Sono-synthesis of MnWO4 ceramic nanomaterials as highly efficient photocatalysts for the decomposition of toxic pollutants

Zinatloo-Ajabshir, Sahar; Baladi, Mahin; Salavati‐Niasari, Masoud

doi:10.1016/j.ceramint.2021.07.197

Cited by 49 publications

(11 citation statements)

References 52 publications

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“…The lack of energy and environmental pollution become a huge worry in the last decades. 1 Water is one of the resources that all human activities depend on this. With the growth of the population meeting, human needs are not more possible by simple methods.…”

Section: Introductionmentioning

confidence: 99%

Study of antifouling and decolorization effect in polyethersulfone membranes improved with dendrimer‐modified metal–organic frameworks

Khosravi

Hosseini

Vatanpour

et al. 2023

J of Applied Polymer Sci

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The Mil‐125(Ti) metal–organic framework nanoparticles were modified with different compounds i.e. polyamidoamine dendrimer (Mil‐Den), chitosan (Mil‐CS) and Mil‐CS‐Den to prepare functional and hydrophilic nanocomposites. These nanocomposites were characterized and applied for modification of polyethersulfone (PES) membrane by blending them in the dope solutions. The mixed matrix PES membranes were manufactured by the nonsolvent‐induced phase inversion method. The introduction of the nanocomposites into the membrane structure led to positive alterations such as the improvement of hydrophilicity and morphology causing the development of permeability and antifouling properties. The bare PES membrane contact angle was decreased from 60° to 34.5° by adding 0.5 wt% of Mil‐CS‐Den nanocomposite. Applications of novel structures with special absorption in 0.5 wt% of Mil‐CS‐Den membrane, caused an increment of porosity, mean pore size and reduction of surface roughness. The permeability was enhanced from 4.2 to 21.43 L/m2 h bar, while fouling was reduced from 48.5% to 13.5% which indicates the strengthening of the antifouling feature of the hydrophobic PES membrane. Also, the flux recovery ratio was enhanced from 66.7% to 89.3% by blending 0.5 wt% of Mil‐CS‐Den. The modified membranes showed an excellent dye separation performance. The attachment of dendrimer and chitosan to the Mil‐125(Ti) surface increased the efficiency of Mil‐125(Ti) in the modification of the PES membrane. The utilization of nanomaterial features can reduce the limitation of membrane processes and reach desirable outcomes. The results of this work indicate the high potential of the modified MOF for the removal of dye contaminants as well as provide a suitable perspective for water purification with the help of membrane processes.

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Section: Introductionmentioning

confidence: 99%

Study of antifouling and decolorization effect in polyethersulfone membranes improved with dendrimer‐modified metal–organic frameworks

Khosravi

Hosseini

Vatanpour

et al. 2023

J of Applied Polymer Sci

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“…Photocatalysis is one promising technology in which new appropriate materials or systems are explored and investigated . In this regard, solar energy is captured and used via redox reactions for practical applications such as water splitting, , contaminant decomposition, , CO 2 photocatalytic reduction, , or CO 2 utilization. , The importance of photocatalysis lies on its ability to offer green and sustainable pathways for future development, , as well as the direct conversion of solar light without causing pollution to the environment . However, some minor concerns are still associated with traditional photocatalysis as it has low efficiency, poor recyclability, a slow rate of electron transport, and limited absorption of visible light .…”

Section: Introductionmentioning

confidence: 99%

Visible-Light-Driven Photocatalytic Coupling of Neat Benzylamine over a Bi-Ellagate Metal–Organic Framework

et al. 2022

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Selective aerobic oxidation of benzylamine to N,N-benzylidenebenzylamine was achieved using a bismuth ellagate (Bi-ellagate) metal–organic framework (MOF) under simulated visible light irradiation. The bismuth ellagate photocatalyst was characterized using several spectroscopic techniques: powder X-ray diffraction (PXRD), diffuse reflectance spectroscopy (DRS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and nitrogen sorption measurements. Product formation was confirmed using 1H-NMR, 13C-NMR, and FTIR. The photocatalytic performance of Bi-ellagate was studied for the first time, which exhibits a band gap value of 2.62 eV, endowing it with a high photocatalytic activity under visible light irradiation. The reaction product, N,N-benzylidenebenzylamine, was selectively obtained with a high conversion yield of ∼96% under solvent-free conditions compared to other control experiments. The Bi-ellagate photocatalyst was recovered and reused four times without any significant loss in its activity, which provides an eco-friendly, low-cost, recyclable, and efficient photocatalyst for potential photocatalytic applications.

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“…Recently, ML approaches are gaining popularity to generate new models for precise prediction in many research areas. For example, ML can be used to study nanomaterials for energy and environmental applications [11,12]. Studies were conducted to develop effective photocatalysts to treat toxic pollutants such as thymol blue [13,14].…”

Section: Introductionmentioning

confidence: 99%

Comparison of different machine learning algorithms to estimate liquid level for bioreactor management

Rhee

Shin

2022

Environmental Engineering Research

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Estimating the liquid level in an anaerobic digester can be disturbed by its closedness, bubbles and scum formation, and the inhomogeneity of the digestate. In our previous study, a soft-sensor approach using seven pressure meters has been proposed as an alternative for real-time liquid level estimation. Here, machine learning techniques were used to improve the estimation accuracy and optimize the number of sensors required in this approach. Four algorithms, multiple linear regression (MLR), artificial neural network (ANN), random forest (RF), and support vector machine (SVM) with radial basis function kernel were compared for this purpose. All models outperformed the cubic model developed in the previous study, among which the ANN and RF models performed the best. Variable importance analysis suggested that the pressure readings from the top (in the headspace) were the most significant, while the other pressure meters showed varying significance levels depending on the model type. The sensor that experienced both headspace and liquid phases depending on the level variation incurred a higher error than other sensors. The results showed that the ML techniques can provide an effective tool to estimate digester liquid levels by optimizing the number of sensors and reducing the error rate.

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Sono-synthesis of MnWO4 ceramic nanomaterials as highly efficient photocatalysts for the decomposition of toxic pollutants

Cited by 49 publications

References 52 publications

Study of antifouling and decolorization effect in polyethersulfone membranes improved with dendrimer‐modified metal–organic frameworks

Study of antifouling and decolorization effect in polyethersulfone membranes improved with dendrimer‐modified metal–organic frameworks

Visible-Light-Driven Photocatalytic Coupling of Neat Benzylamine over a Bi-Ellagate Metal–Organic Framework

Comparison of different machine learning algorithms to estimate liquid level for bioreactor management

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