Fast and effective methylene blue adsorption onto graphene oxide/amberlite nanocomposite: Evaluation and comparison of optimization techniques

Ciğeroğlu, Zeynep; Küçükyıldız, Gürkan; Haşimoğlu, Aydın; Taktak, Fulya; Açıksöz, Nazlıcan

doi:10.1007/s11814-020-0600-8

Cited by 14 publications

(5 citation statements)

References 52 publications

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“…There is a clear preference for PSO kinetic model, as shown by the high coefficient of determination (R 2 = 0.9810) and the presence of a good agreement between the predicted and observed qe values while analyzing the adsorption performance of MO. Besides, the PSO model presented lower average relative error (ARE) and standard deviation (SD) values 49 , 50 . A similar kinetics trend was reported by Liu et al 51 and showed that the PSO model offers the best adsorption rate for methyl orange by GO-based adsorbent.…”

Section: Resultsmentioning

confidence: 99%

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye

Pervez,

Jahid,

Mishu

et al. 2023

Sci Rep

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There has been a lot of attention on water pollution by dyes in recent years because of their serious toxicological implications on human health and the environment. Therefore, the current study presented a novel polyethylene glycol-functionalized graphene oxide/chitosan composite (PEG-GO/CS) to remove dyes from aqueous solutions. Several characterization techniques, such as SEM, TEM, FTIR, TGA/DTG, XRD, and XPS, were employed to correlate the structure–property relationship between the adsorption performance and PEG-GO/CS composites. Taguchi’s (L25) approach was used to optimize the batch adsorption process variables [pH, contact time, adsorbent dose, and initial concentration of methyl orange (MO)] for maximal adsorption capacity. pH = 2, contact time = 90 min, adsorbent dose = 10 mg/10 mL, and MO initial concentration = 200 mg/L were found to be optimal. The material has a maximum adsorption capacity of 271 mg/g for MO at room temperature. With the greatest R2 = 0.8930 values, the Langmuir isotherm model was shown to be the most appropriate. Compared to the pseudo-first-order model (R2 = 0.9685), the pseudo-second-order model (R2 = 0.9707) better fits the kinetic data. Electrostatic interactions were the dominant mechanism underlying MO sorption onto the PEG/GO-CS composite. The as-synthesized composite was reusable for up to three adsorption cycles. Thus, the PEG/GO-CS composite fabricated through a simple procedure may remove MO and other similar organic dyes in real contaminated water.

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Section: Resultsmentioning

confidence: 99%

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye

Pervez,

Jahid,

Mishu

et al. 2023

Sci Rep

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“…6 (b)–(c)). This situation is clearly explained that, a high initial concentration of CPF results in higher concentration gradient owing to the driving force [ 38 ]. Thus, CPF molecules were adsorbed faster to the surface of ZnO/BaTiO 3 .…”

Section: Resultsmentioning

confidence: 99%

Preparation of ZnO/BaTiO3 adsorbent using Elaeagnus Angustifolia L. leaf extract and its evaluation for ciprofloxacin removal from aqueous solutions: an optimization study

Ciğeroğlu

2021

Biomass Conv. Bioref.

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Especially, most papers have reported an increase in antibiotic resistance (AR) bacterial infections during the COVID-19 pandemic. Because of the outbreak of the SARS-CoV-2, antimicrobial resistance (AMR) should be controlled and reduced. Researchers have reported that the adsorption technique is an sufficient procedure for separating drugs such as antibiotics from aqueous solutions. The prepared of ZnO/BaTiO 3 nanocomposite using Elaeagnus Angustifolia L. leaf extract was successfully obtained using green route. The synthesized nanocomposite was interacted with ciprofloxacin hydrochloride (CPF) to aim at eliminating the antibiotic from aqueous solutions. The incorporation of Elaeagnus Angustifolia leaf extract onto ZnO/BaTiO 3 proved a sustainable chemistry study. Hence, this study indicated that green nanoparticles include neither the use of hazardous chemicals nor toxic chemicals. FTIR, XRD, and SEM-EDX analyses were applied to give information about the structural properties of the green nanocomposite. Box-Behnken design (BBD) was executed by response surface methodology (RSM) to gain optimal conditions. The effect of pH, initial concentration of CPF, and nanocomposite dose on CPF-nanocomposite interaction was examined. The experimental findings of adsorption study revealed that the optimal adsorption capacity of CPF onto ZnO/BaTiO 3 was found as 125.29 mgg -1 under optimal conditions (adsorbent dose: 3.00 mg, pH value of solution: 9.88, initial concentration CPF: 49.63 mgL -1 ).

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“…Various treatment methods, such as photochemical processes, biodegradation, electrochemical methods, synthetic coagulation, reverse osmosis, and adsorption, have been employed for azo color removal. In comparison to other physiochemical processes discussed in the literature, both human activities and the MB production process contribute to the proliferation of MB pollution in the environment 13 , 15 .…”

Section: Introductionmentioning

confidence: 98%

“…Several artificial intelligence (AI) models, including artificial neural network (ANN), Multilinear Regression (MLR), Radial Basis Function (RBF), and Support Vector Machine (SVM), have been employed successfully in water quality prediction and monitoring. In many studies, neural networks (NNs) have been utilized for monitoring and assessing surface water quality 12 , 13 . Due to their complex chemical composition, dyes are resistant to light and oxidation, which contributes to their non-biodegradability.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes

Mijwel,

Ahmed,

Afan

et al. 2023

Sci Rep

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This study aims to assess the practicality of utilizing artificial intelligence (AI) to replicate the adsorption capability of functionalized carbon nanotubes (CNTs) in the context of methylene blue (MB) removal. The process of generating the carbon nanotubes involved the pyrolysis of acetylene under conditions that were determined to be optimal. These conditions included a reaction temperature of 550 °C, a reaction time of 37.3 min, and a gas ratio (H2/C2H2) of 1.0. The experimental data pertaining to MB adsorption on CNTs was found to be extremely well-suited to the Pseudo-second-order model, as evidenced by an R2 value of 0.998, an X2 value of 5.75, a qe value of 163.93 (mg/g), and a K2 value of 6.34 × 10–4 (g/mg min).The MB adsorption system exhibited the best agreement with the Langmuir model, yielding an R2 of 0.989, RL value of 0.031, qm value of 250.0 mg/g. The results of AI modelling demonstrated a remarkable performance using a recurrent neural network, achieving with the highest correlation coefficient of R2 = 0.9471. Additionally, the feed-forward neural network yielded a correlation coefficient of R2 = 0.9658. The modeling results hold promise for accurately predicting the adsorption capacity of CNTs, which can potentially enhance their efficiency in removing methylene blue from wastewater.

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Fast and effective methylene blue adsorption onto graphene oxide/amberlite nanocomposite: Evaluation and comparison of optimization techniques

Cited by 14 publications

References 52 publications

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye

Tuning the surface functionality of polyethylene glycol-modified graphene oxide/chitosan composite for efficient removal of dye

Preparation of ZnO/BaTiO3 adsorbent using Elaeagnus Angustifolia L. leaf extract and its evaluation for ciprofloxacin removal from aqueous solutions: an optimization study

Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes

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