Activated carbon/metal-organic framework nanocomposite: Preparation and photocatalytic dye degradation mathematical modeling from wastewater by least squares support vector machine

MOFs for next-generation cancer therapeutics through a biophysical approach-a review

Metal-organic frameworks (MOFs) have emerged as promising nanocarriers for cancer treatment due to their unique properties. Featuring high porosity, extensive surface area, chemical stability, and good biocompatibility, MOFs are ideal for efficient drug delivery, targeted therapy, and controlled release. They can be designed to target specific cellular organelles to disrupt metabolic processes in cancer cells. Additionally, functionalization with enzymes mimics their catalytic activity, enhancing photodynamic therapy and overcoming apoptosis resistance in cancer cells. The controllable and regular structure of MOFs, along with their tumor microenvironment responsiveness, make them promising nanocarriers for anticancer drugs. These carriers can effectively deliver a wide range of drugs with improved bioavailability, controlled release rate, and targeted delivery efficiency compared to alternatives. In this article, we review both experimental and computational studies focusing on the interaction between MOFs and drug, explicating the release mechanisms and stability in physiological conditions. Notably, we explore the relationship between MOF structure and its ability to damage cancer cells, elucidating why MOFs are excellent candidates for bio-applicability. By understanding the problem and exploring potential solutions, this review provides insights into the future directions for harnessing the full potential of MOFs, ultimately leading to improved therapeutic outcomes in cancer treatment.

Effective removal of malachite green oxalate from aqueous solution using Newbouldia laevis husk/MWCNTs nanocomposite: equilibrium, kinetics, and thermodynamics

The discharge of colored effluent into water bodies is a big concern; hence, the current work was designed to fabricate a superior nanocomposite (NBM) using the Newbouldia laevis husk (NB) and functionalized multiwalled carbon nanotubes (f-MWCNTs) for the adsorption of malachite green oxalate (MGO). Brunauer-Emmett-Teller (BET) surface analysis was used to assess the specific surface area of NB (0.7699 m2 g-1) and NBM (94.006 m2 g-1). Fourier transform infrared spectroscopy (FTIR) was employed to determine the chemical moieties on the surface of the adsorbent. Field emission scanning electron microscopy (FESEM) and thermogravimetric analysis (TGA) were used to analyze the surface morphology and the thermal behavior of the adsorbents. Essential factors of the adsorption process were investigated, and it was revealed that pH 6.0, adsorbent dose of 0.05 g, contact time 80 min, concentration of 100 mg dm-3 and maximum adsorption capacity of 35.78 mg g-1 (NB) and 69.97 mg g-1 (NBM) were the optimal parameters. The NB and NBM adsorption processes followed a pseudo-first-order kinetic model. The exothermic and endothermic adsorptive processes were noticed to be the best descriptions of MGO elimination by NB and NBM, respectively. The uptake of MGO by NB and NBM was best described by models of Freundlich and Langmuir isotherms. Besides, NBM demonstrated uptake efficiency that is >80% after the fourth adsorption/desorption cycle. As a result, NBM has a wide range of possible uses in environmental remediation.

Photocatalytic degradation of drugs and dyes using a maching learning approach

The waste management industry uses an increasing number of mathematical prediction models to accurately forecast the behavior of organic pollutants during catalytic degradation. With the increasing quantity of waste generated, these models are critical for reinforcing the efficiency of wastewater treatment strategies. The application of machine-learning techniques in recent years has notably improved predictive models for waste management, which are essential for mitigating the impact of toxic commercial waste on global water supply. Organic contaminants, dyes, pesticides, surfactants, petroleum by-products, and prescription drugs pose risks to human health. Because traditional techniques face challenges in ensuring water quality, modern strategies are vital. Machine learning has emerged as a valuable tool for predicting the photocatalytic degradation of medicinal drugs and dyes, providing a promising avenue for addressing urgent demands in removing organic pollutants from wastewater. This research investigates the synergistic application of photocatalysis and machine learning for pollutant degradation, showcasing a sustainable solution with promising effects on environmental remediation and computational efficiency. This study contributes to green chemistry by providing a clever framework for addressing present-day water pollution challenges and achieving era-driven answers.

Highly efficient heterogeneous electro-Fenton reaction for tetracycline degradation by Fe-Ni LDH@ZIF-67 modified carbon cloth cathode: Mechanism and toxicity assessment

In this work, a novel and efficient Fe-Ni LDH@ZIF-67 catalyst modified carbon cloth (CC) cathode was developed for tetracycline (TC) degradation in heterogeneous electro-Fenton (Hetero-EF) process. Compared to Fe-Ni LDH/CC (75.7%), TC degradation rate of Fe-Ni LDH@ZIF-67/CC cathode increased to 95.6% within 60 min. The synergistic effect of hetero-EF and anodic oxidation process accelerated electron transfer, the maximum H2O2 production of Fe-Ni LDH@ZIF-67/CC electrode reached 264 mg/L, improving utilization efficiency of H2O2. The cathode possessing a satisfied TC degradation performance over a wide pH (3-9). Free radical capture experiment revealed the collaboration of ·O2-, ·OH, and 1O2 play a significant role in TC degradation. The 5 cycles experiment and metal ion leaching experiment showed that the proposed Fe-Ni LDH@ZIF-67/CC has good recyclability and stability. In addition, the proposed Fe-Ni LDH@ZIF-67/CC cathode achieved satisfying performance in real water (tap water: 97.3%, lake water: 97.7%), demonstrating the possibility for practical application. TC degradation pathways were proposed by theory analysis and experimental results. The toxicity of TC intermediates was reduced by Hetero-EF degradation according to Toxicity Estimation Software Tool and Escherichia coli growth inhibition experiments. This work provides a novel modified cathode to improve removal efficiency of antibiotics in wastewater.

Machine learning, a powerful tool for the prediction of BiVO4 nanoparticles efficiency in photocatalytic degradation of organic dyes

Wastewater pollution caused by organic dyes is a growing concern due to its negative impact on human health and aquatic life. To tackle this issue, the use of advanced wastewater treatment with nano photocatalysts has emerged as a promising solution. However, experimental procedures for identifying the optimal conditions for dye degradation could be time-consuming and expensive. To overcome this, machine learning methods have been employed to predict the degradation of organic dyes in a more efficient manner by recognizing patterns in the process and addressing its feasibility. The objective of this study is to develop a machine learning model to predict the degradation of organic dyes and identify the main variables affecting the photocatalytic degradation capacity and removal of organic dyes from wastewater. Nine machine learning algorithms were tested including multiple linear regression, polynomial regression, decision trees, random forest, adaptive boosting, extreme gradient boosting, k-nearest neighbors, support vector machine, and artificial neural network. The study found that the XGBoosting algorithm outperformed the other models, making it ideal for predicting the photocatalytic degradation capacity of BiVO4. The results suggest that XGBoost is a suitable model for predicting the photocatalytic degradation of wastewater using BiVO4 with different dopants.

Integrative analysis of multi machine learning models for tetracycline photocatalytic degradation with MOFs in wastewater treatment

This study focuses on the utilization of connectionist models, specifically Independent Component Analysis (ICA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Genetic Algorithm-Particle Swarm Optimization (GAPSO) integrated with a least-squares support vector machine (LSSVM) to forecast the degradation of tetracycline (TC) through photocatalysis using Metal-Organic Frameworks (MOFs). The primary objective of this study was to evaluate the viability and precision of these connectionist models in estimating the efficiency of TC degradation, particularly within the context of wastewater treatment. The input parameters for these models cover essential MOF characteristics, such as pore size and surface area, along with critical operational factors, such as pH, TC concentration, catalyst dosage, and illumination duration, all of which are linked to the photocatalytic performance of MOFs. Sensitivity analysis revealed that the illumination duration is the primary influencer of TC photodegradation with MOF photocatalysts, while the MOFs' surface area is the second crucial parameter shaping the efficiency and dynamics of the TC-MOF photocatalytic system. The developed LSSVM models display impressive predictive capabilities, effectively forecasting the experimental degradation of TC with high accuracy. Among these models, the GAPSO-LSSVM model excels as the top performer, achieving notable evaluation metrics, including STD, RMSE, MSE, MRE, and R2 at values of 3.09, 3.42, 11.71, 5.95, and 0.986, respectively. In comparison, the PSO-LSSVM, ICA-LSSVM, and GA-LSSVM models yield mean relative errors of 6.18%, 7.57%, and 11.37%, respectively. These outcomes highlight the exceptional predictive capabilities of the GAPSO-LSSVM model, solidifying its position as the most accurate and dependable model for predicting TC photodegradation in this study. This study contributes to advancing photocatalytic research and effectively reinforces the importance of leveraging machine learning methodologies for tackling environmental challenges.

The Synthesis of carbon dots//zincoxide (CDs/ZnO-H400) by using hydrothermal methods for degradation of ofloxacin antibiotics and reactive red azo dye (RR141)

The development of photocatalytic powders to remove contaminants from air solutions is an important field of research in the field of environmental conservation. CD/ZnO-H400, a heterogeneous photocatalytic production, is utilized to degrade the reactive red dye and the antibiotic ofloxacin found in wastewater. This study explains the synthesis of carbon dots (CDs) derived from coconut air and zinc oxide (ZnO) using a hydrothermal method at a temperature of 180 °C with a duration of 4 h and subsequently calcinated at a 400 °C temperature for 4 h. This shows a significant improvement in photocatalytic performance due to improved delivery efficiency at the interface. The cost-efficient use of solar energy allows the comprehensive elimination of harmful pollutants through detoxification. The removal of the contaminant takes place through the first-order reaction, with RR141 showing the highest constant rate at 0.03 min-1, while ofloxacin has a constant speed at 0.01 min-1. The photocatalytic stability is measured after five cycles. The study also tested the impact of sunlight on degradation, showing a degrading rate of 98% for RR141 and 96% for ofloxacin. This study displays a new catalyst powder synthesized from carbon dots derived from the air, coconut and ZnO, showing remarkable photoactivity to completely remove harmful dyes and antibiotics from the surrounding environment.

Recent advances in cellulose-based sustainable materials for wastewater treatment: An overview

Water pollution presents a significant challenge, impacting ecosystems and human health. The necessity for solutions to address water pollution arises from the critical need to preserve and protect the quality of water resources. Effective solutions are crucial to safeguarding ecosystems, human health, and ensuring sustainable access to clean water for current and future generations. Generally, cellulose and its derivatives are considered potential substrates for wastewater treatment. The various cellulose processing methods including acid, alkali, organic & inorganic components treatment, chemical treatment and spinning methods are highlighted. Additionally, we reviewed effective use of the cellulose derivatives (CD), including cellulose nanocrystals (CNCs), cellulose nano-fibrils (CNFs), CNPs, and bacterial nano-cellulose (BNC) on waste water (WW) treatment. The various cellulose processing methods, including spinning, mechanical, chemical, and biological approaches are also highlighted. Additionally, cellulose-based materials, including adsorbents, membranes and hydrogels are critically discussed. The review also highlighted the mechanism of adsorption, kinetics, thermodynamics, and sorption isotherm studies of adsorbents. The review concluded that the cellulose-derived materials are effective substrates for removing heavy metals, dyes, pathogenic microorganisms, and other pollutants from WW. Similarly, cellulose based materials are used for flocculants and water filtration membranes. Cellulose composites are widely used in the separation of oil and water emulsions as well as in removing dyes from wastewater. Cellulose's natural hydrophilicity makes it easier for it to interact with water molecules, making it appropriate for use in water treatment processes. Furthermore, the materials derived from cellulose have wider application in WW treatment due to their inexhaustible sources, low energy consumption, cost-effectiveness, sustainability, and renewable nature.

A review on the lignocellulosic derived biochar-based catalyst in wastewater remediation: Advanced treatment technologies and machine learning tools

Wastewater disposal in the ecosystem affects aquatic and human life, which necessitates the removal of the contaminants. Eliminating wastewater contaminants using biochar produced through the thermal decomposition of lignocellulosic biomass (LCB) is sustainable. Due to its high specific surface area, porous structure, oxygen functional groups, and low cost, biochar has emerged as an alternate contender in catalysis. Various innovative advanced technologies were combined with biochar for effective wastewater treatment. This review examines the use of LCB for the synthesis of biochar along with its activation methods. It also elaborates on using advanced biochar-based technologies in wastewater treatment and the mechanism for forming oxidizing species. The research also highlights the use of machine learning in pollutant removal and identifies the obstacles of biochar-based catalysts in both real-time and cutting-edge technologies. Probable and restrictions for further exploration are discussed.

Influence of humic acid on U(VI) elimination by ZIF-8: Synergistic chemical effect

ZIF-8, a sort of zeolitic imidazolate frameworks (ZIFs), had showed superior adsorptive property of typical radionuclide U(VI), but it reminded uncertain how the performance of ZIF-8 would be affected by adding humic acid (HA). HA could significantly change the surface charge of ZIFs and the transport of U(VI) in natural settings, which affected the eradication of U(VI) in aquatic ecology. Thus the impact of HA for the U(VI) removal by ZIF-8 as well as its mechanism had been analyzed by batch experiments and spectral analyses. It was demonstrated that the addition of HA increased the maximum removal capacity towards U(VI) from 781.2 mg g-1 to 1398.5 mg g-1. Moreover, removal property in acidic solution was improved, and the influence of background ions on ZIF-8 was reduced. The detailed mechanism was further explored by microscopic spectral analysis. The zeta potential showed that HA enhanced the electronegativity of ZIF-8 thus enhancing the electrostatic interaction with positive ions. Moreover, FT-IR and XPS further indicated that HA enhanced the removal capacity by affecting the surface complexation phenomena and strong chemical interactions between U(VI) and ZIF-8. Also, investigations indicated that the incorporation of HA improved the removal efficiency for U(VI), which had far-reaching significance for the application of ZIF-8 in practical environment.

Effects and Mechanisms of Cu Species in Fe-MOFs on Fenton-Like Catalytic Activity and Stability

Fe-based MOFs (Fe-MOFs) are deemed promising Fenton-like catalysts due to their well-developed pores and accessible active sites. However, their inferior catalytic activity, iron leaching, and low H₂O₂ utilization always hinder their application as Fe-based MOF catalysts. In this work, we manipulated the structure of Fe-oxo nodes in MIL-88B(Fe) via a Cu^I species substitution method, affording a mixed-valence (Cu-incorporated Fe-MOFs) with highly improved Fenton-like performance. It is found that the Cu^I serves as a shuttle to promote transfer between Fe^II/Fe^III, inducing the formation of a larger amount of stable Fe^II sites, which was proven by experimental and DFT calculation results. A linear relationship was observed for the Fenton-like performance and the amount of Cu^I species for the catalysts. The corresponding value of the ^•OH formation is 2.17 eV for Cu-incorporated MIL-88B(Fe), which is significantly lower than that of MIL-88B(Fe) (2.69 eV). Meanwhile, the enriched Cu^I species suppress Fe species leaching during the catalytic reaction. The Fe-ion leakage of 0.4Cu@MIL-88B is very tiny (0.01-0.03 mg/L), significantly less than that of MIL-88B (2.00-3.02 mg/L). At the same time, H₂O₂ utilization for 0.4Cu@ MIL-88B(Fe) is 88%, which is almost 4.4 times that of pure MIL-88B(Fe). This work provides insights into the rational design of Fe-MOFs as promising Fenton-like catalysts for wastewater treatment.

Low-temperature aerobic carbonization and activation of cellulosic materials for Pb2+ removal in water source

Targeting the removal of Pb²⁺ in wastewater, cellulosic materials were carbonized in an aerobic environment and activated via ion exchange. The maximum adsorption capacity reached 243.5 mg/g on an MCC-derived adsorbent activated with sodium acetate. The modified porous properties improved the adsorption capacity. The capacity could be completely recovered five times through elution with EDTA. Because of the negative effects of Ni, Mg, and Ca elements, the adsorption capacities of activated carbonized natural materials were lower than that of pure cellulose. N₂ adsorption measurement showed that the adsorbent had a large specific surface area as well as abundant micropores and 4-nm-sized mesopores. FTIR and surface potential results proved that carboxyl group was generated in the aerobic carbonization, and was deprotonated during ion exchange. This adsorbent consisted of C-C bonds as the building blocks and hydrophilic groups on the surface. XPS results demonstrated that the Pb 4f binding energies were reduced by 0.7-0.8 eV due to the interaction between Pb²⁺ and the activated adsorbent, indicating that the carboxylate groups bonded with Pb²⁺ through coordination interactions. Pseudo-second-order and Elovich kinetic models were well fitted with the adsorption processes on the pristine and activated carbonized adsorbents, indicative of chemisorption on heterogeneous surfaces. The Freundlich expression agreed well with the data measured, and the pristine and activated adsorbents had weak and strong affinities for Pb²⁺, respectively. The Pb²⁺ adsorption process was exothermic and spontaneous, and heat release determined the spontaneity. The adsorption capacity is attributed to the carboxylate groups and pores generated in the aerobic oxidation and ion exchange procedures.

Ag-Modified ZnO for Degradation of Oxytetracycline Antibiotic and Reactive Red Azo Dye

It is known that low electron-hole separation efficiency is the major disadvantage influencing low photoactivity of the UV-active ZnO photocatalyst. To solve this drawback, the excellent fabrication technique has been used to disperse silver metal on ZnO surface. In this study, an addition of silver content up to 15 wt% was carried out. The 5Ag-ZnO sample, comprising 5 wt% of silver metal, displayed a hexagonal wurtzite structure, and a band gap of 3.00 eV, with high sunlight-active photocatalytic performance of 99-100% and low photo-corrosion problem. The complete degradation of oxytetracycline (OTC) antibiotic and reactive red dye 141 (RR141) dye under natural sunlight was achieved. The highest rate constant of 0.061 min-1 was detected. The enhancement of the performance is mainly due to lowering of the electron-hole recombination rate. Dispersion of silver on ZnO causes the generation of the Schottky barrier at the interface between Ag and ZnO, so that improvement of quantum efficiency and enhancement of the resultant photoactivity could be expected. Furthermore, good distribution of metallic silver also causes a red shift in absorption of light toward the visible spectrum. This is strongly attributed to the surface plasmon resonance effect, which occurred after successful decoration of the noble metal on ZnO. The photocatalyst, with great structural stability, still maintains high photocatalytic efficiency even after five times of use, implying its excellent cycling ability. The present finding offers a new road to generate a silver decorated ZnO photocatalyst for the complete removal of dye and antibiotics contaminated in the environment.

Visible-light-assisted persulfate activation by SnS2/MIL-88B(Fe) Z-scheme heterojunction for enhanced degradation of ibuprofen

Herein, a highly efficient Z-scheme SnS₂/MIL-88B (Fe) (SnSFe) heterojunction was successfully synthesized to use both as photocatalysts and persulfate (PS) activator for ibuprofen (IBP) degradation. Flower-liked SnS₂ was uniformly loaded on MIL-88B (Fe), and SnSFe retained the original polyhedral morphology of MIL-88B (Fe). The highest removal of IBP was achieved in the presence of SnSFe with 0.5% SnS₂(SnSFe0.5). Characteristic results and density functional theory calculations demonstrated that the enhanced degradation of IBP was due to the difference in Fermi energy levels of SnS₂ and MIL-88B (Fe) leading to electrons transferred from SnS₂ to MIL-88B (Fe), and SnO bond was formed in SnSFe. , OH and O₂^- were the main active species in SnSFe0.5/PS/visible light system. Z-scheme heterojunction of SnSFe was constructed to propose the degradation mechanism. This research revealed that the synergism of photocatalysis and PS activation using SnS₂/Fe-based MOFs composites possessed great potentials in wastewater remediation.

Adsorption Behaviors of Cationic Methylene Blue and Anionic Reactive Blue 19 Dyes onto Nano-Carbon Adsorbent Carbonized from Small Precursors

In this work, an innovative nano-carbon material (N-CM) adsorbent was reported for exploring its adsorption behaviors toward cationic methylene blue (MB) and anionic reactive blue 19 (RB19) pollutants. The proposed N-CM was synthesized by a one-step solvothermal treatment of citric acid and zinc gluconate small precursors. N-CM consists of nanosheets that have an advantageous specific surface area, large sp2/sp3 hybridized domains, and abundant nitrogen/oxygen-containing surface functional groups. The synergistic effects of these features are conducive to the MB and RB19 adsorption. Different from anionic RB19 adsorption (79.54 mg/g) by the cooperative π-π stacking and hydrogen bonding, cationic MB adsorbed onto N-CM mainly by the electrostatic attraction at the natural pH solution (> pHpzc), with an adsorption capacity up to 118.98 mg/g. Interestingly, both MB and RB19 adsorption conformed to the pseudo-second order kinetic (R2 ≥ 0.995) and Langmuir isothermal (R2 ≥ 0.990) models, accompanied by similar maximum monolayer adsorption capacities of 120.77 and 116.01 mg/g, respectively. Their adsorption processes exhibited spontaneously endothermic characteristics. Moreover, N-CM showed superior selective capability toward MB in different mixed dye systems, with high removal efficiencies of 73−89%. These results demonstrate that the high-performance carbon adsorbent prepared from small precursors via low-temperature carbonization shows great potentials in wastewater treatment.

Thermo-Responsive ZnPc-g-TiO2-g-PNIPAM Photocatalysts Sensitized with Phthalocyanines for Water Purification under Visible Light

A novel thermo-responsive 2,9(10),16(17),23(24)-tetrakis[(3-carboxyacrylamide) phthalocyaninato] zinc (ZnPc)-g-TiO₂-g-poly(N-isopropylacrylamide) (PNIPAM) photocatalyst modified with phthalocyanines was prepared. The photocatalyst exhibited thermo-responsive properties due to the introduction of PNIPAM, which performed recovery for reuse above the lower critical solution temperature (LCST, about 26 °C). ZnPc-g-TiO₂-g-PNIPAM effectively expanded the light response range to the visible light region and inhibited the recombination of electron–hole pairs, which enhanced the performance of the photocatalyst. As expected, ZnPc-g-TiO₂-g-PNIPAM (0.3 g/L) exhibited excellent photocatalytic performance for the removal of Rhodamine B (RhB, 1.0 × 10⁻⁵ mol/L) and methylene blue (MB, 1.0 × 10⁻⁵ mol/L) under visible light, which reached 97.2% and 88.6% at 20 °C within 40 min, respectively. Furthermore, the influence of temperature upon photocatalytic performance was also investigated. When the temperature increased from 20 °C to 45 °C, the removal of RhB decreased by approximately 53.8%. The stability of the photocatalyst demonstrated that the photocatalytic activity was still above 80% for the removal of RhB after 3 cycles. Above all, this work provided an intelligent thermally responsive photocatalyst based on phthalocyanine for water purification under visible light.

An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique

Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment and livestock growth promotion. The consumption of such antibiotics has been ever-growing nowadays due to various bacterial infections and other pathologic conditions, resulting in more discharge into the aquatic environments. This brings threats to ecosystems and human bodies. Up to now, several attempts have been made to reduce TC amounts in the wastewater, among which photocatalysis, an advanced oxidation process, is known as an eco-friendly and efficient technology. In this regard, metal organic frameworks (MOFs) have been known as the promising materials as photocatalysts. Thus, studying TC photocatalytic degradation by MOFs would help scientists and engineers optimize the process in terms of effective parameters. Nevertheless, the costly and time-consuming experimental methods, having instrumental errors, encouraged the authors to use the computational method for a more comprehensive assessment. In doing so, a wide-ranging databank including 374 experimental data points was gathered from the literature. A powerful machine learning method of Gaussian process regression (GPR) model with four kernel functions was proposed to estimate the TC degradation in terms of MOFs features (surface area and pore volume) and operational parameters (illumination time, catalyst dosage, TC concentration, pH). The GPR models performed quite well, among which GPR-Matern model shows the most accurate performance with R², MRE, MSE, RMSE, and STD of 0.981, 12.29, 18.03, 4.25, and 3.33, respectively. In addition, an analysis of sensitivity was carried out to assess the effect of the inputs on the TC photodegradation by MOFs. It revealed that the illumination time and the surface area play a significant role in the decomposition activity.

The state of art on the prediction of efficiency and modeling of the processes of pollutants removal based on machine learning

During the last few years, important advances have been made in big data exploration, complex pattern recognition and prediction of complex variables. Machine learning (ML) algorithms can efficiently analyze voluminous data, identify complex patterns and extract conclusions. In chemical engineering, the application of machine learning approaches has become highly attractive due to the growing complexity of this field. Machine learning allows computers to solve problems by learning from large data sets and provides researchers with an excellent opportunity to enhance the quality of predictions for the output variables of a chemical process. Its performance has been increasingly exploited to overcome a wide range of challenges in chemistry and chemical engineering, including improving computational chemistry, planning materials synthesis and modeling pollutant removal processes. In this review, we introduce this discipline in terms of its accessible to chemistry and highlight studies that illustrate in-depth the exploitation of machine learning. The main aim of the review paper is to answer these questions by analyzing physicochemical processes that exploit machine learning in organic and inorganic pollutants removal. In general, the purpose of this review is both to provide a summary of research related to the removal of various contaminants performed by ML models and to present future research needs in ML for contaminant removal.

Metal-organic frameworks (MOFs) based nanofiber architectures for the removal of heavy metal ions

Environmental heavy metal ions (HMIs) accumulate in living organisms and cause various diseases. Metal-organic frameworks (MOFs) have proven to be promising and effective materials for removing heavy metal ions from contaminated water because of their high porosity, remarkable physical and chemical properties, and high specific surface area. MOFs are self-assembling metal ions or clusters with organic linkers. Metals are used as dowel pins to build two-dimensional or three-dimensional frameworks, and organic linkers serve as carriers. Modern research has mainly focused on designing MOFs-based materials with improved adsorption and separation properties. In this review, for the first time, an in-depth look at the use of MOFs nanofiber materials for HMIs removal applications is provided. This review will focus on the synthesis, properties, and recent advances and provide an understanding of the opportunities and challenges that will arise in the synthesis of future MOFs-nanofiber composites in this area. MOFs decorated on nanofibers possess rapid adsorption kinetics, a high adsorption capacity, excellent selectivity, and good reusability. In addition, the substantial adsorption capacities are mainly due to interactions between the target ions and functional binding groups on the MOFs-nanofiber composites and the highly ordered porous structure.

Hybrid support vector regression and crow search algorithm for modeling and multiobjective optimization of microalgae-based wastewater treatment

Microalgae-based wastewater treatment (and biomass production) is an environmentally benign and energetically efficient technique as compared to traditional practices. The present study is focused on optimization of the major treatment variables such as temperature, light-dark cycle (LD), and nitrogen (N)-to-phosphate (P) ratio (N/P) for the elimination of N and P from tertiary municipal wastewater utilizing Chlorella kessleri microalgae species. In this regard, a hybrid support vector regression (SVR) technique integrated with the crow search algorithm has been applied as a novel modeling/optimization tool. The SVR models were formulated using the experimental data, which were furnished according to the response surface methodology with Box-Behnken Design. Various statistical indicators, including mean absolute percentage error, Taylor diagram, and fractional bias, confirmed the superior performance of SVR models as compared to the response surface methodology (RSM) and generalized linear model (GLM). Finally, the best SVR model was hybridized with the crow search algorithm for single/multi-objective optimizations to acquire the global optimal treatment conditions for maximum N and P removal efficiencies. The best-operating conditions were found to be 29.3°C, 24/0 h/h of LD, and 6:1 of N/P, with N and P elimination efficiencies of 99.97 and 93.48%, respectively. The optimized values were further confirmed by new experimental data.

Artificial intelligence (AI) applications in adsorption of heavy metals using modified biochar

The process of removal of heavy metals is important due to their toxic effects on living organisms and undesirable anthropogenic effects. Conventional methods possess many irreconcilable disadvantages pertaining to cost and efficiency. As a result, the usage of biochar, which is produced as a by-product of biomass pyrolysis, has gained sizable traction in recent times for the removal of heavy metals. This review elucidates some widely recognized harmful heavy metals and their removal using biochar. It also highlights and compares the variety of feedstock available for preparation of biochar, pyrolysis variables involved and efficiency of biochar. Various adsorption kinetics and isotherms are also discussed along with the process of desorption to recycle biochar for reuse as adsorbent. Furthermore, this review elucidates the advancements in remediation of heavy metals using biochar by emphasizing the importance and advantages in the usage of machine learning (ML) and artificial intelligence (AI) for the optimization of adsorption variables and biochar feedstock properties. The usage of AI and ML is cost and time-effective and allows an interdisciplinary approach to remove heavy metals by biochar.

Preparation of novel and highly active magnetic ternary structures (metal-organic framework/cobalt ferrite/graphene oxide) for effective visible-light-driven photocatalytic and photo-Fenton-like degradation of organic contaminants

Herein, MIL-101(Fe), CoFe₂O₄, novel binary (MIL-101(Fe)/CoFe₂O₄, MIL-101(Fe)/GO and CoFe₂O₄/GO), and ternary (MIL-101(Fe)/CoFe₂O₄/(3%)GO and MIL-101(Fe)/CoFe₂O₄/(7%)GO) magnetic composites based upon the MIL-101(Fe) were synthesized. The XRD, FESEM, TEM, EDX, BET-BJH, FTIR, VSM, DRS, PL, EIS and other electrochemical analyses were applied to characterize samples. The MIL/CoFe₂O₄/(3%)GO demonstrated the best performance compared to other samples for visible light photocatalytic and photo-Fenton-like degradation of Direct Red 23 (DtR-23), Reactive Red 198 (ReR-198) dyes as well as Tetracycline Hydrochloride (TC-H) antibiotic. Degradation of dyes using the ternary composite after 70 min of visible light irradiation was greater than that of 99%. The presence of the optimum GO as a strong electron acceptor in MIL/CoFe₂O₄/(3%)GO not only led to the effective separation of charge carriers and thus reduction of their recombination but also increased the absorption of visible light. The composite possessed good durability in terms of stability and reusability. The PL, EIS and electrochemical analyses indicated that the MIL/CoFe₂O₄/(3%)GO improved the optical properties and photocatalytic performance.

Emerging novel polymeric adsorbents for removing dyes from wastewater: A comprehensive review and comparison with other adsorbents

Dye molecules are one of the most hazardous compounds for human and animal health and the excess intake of these materials can create toxic impacts. Several studies show the practicality of the adsorption process for dye uptake from wastewaters. In recent years, various adsorbents were used to be efficient in this process. Among all, polymeric adsorbents demonstrate great applicability in different environmental conditions and attract many researchers to work on them, although there is not enough reliable and precise information regarding these adsorbents. This study aims to investigate some influential parameters such as their type, physical properties, experimental conditions, their capacity, and further modeling along with a comparison with non-polymeric adsorbents. The influence of the main factors of adsorption capacity was studied and the dominant mechanism is explained extensively.

Impact of Doping and Additive Applications on Photocatalyst Textural Properties in Removing Organic Pollutants: A Review

The effect of ion doping and the incorporation of additives on photocatalysts’ textural properties have been reviewed. Generally, it can be summarised that ion doping and additives have beneficial effects on photocatalytic efficiency and not all have an increase in the surface area. The excessive amount of dopants and additives will produce larger aggregated particles and also cover the mesoporous structures, thereby increasing the pore size (Pd) and pore volume (Pv). An excessive amount of dopants also leads to visible light shielding effects, thus influence photocatalytic performance. Ion doping also shows some increment in the surface areas, but it has been identified that synergistic effects of the surface area, porosity, and dopant amount contribute to the photocatalytic performance. It is therefore important to understand the effect of doping and the application of additives on the textural properties of photocatalysts, thus, their performance. This review will provide an insight into the development of photocatalyst with better performance for wastewater treatment applications.

Boron nitride nanosheets decorated MIL-53(Fe) for efficient synergistic ibuprofen photocatalytic degradation by persulfate activation

In this study, based on one-step hydrothermal method, boron nitride nanosheets (BNNs) and MIL-53(Fe) composites (BNFe-X) were successfully prepared and the catalytic performance of BNFe-X on persulfate (PS) activation for ibuprofen (IBP) photodegradation was investigated. The introduction of BNNs changed the morphology of MIL-53(Fe) to be a unique prism-like structure and enhanced the degradation efficiency of IBP, which followed the pseudo-first-order rate kinetics. Among the prepared composites, BNFe-3 (3% BNNs) exhibited the highest IBP degradation activity and possessed strong stability after four cycles. Over 99% IBP removal was achieved at the irradiation time of 60 min. The promoted decomposition rate of IBP could be ascribed to be the activation of PS and the enhanced electrons transfer efficiency between BNNs and MIL-53(Fe). The scavenger studies and electron spin-resonance spectroscopy (ESR) demonstrated the generation of SO₂^-, OH and O₂^-, and all these radicals had the different contributions in IBP degradation. Based on the LC-MS-MS and TOC results, the possible decomposition pathways of IBP in BNFe-3/PS system were proposed. This work suggested that the BNNs/Fe-based MOFs composites and PS system had great potential in organic pollutants degradation in aqueous solution.

Synthesis of the magnetic core-shell bi-metallic and tri-metallic metal-organic framework nanocomposites for dye adsorption

Bi-metallic and tri-metallic metal-organic frameworks (MOFs) supported on the magnetic activated carbon (MAC) were synthesized for the reduction of methylene blue (MB) concentration in the aqueous solutions. The adsorbent nanocomposites were characterized by applying the general tests including XRD, FTIR, FESEM, TEM, BET, and VSM. The XRD achievements demonstrated that crystalline structure of MOFs was derived on the MAC by the presented method. The core-shell morphology with nano-scale size of the magnetic carbonaceous MOFs was detected in TEM and FESEM micro-images. The acceptable magnetic strength of the prepared adsorbents was proved by using the VSM analysis. The important operating conditions including pH and temperature were also evaluated, while the other parameters were kept constant. The pseudo-second-order kinetic model was matched with the experimental data to show the kinetic behavior of the multi-component MOFs. The isotherm studies showed that the good agreement between the experimental data with both Langmuir model and the maximum capacities was calculated to be about 66.51 and 71.43 mg/g for the bi-metallic and tri-metallic nanocomposites, respectively. Regeneration experiments indicated that the fabricated adsorbents have an excellent reusing adsorption capacity which can be a proper selection for the industrial applications. PRACTITIONER POINTS: Bi-metallic and tri-metallic MOFs supported on the magnetic activated carbon were synthesized by the facile preparation method. Adsorption of methylene blue by using MOFs were successfully done. Nanocomposites were evaluated by XRD, FTIR, BET, FESEM, TEM, and VSM techniques. Maximum of adsorption capacity was observed for tri-metallic MOF as 71.43 mg/g.

Composite of MOF and chitin as an efficient catalyst for photodegradation of organic dyes

A novel composite has been fabricated by using MOF and chitin as a natural and biocompatible compound. To this purpose, MOF was synthesized by using 2-aminoterephthalic acid and iron (III) chloride hexahydrate and then reacted with Cl-functionalized chitin. The resulting composite was characterized and utilized as a catalyst for degradation of methylene blue both in dark condition and under visible light irradiation. The results indicated superior catalytic activity under visible light irradiation. Furthermore, study of the reaction variables, including basicity, dye concentration and catalyst loading showed that the highest catalytic activity was achieved at basic condition. It was also found that both initial dye concentration and catalyst loading can affect the catalytic activity. To disclose the merits of the composite compared to its individual components, kinetic studies of the photo-degradation process in the presence of the composite, chitin and MOF have been performed. The results confirmed superior activity the composite compared to its components. The study of the mechanism of the reaction using scavengers confirmed that the created holes (h⁺) are the most effective species in the process of photocatalytic degradation of MB. Notably, the catalyst was recyclable and could be used for degradation of other dyes.

Aqueous degradation of artificial sweeteners saccharin and neotame by metal organic framework material

The artificial sweeteners (ASs) saccharin (SAC) and neotame (NEO) are widely used across the globe and are considered as emerging contaminants in surface, ground, and drinking waters. To degrade SAC and NEO, the metal organic framework material Co-based bio-MOF-11 was prepared by hydrothermal reaction and used with peroxymonosulfate (PMS) activator. The effects of the initial concentration of SAC and NEO, bio-MOF-11-Co dosage, PMS concentration, initial pH, temperature, and competitive anions were determined. The results revealed that bio-MOF-11-Co effectively catalyzed the degradation of SAC and NEO and possessed good stability and recycling efficiency. The degradation reaction was effective from pH 3.6-9.8 and followed quasi-first-order kinetics with degradation rate constants of 0.001-0.013 min^-1 for SAC and 0.03-0.52 min^-1 for NEO. Increased temperature was conducive to the degradation of both artificial sweeteners. The presence of Cl^- inhibited the degradation of SAC and NEO, while the presence of CO₃^2- promoted their degradation. Electron paramagnetic resonance (EPR) and free radical quenching demonstrated that the primary free radicals were sulfate radicals ( [Formula: see text] ) and hydroxyl radicals (HO). The change of cobalt oxidation state and electron transfer in bio-MOF-11-Co mainly induces the production of [Formula: see text] . A plausible mechanism for degradation is [Formula: see text] and HO attack on CS bonds, NS bonds, and benzene rings.

Effect of carbon nanotubes loading on the photocatalytic activity of BiSI/BiOI as a novel photocatalyst

In this paper, a simple hydrothermal method is employed to synthesize BiSI/BiOI/CNT nanocomposite with enhanced photocatalytic activity. The properties of the prepared samples were studied using nitrogen adsorption-desorption isotherm, photoluminescence, X-ray diffraction analysis (XRD), field-emission scanning electron microscopy (FE-SEM), energy dispersive spectrometry (EDS), UV-vis diffuse reflectance spectroscopy (DRS), and electrochemical impedance spectroscopy (EIS). The loading amount of CNT had a significant influence on the photoactivity of the BiSI/BiOI/CNT composite. In this study, several BiSI/BiOI/CNT nanocomposite samples with various mass ratios of CNT were made-up for further investigation to scrutinize the influence of CNT content on the photocatalytic activity of the nanocomposite. Photocatalysis measurements revealed that 2% Wt of CNT possesses the highest photocatalytic activity in the visible light irradiation with 93.1% photodegradation of malachite green (MG) as a test dye. The enhanced photocatalytic performance can be due to the large surface area, excellent conductivity performance, and high absorption ability in the visible light region. The synergistic effect of the factors mentioned above makes BiSI/BiOI/CNT nanocomposite a high-performance photocatalyst under visible light irradiation. An appropriate reaction mechanism of dye photodegradation has suggested according to the result of active species trapping experiments.

Ag-doped magnetic metal organic framework as a novel nanostructured material for highly efficient antibacterial activity

In the last decades, numerous attempts have been made to prevent microbial pollution spreading, using antibacterial agents. Zeolitic imidazolate framework-8 (ZIF-8) belongs to a subgroup of metal organic frameworks (MOFs) merits of attention due to the zinc ion clusters and its effective antibacterial activity. In this work, Ag-doped magnetic microporous γ-Fe₂O₃@SiO₂@ZIF-8-Ag (FSZ-Ag) was successfully synthesized by a facile methodology in room temperature and used as an antibacterial agent against the growth of the Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus bacteria. Several characterization methods were applied to analyze the properties of the materials, and the results confirmed the accuracy of the synthesis procedure. Silver ions have employed to enhance the efficiency of antibacterial activity. As the results illustrated, FSZ-Ag nanostructured material had superior performance to inactive E. coli and S. aureus in growth inhibition test in liquid media. The best antibacterial activity as minimum inhibitory concentration (MIC) was 100 mg/L of FSZ-Ag against both bacteria. Leaching rates of silver ions showed that 80% of Ag released in the solutions, which was responsible for inhibiting the growth of bacteria. Also, fluorescence microscopy was used to investigate bacterial viability after 20 h contacting FSZ-Ag to distinguish live and dead bacteria by staining with DAPI and PI fluorescence stains. This novel magnetic nanostructured material is an excellent promising candidate to use in biological applications as high potential bactericidal materials.

Metal-Organic Framework (MOF)/Epoxy Coatings: A Review

Epoxy coatings are developing fast in order to meet the requirements of advanced materials and systems. Progress in nanomaterial science and technology has opened a new era of engineering for tailoring the bulk and surface properties of organic coatings, e.g., adhesion to the substrate, anti-corrosion, mechanical, flame-retardant, and self-healing characteristics. Metal-organic frameworks (MOFs), a subclass of coordinative polymers with porous microstructures, have been widely synthesized in recent years and applied in gas and energy storage, separation, sensing, environmental science and technology, and medicine. Nevertheless, less attention has been paid to their performance in coatings. Well-known as micro- and nanoporous materials, with a tailorable structure consisting of metal ions and organic linkers, MOFs have a huge loading capacity, which is essential for the delivery of corrosion inhibitors. This review paper attempts to highlight the importance of epoxy/MOF composites for coating applications. A particular emphasis was explicitly placed on the anti-corrosion, flame-retardant, mechanical, and dielectric properties of epoxy/MOF coatings.

Metal–Organic Framework (MOF) through the Lens of Molecular Dynamics Simulation: Current Status and Future Perspective

As hybrid porous structures with outstanding properties, metal–organic frameworks (MOFs) have entered into a large variety of industrial applications in recent years. As a result of their specific structure, that includes metal ions and organic linkers, MOFs have remarkable and tunable properties, such as a high specific surface area, excellent storage capacity, and surface modification possibility, making them appropriate for many industries like sensors, pharmacies, water treatment, energy storage, and ion transportation. Although the volume of experimental research on the properties and performance of MOFs has multiplied over a short period of time, exploring these structures from a theoretical perspective such as via molecular dynamics simulation (MD) requires a more in-depth focus. The ability to identify and demonstrate molecular interactions between MOFs and host materials in which they are incorporates is of prime importance in developing next generations of these hybrid structures. Therefore, in the present article, we have presented a brief overview of the different MOFs’ properties and applications from the most recent MD-based studies and have provided a perspective on the future developments of MOFs from the MD viewpoint.

From microporous to mesoporous mineral frameworks: An alliance between zeolite and chitosan

Microporous and mesoporous minerals are key elements of advanced technological cycles nowadays. Nature-driven microporous materials are known for biocompatibility and renewability. Zeolite is known as an eminent microporous hydrated aluminosilicate mineral containing alkali metals. It is commercially available as adsorbent and catalyst. However, the large quantity of water uptake occupies active sites of zeolite making it less efficient. The widely-used chitosan polysaccharide has also been used in miscellaneous applications, particularly in medicine. However, inferior mechanical properties hampered its usage. Chitosan-modified zeolite composites exhibit superior properties compared to parent materials for innumerable requests. The alliance between a microporous and a biocompatible material with the accompaniment of negative and positive charges, micro/nanopores and proper mechanical properties proposes promising platforms for different uses. In this review, chitosan-modified zeolite composites and their applications have been overviewed.

Photosensitive Hybrid Nanostructured Materials: The Big Challenges for Sunlight Capture

Solar radiation is becoming increasingly appreciated because of its influence on living matter and the feasibility of its application for a variety of purposes. It is an available and everlasting natural source of energy, rapidly gaining ground as a supplement and alternative to the nonrenewable energy feedstock. Actually, an increasing interest is involved in the development of efficient materials as the core of photocatalytic and photothermal processes, allowing solar energy harvesting and conversion for many technological applications, including hydrogen production, CO2 reduction, pollutants degradation, as well as organic syntheses. Particularly, photosensitive nanostructured hybrid materials synthesized coupling inorganic semiconductors with organic compounds, and polymers or carbon-based materials are attracting ever-growing research attention since their peculiar properties overcome several limitations of photocatalytic semiconductors through different approaches, including dye or charge transfer complex sensitization and heterostructures formation. The aim of this review was to describe the most promising recent advances in the field of hybrid nanostructured materials for sunlight capture and solar energy exploitation by photocatalytic processes. Beside diverse materials based on metal oxide semiconductors, emerging photoactive systems, such as metal-organic frameworks (MOFs) and hybrid perovskites, were discussed. Finally, future research opportunities and challenges associated with the design and development of highly efficient and cost-effective photosensitive nanomaterials for technological claims were outlined.

Modeling the degradation and disinfection of water pollutants by photocatalysts and composites: A critical review

Recently, a series of new photocatalysts have been developed for to combat diverse bio-recalcitrant contaminants and the inactivation of bacteria. Modeling photocatalytic processes is important to assess these materials, and to understand and optimize their performance. In this study, the recent literature is critically reviewed and analyzed to identify and compare methods of modeling photocatalytic performance. The Langmuir-Hinshelwood model (L-H) has been used in many studies to rationalize the degradation kinetics of single contaminants because it is the simplest model including both the adsorption equilibrium and degradation rates. Other studies report the development of more sophisticated variants of the L-H model that include the rates of catalyst excitation, recombination of electron-hole pairs, production of reactive oxygen species (ROS), and formation of by-products. Modified Chick-Watson (CW) and Hom models have been used by many researchers to include lag phases of bacteria in the description of disinfection kinetics. Artificial neural networks (ANNs) have been used to analyze the effects of operational conditions on photocatalyst performance. Moreover, response surface methodology (RSM) has been employed for experimental design, and optimization of operational conditions. We have reviewed and analyzed all available articles that model photocatalytic activity towards water pollution, summarized and put them in context, and recommended future research directions.

A simple and effective synthesis of magnetic γ-Fe2O3@SiO2@TiO2-Ag microspheres as a recyclable photocatalyst: dye degradation and antibacterial potential

PURPOSE AND METHODS

In this study, an effective technique for synthesizing γ-Fe₂O₃@SiO₂@TiO₂-Ag magnetically separable photocatalyst was introduced by combining co-precipitation, sol-gel, and photo-deposition methods. A series of analyses including FTIR, SEM, EDS, XRD, and VSM were applied to characterize the prepared materials and the investigations on photocatalytic activity of the prepared composites were accomplished.

RESULTS

Compared to bare γ-Fe₂O₃@SiO₂@TiO₂, the Ag-doped composite was more active in terms of photocatalytic characteristics. By applying γ-Fe₂O₃@SiO₂@TiO₂-Ag, the decomposition rate of the Basic blue 41 reached to about 94% after 3 h of UV irradiation; this rate was 63% for pure γ-Fe₂O₃@SiO₂@TiO₂. The results indicated that the dye degradation kinetics followed first-order kinetic model. During the five cycles of separation, it was observed that the Ag-doped composite was greatly effective and stable in terms of recycling. Moreover, the results indicated that antibacterial activity of γ-Fe₂O₃@SiO₂@TiO₂-Ag was remarkably stronger than that of pure Fe₂O₃@SiO₂@TiO₂ particles.

CONCLUSION

It was concluded that by modifying magnetic TiO₂ by silver nanoparticles, charge separation was eased by catching photo-generated electrons, resulted in an enhanced photo- and biological activity. Graphical abstract.

In Situ Synthesis of MIL-100(Fe) at the Surface of Fe3O4@AC as Highly Efficient Dye Adsorbing Nanocomposite

A new magnetic nanocomposite called MIL-100(Fe) @Fe3O4@AC was synthesized by the hydrothermal method as a stable adsorbent for the removal of Rhodamine B (RhB) dye from aqueous medium. In this work, in order to increase the carbon uptake capacity, magnetic carbon was first synthesized and then the Fe3O4 was used as the iron (III) supplier to synthesize MIL-100(Fe). The size of these nanocomposite is about 30-50 nm. Compared with activated charcoal (AC) and magnetic activated charcoal (Fe3O4@AC) nanoparticles, the surface area of MIL-100(Fe) @Fe3O4@AC were eminently increased while the magnetic property of this adsorbent was decreased. The surface area of AC, Fe3O4@AC, and MIL-100(Fe) @Fe3O4@AC was 121, 351, and 620 m2/g, respectively. The magnetic and thermal property, chemical structure, and morphology of the MIL-100(Fe) @Fe3O4@AC were considered by vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), zeta potential, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), Brunner-Emmet-Teller (BET), and transmission electron microscopy (TEM) analyses. The relatively high adsorption capacity was obtained at about 769.23 mg/g compared to other adsorbents to eliminate RhB dye from the aqueous solution within 40 min. Studies of adsorption kinetics and isotherms showed that RhB adsorption conformed the Langmuir isotherm model and the pseudo second-order kinetic model. Thermodynamic amounts depicted that the RhB adsorption was spontaneous and exothermic process. In addition, the obtained nanocomposite exhibited good reusability after several cycles. All experimental results showed that MIL-100(Fe) @Fe3O4@AC could be a prospective sorbent for the treatment of dye wastewater.

In situ deposition of Ag/AgCl on the surface of magnetic metal-organic framework nanocomposite and its application for the visible-light photocatalytic degradation of Rhodamine dye

Herein, NH₂-MIL-125(Ti) (NMT) as one of the known stable metal-organic frameworks (MOFs) in aqueous solution was successfully magnetized with CoFe₂O₄ nanoparticles through the hydrothermal method. The Ag/AgCl as a plasmonic photocatalyst was assembled on the CoFe₂O₄/NMT (CFNMT) at room temperature by in situ deposition, and photo-reduction methods to improve the photocatalytic activity of CFNMT under LED visible light. The prepared materials were fully characterized by SEM/EDX, TEM, FTIR, XRD, UV-DRS, and VSM analysis. Rhodamin B (RhB) was selected as the pollutant model. The results showed that the Ag/AgCl@CFNMT had super-fast degradation ability of RhB molecule due to the synergetic effect between Ag/AgCl and CFNMT in comparison with NMT and CFNMT. The introduced Ag/AgCl on the surface of CFNMT increased absorption of photons in the visible region and enhanced the transfer and separation of the produced charge on the contact area between Ag/AgCl and CFNMT. Also, after seven times recycling, besides the simple magnetic separation of Ag/AgCl@CFNMT from liquid media, the composite still showed high photodegradation ability (89%).

Sustainable synthesis of silver nanoparticles using exposed X-ray sheets and forest-industrial waste biomass: Assessment of kinetic and catalytic properties for degradation of toxic dyes mixture

Silver being the precious metal, its recovery from the waste and utilization is a worthy attempt. The present study represents a very promising sustainable approach for the synthesis of silver nanoparticles (AgNPs), where prime raw materials are waste products (silver metal extracted from waste X-ray sheets and Sal deoiled seed cake (DOC), a plant-based waste as reducing-capping agent). Upon reaction of silver nitrate extracted from waste X-ray sheets and Sal DOC extract at room temperature, the characteristic yellowish-brown color appeared within 30 min. Peak at 485-495 in UV-visible spectrophotometer confirmed the synthesis of AgNPs. X-ray waste synthesized (XRWS) AgNPs were polycrystalline in nature and have face centered cubic (fcc) lattice. Majority of them were polygonal in shape (size range 30-150 nm) with some flower like aggregates as revealed by Transmission Electron Microscope. The XRWS-AgNPs were stabilized by organic groups adhered to their surface and had good stability with a zeta potential of -27.60 mV. These XRWS-AgNPs could work as an efficient catalyst for the reduction of five selected azo dyes individually as well as mixture of these dyes. The degraded products of the individual dyes were identified using Gas Chromatography Mass Spectroscopy. Experimental values obtained for dye degradation study were fitted with first and second order linear kinetic model to know about rate of the reaction.