Adsorption of phosphorus from aqueous solution by cubic zeolitic imidazolate framework-8: Modeling, mechanical agitation versus sonication

Shams, Mahmoud; Dehghani, Mohammad Hadi; Nabizadeh, Ramin; Mesdaghinia, Alireza; Alimohammadi, Mahmood; Najafpoor, Ali Asghar

doi:10.1016/j.molliq.2016.09.059

Cited by 101 publications

(35 citation statements)

References 29 publications

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“…Furthermore, the value of model lack fit was 0.0559. The model lack fit is another index which is used to describe the adequacy of developed models and it should not be significant toward the pure error [26]. The obtained values of R 2 , R 2 adjust and model lack fit in this study suggest that the behavior of persulfate/Nano zero valent iron system can be explained by the developed quadratic model.…”

Section: Central Composite Designmentioning

confidence: 72%

“…It is recommended that for a statistically valid model, adjusted determination coefficient (R 2 adjust) should be in the range of determination coefficient (R 2 ) ± 0.2 [26]. As can be seen in Table 2, the values of R 2 and R 2 adjust for the developed model are 0.913 and 0.8847 respectively.…”

Section: Central Composite Designmentioning

confidence: 99%

“…A set of three dimension (3D) response graphs was employed for visualizing the interaction effects of operating process parameters toward the response (% removal). A 3D response graph can illustrate the optimal points in which the maximum response is occurred [26]. 4-CP degradation as a function of NZVI dosage, pH and persulfate concentration is presented in Figure 3(a, b).…”

Section: Effect Of Process Operating Parameters On 4-chlorophenol Elimentioning

confidence: 99%

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Application of Adaptive Neural Fuzzy Inference System and Fuzzy C- Means Algorithm in Simulating the 4-Chlorophenol Elimination from Aqueous Solutions by Persulfate/Nano Zero Valent Iron Process

Baziar¹,

Nabizadeh²,

Mahvi³

et al. 2017

Eurasian J Anal Chem

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This study investigated the application of adaptive neural fuzzy inference system (ANFIS) and Fuzzy c-means (FCM) algorithm for the simulation and prediction of 4-chlorophenol elimination in aqueous media by the persulfate/Nano zero valent iron process. The structure of developed model which resulted to the minimum value of mean square error was a Gaussian membership function with a total number 10 at input layer, a linear membership function at output layer and a hybrid optimum method, which is a combination of backpropagation algorithm and least squares estimation, for optimization of Gaussian membership function parameters. The prediction of developed model in elimination 4-chlorophenol was significantly close to the observed experimental results with R2 value of 0.9942. The results of sensitivity analysis indicated that all operating variables had a strong effect on the output of model (4-CP elimination). However, the most effective variable was pH followed by persulfate, NZVI dosage, reaction time and 4-CP concentration. The performance of developed model was also compared with a quadratic model generated in a study by Response Surface Methodology (RSM). The results indicated that the ANFIS-FCM model was superior to the quadratic model in terms of prediction accuracy and capturing the behavior of the process.

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Section: Central Composite Designmentioning

confidence: 72%

Section: Central Composite Designmentioning

confidence: 99%

Section: Effect Of Process Operating Parameters On 4-chlorophenol Elimentioning

confidence: 99%

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Application of Adaptive Neural Fuzzy Inference System and Fuzzy C- Means Algorithm in Simulating the 4-Chlorophenol Elimination from Aqueous Solutions by Persulfate/Nano Zero Valent Iron Process

Baziar¹,

Nabizadeh²,

Mahvi³

et al. 2017

Eurasian J Anal Chem

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“…The higher F value (362.72) and accordingly lower P value (0.000) in Table 4 implies that the second-order polynomial model is statistically significant, in other words, the model fitted well with the experimental results [11,49]. The lack of fit (LOF) test evaluates the goodness of fit and must be insignificant in a well fitted model [50]. The LOF value for the experiments was 0.3698 (Table 4).…”

Section: Fitting the Process Modelmentioning

confidence: 96%

Adsorption of Cr(VI) ions from aqueous systems using thermally sodium organo-bentonite biopolymer composite (TSOBC): response surface methodology, isotherm, kinetic and thermodynamic studies

Dehghani¹,

Zarei²,

Mesdaghinia³

et al. 2017

Desalination and Water Treatment

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a b s t r a c tChromium, as a serious environmental contaminant, is frequently encountered in different industrial effluents. In the present study, we focused on the combined application of a surfactant-modified bentonite and chitosan for the removal of Cr(VI). In addition, the effects of several important parameters such as pH (2-8), adsorbent dosage (0.1-1.5 g/L), Cr(VI) concentration (20-200 mg/L) and contact time (60-240 min) were also investigated and the process was optimized by means of response surface methodology. The analysis of variance of the quadratic model demonstrates that the model was highly significant. Optimized values of pH, adsorbent dosage, initial Cr(VI) concentration and contact time were found to be 3.7, 1.40 g/L, 77 mg/L and 180 min, respectively. The results revealed that the prepared adsorbent had significant adsorption capacity (124.1 mg/g) for Cr(VI). All results showed that thermally sodium organo-bentonite biopolymer composite (TSOBC) had a good affinity toward Cr(VI). Among the isotherm models tested, Langmuir isotherm model was found to be the best fit for the obtained data. The adsorption kinetics indicated that Cr(VI) adsorption on TSOBC followed pseudo-second-order better than pseudo-first-order model. Moreover, thermodynamic studies showed that adsorption of Cr(VI) on TSOBC was spontaneous and endothermic in nature. The applied adsorbent was characterized by scanning electron microscopy, X-ray diffraction, energy dispersive X-ray and Fourier-transform infrared spectroscopic techniques.

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“…As a consequence, a shaking rate of 100 rpm was selected as desirable for subsequent studies because it was obvious that there was no significant increase or effect on the process. A research reported that, higher mass transfer rate and removal efficiency were obtained when the solution was agitated at higher mechanical speed [18]. …”

Section: Effect Of Agitation Speedmentioning

confidence: 99%

Preparation, Characterization and Adsorption Study of Granular Activated Carbon/Iron oxide composite for the Removal of Boron and Organics from Wastewater

et al. 2018

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Abstract. Boron and organics maybe in high concentration during production of oil and gas, fertilizers, glass, and detergents. In addition, boron added to these industrial processes may require to be removed by the wastewater treatment plant. The preparation, characterization and application of iron oxide-activated carbon composite for removal of boron and COD was studied. The one variable at a time (OVAT) method was implemented to obtain desirable operating conditions (adsorbent dosage 5 g/L, reaction time 2 h, agitation speed 100 rpm, pH 5 for COD removal and pH 9 for boron removal). It was found that boron and organics present in a sample wastewater may require to be treated separately to remove the contaminants. The study achieved 97 and 70% for boron and COD removal, respectively. Adsorption as an alternative cheap source of treatment and its practicability for small communities is recommended as effective in removal of contaminants from river water.

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Adsorption of phosphorus from aqueous solution by cubic zeolitic imidazolate framework-8: Modeling, mechanical agitation versus sonication

Cited by 101 publications

References 29 publications

Application of Adaptive Neural Fuzzy Inference System and Fuzzy C- Means Algorithm in Simulating the 4-Chlorophenol Elimination from Aqueous Solutions by Persulfate/Nano Zero Valent Iron Process

Application of Adaptive Neural Fuzzy Inference System and Fuzzy C- Means Algorithm in Simulating the 4-Chlorophenol Elimination from Aqueous Solutions by Persulfate/Nano Zero Valent Iron Process

Adsorption of Cr(VI) ions from aqueous systems using thermally sodium organo-bentonite biopolymer composite (TSOBC): response surface methodology, isotherm, kinetic and thermodynamic studies

Preparation, Characterization and Adsorption Study of Granular Activated Carbon/Iron oxide composite for the Removal of Boron and Organics from Wastewater

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