Rapid and high-capacity ultrasonic assisted adsorption of ternary toxic anionic dyes onto MOF-5-activated carbon: Artificial neural networks, partial least squares, desirability function and isotherm and kinetic study

Using predictive models unravel the potential of titanium oxide-loaded activated carbon for the removal of leachate ammoniacal nitrogen

The TiO2 nanocomposite efficiency was determined under optimized conditions with activated carbon to remove ammoniacal nitrogen (NH3-N) from the leachate sample. In this work, the facile impregnation and pyrolysis synthesis method was employed to prepare the nanocomposite, and their formation was confirmed using the FESEM, FTIR, XRD, and Raman studies. In contrast, Raman phonon mode intensity ratio ID/IG increases from 2.094 to 2.311, indicating the increase of electronic conductivity and defects with the loading of TiO2 nanoparticles. The experimental optimal conditions for achieving maximum NH3-N removal of 75.8% were found to be a pH of 7, an adsorbent mass of 1.75 mg/L, and a temperature of 30 °C, with a corresponding time of 160 min. The experimental data were effectively fitted with several isotherms (Freundlich, Hill, Khan, Redlich-Peterson, Toth, and Koble-Corrigan). The notably elevated R2 value of 0.99 and a lower ARE % of 14.61 strongly support the assertion that the pseudo-second-order model compromises a superior depiction of the NH3-N reduction process. Furthermore, an effective central composite design (CCD) of response surface methodology (RSM) was employed, and the lower RMSE value, precisely 0.45, demonstrated minimal disparity between the experimentally determined NH3-N removal percentages and those predicted by the model. The subsequent utilization of the desirability function allowed us to attain actual variable experimental conditions.

Recent trends in wastewater treatment by using metal-organic frameworks (MOFs) and their composites: A critical view-point

Respecting the basic need of clean and safe water on earth for every individual, it is necessary to take auspicious steps for waste-water treatment. Recently, metal-organic frameworks (MOFs) are considered as promising material because of their intrinsic features including the porosity and high surface area. Further, structural tunability of MOFs by following the principles of reticular chemistry, the MOFs can be functionalized for the high adsorption performance as well as adsorptive removal of target materials. However, there are still some major concerns associated with MOFs limiting their commercialization as promising adsorbents for waste-water treatment. The cost, toxicity and regenerability are the major issues to be addressed for MOFs to get insightful results. In this article, we have concise the current strategies to enhance the adsorption capacity of MOFs during the water-treatment for the removal of toxic dyes, pharmaceuticals, and heavy metals. Further, we have also discussed the role of metallic nodes, linkers and associated functional groups for effective removal of toxic water pollutants. In addition to conformist overview, we have critically analyzed the MOFs as adsorbents in terms of toxicity, cost and regenerability. These factors are utmost important to address before commercialization of MOFs as adsorbents for water-treatment. Finally, some future perspectives are discussed to give directions for potential research.

Dye removal with emulsion liquid membrane: experimental design and response surface methodology

This work aims to removing anionic food dyes, Acid Red18 (E124) and Quinoline Yellow WS (E104), from their aqueous solutions. The Emulsion Liquid Membrane (ELM) technique was used. ELM consists of diluent (kerosene), nonionic surfactant (0.5 wt. % Triton X-45), Aliquat 336 as an extractant. Sulfuric acid (H2SO4) solution was used as an internal aqueous phase. The key parameters impacting the stability of liquid membrane and the efficiency of dye removal were investigated; Almost 98% of E124 at 50 mg/L are successfully extracted under optimum conditions. The extraction of a mixture of the two dyes at equal concentrations (25 mg/L) was conducted and their extraction showed more than 95% of efficiency. The experimental results of dye mixture (E124, E104) extraction were expressed by the following three quantities: The concentration of Triton X-45, the concentration of Aliquat 336, and the internal phase concentration of H2SO4, represented on three dimensional plots using the Box-Behnken design and the response surface methodology. For each of the parameters, the values of which were determined by experimental design, these results were subjected to empirical smoothing. The values, thus calculated, are consistent with the measurements.

Sonoactivated Nanomaterials: A potent armament for wastewater treatment

The world is currently facing a critical issue of water pollution, with wastewater being a major contributor. It comes from different types of pollutants, including industrial, medical, agricultural, and domestic. Effective treatment of wastewater requires efficient degradation of pollutants and carcinogens prior to discharge. Commonly used methods for wastewater treatment include filtration, adsorption, biodegradation, advanced oxidation processes, and Fenton oxidation, among others.The sonochemical effect refers to the decomposition, oxidation, reduction, and other reactions of pollutant molecules in wastewater upon ultrasound activation, achieving pollutants removal. Furthermore, the micro-flow effect generated by ultrasonic waves creates tiny bubbles and eddies. This significantly increases the contact area and exchange speed of pollutants and dissolved oxygen, thereby accelerating pollutant degradation. Currently, ultrasonic-assisted technology has emerged as a promising approach due to its strong oxidation ability, simple and cheap equipments, and minimal secondary pollution. However, the use of ultrasound in wastewater treatment has some limitations, such as high energy consumption, lengthy treatment time, limited water treatment capacity, stringent water quality requirements, and unstable treatment effects. To address these issues, the combination of enhanced ultrasound with nanotechnology is proposed and has shown great potential in wastewater treatment. Such a combination can greatly improve the efficiency of ultrasonic oxidation, resulting in an improved performance of wastewater purification. This article presents recent progress in the development of sonoactivated nanomaterials for enhanced wastewater disposal. Such nanomaterials are systematically classified and discussed. Potential challenges and future prospects of this emerging technology are also highlighted.

A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique

Water is the most necessary and significant element for all life on earth. Unfortunately, the quality of the water resources is constantly declining as a result of population development, industry, and civilization progress. Due to their extreme toxicity, heavy metals removal from water has drawn researchers' attention. A lot of scientific applications use artificial neural networks (ANNs) because of their excellent ability to map nonlinear relationships. ANNs shown excellent modelling capabilities for the water treatment remediation. The adsorption process uses a variety of variables, making the interaction between them nonlinear. Selecting the best technique can produce excellent results; the adsorption approach for removing heavy metals is highly effective. Different studies show that the ANNs modelling approach can accurately forecast the adsorbed heavy metals and other contaminants in order to remove them.

An electrochemical sensing platform with a molecularly imprinted polymer based on chitosan-stabilized metal@metal-organic frameworks for topotecan detection

The present study aims to develop an electroanalytical method to determine one of the most significant antineoplastic agents, topotecan (TPT), using a novel and selective molecular imprinted polymer (MIP) method for the first time. The MIP was synthesized using the electropolymerization method using TPT as a template molecule and pyrrole (Pyr) as the functional monomer on a metal-organic framework decorated with chitosan-stabilized gold nanoparticles (Au-CH@MOF-5). The materials' morphological and physical characteristics were characterized using various physical techniques. The analytical characteristics of the obtained sensors were examined by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). After all characterizations and optimizing the experimental conditions, MIP-Au-CH@MOF-5 and NIP-Au-CH@MOF-5 were evaluated on the glassy carbon electrode (GCE). MIP-Au-CH@MOF-5/GCE indicated a wide linear response of 0.4-70.0 nM and a low detection limit (LOD) of 0.298 nM. The developed sensor also showed excellent recovery in human plasma and nasal samples with recoveries of 94.41-106.16 % and 95.1-107.0 %, respectively, confirming its potential for future on-site monitoring of TPT in real samples. This methodology offers a different approach to electroanalytical procedures using MIP methods. Moreover, the high sensitivity and selectivity of the developed sensor were illustrated by the ability to recognize TPT over potentially interfering agents. Hence, it can be speculated that the fabricated MIP-Au-CH@MOF-5/GCE may be utilized in a multitude of areas, including public health and food quality.

Comparative study of ZIF-8-materials for removal of hazardous compounds using physio-chemical remediation techniques

The inherent toxicity, mutagenicity and carcinogenicity of dyes that are discharged into aquatic ecosystems, harming the health of humans and animals. ZIF-8 based composites are regarded as good adsorbents for the breakdown of dyes in order to remove or degrade them. In the course of this research, metal-organic framework materials known as ZIF-8 and its two stable composites, ZIF-8/BiCoO₃ (MZBC) and ZIF-8/BiYO₃ (MZBY), were produced via a hydrothermal process and solvothermal process, respectively, for the dangerous Congo red (CR) dye removal from the solution in water using adsorption method. According to the findings, the most significant amount of CR dye that could be adsorbed is onto MZBC, followed by MZBY and ZIF-8. The pseudo-second-order kinetic model was used effectively to match the data for adsorption behavior and was confirmed using the Langmuir isotherm equation. There is a possibility that the pH and amount of adsorbent might influence the adsorption behavior of the adsorbents. According to the experiment results, the technique featured an endothermic adsorption reaction that spontaneously occurred. The higher adsorption capability of MZBC is because of the large surface area. This results in strong interactions between the functional groups on the surface of MZBC and CR dye molecules. In addition to the electrostatic connection between functional group Zn-O-H on the surface of ZIF-8 in MZBC and the -NH₂ or SO₃ functional group areas in CR molecules, it also includes the strong π-π interaction of biphenyl rings.

How Effective are Metal Nanotherapeutic Platforms Against Bacterial Infections? A Comprehensive Review of Literature

The emergence of multidrug-resistant bacteria has been deemed a global crisis that affects humans worldwide. Novel anti-infection strategies are desperately needed because of the limitations of conventional antibiotics. However, the increasing gap between clinical demand and antimicrobial treatment innovation, as well as the membrane permeability obstacle especially in gram-negative bacteria fearfully restrict the reformation of antibacterial strategy. Metal-organic frameworks (MOFs) have the advantages of adjustable apertures, high drug-loading rates, tailorable structures, and superior biocompatibilities, enabling their utilization as drug delivery carriers in biotherapy applications. Additionally, the metal elements in MOFs are usually bactericidal. This article provides a review of the state-of-The-art design, the underlying antibacterial mechanisms and antibacterial applications of MOF- and MOF-based drug-loading materials. In addition, the existing problems and future perspectives of MOF- and MOF-based drug-loading materials are also discussed.

Recent developments in MOF and MOF based composite as potential adsorbents for removal of aqueous environmental contaminants

With the growth of globalization which has been the primary cause of water pollution, it is utmost necessary for us living being to have access to clean water for the purpose of drinking, washing and various other useful applications. With the purpose of future security and to restore our ecological balance, it is essential to give much significance towards the removal of unwanted toxic contaminants from our water resources. In this regard adsorptive removal of toxic pollutants from wastewater with porous adsorbent is regarded as one of the most promising way for water decontamination process. Metal organic frameworks (MOFs) comprising of uniformly arranged pores, abundant active sites and containing an easily tunable structure has aroused as a promising material for adsorbent to remove the unwanted contaminants from water sources. The adsorption of pollutants by the different MOFs surface are driven by various interactions including π-π, acid-base, electrostatic and H-bonding etc. On the other hand, the removal of various contaminants by MOFs is influenced by various factors including pH, temperature and initial concentration. In this review we will specifically discuss the adsorptive removal of different organic and inorganic pollutants present in our water systems with the use of MOFs as adsorbent along with the various factors and interaction mechanism manipulating the adsorption behaviour.

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.

Experimental and Density Functional Theory Studies on a Zinc(II) Coordination Polymer Constructed with 1,3,5-Benzenetricarboxylic Acid and the Derived Nanocomposites from Activated Carbon

A coordination polymer with the composition C₁₂H₂₀O₁₆Zn₂ (ZnBTC) (BTC = benzene-1,3,5-tricarboxylate) was synthesized under hydrothermal conditions at 120 °C, and its crystal structure was determined using single-crystal X-ray crystallography. First-principles electronic structure investigation of the compound was carried out using the density functional theory computational approach. The highest occupied molecular orbital, the lowest unoccupied molecular orbital, the energy gap, and the global reactivity descriptors of ZnBTC were investigated in both the gas phase and the solvent phase using the implicit solvation model, while the donor-acceptor interactions were studied using natural bond orbital analyses. The results revealed that ZnBTC is more stable but less reactive in solvent medium. The larger stabilization energy E ⁽²⁾ indicates a greater interaction of ZnBTC in the solvent than in the gas phase. Orange peel activated carbon and banana peel activated carbon chemically treated with ZnCl₂ and/or KOH were used to modify the synthesis of ZnBTC to obtain nanocomposites. ZnBTC and the nanocomposites were characterized by powder X-ray diffraction (PXRD), thermogravimetric analysis, and Fourier transform infrared. The specific surface area (S _BET) and the average pore diameter of the materials were determined by nitrogen sorption measurements using the Brunauer-Emmett-Teller (BET) method, while scanning electron microscopy and transmission electron microscopy were used to observe their morphology and particle size, respectively. The PXRD of all the activated carbon materials exhibited peaks at 2θ values of 12.7 and 13.9° corresponding to a d-spacing of 6.94 and 6.32 Å, respectively. The N₂ adsorption-desorption isotherm of the materials are of type II with nanocomposites showing enhanced S _BET compared to the pristine ZnBTC. The results also revealed that activated carbons from the banana peel and the derived nanocomposites exhibited better porous structure parameters than those obtained from orange peel. The degradation efficiency of methyl orange in aqueous solutions using ZnBTC as a photocatalyst was found to be 52 %, while that of the nanocomposites were enhanced up to 79 %.

Modern Carbon-Based Materials for Adsorptive Removal of Organic and Inorganic Pollutants from Water and Wastewater

Currently, a serious threat for living organisms and human life in particular, is water contamination with persistent organic and inorganic pollutants. To date, several techniques have been adopted to remove/treat organics and toxic contaminants. Adsorption is one of the most effective and economical methods for this purpose. Generally, porous materials are considered as appropriate adsorbents for water purification. Conventional adsorbents such as activated carbons have a limited possibility of surface modification (texture and functionality), and their adsorption capacity is difficult to control. Therefore, despite the significant progress achieved in the development of the systems for water remediation, there is still a need for novel adsorptive materials with tunable functional characteristics. This review addresses the new trends in the development of new adsorbent materials. Herein, modern carbon-based materials, such as graphene, oxidized carbon, carbon nanotubes, biomass-derived carbonaceous matrices-biochars as well as their composites with metal-organic frameworks (MOFs) and MOF-derived highly-ordered carbons are considered as advanced adsorbents for removal of hazardous organics from drinking water, process water, and leachate. The review is focused on the preparation and modification of these next-generation carbon-based adsorbents and analysis of their adsorption performance including possible adsorption mechanisms. Simultaneously, some weak points of modern carbon-based adsorbents are analyzed as well as the routes to conquer them. For instance, for removal of large quantities of pollutants, the combination of adsorption and other methods, like sedimentation may be recommended. A number of efficient strategies for further enhancing the adsorption performance of the carbon-based adsorbents, in particular, integrating approaches and further rational functionalization, including composing these adsorbents (of two or even three types) can be recommended. The cost reduction and efficient regeneration must also be in the focus of future research endeavors. The targeted optimization of the discussed carbon-based adsorbents associated with detailed studies of the adsorption process, especially, for multicomponent adsorbate solution, will pave a bright avenue for efficient water remediation.

Efficient Removal of Chromium(VI) Anionic Species and Dye Anions from Water Using MOF-808 Materials Synthesized with the Assistance of Formic Acid

This study presents a simple approach to prepare MOF-808, an ultra-stable Zr-MOF constructed from 6-connected zirconium clusters and 1,3,5-benzene tricarboxylic acid, with tailored particle sizes. Varying the amount of formic acid as a modulator in the range of 200-500 equivalents results in MOF-808 materials with a crystal size from 40 nm to approximately 1000 nm. Apart from the high specific surface area, a combination of a fraction of mesopore and plenty of acidic centers on the Zr-clusters induces a better interaction with the ionic pollutants such as K2Cr2O7 and anionic dyes. MOF-808 shows uptakes of up to 141.2, 642.0, and 731.0 mg/g for K2Cr2O7, sunset yellow, and quinoline yellow, respectively, in aqueous solutions at ambient conditions. The uptakes for the ionic dyes are significantly higher than those of other MOFs reported from the literature. Moreover, the adsorption capacity of MOF-808 remains stable after four cycles. Our results demonstrate that MOF-808 is a promising ideal platform for removing oxometallates and anionic dyes from water.

Experimental and predictive study on the performance and energy consumption characteristics for the regeneration of activated alumina assisted by ultrasound

Activated alumina used in dehumidification should be regenerated at more than 110 °C temperature, resulting in excessive energy consumption. Comparative experiments were conducted to study the feasibility and performance of ultrasonic assisted regeneration so as to lower the regeneration temperature and raise the efficiency. The mean regeneration speed, regeneration degree, and enhanced rate were used to evaluate the contribution of ultrasound in regeneration. The effective moisture diffusivity and desorption apparent activation energy were calculated by theoretical models, revealed the enhanced mechanism caused by ultrasound. Also, we proposed some specific indexes such as unit energy consumption and energy-saving ratio to assess the energy-saving characteristics of this process. The unit energy consumption was predicted by artificial neural network (ANN), and the recovered moisture adsorption of activated alumina was measured by the dynamic adsorption test. Our analysis illustrates that the introduction of power ultrasound in the process of regeneration can reduce the unit energy consumption and improve the recovered moisture adsorption, the unit energy consumption was decreased by 68.69% and the recovered moisture adsorption was improved by 16.7% under 180 W power ultrasound compared with non-ultrasonic assisted regeneration at 70 °C when initial moisture adsorption was 30%. Meanwhile, an optimal regeneration condition around the turning point could be obtained according to the predictive results of ANN, which can minimize the unit energy consumption. Moreover, it was found that a larger specific surface area of activated alumina induced by ultrasound contributed to a better recovered moisture adsorption.

Metal-organic framework MIL-100(Fe) for dye removal in aqueous solutions: Prediction by artificial neural network and response surface methodology modeling

In this study, a metal organic framework MIL-100(Fe) was synthesized for rhodamine B (RB) removal from aqueous solutions. An experimental design was conducted using a central composite design (CCD) method to obtain the RB adsorption data (n = 30) from batch experiments. In the CCD approach, solution pH, adsorbent dose, and initial RB concentration were included as input variables, whereas RB removal rate was employed as an output variable. Response surface methodology (RSM) and artificial neural network (ANN) modeling were performed using the adsorption data. In RSM modeling, the cubic regression model was developed, which was adequate to describe the RB adsorption according to analysis of variance. Meanwhile, the ANN model with the topology of 3:8:1 (three input variables, eight neurons in one hidden layer, and one output variable) was developed. In order to further compare the performance between the RSM and ANN models, additional adsorption data (n = 8) were produced under experimental conditions, which were randomly selected in the range of the input variables employed in the CCD matrix. The analysis showed that the ANN model (R² = 0.821) had better predictability than the RSM model (R² = 0.733) for the RB removal rate. Based on the ANN model, the optimum RB removal rate (>99.9%) was predicted at pH 5.3, adsorbent dose 2.0 g L^-1, and initial RB concentration 73 mg L^-1. In addition, pH was determined to be the most important input variable affecting the RB removal rate. This study demonstrated that the ANN model could be successfully employed to model and optimize RB adsorption to the MIL-100(Fe).

Modeling of Mechanical Properties of Clay-Reinforced Polymer Nanocomposites Using Deep Neural Network

Due to the non-linear characteristics of the processing parameters, predicting the desired properties of nanocomposites using the conventional regression approach is often unsatisfactory. Thus, it is essential to use a machine learning approach to determine the optimum processing parameters. In this study, a backpropagation deep neural network (DNN) with nanoclay and compatibilizer content, and processing parameters as input, was developed to predict the mechanical properties, including tensile modulus and tensile strength, of clay-reinforced polyethylene nanocomposites. The high accuracy of the developed model proves that DNN can be used as an efficient tool for predicting mechanical properties of the nanocomposites in terms of four independent parameters.

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

This paper reports a very high capacity and recyclable Mg-Co-Al-layered double hydroxide@ g-C₃N₄ nanocomposite as the new adsorbent for remediation of radioisotope-containing medical-based solutions. In this work, a convenient solvothermal method was employed to synthesize a new nano-adsorbent, whose features were determined by energy dispersive X-ray (EDS/EDX), XRD, FESEM, TEM, TGA, BET, and FT-IR spectroscopy. The as-prepared nano-adsorbent was applied to capture the radioisotope iodine-131 mainly from the medical-based wastewater under different conditions of main influential parameters, (i.e. adsorbent dose, initial I₂ concentration, sonication time, and temperature). The process was evaluated by three models of RSM, CCD-ANFIS, and CCD-GRNN. Furthermore, comprehensive kinetic, isotherm, thermodynamic, reusability cycles and optimization (by GA and DF) studies were conducted to evaluate the behavior and adsorption mechanism of I₂ on the surface of Mg-Co-Al-LDH@ g-C₃N₄ nanocomposite. High removal efficiency (95.25%) of ¹³¹I in only 30 min (i.e. during 1/384 its half-life), along with an excellent capacity that has ever been reported (2200.70 mg/g) and recyclability (seven times without breakthrough in the efficiency), turns the nanocomposite to a very promising option in remediation of ¹³¹I-containing solutions. Besides, from the models studied, ANFIS described the process with the highest accuracy and reliability with R² > 0.999.

New MOF/COF Hybrid as a Robust Adsorbent for Simultaneous Removal of Auramine O and Rhodamine B Dyes

In this study, by hybridization of zinc-based metal-organic framework-5 (MOF-5) and melamine-terephthaldehyde-based intergrade two-dimensional π-conjugated covalent organic framework (COF), a novel MOF-5/COF (M5C) hybrid material was prepared and characterized by Fourier transform infrared, field emission scanning electron microscopy, X-ray diffraction, and thermogravimetric analysis. MOF-5 has a well-defined cubic structure, and the proposed COF has an orderly and spherical nanosize shape. The prepared MOF-5/COF was applied as an effective adsorbent for rapid and high-efficient simultaneous removal of auramine O (AO) and rhodamine B (RB) cationic dyes via electrostatic, H-bonding, Lewis acid-base interactions, and π-π stacking from aqueous solution. The effect of experimental parameters such as pH, M5C mass, contact time, and AO and RB dyes concentration was investigated for removal efficiency and optimized. The M5C adsorbent showed an adsorption capacity of 17.95 and 16.18 mg/g for AO and RB dyes, respectively, at pH 9.5. The adsorption study of AO and RB dyes by M5C comprises both isotherm and kinetic studies. The equilibrium adsorption data followed by Langmuir isotherm and the adsorption kinetic process were found to be a pseudo-second-order model. The robustness adsorption efficiency of MOF/COF hybrids can be attributed to the formation of amide bonds between COF and MOFs, which improve the stability of the adsorbent.

Colorimetric determination of F-, Br- and I- ions by Ehrlich's bio-reagent oxidation over enzyme mimic like gold nanoparticles: Peroxidase-like activity and multivariate optimization

Citrate and polyvinyl alcohol capped gold nanoparticles (PVA-GNPs) were synthesized via chemical reduction technique and fully characterized by DLS, SEM, EDS, XRD, UV-Vis and FT-IR analysis. A simple and practical colorimetric sensor based on red-ox reaction of p-dimethylaminobenzaldehyde (DABA) as ehrlich's bio-reagent and Au(III) with H₂O₂ on PVA-GNPs mimic catalyst with enzyme-like activity, has been fabricated for determination of F^-, Br^- and I^- halide anions. Prepared PVA-GNPs, can simultaneously catalyze the disintegration of H₂O₂, that used to reduce Au(III) ions into co-doped Au-NPs and oxidation of p-dimethylaminobenzaldehyde ehrlich's bio-reagent while in the presence of halide ions Au-X complex can be formed and improved sensor selectivity. Halide ions (F^-, Br^- and I^-) effectively diminishes the catalytic activity of GNPs to disintegrate oxygenated water by the interaction among Au⁺ and Au⁰ and suppressing oxidation of p-dimethylaminobenzaldehyde ehrlich's bio-reagent. In this system which contains PVA-GNPs, H₂O₂, p-dimethylaminobenzaldehyde ehrlich's bio-reagent, and Au(III), increasing the halide ions (F^-, Br^- and I^-) concentration show color changes from deep green to red. In view of this rule, in this work, a novel colorimetric technique for sensitive determination of F^-, Br^- and I^- was developed. This method has the detection limits of 2.60 × 10^-6 M, 6.64 × 10^-8 M and 9.93 × 10^-9 M and linear ranges between 1.98 × 10^-5-1.22 × 10^-3 M, 1.99 × 10^-6-2.0 × 10^-4 M and 1.07 × 10^-7- 2.86 × 10^-5 M for F^-, Br^- and I^-, respectively. Assays are highly selective over other ions. They effectively applied to detection of halide ions in real water samples.

Developing a new colorimetric bioassay for iodide determination based on gold supported iridium peroxidase catalysts

A schematic sketch of the colorimetric bioassay for iodide determination based on gold supported iridium peroxidase catalysts.

A review on carbon-based materials for heterogeneous sonocatalysis: Fundamentals, properties and applications

Contamination of water resources by refractory organic pollutants is of great environmental and health concern because these compounds are not degraded in the conventional wastewater treatment plants. In recent years, sonocatalytic treatment has been considered as a promising advanced oxidation technique for the acceptable degradation and mineralization of the recalcitrant organic compounds. For this purpose, various sonocatalysts have been utilized in order to accelerate the degradation process. The present review paper provides a summary of published studies on the sonocatalytic degradation of various organic pollutants based on the application of carbon-based catalysts, including carbon nanotubes (CNTs), graphene (GR), graphene oxide (GO), reduced graphene oxide (rGO), activated carbon (AC), biochar (BC), graphitic carbon nitride (g-C₃N₄), carbon doped materials, buckminsterfullerene (C60) and mesoporous carbon. The mechanism of sonocatalytic degradation of different organic compounds by the carbon-based sonocatalysts has been well assessed based on the literature. Moreover, the details of experimental conditions such as sonocatalyst dosage, solute concentration, ultrasound power, applied frequency, initial pH and reaction time related to each study have also been discussed in this review. Finally, concluding remarks as well as future challenges in this research field regarding new areas of study are also discussed and recommended.

Metal-organic frameworks/carbon-based materials for environmental remediation: A state-of-the-art mini-review

In recent years, many research groups started to study the combination of metal-organic frameworks (MOFs) with nanocarbon materials, which showed the excellent improved performances than MOFs alone. The addition of carbon materials such as graphene oxides (GOs) and carbon nanotubes (CNTs) into MOFs can improve the physico-chemical properties of parent MOFs with excellent chemical robustness, high mechanical and distinguished electronic thermal robustness. These advantages facilitate the wider applications of MOFs/carbon materials (MOFs-C) in more research fields. This paper is devoted to reviewing the recent studies about the preparation and applications of MOFs-C in environmental remediation. This paper discusses the efficient adsorptive removal of a wide range of pollutants by MOFs-C, including organic contaminants and heavy metals from water as well as VOCs and some other toxic gases from atmospheric environment. Additionally, the catalytic performance of these nanocomposites for photocatalysis and Fenton-like oxidation of water pollutants is discussed in details. Meanwhile, the significant roles of nanocarbons and in-depth mechanisms for improved adsorption or catalysis are summarized. Finally, future perspectives on the development and application of MOFs-C composites for pollution remediation are presented at the end of this paper.

Preparation of Magnetic Fe₃O₄/MIL-88A Nanocomposite and Its Adsorption Properties for Bromophenol Blue Dye in Aqueous Solution

Metal-organic frameworks (MOFs) are considered as good materials for the adsorption of many environmental pollutants. In this study, magnetic Fe₃O₄/MIL-88A composite was prepared by modification of MIL-88A with magnetic nanoparticles using the coprecipitation method. The structures and magnetic property of magnetic Fe₃O₄/MIL-88A composite were characterized and the adsorption behavior and mechanism for Bromophenol Blue (BPB) were evaluated. The results showed that magnetic Fe₃O₄/MIL-88A composite maintained a hexagonal rod-like structure and has good magnetic responsibility for magnetic separation (the maximum saturation magnetization was 49.8 emu/g). Moreover, the maximum adsorption amount of Fe₃O₄/MIL-88A composite for BPB was 167.2 mg/g and could maintain 94% of the initial adsorption amount after five cycles. The pseudo-second order kinetics and Langmuir isotherm models mostly fitted to the adsorption for BPB suggesting that chemisorption is the rate-limiting step for this monomolecular-layer adsorption. The adsorption capacity for another eight dyes (Bromocresol Green, Brilliant Green, Brilliant Crocein, Amaranth, Fuchsin Basic, Safranine T, Malachite Green and Methyl Red) were also conducted and the magnetic Fe₃O₄/MIL-88A composite showed good adsorption for dyes with sulfonyl groups. In conclusion, magnetic Fe₃O₄/MIL-88A composite could be a promising adsorbent and shows great potential for the removal of anionic dyes containing sulfonyl groups.

Facile synthesis, growth process, characterisation of a nanourchin-structured α-MnO2 and their application on ultrasonic-assisted adsorptive removal of cationic dyes: A half-life and half-capacity concentration approach

Textile dyes pose a serious threat in terms of water pollution due to its complex aromatic structures and poor degradability. In order to reduce the toxic effects of Crystal Violet (CV) and Methylene Blue (MB), an ultrasonic-assisted dye adsorption using urchin like α-MnO₂ nanostructures was studied. The adsorbent was synthesised by hydrothermal method at low-temperature. The crystallinity and morphology were determined to investigate the growth mechanism of α-MnO₂ nanourchins which consists of two main stages. The initial stage includes the formation of α-MnO₂ microspheres followed by the epitaxial growth of nanoneedles on to the surface of them. The α-MnO₂ was characterised by BET, XRD, FT-IR, XPS, SEM, TEM and TGA. At 5.6, the point of zero charge of α-MnO₂ nanostructures was determined. The total pore volume and average pore radius were confirmed to be 4.751 × 10^-2 cc/g and 10.99 Å respectively from the BET analysis. Batch adsorption experiments were performed to investigate the effect of pH, adsorbent dosage, sonication time, initial dye concentration, temperature, ultrasonic frequency and power. The adsorption mechanism was studied using several isotherm and kinetic models. The adsorption data of CV and MB at equilibrium was observed to adopt the Langmuir isotherm model and pseudo-second order kinetic model. The maximum adsorption capacities for CV and MB were found to be 5882.3 and 5000 mg/g respectively. The thermodynamic study predicted that the process was exothermic for CV and endothermic for MB. The effects of competitive ions, ionic strength and humic acid on the uptake of both the dyes were also investigated. And finally, the reusability of recovered α-MnO₂ after dye adsorption was studied up to five cycles for its potential industrial applications.

Effect of the main process parameters on the mechanical strength of polyphenylsulfone (PPSU) in ultrasonic micro-moulding process

Ultrasonic micro-moulding technology was used to process high performance polymer polyphenylsulfone (PPSU) due to investigate mechanical and chemical characteristics of manufacturing parts. Both the processing window and dependence between the main input parameters, in this case amplitude, plunger velocity and ultrasonic exposure time and their influence on the mechanical properties were appointed. The experiments showed that each available amplitude level (58 µm, 52.2 µm, 46.4 µm, 40.6 µm) are suitable to produce specimens characterised by high mechanical strength but only when combined with the appropriate values of the rest of the parameters. The parameter, which influenced the most on the part degradation is the ultrasonic vibration time. Samples from the combination of parameters, where the amplitude and velocity had the highest value but time of sonication is one of the lowest are less exposed for degradation. Cavitation bubbles makes polymer falling apart which decreases mechanical strength of the manufacturing parts. Degradation was observed via FTIR analysis even if it was not visually visible. Finally, the model as a tool for selecting the appropriate values for the input process parameters when using the novel ultrasonic micro-moulding technology required to produce PPSU parts characterised by their high mechanical strength was developed.

Sonochemical incorporated of cytosine in Cu-H2bpdc as an antibacterial agent against standard and clinical strains of Proteus mirabilis with rsbA gene

The cytosine embedded copper based metal-organic framework (Bio-MOF) was synthesized by facile one-step sonochemical method by simply mixing of 4-4, biphenyldicarboxylic, cytosine and copper nitrate (Bio-Cu-H₂bpdc-Cy). The prepared bio-MOF was characterized by XRD, FTIR and FE-SEM techniques. The effect of Cu-H₂bpdc-Cy on the expression of the rsbA gene was evaluated in the clinical and standard Proteus mirabilis and study of MIC of Cu-H₂bpdc-Cy by microdilution against them that have the rsbA gene. According to different concentrations of MIC, MBC concentrations was cultured on blood agar culture medium. Regarding to the concentration of MIC, gene expression changes were obtained by real-time PCR. MIC for standard and clinical strains of Proteus mirabilis was 1.6 and 1.8 mg/ml, and also MBC was obtained to be 1.8 and 2.0 mg/ml, respectively. Finally, in the real time PCR method, expression of the rsbA gene in presences of bio-Cu-H₂bpdc-Cy was reduced, but has no effect on the gene expression of the Housekeeping DNA Gyrase-B gene. Considering the effect of Cu-H₂bpdc-Cy on the rsbA gene in Proteus mirabilis bacteria, it is possible to use of Cu-H₂bpdc-Cy agent as a therapeutic supplement against this bacterium.

Sonochemical-solvothermal synthesis of guanine embedded copper based metal-organic framework (MOF) and its effect on oprD gene expression in clinical and standard strains of Pseudomonas aeruginosa

The guanine incropped Cu based metal-organic framework (Guanine-Cu-MOF) was synthesized by facile one-step sonochemical method by simply mixing of 4-4, biphenyldicarboxylic, guanine and copper nitrate (Bio-Cu-H₂bpdc-Gu). The prepared guanine-MOF was characterized by using X-Ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Field emission scanning electron microscopy (FE-SEM) techniques. The morphology of prepared material was sponge-shaped which it was well documented, together with the presence of existing functional groups. The effect of prepared material on oprD Gene Expression was investigated in Clinical and Standard Strains of Pseudomonas aeruginosa (PAO-1) and minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of prepared samples against P. aeruginosa strains were determined through the broth micro-dilution method. The expression of oprD gene in strains affected by Cu-H₂bpdc-Gu was quantitatively investigated through real-time PCR. MIC of Bio-Cu-H₂bpdc-Gu was 400 μg/mL for the standard and clinical strains of P. aeruginosa, while, MBC of this compound was 700 μg/mL for standard strain and 800 μg/mL for clinical strains. The highest and the lowest rate of oprD gene expression were found to be 3.6 and 1.1 fold in the strains, respectively.

Ultrasound-assisted synthesis of Zinc(II)-based metal organic framework nanoparticles in the presence of modulator for adsorption enhancement of 2,4-dichlorophenol and amoxicillin

In this study, under a sonochemical method, a 3D, porous Zn(II)-based metal-organic framework [Zn(TDC)(4-BPMH)]_n·n(H₂O) is produced, which is called compound 1. To this end, the dicarboxylate linker of TDC, (2,5-thiophene dicarboxylic acid) and the pillar spacer of 4-BPMH, (N,N-bis-pyridin-4-ylmethylene-hydrazine) were employed. Moreover, variations in the morphology and growth of the micro/nanoparticles of compound 1 were investigated in terms of the effect of temperature, ultrasound irradiation power, sonication time, initial reagent concentrations, and pyridine concentration as a modulator. DFT model was used to examine the sonication effect on the distribution of the pore sizes. Moreover, the preparation method effect on the porosity and removal of two sample pollutants (i.e., 2,4-dichlorophenol (24-DCP) and amoxicillin (AMX)) from wastewater was studied.

A novel synthesis of a new thorium (IV) metal organic framework nanostructure with well controllable procedure through ultrasound assisted reverse micelle method

Reverse micelle (RM) and ultrasound assisted reverse micelle (UARM) were applied to the synthesis of novel thorium nanostructures as metal organic frameworks (MOFs). Characterization with different techniques showed that the Th-MOF sample synthesized by UARM method had higher thermal stability (354°C), smaller mean particle size (27nm), and larger surface area (2.02×10³m²/g). Besides, in this novel approach, the nucleation of crystals was found to carry out in a shorter time. The synthesis parameters of UARM method were designed by 2^k-1 factorial and the process control was systematically studied using analysis of variance (ANOVA) and response surface methodology (RSM). ANOVA showed that various factors, including surfactant content, ultrasound duration, temperature, ultrasound power, and interaction between these factors, considerably affected different properties of the Th-MOF samples. According to the 2^k-1 factorial design, the determination coefficient (R²) of the model is 0.999, with no significant lack of fit. The F_value of 5432, implied that the model was highly significant and adequate to represent the relationship between the responses and the independent variables, also the large R-adjusted value indicates a good relationship between the experimental data and the fitted model. RSM predicted that it would be possible to produce Th-MOF samples with the thermal stability of 407°C, mean particle size of 13nm, and surface area of 2.20×10³m²/g. The mechanism controlling the Th-MOF properties was considerably different from the conventional mechanisms. Moreover, the MOF sample synthesized using UARM exhibited higher capacity for nitrogen adsorption as a result of larger pore sizes. It is believed that the UARM method and systematic studies developed in the present work can be considered as a new strategy for their application in other nanoscale MOF samples.

Application of machine/statistical learning, artificial intelligence and statistical experimental design for the modeling and optimization of methylene blue and Cd(ii) removal from a binary aqueous solution by natural walnut carbon

Analytical chemists apply statistical methods for both the validation and prediction of proposed models. Methods are required that are adequate for finding the typical features of a dataset, such as nonlinearities and interactions. Boosted regression trees (BRTs), as an ensemble technique, are fundamentally different to other conventional techniques, with the aim to fit a single parsimonious model. In this work, BRT, artificial neural network (ANN) and response surface methodology (RSM) models have been used for the optimization and/or modeling of the stirring time (min), pH, adsorbent mass (mg) and concentrations of MB and Cd²⁺ ions (mg L^-1) in order to develop respective predictive equations for simulation of the efficiency of MB and Cd²⁺ adsorption based on the experimental data set. Activated carbon, as an adsorbent, was synthesized from walnut wood waste which is abundant, non-toxic, cheap and locally available. This adsorbent was characterized using different techniques such as FT-IR, BET, SEM, point of zero charge (pH_pzc) and also the determination of oxygen containing functional groups. The influence of various parameters (i.e. pH, stirring time, adsorbent mass and concentrations of MB and Cd²⁺ ions) on the percentage removal was calculated by investigation of sensitive function, variable importance rankings (BRT) and analysis of variance (RSM). Furthermore, a central composite design (CCD) combined with a desirability function approach (DFA) as a global optimization technique was used for the simultaneous optimization of the effective parameters. The applicability of the BRT, ANN and RSM models for the description of experimental data was examined using four statistical criteria (absolute average deviation (AAD), mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R²)). All three models demonstrated good predictions in this study. The BRT model was more precise compared to the other models and this showed that BRT could be a powerful tool for the modeling and optimizing of removal of MB and Cd(ii). Sensitivity analysis (calculated from the weight of neurons in ANN) confirmed that the adsorbent mass and pH were the essential factors affecting the removal of MB and Cd(ii), with relative importances of 28.82% and 38.34%, respectively. A good agreement (R² > 0.960) between the predicted and experimental values was obtained. Maximum removal (R% > 99) was achieved at an initial dye concentration of 15 mg L^-1, a Cd²⁺ concentration of 20 mg L^-1, a pH of 5.2, an adsorbent mass of 0.55 g and a time of 35 min.

Preparation and characterization of monoliths HKUST-1 MOF via straightforward conversion of Cu(OH)2-based monoliths and its application for wastewater treatment: artificial neural network and central composite design modeling

Highly crystalline water stable monolithic HKUST-1 MOF by a straightforward conversion of Cu(OH)₂-based monoliths was prepared and characterized via FE-SEM, XRD and EDS analysis.

Sonochemistry: a good, fast and clean method to promote the removal of Cu(ii) and Cr(vi) by MWCNT/CoFe2O4@PEI nanocomposites: optimization study

In this study, branched polyethylenimine (PEI) loaded on magnetic multiwalled carbon nanotubes (MWCNT/CoFe₂O₄) was synthesized and characterized by transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis and Fourier transform infrared spectroscopy (FTIR).

Ultrasound assisted extraction of phenolic acids from broccoli vegetable and using sonochemistry for preparation of MOF-5 nanocubes: Comparative study based on micro-dilution broth and plate count method for synergism antibacterial effect

The aim of this work was comparison study of dilution and plating method for evaluation of the synergism effect of metal-organic framework nanocubes (MOF-5-NCs) and broccoli extract (Brassica oleracea) on antibacterial activity of standard and clinical Pseudomonas aeruginosa strains. For this purpose, sonochemical synthesis of MOF-5-NCs was performed and it was characterized using XRD, FT-IR, FESEM and EDS techniques. Maceration extraction (ME) and ultrasound assisted extraction (UAE) methods in three different solvents were prepared and applicability of their extracts were compared in some cases such as radical scavenging and antioxidant activity. The HPLC/UV analysis was applied for separation, identification and evaluation of phenolic acids in prepared broccoli extracts. Then, antimicrobial activity of MOF-5NCs and broccoli extract against gram-negative bacteria, Pseudomonas aeruginosa was evaluated by detection of minimal inhibition concentration (MIC), minimal bactericidal concentration (MBC) and zone of inhibition (ZOI). The results of in vitro assays showed that dilution method due to flase estimation of 4% viability percentage which is not logic by consideration of MBC well could not be able to estimate MBC. Therefore, plate count method was performed for precise calculation of MBC. MIC of broccoli extract and MOF-5-NCs on Pseudomonas aeruginosa strains were 7.81mgmL^-1 and 3.13mgmL^-1, respectively.

Structure and adsorptive desulfurization performance of the composite material MOF-5@AC

The performance of adsorption desulfurization and stability of MOF-5@AC were improved, when MOF-5 was covered on the surface of AC.