Carboxymethyl cellulose improved adsorption capacity of polypyrrole/CMC composite nanoparticles for removal of reactive dyes: Experimental optimization and DFT calculation
Graphical abstract
Introduction
The discharge of wastewaters that come from a myriad of industries developed in the last decades, into the environment has placed human life and living organisms at risk. Reactive dyes are one of these destructive contaminants that are noxious and non-degradable due to having an aromatic ring in their structures(Zhou et al., 2017; Ahmed et al., 2020; Tshikovhi et al., 2020). These chemicals are broadly applied in textile, food, leather finishing, paper mill, cosmetics, and plastics(Mittal et al., 2010; Anil Kumar et al., 2015; Vanaamudan et al., 2016). Reactive dyes are of mostly used dyes in textiles, which comprise wastewater discharge in the range of 10–60 percent. These dyes can cause skin irritation, carcinogenesis, and mutagenesis(Cardoso et al., 2012; Irem et al., 2013; Rahman et al., 2013; Dehghani et al., 2017; Hassan and Carr, 2018). Hence, water pollution by textile wastewater discharge is invariable of grave concern which scientists are seeking remedies to resolve.
Several physical and chemical methods including photocatalytic degradation(Govindan et al., 2019; Zhao et al., 2019), coagulation-flocculation(Beluci et al., 2019; Nordin et al., 2019; Torres et al., 2019), biological treatments(Bonakdarpour et al., 2011; Liu et al., 2019; Zhao et al., 2020), catalytic reduction(Lajevardi et al., 2019; Mosaviniya et al., 2019; Nouri et al., 2020), Membrane bioreactors (Giwa et al., 2019; Berkessa et al., 2020) and adsorption (Abbasi et al., 2020; Hu et al., 2020; Wan et al., 2020) have been developed for the removal of different pollutants, especially reactive dyes (Chiou and Li, 2003; Chiou and Chuang, 2006; Hassan and Carr, 2018; Huang et al., 2020), from their aqueous solutions. Among them, the adsorption process is such a predominantly-used methodology due to its cost-effective, efficient, and easy-to-operate process with comparatively high capacity (Silva et al., 2016; Karri et al., 2018; Tanzifi et al., 2018b; Azari et al., 2020). Despite the several adsorption studies on removal of reactive dyes (Vanaamudan et al., 2016; Hassan and Carr, 2018; Değermenci et al., 2019; Li et al., 2019), there is limted studies on some of them, especially reactive red 56 and reactive blue 160(Semião et al., 2020).
Conducting polymers have been considerably utilized in developing different adsorbents due to their simple synthesis method, reasonable price, and high stability(Bhowmik et al., 2018; Lyu et al., 2019). Some of these polymers, such as polypyrrole and polyaniline, have the amine group in their structures making them capable of removing anionic contaminants from the aquoues solutions(Zhang and Bai, 2003; Li et al., 2016; Ali et al., 2018). The addition of small amount of natural polymers (e.g., hydroxypropyl cellulose and hydroxyethyl cellulose) to the polymerization reaction vessel of conducting polymers not only reduce the final size of the polymeric nanoparticles but also helps to stabilize the nanoparticles owing to their various functional groups(Tanzifi and Eisazadeh, 2011; Tanzifi et al., 2014). The presence of different functional groups improve the interaction between the polymeric nanoparticles and different sites in the contaminant molecules (i.e, dyes), resulting in enhanced adsorption capacity of the polymeric nanoparticles. For example, addition of carboxymethyl cellulose as a natural polymer which is non-toxic, highly soluble in water, and enriched of carboxyl and hydroxyl, have enhanced the adsorption capacity of the polymeric nanoadsorbent to remove Congo Red dye by 99%(Tanzifi et al., 2018a). However, no information is available about the effect of CMC on adsorption process in the molecular scale. Therefore, there is a need to investigate the interactions between the molecules in the adsorption process using molecular simulation.
As the adsorption process is a complex process with non-linear response to the effective parameters (e.g., pH, temperature, adsorbent dosage, time etc.), utilizing the computational intelligence models to predict the behavior of the system with a minimum number of experiments have recived tremendous attention(Ghaedi and Vafaei, 2017; Jiang et al., 2020). However, each of these optimization techniques (i.e., artifcal neural network, genetic programming and response surface methodology) have their own pros and cons and might not be a universal technique for all adsorptive systems. Therefore, the evaluation of the accuracy of these methods are of importance to better understand and predict the studied adsorption system.
Despite the experimental adsorption data that provide macro-level insight about the process, our understanding about the nature of interactions between the adsorbent and adsorbate is limited. To address this drawback, molecular-level studies such as density functional theory could be performed to gain insight into the process in molecular level and even atomic scale. The results of these methods are of importance for designing new adsorbents with higher efficiencies.
In this study, the role of introducing carboxymethyl cellulose to polypyrrole and its effect on adsorption properties of final polypyrrole/carboxymethul cellulose (PPy/CMC) composite were investigated by synthesis of PPy/CMC nanoparticles. The as-developed PPy/CMC nanoparticles were employed for removal of two different reactive dyes, i.e., reactive red 56 (RR56) and reactive blue 160 (RB160). After that, the effect of different parameters was studied and optimized by three different optimizion methods, including ANN, GP and RSM, to find the more accurate optimization method to predict the behavior of each system. Then, the isotherm, kinetic, and thermodynamic studies were conducted and the obtained data were evaluated using different models for each set of data. Moreover, the DFT calculations were carried out to gain insight about the adsorption process in the molecular level. The results obtained in this study indicate the important role of CMC percentage in the adsorption properties of PPy/CMC NPs, where could open up new windows for developing more novel adsorbents based on conductive polymers for efficient removal of different dyes from wastewaters.
Section snippets
Chemicals
Pyrrole monomer, carboxymethyl cellulose sodium salt, FeCl3, sulfuric acid, sodium hydroxide, reactive red 56 dye, and reactive blue 160 dye were purchased from Merck (Germany). Pyrrole monomer was distilled once to remove its impurities and was stored in a dark and cold environment before the polymerization process.
Instrumentation
A scanning electron microscope (SEM) (KYKY-EM 3200) was used to investigate the morphology of the adsorbent particles. Fourier transform infrared spectrums was obtained by a
Synthesis and characterization of polypyrrole/CMC nanoparticles
Fig. 1a shows the synthesis procedure of the PPy/CMC composite nanoparticles. The obtained nanoparticles were characterized using different techniques. The scanning electron microscopy (SEM) of the obtained nanopartilces shows that the nanopartciles have spherical shape with average diameter of 75 ± 5 nm (Fig. 1b), indicating narrow size distribution for these PPy/CMC nanoparticles. The smaller size with narrow size distribution in PPy/CMC compared to pure polypyrrole (Fig. 1c) could be
Conclusion
PPy/CMC composite nanoparticles were synthesized with chemical polymerization method and applied for removal of RR56 and RB160 dyes from their aquoues solutions. The weight ratio of CMC to pyrrole significantly contributed to the adsorption process, where the weight ratio of 0.2 was obtained as optimum value. Influential operational parameters on adsorption process including pH, amount of adsorbent, initial concentration and time were optimized using three different methods including artificial
CRediT authorship contribution statement
Marjan Tanzifi: Conceptualization, Methodology, Investigation, Writing - original draft, Supervision. Mohammad Tavakkoli Yaraki: Conceptualization, Methodology, Software, Writing - original draft, Writing - review & editing, Supervision. Zahra Beiramzadeh: Visualization, Writing - original draft. Leily Heidarpoor Saremi: Software, Visualization. Mohammad Najafifard: Investigation. Hojatollah Moradi: Software. Mohsen Mansouri: Software. Mojtaba Karami: Software. Hossein Bazgir: Investigation.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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M.T. and M.T.Y. contributed equally to this work.
- 2
Z.B., L.H·S., M.N. and H.M. contributed equally to this work.