Carboxymethyl cellulose improved adsorption capacity of polypyrrole/CMC composite nanoparticles for removal of reactive dyes: Experimental optimization and DFT calculation

Highlights

• PPy/CMC NPs were synthesized, and used for adsorption of two reactive dyes.

• PPy/CMC NPs had maximum adsorption capacity of 104.9 mg/g and 120.7 mg/g for RR56 and RB160, respectively.

• DFT results confirmed the significant role of CMC on the adsorption efficiencies.

• ANN predicts the behaviour of system with more accuracy than GP and RSM.

• Hydrogen bonds and van der Waals interactions are the main intermolecular forces.

Abstract

In this study, polypyrrole/carboxymethyl cellulose nanocomposite particles (PPy/CMC NPs) were synthesized and applied for removal of reactive red 56 (RR56)and reactive blue 160 (RB160) as highly toxic dyes. The amount of CMC was found significantly effective on the surface adsorption efficiency. Different optimization methods including the genetic programming, response surface methodology, and artificial neural network (ANN) were used to optimize the effect of different parameters including pH, adsorption time, initial dye concentration and adsorbent dose. The maximum adsorption of RR56 and RB160 were found under the following optimum conditions: pH of 4 and 5, adsorption time of 55 min and 52 min for RR56 and RB160, respectively, initial dye concentration of 100 mg/L and adsorbent dose of 0.09 g for both dyes. were obtained for RR56 and RB160, respectively. Also, the results indicated that ANN method could predict the experimental adsorption data with higher accuracy than other methods. The analysis of ANN results indicated that the adsorbent dose is the main factor in RR56 removal, followed by time, pH and initial concentration, respectively. However, initial concentration mostly determines the RB160 removal process. The isotherm data for both dyes followed the Langmuir isotherm model with a maximum adsorption capacity of 104.9 mg/g and 120.7 mg/g for RR56 and RB160, respectively. In addition, thermodynamic studies indicated the endothermic adsorption process for both studied dyes. Moreover, DFT calculations were carried out to obtain more insight into the interactions between the dyes and adsorbent. The results showed that the hydrogen bondings and Van der Waals interactions are dominant forces between the two studied dyes and PPy/CMC composite. Furthermore, the interaction energies calculated by DFT confirmed the experimental adsorption data, where PPy/CMC resulted in higher removal of both dyes compared to PPy. The developed nanocomposite showed considerable reusability up to 3 cylces of the batch adsorption process.

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.