmaline extraction was modeled and optimized using the response surface methodology based on central composite design (RSM-CCD). In addition, for modeling the isotherm of harmaline sorption by the MMIP, Langmuir and Freundlich isotherm equations were used. The obtained results showed that the extraction of harmaline with the MMIP was well described with Freundlich isotherm. The results of the validation of the method showed that the measurement of harmaline in the concentration range of 1.0-4000 ng mL^-1 followed a linear relationship (R² = 9986.0). Moreover, the accuracy or repeatability index (% RSD) was determined to be < 10, and the LOQ and LOD values were 0.526 and 0.158 ng mL^-1, respectively. The results of this study showed that the DSPME technique by using the synthesized MMIP as an effective sorbent with high efficiency and capacity could be utilized for pre-concentration and extraction of harmaline from real and complex samples.

Reusable fibrous adsorbent prepared via Co-radiation induced graft polymerization for iodine adsorption

Volatile iodine released from nuclear power plant reactors is radiological hazard to environment and human's health because of their high fission yield and environmental mobility. The complexity of nuclear waste management motivated the development of solid-phase adsorbents. Herein, co-radiation induced graft polymerization (CRIGP) was employed in the graft polymerization of N-vinyl-2-pyrrolidone (NVP) onto polyethylene-coated polypropylene skin-core (PE/PP) fibers using electron beam (EB) irradiation. This work provides a one-step green synthetic approach to prepare iodine fibrous adsorbents without any chemical initiators or large amount of organic solvent. The original and modified PE/PP fibers were characterized by fourier transform infrared spectrometry (FTIR), X-ray photoelectron spectroscopy (XPS), thermogravimetric (TG) and scanning electron microscopy (SEM) to demonstrate the grafting of NVP onto the PE/PP fibers. The capacity of iodine absorbed by the PE/PP-g-PNVP fibers was 1237.8 mg/g after 180 min. Meanwhile, absorbents can be regenerated efficiently by two different means of ethanol elution and heating at 120 °C, respectively. Within 10 min, 94.17% and 90.12% of the iodine can be released from the PE/PP-g-PNVP fibers with these two methods, respectively. The adsorbent exhibited a long service life of at least ten adsorption-desorption cycles, suggesting that PE/PP-g-PNVP fibers might be a promising adsorbent for volatile iodine adsorption from fission products in nuclear power plant reactors.