Highly improved dechlorination of 2,4-dichlorophenol in aqueous solution by Fe/Ni nanoparticles supported by polystyrene resin

Zhang, Zhiyong; Hu, Yibo; Ruan, Wen‐Juan; Ai, Huiying; Yuan, Baoling; Fu, Ming‐Lai

doi:10.1016/j.chemosphere.2020.128976

Cited by 28 publications

(10 citation statements)

References 41 publications

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“…The ultra-high lime aluminum process has sufficient raw materials and low requirements for water quality and impact load resistance. However, its raw material utilization rate is low, the reaction conditions are complex, and the effluent hardness will increase [ 28 ]. Layered bimetallic hydroxide is a kind of anionic clay with a layered structure.…”

Section: Methodsmentioning

confidence: 99%

Optimization of Dechlorination Experiment Design Using Lightweight Deep Learning Model

Peng

Tan

2022

Computational Intelligence and Neuroscience

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This exploration intends to remove chloride ions in production and life, enhance buildings’ durability, and protect the natural environment from pollution. The current dechlorination technology is discussed based on the relevant theories, such as the lightweight deep learning (DL) model and chloride ion characteristics. Next, data statistics and comparative analysis methods are used to study the adsorption and desorption performance of dechlorination adsorbents. Finally, the lightweight DL model is introduced into the chloride diffusion prediction experiment of slag powder and fly ash concrete. The results show that in the study of dechlorination adsorption performance, the chloride ion concentration decreases gradually with the extension of adsorption time. However, with the increasing temperature, the chloride ion removal rate is increasing. The removal rate of chloride ions in water can decrease slowly with the increase of adsorbent. Therefore, selecting the 2 mol/L sodium hydroxide as the alkali concentration for adsorbent regeneration is the most appropriate. Besides, the regeneration performance of the adsorbent gradually declines with the increase of sodium chloride concentration in the solution. The lightweight DL model is applied to the chloride diffusion prediction experiment of slag powder and fly ash concrete. It is found that when the curing age is selected at 18 days, 90 days, and 180 days, respectively, the error between the lightweight DL model and the experimental results is about 0.2. It shows that the lightweight DL model is feasible for predicting the diffusion of chloride ions. Therefore, this exploration designs and studies the dechlorination experiment based on the lightweight DL model, which provides a new theoretical basis and optimization direction for removing chloride ions in the future industry.

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Section: Methodsmentioning

confidence: 99%

Optimization of Dechlorination Experiment Design Using Lightweight Deep Learning Model

Peng

Tan

2022

Computational Intelligence and Neuroscience

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“…The halogenated organic compound like 2,4 dichlorophenol (2,4-DCP) has been removed by using the bimetallic nanoparticle (Fe-Ni) supported by polystyrene resin (Fe-Ni-D072). 104 Another bimetallic nanoparticle was used for the degradation of halogenated organic compounds (1,1,1-trichloro 2,2bis ( p-chlorophenyl)-ethane(DDT) by using the ball mill process, bimetallic nanoparticle used is Fe -Zn which acts as mechanochemically for the destruction of DDT. It was observed that almost 94% destruction of DDT was achieved mechano-chemically following conditions like, 350 rpm rotation speed and optimal charge ratio was 35:1.…”

Section: Removal Of Pollutants From Water Using Bimetallic Nanoparticlesmentioning

confidence: 99%

Review—Bi-Metallic Nanoparticles for Water Treatment: Synthesis Routes, Purification, Challenges and Future Perspectives

Aaallie¹,

Shah

Andrabi

2023

ECS J. Solid State Sci. Technol.

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Bimetallic nanoparticles have attracted huge attention because they exhibit more efficient characteristics due to the extensive array of chemical and physical properties, synergistic effects, and different mechanisms of action. This review highlights the synthetic routes for synthesis of different bimetallic nanoparticles such as physical, chemical, and biological routes and their use for the removal of pollutants from water such as heavy metals, metalloids, dyes, pharmaceuticals, bacteria’s etc. The study shows that bimetallic nanoparticles have been synthesized by various methods and used for the purification and application of water. It also is revealed that the bimetallic nanoparticles are efficient for removal of organic, inorganic, and biological pollutants from water. Furthermore, an up to date review of use of various bimetallic nanoparticles for water treatment is presented in the form of table and the future perspectives and challenges in the field are discussed in detail.

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“…The use of Fe and Ni bimetallic systems showed advantages when compared to other nanoparticles in terms of cost and efficiency [17]. The synergetic effect between Fe and Ni accelerates the dechlorination of the chlorinated compound by the production of active hydrogen in pollutants [18]. Reports by Li et al (2021) and Ezaj et al (2022) on Fe/Nimediated dechlorination of 2,4-DCP suggested the subsequent formation of aggregates, and the reduction in the potency of the bimetallic nanoparticles while removal of chlorophenols [14,19].…”

Section: Introductionmentioning

confidence: 99%

Study on free and entangled binary metal nanocatalysts for removal of 2,4,6-trichlorophenol in aqueous phase: a comparative study

Felshia

Gnanamani

2023

Nanotechnology

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The present study highlights the comparative catalytic removal of 2,4,6-trichlorophenol (TCP) in aqueous phase by binary metal nanocatalysts in free as well as entangled forms. In brief, binary nanocatalysts comprising of Fe-Ni are prepared, characterized, and subsequently entangled in reduced graphene oxide (rGO) for better performances and reuse applications. Optimization studies on the mass of free and rGO-entangled binary nanocatalysts with respect to TCP concentration and other environmental factors are studied in detail. Results suggest binary nanocatalysts in free form at 40 mg/ml took 300 min to dechlorinate 600 ppm of TCP, whereas rGO-entangled Fe-Ni catalyst took only 190 min. Experiments on the reuse of the catalyst with respect to removal efficiency implied compared to free form rGO-entangled nanocatalysts exemplify more than 98% of removal efficacy even after 5 times of exposure to 600 ppm TCP concentration. High-performance liquid chromatography analysis display a pattern of sequential dechlorination during catalytic process. Followed by dechlorination, the phenol-enriched aqueous phase exposed to Bacillus licheniformis SL10, which degrades the phenol effectively within 24 hours. In conclusion, the prepared binary metal nanocatalysts, both in free as well as in rGO-entangled forms, effectively dechlorinate 2,4,6-TCP contaminations in aqueous phase, but with significant differences in time taken for the removal. And entanglement facilitate the reuse of the catalyst more effectively. The accumulated phenol biocatalytically removed and suggests the reuse applications of treated water.

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Highly improved dechlorination of 2,4-dichlorophenol in aqueous solution by Fe/Ni nanoparticles supported by polystyrene resin

Cited by 28 publications

References 41 publications

Optimization of Dechlorination Experiment Design Using Lightweight Deep Learning Model

Optimization of Dechlorination Experiment Design Using Lightweight Deep Learning Model

Review—Bi-Metallic Nanoparticles for Water Treatment: Synthesis Routes, Purification, Challenges and Future Perspectives

Study on free and entangled binary metal nanocatalysts for removal of 2,4,6-trichlorophenol in aqueous phase: a comparative study

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