Paracetamol is a non-steroidal, anti-inflammatory drug widely used in pharmaceutical applications for its sturdy, antipyretic and analgesic action. However, an overdose of paracetamol can cause ...fulminant hepatic necrosis and other toxic effects. Thus, the development of advantageous analytical tools to detect and determine paracetamol is required. Due to simplicity, higher sensitivity and selectivity as well as costefficiency, electrochemical sensors were fully investigated in last decades. This review describes the advancements made in the development of electrochemical sensors for the paracetamol detection and quantification in pharmaceutical and biological samples. The progress made in electrochemical sensors for the selective detection of paracetamol in the last 10 years was examined, with a special focus on highly innovative features introduced by nanotechnology. As the literature is rather extensive, we tried to simplify this work by summarizing and grouping electrochemical sensors according to the by which manner their substrates were chemically modified and the analytical performances obtained.
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•An overview of the electrochemical sensors developed for the sensing of paracetamol in the last 10 years.•Carbon paste, glassy carbon and screen printed are the most investigated carbon-based electrodes.•Multiwalled carbon nanotubes-based composites are the most efficient modifiers for paracetamol detection.•Metal organic frameworks allowed the detection of paracetamol at picomolar levels.•Differential pulse voltammetry was the most useful to discriminate multiple compounds and improve sensitivity.
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FFLJ, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, ODKLJ, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
•An overview of the electrochemical sensors and biosensors developed for the analysis of diclofenac.•Carbon based-electrodes are the most investigated electrodes in diclofenac analysis.•Carbon ...nanotubes and graphene-based composites are the most efficient modifiers for diclofenac detection.•Constructed biosensors allowed the detection of diclofenac at picomolar levels.
Diclofenac is a non-steroidal anti-inflammatory drug of wide use around the world for the treatment of several diseases such as ankylosing spondylitis, acute muscle pain conditions, and osteoarthritis. Although in proper doses it does not display any side effects, an overdose of diclofenac can cause adverse effects in the human body. Moreover, the presence of diclofenac in ecosystems directly affects the health of living organisms, even if it is present at trace. Therefore, the development of analytical tools for diclofenac monitoring was needed. In this context, electrochemical sensing and biosensing methods have been commonly reported. In this review, a critical evaluation of the methods employed for diclofenac analysis is presented according to the following classifications: potentiometric sensors, sensing at non-modified solid electrodes, chemically modified electrodes and biosensors. Recent developments related to the use of electrochemical detection of diclofenac in pharmaceutical formulations, biological fluids and environmental samples were reported and discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
This work focuses on the adsorptive removal of patent blue V (PBV) dye from aqueous solution by Zn/Al layered double hydroxide in fresh (LDH) and calcined (CLDH) forms. The material was synthesized ...via coprecipitation and samples were characterized by XRD, FTIR and TGA-DTA. Dye retention was evaluated under different experimental conditions of contact time, pH, adsorbent dosage, temperature and initial dye concentration. Experimental results show that highest adsorption capacity occurred at acidic medium. Kinetics data were properly fitted with the pseudo-second-order model. Equilibrium data were best correlated to Langmuir model with maximum monolayer adsorption capacities of 185.40 and 344.37 mg/g, respectively, for LDH and CLDH. The process was endothermic and spontaneous in nature. Based on the preliminary study, full factorial experimental design (24) was used for the optimization of the effect of solution pH, adsorbent dose, initial dye concentration and the calcination. Thus, the optimal conditions to reach high equilibrium adsorption capacity were achieved at pH of 5, adsorbent dosage of 0.1 g/L, and initial dye concentration of 15 mg/L by CLDH.
Nowadays, pharmaceuticals are the center of significant environmental research due to their complex and highly stable bioactivity, increasing concentration in the water streams and high persistence ...in aquatic environments. Conventional wastewater treatment techniques are generally inadequate to remove these pollutants. Aiming to tackle this issue effectively, various methods have been developed and investigated on the light of chemical, physical and biological procedures. Increasing attention has recently been paid to the advanced oxidation processes (AOPs) as efficient methods for the complete mineralization of pharmaceuticals. Their high operating costs compared to other processes, however, remain a challenge. Hence, this review summarizes the current and state of art related to AOPs, biological treatment and their effective exploitation for the degradation of various pharmaceuticals and other emerging molecules present in wastewater. The review covers the last decade with a particular focus on the previous five years. It is further envisioned that this review of advanced oxidation methods and biological treatments, discussed herein, will help readers to better understand the mechanisms and limitations of these methods for the removal of pharmaceuticals from the environment. In addition, we compared AOPs and biological treatments for the disposal of pharmaceuticals from the point of view of cost, effectiveness, and popularity of their use. The exploitation of coupling AOPs and biological procedures for the degradation of pharmaceuticals in wastewater was also presented. It is worthy of note that an integrated AOPs/biological system is essential to reach the complete degradation of pharmaceuticals; other advantages of this hybrid technique involve low energy cost, an efficient degradation process and generation of non-toxic by-products.
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•Pharmaceutical compounds in different water matrices contribute to ecotoxicity.•Water treatment plants are efficient to reduce but not remove pharmaceuticals present in water.•Removal of pharmaceuticals by advanced oxidation processes (AOPs) from wastewater appears efficient.•Biological processes are promising techniques in the removal of pharmaceuticals.•The hybrid AOPs/biological system is economical and efficiency for complete degradation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
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.
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•An introduction to machine learning in terms attainable by the chemistry•Step-by-step procedure of applying machine learning to pollutants removal.•A systematic review compiling high quality works in the removal of various pollutants using machine learning.•Suggestions are made for future studies related to the association of these two disciplines.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
•Various Synthetic procedures for the synthesis of nanomaterials of Layered Double Hydroxides (LDH) are discussed.•A Systematic Literature Review (SLR) has been conducted to synthesize concrete ...insights into the potential of LDHs as catalytic materials for the degradation of emerging pollutants.•LDH-based materials offer superior catalytic capabilities for the removal of various emerging compounds.
Layered double hydroxides (LDHs), one of the most important 2D heterostructure materials, have provided massive improvements for various applications in many fields. Especially, their application in water treatment as efficient catalysts owing to their unique features such as tunable structure, excellent thermal stability and regeneration performances. LDHs represent an eco-friendly alternative to conventional catalysts especially for the degradation of noxious emerging contaminants in aqueous solution. They have the ability to host anions in their interlayer structure and the particularity of having a memory effect which facilitates the phenomena of regeneration. Thus, this paper discusses the available knowledge about the synthesis of LDHs and their derivative catalysts, and the factors affecting in AOPs for the removal of emerging compounds. Incontestably, LDHs and LDH-based materials possess an exceptional flexible structure with adsorption ability and catalytic activity, which allows them to be extensively employed in the environmental remediation of emerging contaminants in water.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
Dyes rejected by various industries are one of the major hazardous pollutants to be quantified. It is therefore necessary to remove the dye before discharging it into the main water stream. In this ...study, the catalytic degradation of methyl green (MG) cationic dye by Fenton process 'Fe
2+
/H
2
O
2
' was modelled using four artificial intelligence (AI) models; artificial neural networks (ANN), support vector machine (SVM), random forest (RF) and gradient boosting regressor tree (GBRT) and compared with response surface methodology (RSM). The models were analysed by considering four factors that affect the degradation process: concentration of MG, concentration of Fe
2+
, concentration of H
2
O
2
and temperature . The objective of this analysis was to quantify the accuracy of prediction of four types of AI models along with RSM model. Sensitivity analyses comprising correlation coefficient, mean square error (MSE) were employed to assess the adequacy of the proposed models. The mean square error (MSE) values corresponding to the validation set for MG degradation were 0.434, 0.232, 0.307, 0.177 and 0.223 while the respective coefficient of determination values were 0.9658, 0.95780 0.9440, 0.9677 and 0.9574 for the ANN, SVM, RF, GBRT and CCD models, respectively. According to these results, the AI and RSM gave a high accuracy in predicting the degradation of the methyl green dye. The four AI models have satisfactory goodness-of-fit, robustness and predictive ability compared to RSM model. The GBRT performs slightly better performance than the other models. Maximum degradation (De% > 98) was achieved at an initial dye concentration of 20 mg/L, a Fe
2+
concentration of 7 mM, a hydrogen peroxide dose of 25 mM, and a temperature of 50°C. Overall, the applied statistical analysis of the results indicates that the four methods can be employed as an AI models for monitoring and prediction the degradation by Fenton process.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
In this study, ZnO-Zn
2
TiO
4
(ZTM) material was prepared through a novel synthesis method based on a ultrasound-assisted polyol-mediated process followed by calcination at a different temperature. ...Physical features of the samples were studied by using various analysis techniques including XRD, FT-IR, SEM/EDX, pH
PZC
, and UV–Vis DRS. Subsequently, the materials were employed as catalysts for the photocatalytic degradation of clofibric acid as a model pharmaceutical contaminant. The photocatalytic performance was evaluated under different conditions of calcination temperature, catalyst dosage, starting concentration, and initial pH of clofibric acid solution. The finding results revealed that hexagonal-tetragonal phases of ZnO-Zn
2
TiO
4
calcined at 600 °C (ZTM-600) with an average crystallite size of 97.8 Å exhibited the best degradation efficiency (99%). The primary bands characteristic of ZnO and Zn
2
TiO
4
were displayed by FT-IR analysis and the UV–visible DRS confirms the larger absorption capacity in UV–visible regions. The photogenerated electrons are the powerful reactive species involved in clofibric acid photodegradation process. This study shows a promising photocatalyst and provides new sight to rational design the facets of photocatalysis process for enhanced photocatalytic performances and effective wastewater treatment.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Mn
3
O
4
/ZnO-Al
2
O
3
-CeO
2
catalyst was synthesized through a solid-state process from a 3% Mn-doped Zn-(Al/Ce) layered double hydroxide structure. Detailed structural and optical characterization ...using XRD, FTIR, UV–visible DRS, and TEM was conducted. By investigating clofibric acid (CA) degradation in aqueous solution, Mn
3
O
4
/ZnO-Al
2
O
3
-CeO
2
photocatalytic activity was evaluated. The results show that the heterostructure mixed oxide catalyst has excellent CA photodegradation performance. Further, the characterization reveals that such photocatalytic efficiency can be attributed to two facts that are summarized in the optical properties and the synergic effect between Mn and Ce elements. The sample demonstrated a narrow band gap of 2.34 eV based on DRS. According to the experimental results of the photodegradation, after 120 min of irradiation, the photocatalyst exhibited the highest photocatalytic activity, with a degradation efficiency of 93.6%. Optimization outcomes indicated that maximum degradation efficiency was attained under the following optimum conditions: catalyst dose of 0.3 g/L, initial dye concentration of 20 mg/L, pH 3.86, and 120 min of reaction time. The quenching test demonstrates that photogenerated electrons and superoxide radicals are the most powerful reactive species. The catalyst could be useful in decreasing the photogenerated charges recombination, which offers more redox cycles simultaneously during the catalytic process. The strong Ce-Mn interaction and the formation of their different oxidation states offer a high degradation efficiency by facilitating electron–hole transfer. The introduction of Mn
3
O
4
in the catalyst can effectively improve the visible absorption properties, which are beneficial in the photocatalytic process by reaching a high catalytic efficiency at a low cost.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Mn
O
/ZnO-Al
O
-CeO
catalyst was synthesized through a solid-state process from a 3% Mn-doped Zn-(Al/Ce) layered double hydroxide structure. Detailed structural and optical characterization using ...XRD, FTIR, UV-visible DRS, and TEM was conducted. By investigating clofibric acid (CA) degradation in aqueous solution, Mn
O
/ZnO-Al
O
-CeO
photocatalytic activity was evaluated. The results show that the heterostructure mixed oxide catalyst has excellent CA photodegradation performance. Further, the characterization reveals that such photocatalytic efficiency can be attributed to two facts that are summarized in the optical properties and the synergic effect between Mn and Ce elements. The sample demonstrated a narrow band gap of 2.34 eV based on DRS. According to the experimental results of the photodegradation, after 120 min of irradiation, the photocatalyst exhibited the highest photocatalytic activity, with a degradation efficiency of 93.6%. Optimization outcomes indicated that maximum degradation efficiency was attained under the following optimum conditions: catalyst dose of 0.3 g/L, initial dye concentration of 20 mg/L, pH 3.86, and 120 min of reaction time. The quenching test demonstrates that photogenerated electrons and superoxide radicals are the most powerful reactive species. The catalyst could be useful in decreasing the photogenerated charges recombination, which offers more redox cycles simultaneously during the catalytic process. The strong Ce-Mn interaction and the formation of their different oxidation states offer a high degradation efficiency by facilitating electron-hole transfer. The introduction of Mn
O
in the catalyst can effectively improve the visible absorption properties, which are beneficial in the photocatalytic process by reaching a high catalytic efficiency at a low cost.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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