Mechanism of Adsorption on Nanomaterials

CHAPTER

4

MECHANISM OF ADSORPTION ON NANOMATERIALS

Rustem Kecili*, Chaudhery Mustansar Hussain** *Anadolu University, Yunus Emre Vocational School of Health Services, Eskişehir , Turkey **New Jersey Institute of Technology, Newark, NJ, United States

1 INTRODUCTION Nanomaterials have received growing attention from many scientists due to their superior features such as large surface area, small size, high stability, high reactivity, and versatile chemistry for further functionalization [1]. The chemical and physical properties of the materials at nanoscale (1–100 nm) are different compared to the same materials at macroscale. For example, bulk gold particles are yellow while gold nanoparticles exhibit red color. This feature originates from the interaction between restricted electrons of the gold nanoparticles with light. A decrease in the size of a material also leads to an increase in the surface area. This is very important especially for the adsorption processes. More binding sites are available on the surface of nanomaterials that are used for the adsorption processes. In the adsorption processes for environmental samples, chemical and biological approaches are used for the adsorption of undesired compounds from contaminated samples. In biological processes, microorganisms such as fungi, bacteria, algae, and so on have been used [2–4]. Although this technique is low-cost and environmentally friendly, it is challenging and not efficient. On the other hand, conventional materials such as clays and lichens are used as economical adsorbents applied for the removal of undesired compounds such as heavy metals, pharmaceuticals, and dye pigments from environmental samples [5–8]. However, these microscale materials have low surface area and low adsorption capacities. Thus the development of innovative and efficient adsorbents for the adsorption processes are crucial. The drawbacks of the conventional adsorbents can be overcome by using nanomaterials. So far, many research groups have reported the use of nanomaterials [e.g., nanoparticles, carbon nanotubes (CNTs), nanorods, and graphene] as efficient adsorbents for the adsorption of various compounds in complex matrices such as environmental [9], biological [10], and food samples [11]. In this chapter, an overview of the recent developments and applications of nanomaterials as efficient adsorbents is provided. It starts with a summary of the adsorption phenomena, which is followed by the demonstration of different adsorption isotherms. Then adsorption kinetics and thermodynamics are described. In the last sections, the applications and adsorption mechanisms of nanomaterials such as nanoparticles (Ag, Au, TiO2, and ZnO nanoparticles) and carbon-based nanomaterials (CNTs, fullerenes, and graphene) are presented.

Nanomaterials in Chromatography. http://dx.doi.org/10.1016/B978-0-12-812792-6.00004-2 Copyright © 2018 Elsevier Inc. All rights reserved.

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CHAPTER 4  Mechanism of Adsorption on Nanomaterials

2  ADSORPTION MECHANISM Adsorption is a surface-based exothermic process in which molecules of a compound in gas or liquid state are accumulated at an adsorbent surface [12]. The compound that is adsorbed to the adsorbent is named as adsorbate. On the other hand, desorption is the release of the adsorbed molecules from the surface of the adsorbent, which is the opposite of adsorption. This process is schematically depicted in Fig. 4.1. Adsorption of the molecules to the adsorbent surface can occur in two ways which are “physical adsorption,” also called “physisorption,” and “chemical sorption,” also called “chemisorption.” This depends on the interactions between the molecules and the surface. In physical adsorption, the weak forces such as electrostatic interactions and Van der Waals forces are involved. The strong chemical bonds such as covalent bonds are formed between the surface and the adsorbed molecules in chemical adsorption. Chemical adsorption is slower than physical adsorption and usually a monomolecular layer (monolayer) is formed on the adsorbent surface while physical adsorption usually involves the formation of thick multilayer on the surface [13]. Fig. 4.2 shows a schematic representation of the monolayer and multilayer adsorption on the adsorbent surface. Table 4.1 shows the differences between physical adsorption and chemical adsorption.

2.1  ADSORPTION ISOTHERMS The adsorption isotherm of any adsorption system is referred to as a curve of the amount of adsorbed molecules to the adsorbent surface as a function of the partial pressure or concentration of the adsorbate at a constant temperature [14].

FIGURE 4.1  Schematic Depiction of Adsorption and Desorption Processes.

FIGURE 4.2  (A) Monolayer and (B) multilayer adsorption.

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Table 4.1  Comparison Between Physical Adsorption and Chemical Adsorption Physical Adsorption

Chemical Adsorption

Electrostatic interactions and Van der Waals forces are involved

Covalent bonds are formed between the surface and the adsorbed molecules

Fast

Slow

Reversible

Irreversible

Not very specific

It is specific

Multilayers are formed

Monolayers are formed

Activation energy is not required

Activation energy is required

It usually occurs at low temperature values and decreases with increasing temperature

High temperature is needed

There are six types of adsorption isotherms according to the IUPAC classification for gas adsorption on the surface of solid adsorbents [15] as shown in Fig. 4.3. Type I adsorption isotherms describe the adsorption of gas molecules to the adsorbents having micropores such as activated carbon and the surface of the adsorbent is covered with a monolayer of adsorbed molecules. On the other hand, Type II adsorption isotherm describes the adsorption of gas molecules to the macroporous adsorbents. Type II adsorption isotherm does not display any saturation point as seen in Type I isotherm and a multilayer of adsorbed molecules is formed after the coverage of the adsorbent surface with monolayer adsorbed molecules.

FIGURE 4.3  Types of Adsorption Isotherms According to the IUPAC Classification. Reproduced with permission from M.D. Donohue, G.L. Aranovich, Classification of Gibbs adsorption isotherms, Adv. Colloid Interface Sci. 76–77 (1998) 137–152.

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CHAPTER 4  Mechanism of Adsorption on Nanomaterials

Type III adsorption isotherm refers to multilayer adsorption by weak interactions with low energy between adsorbed molecules and the adsorbent having macropores. Type IV and Type V adsorption models represent the multilayer adsorption together with capillary condensation to the mesoporous adsorbents. Type VI adsorption isotherm describes the stepwise formation of a multilayer on the surface of nonporous adsorbent. Various adsorption isotherm models such as the Langmuir, Freundlich, Temkin, Dubinin–Radushkevich, Harkins–Jura and Halsey, Redlich–Peterson, and BET (Brunauer, Emmett, and Teller) are used to get detailed information about the interactions between the surface of the adsorbents and molecules to be adsorbed. These isotherm models are briefly explained in the following sections.

2.1.1  Langmuir isotherm In 1932, the Langmuir adsorption model was proposed by Irving Langmuir [16] and the main assumptions of this isotherm model are the following: • • • •

Adsorption occurs at specific binding sites that are localized on the surface of the adsorbent. All adsorption sites on the surface of the adsorbent are identical. The surface of the adsorbent is covered with a monolayer of adsorbed molecules. There is no interaction between the adsorbed molecules on the adsorbent surface. The Langmuir adsorption model can be demonstrated by the following equation:



Ce C 1 = + e qm K L qmax qmax

(4.1)

In the equation above, Ce (mg L−1) and qm (mg g−1) are the concentration of the molecules at equilibrium and the amount of adsorbed molecules on the surface of the adsorbent at any time, respectively. qmax shows the maximum adsorption capacity (mg g−1) and KL represents the Langmuir constant (L mg−1).

2.1.2  Freundlich isotherm The Freundlich isotherm model [17] is another approach that is used for the description of the multilayer and heterogeneous adsorption of molecules to the adsorbent surface. This model is demonstrated by Eq. (4.2):

1 log qm = log K F + log Ce n

(4.2)

where qm (mg g−1) represents the amount of adsorbed molecules to the adsorbent surface at any time, Ce (mg L−1) is the equilibrium concentration, n and KF are the Freundlich constant and Freundlich exponent, respectively. KF (mg g−1) indicates the adsorption capacity of the adsorbent toward the adsorbate and n is an indicator for the degree of the surface heterogeneity and describes the distribution of the adsorbed molecules on the adsorbent surface. A value of n higher than 1 indicates a favorable adsorption of the molecules onto the adsorbent surface. A value of higher n reflects the higher intensity of adsorption.

2.1.3  Temkin isotherm Temkin and Pyzhev proposed another adsorption isotherm in 1940 [18,19]. In this model, the effect of adsorption heat, which linearly decreases with the coverage of adsorbed molecules layer, is considered. The decrease of the adsorption heat is due to the interactions between the adsorbed molecules on the surface.

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The Temkin adsorption isotherm is illustrated by the following equation:   RT   qe =     ln ( ACe )   bT  



(4.3)

where T is the temperature (K), R is the ideal gas constant (8.314 Jmol−1 K−1), bT represents the Temkin constant (J mol−1), which depends on the adsorption heat, and A is the equilibrium adsorption constant, which corresponds to the maximum adsorption energy (L mg−1).

2.1.4  Dubinin–Radushkevich model The adsorption of the molecules into the micropores of the adsorbents is described by the Dubinin– Radushkevich adsorption model [20,21]. According to this model, molecular adsorption occurs in the micropores (pore filling) instead of adsorption on the surface of the adsorbents that leads to monolayer or multilayer formation. The Dubinin–Radushkevich adsorption model is commonly applied to the adsorption processes of the subcritical vapors in the pores of the adsorbents such as zeolites and activated carbons. This model is demonstrated by Eq. (4.4): ln qe = ln qm − βε 2 (4.4)

where qe is the amount of adsorbed molecules per mass of adsorbent (mg g−1), qm represents the adsorption capacity (mg g−1), β is the activity coefficient (mol2 J−2), which represents the adsorption energy, and ε demonstrates the Polanyi potential as given in the following formula:  1 ε = RT ln  1 +  Ce  



(4.5)

where R is the ideal gas constant (Jmol−1 K−1), T is the temperature (K), and Ce is the concentration of the molecules at equilibrium (mg L−1).

2.1.5  Harkins–Jura and Halsey isotherms The Harkins–Jura isotherm is mainly applied for the description of the multilayer adsorption processes to the adsorbent surfaces having heterogeneous pore distribution [22]. This isotherm model is defined as the following equation:  1   BHJ   1   qe2  =  A  −  A  log Ce HJ HJ



(4.6)

where BHJ and AHJ represent the Harkins–Jura constants, which can be determined using the linear plot  1  versus log Ce.  qe2 

of 

On the other hand, the Halsey isotherm [23] is demonstrated by Eq. (4.7). This model is also applied for the multilayer adsorption processes on the heterogeneous surface of the adsorbents. log Ce (4.7)

where nH and KH are the Halsey constants and can be calculated using the slope of the linear plot of ln qe versus ln (1/Ce) for nH and the intercept of the linear plot of ln qe versus ln (1/Ce) for KH.

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CHAPTER 4  Mechanism of Adsorption on Nanomaterials

2.1.6  Redlich–Peterson isotherm The Redlich–Peterson isotherm [24] is a combined model that exhibits the features of both Langmuir and Freundlich isotherm models. It is used to describe the adsorption process to the homogenous and heterogeneous surfaces of adsorbents over a wide range of adsorbate concentrations. This isotherm model shows the features of the Freundlich isotherm model at higher adsorbate concentrations while it obeys the Henry’s law at lower adsorbate concentrations. This model is demonstrated by Eq. (4.8):



 1   1 1 ln qe =  ln K H  −  ln  nH   nH Ce 

(4.8)

where KRP (L g−1) and α (L mg−1) are Redlich–Peterson constants, β is the exponential value in the range between 0 and 1. If the β value is 0, the isotherm behaves as a Langmuir model while it obeys Henry’s law when the β value is 1.

2.1.7  Brunauer, Emmett, and Teller isotherm The BET isotherm model is another milestone in the progress of adsorption science [25–27]. This model represents the multilayer adsorption of the molecules to the adsorbent surface and the assumptions of the BET isotherm are the same as for the Langmuir isotherm model. This isotherm model is widely used for the adsorption processes in the gas–solid systems and the surface area and the porosity of the materials can be determined by using the BET isotherm model. The following equation is used for the description of the BET isotherm model. ln qe (4.9)

where Ce (mg L−1) is the equilibrium concentration, Cs (mg L−1) is the saturation concentration, qe is the amount of adsorbed molecules per mass of adsorbent (mg g−1) at equilibrium, qm represents the theoretical saturation capacity (mg g−1), and CBET (L mg−1) represents the energy of surface interaction.

2.2  ADSORPTION KINETICS AND THERMODYNAMICS There are three main steps during the adsorption of a compound to the surface of the adsorbent. In the first step, molecular mass transfer from the solution to the adsorbent surface occurs. Then, internal molecular diffusion to the adsorption sites placed on the adsorbent takes place. The adsorption is then completed in the final step of the process. The investigation of adsorption kinetics and thermodynamics is very important to estimate the adsorption mechanism. For this purpose, the adsorption kinetics models such as the pseudo-first-order, the pseudo-second-order, and intraparticle diffusion models are widely applied to the adsorption systems.

2.2.1  Pseudo-first-order kinetics The pseudo-first-order model was developed by Lagergren [28]. The main assumptions of this kinetic model are the following: • Adsorption only occurs at specific binding sites, which are localized on the surface of the adsorbent. • Adsorption energy does not depend on the formation of a layer on the adsorbent surface. • The first-order equation governs the rate of the adsorption process.

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95

• No interaction occurs between the adsorbed molecules on the surface of the adsorbent. The equation for the pseudo-first-order kinetic model is given in the following: ln



1 Ce

(4.10)

where, q1 is the amount of adsorbed compound (mg g−1) to the adsorbent at equilibrium, qt is the amount of adsorbed compound (mg g−1) to the adsorbent at time t (min), and k1 (min−1) represents the rate constant for the first-order adsorption process.

2.2.2  Pseudo-second-order kinetics The pseudo-second-order kinetic model has almost the same assumptions as the pseudo-first-order model; the only difference is the rate of the model [29]. It is demonstrated by Eq. (4.11): (4.11) ln qe

2.2.3  Intraparticle diffusion model This model is mainly used for the description of the adsorption process if the adsorbate diffusion to the porous adsorbent is the rate-limiting step. Weber and Morris have proposed this kinetic model [30] and described it in the following formula: ln



1 Ce

(4.12)

where C is the intercept and represents the boundary layer thickness. The higher the C value, the higher the effect of the boundary layer. qt represents the amount of adsorbed compound (mg g−1) to the adsorbent at time t (min) and kid is the rate constant of the intraparticle diffusion (mg g−1 min−0.5).

2.2.4  Thermodynamic study Thermodynamic studies are performed to investigate the temperature effect on the adsorption process. For this purpose, the following equations are used to calculate various thermodynamic parameters such as enthalpy change (∆H0), Gibbs free energy change (∆G0), and entropy change (∆S0), which are the main characteristics of the adsorption process [31]. The nature of the adsorption process can be predicted by calculating these thermodynamic parameters. qe = qe =

K RP Ce

1 + (α Ce )

β

qs C BET Ce  C  (Cs − Ce ) 1 + (CBET − 1) Ce   s  ln ( q1 − qt ) = ln q1 − k1t

(4.13)

(4.14)

(4.15)

where T is the temperature (K), R represents the ideal gas constant (8.314 Jmol−1 K−1), and Kd is the equilibrium constant.

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The ∆G0 value indicates whether the adsorption process is spontaneous or not. If the ∆G0 value is negative, the adsorption takes places spontaneously. On the other hand, ∆H0 gives information about whether the adsorption process is endothermic or not. The adsorption process is endothermic when the ∆H0 is a positive value.

2.3  ADSORPTION ON CHROMATOGRAPHIC NANOSTATIONARY PHASES Nanostationary phases such as metallic nanoparticles (e.g., Ag and Au), metal oxide nanoparticles (e.g., ZnO and TiO2), and magnetic nanoparticles (MNPs) (e.g., Fe3O4) are excellent candidates as efficient nanoadsorbents due to their unique properties such as high reactivity, small size, and high surface area-to-volume ratio, which provides high adsorption capacities toward the target compound. The applications of these nanoadsorbents are briefly described in the following sections.

2.3.1  Silver nanoparticles Silver nanoparticles (Ag NPs) are commonly used for the removal of environmental pollutants such as heavy metals and industrial dyes. Many studies that demonstrate the use of Ag NPs for the adsorption processes have been reported. In one of these published studies, efficient removal of Fe (II) ions from aqueous solutions were performed by Asthana et al. [32]. For this purpose, they prepared calcium alginate beads entrapped with Ag NPs and tested their adsorption performance toward Fe (II) ions. Langmuir, Freundlich, Temkin, and Harkins–Jura adsorption isotherm models were applied for the characterization of the adsorption process. The pseudo-first-order, pseudo-second-order, and Elovich kinetic models, and the intraparticle diffusion model were also used for the investigation of the adsorption kinetics. The obtained results showed that adsorption of Fe (II) ions by the prepared Ag NPmodified adsorbent is well fitted to the Langmuir isotherm model and the pseudo-second-order kinetic model. The adsorption capacity of the adsorbent was calculated as 236.40 mg g−1. Gari and Kim prepared graphene oxide (GO) decorated with Ag NPs and used as a nanocomposite adsorbent for the removal of Pb (II) ions from aqueous solutions [33]. The obtained results demonstrated that the adsorption process is well described by the Langmuir isotherm model and the pseudo-second-order kinetic model. The adsorption capacity of the prepared nanoadsorbent was found as 312.57 mg g−1. In another study [34], Ghaedi et al. prepared activated carbon modified with Ag NPs and used it for the adsorption of direct yellow 12 dye from aqueous solutions. The maximum adsorption of dye (∼98%) was obtained in 10 min at pH 1.0 and the prepared adsorbent exhibited high adsorption capacity (454.54 mg g−1) toward direct yellow 12. The studies on the adsorption kinetics confirmed that adsorption of direct yellow 12 to activated carbon modified with Ag NPs is well described by the pseudo-second-order kinetic model. Another textile dye methyl orange was efficiently removed by using activated carbon coated with Ag NPs [35]. The adsorption capacity of the prepared adsorbent was found to be 27.48 mg g−1 and the results obtained from the experiments for the adsorption kinetics showed that the adsorption process follows the pseudo-second-order kinetic model. On the other hand, Ag NPs are efficient antibacterial materials due to their high toxicity toward various microorganisms such as bacteria and viruses. Thus, they are commonly used for the removal of microorganisms from contaminated water. The adsorbent materials are generally coated with Ag NPs

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instead of direct use of the Ag NPs in the treatment of water samples due to the agglomeration problems of the nanoparticles. Dankovich and Gray [36] prepared antibacterial filter paper containing Ag NPs and used it for the removal of Escherichia coli and Enterococcus faecalis from contaminated water. The removal process for the bacteria is schematically demonstrated in Fig. 4.4. The obtained results showed that filter paper containing Ag NPs displayed antibacterial features toward E. coli and E. faecalis. The authors reported that the prepared Ag NP-embedded filter paper could be used as an efficient antibacterial material for the treatment of contaminated water. Ceramic filters modified with Ag NPs were also applied for the treatment of water. For example, Kallman et al. successfully applied porous ceramic filters containing Ag NPs for the efficient removal of E. coli [37]. In another study, Vinka et al. reported the use of ceramic filters modified with colloidal Ag NPs for the treatment of E. coli-contaminated water samples [38]. The obtained results showed that the incorporation of Ag NPs increased the removal performance of the ceramic filter and the prepared Ag NP-embedded ceramic filter exhibits efficient removal performance toward E. coli (over 97.8%).

2.3.2  Gold nanoparticles Gold nanoparticles (Au NPs) are efficient metallic nanoadsorbents similar to Ag NPs due to their easy preparation by using reducing agents such as hydroxyl amine and citrate. Au NPs can also be incorporated into the various adsorbents to increase the adsorption efficiency. In a study reported by Roosta et al. [39], methylene blue was successfully removed from the aqueous solutions by using activated carbon containing Au NPs. The prepared adsorbent exhibited high affinity toward the target dye compound and the adsorption capacity was found to be 185.18 mg g−1. Different adsorption isotherm models such as the Freundlich, Langmuir, Dubinin–Radushkevich, and Tempkin models and adsorption kinetics models such as pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models were applied for the investigation of adsorption mechanism and kinetics. The obtained results from these investigations showed that the adsorption of methylene blue to the activated carbon modified with Au NPs is well described by the Langmuir adsorption model and pseudo-second-order kinetic model.

FIGURE 4.4  The Schematic Representation of the Removal of E. coli and E. faecalis From Contaminated Water. Reproduced with permission from T.A. Dankovich, D.G. Gray, Bactericidal paper impregnated with silver nanoparticles for point-ofuse water treatment, Environ. Sci. Technol. 45 (2011) 1992–1998.

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CHAPTER 4  Mechanism of Adsorption on Nanomaterials

The same research group [40] prepared activated carbon modified with Au NPs and used it for the removal of alizarin red S dye from aqueous solutions. The prepared adsorbent containing Au NPs exhibited high adsorption capacity (123.4 mg g−1) toward alizarin red S. It has been reported that ∼15 mg of the adsorbent is sufficient for the efficient removal of dye (over 95%) within 5 min. The obtained results from the adsorption isotherms and kinetics showed that the adsorption process is well demonstrated by the Langmuir adsorption model and pseudo-second-order kinetic model. In another study [41], Solis et al. prepared Au NP-modified silica particles for the removal of inorganic mercury (II) from aqueous solutions. The obtained results showed that adsorption of mercury (II) ions to the Au NP-modified silica nanocomposite adsorbent is well fitted to the pseudo-second-order kinetic model and 96% of the mercury (II) ions was successfully removed. The group of Say prepared gold–silver nanoclusters having dipicolinic acid (DPA) imprinted nanoshell for selective adsorption of Bacillus cereus spores [42]. For this purpose, DPA and methacryloyl imidodiacetic acid–chromium (III) were used as the template and metal-chelate functional monomer, respectively. The obtained results from fluorescence measurements showed that the prepared nanoadsorbent exhibits high affinity and selectivity toward DPA. Langmuir and Scatchard adsorption isotherms were applied to describe the adsorption behavior of the prepared nanoadsorbent toward the target DPA. Kaffinity values were 2.9 × 106 M−1 and 2 × 106 M−1, respectively.

2.3.3  Zinc oxide nanoparticles Metal oxide nanoparticles such as zinc oxide (ZnO) nanoparticles have large surface area and exhibit chemical and thermal stability and antimicrobial properties. Therefore, ZnO nanoparticles are also used as efficient nanoadsorbents. Dehaghi et al. prepared ZnO-modified chitosan particles and used them for the removal of permethrin (a neurotoxin pesticide) from water samples [43]. The obtained results showed that permethrin was successfully removed with 96% efficiency by using a small amount of ZnO-modified chitosan adsorbent (500 mg). In another study, activated silica having ZnO nanoparticles was applied for the removal of arsenic (III) ions from aqueous solutions [44]. The results from adsorption isotherms showed that the adsorption of arsenic (III) ions is well fitted to the BET and Langmuir isotherms compared to the Temkin and Freundlich models. The kinetic data indicated that the adsorption process follows the pseudo-secondorder kinetic model. It was reported that 3.5 g of the prepared adsorbent is sufficient for the 99% removal of arsenic (III) ions from aqueous solutions. The group of Salmani prepared ZnO nanoparticles for the adsorption of cadmium (II) ions from aqueous solutions [45]. The obtained results indicated that the adsorption process is well demonstrated by the Langmuir isotherm model and the pseudo-second-order kinetic model. In a study reported by Sasidharana et al. [46], colloidal ZnO nanoparticles were used for the adsorption of bovine serum albumin (BSA). The results showed that adsorption of BSA to colloidal ZnO nanoadsorbent follows the Freundlich isotherm model and the pseudo-second-order kinetic model.

2.3.4  Magnetic Fe3O4 nanoparticles

MNPs are interesting materials that are widely used in many application areas such as separation [47], catalysis [48], and drug delivery [49]. MNPs can easily be separated from the complex matrices such as environmental and biological samples by applying an external magnetic field. Thus no centrifugation or filtration steps are required. Although MNPs exhibit excellent features, there are some drawbacks such

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as agglomeration of the particles and stability issues. Bare metallic nanoparticles are chemically quite active and easily oxidized, which lead to loss of their magnetic features. Thus these nanoparticles need to be coated with a layer (e.g., carbon, silica, or polymers) to protect their stability. Various magnetic Fe3O4 nanoparticles have been prepared as efficient adsorbents and used for the adsorption of heavy metals and dyes from aqueous samples. For example, Qi et al. prepared magnetic Fe3O4 nanoparticles doped with Ce (III) ions for the removal of antimony (III) ions from aqueous solutions [50]. The prepared magnetic nanoadsorbent exhibit high adsorption behavior toward the target antimony (III) ions and the maximum adsorption capacity was obtained as 224.2 mg g−1. In another study [51], reactive blue 19 dye was successfully removed from wastewater using magnetic Fe3O4 nanoparticles modified with l-arginine. The maximum dye removal (96.34%) was achieved at pH 3.0. The obtained data showed that adsorption of reactive blue 19 dye to the magnetic nanoadsorbent follows the pseudo-second-order kinetic model and the Freundlich isotherm model. The combination of magnetic Fe3O4 nanoparticles and molecularly imprinted polymers (MIPs) is also popular for the development of magnetic nanocomposite materials. In a study conducted by Yang et al., core–shell magnetic MIPs were prepared for selective removal of indole from fuel oil [52]. In their research, magnetic Fe3O4 nanoparticles were synthesized by using coprecipitation technique. Then, the surface of the prepared nanoparticles were coated with SiO2 using 3-(trimethosysilyl) propyl methacrylate. In the final step, methacrylic acid as the functional monomer and ethylene glycol dimethacrylate as the cross-linker were used for the preparation of selective MIP toward indole on the surface of the modified MNPs. The results obtained from rebinding studies showed that the prepared magnetic MIP composite shows high affinity and selectivity toward indole. The binding capacity of the composite for indole was found to be as 50.25 mg g−1. Zhang et al. prepared MIP-based magnetic nanocomposites for Pb2+ extraction from environmental samples [53]. 3-(2-Aminoethylamino)propyltrimethoxysilane as the functional monomer, tetraethylorthosilicate as the cross-linker, and template ion Pb2+ were used for the preparation of nanocomposites toward Pb2+ ions. Different factors that affect the selective extraction of the target ion such as pH and sample volume were studied. The results obtained from solid phase extraction (SPE) studies for Pb2+ in the presence of other potential interfering ions such as Zn2+, Cd2+, and Hg2+ in environmental samples showed that the prepared MIP-based magnetic nanocomposites display high selectivity toward Pb2+ ions. The adsorption capacity of the nanocomposites for Pb2+ ions was determined as 19.61 mg g−1. Table 4.2 shows the recent reported examples of nanoparticle-based adsorption systems.

2.4  ADSORPTION OF MECHANISM ON CARBON NANOMATERIALS Carbon nanomaterials such as activated carbon, CNTs, and GO have been widely applied for the adsorption processes since they exhibit high stability, low density, and large surface area that enhance adsorption capacity. In addition, carbon nanomaterials can easily be modified with different functional groups. These superior features of the carbon nanomaterials make them excellent nanoadsorbents for the efficient removal of various contaminants from environmental samples.

2.4.1  Activated carbon Activated carbon as the conventional adsorbent were widely applied for the adsorption processes. In one of these applications, Tang et al. prepared activated carbon-alginate composite beads for the removal of bisphenol AF [89]. The obtained results from the kinetic experiments showed that adsorption

Adsorbent Composition

Adsorbate

Adsorption Capacity (mg g−1)

Sample

Silver Nanoparticles [54]

Activated carbon modified with silver nanoparticles

Dibenzothiophene

29.8

n-Heptane

[55]

Activated carbon modified with silver nanoparticles

Formaldehyde

76

Air

[56]

Chitosan embedded with silver nanoparticles

Atrazine

0.5

Aqueous solution

[57]

Alumina modified with silver nanoparticles

Mercury (II) ions

800

Tap water

[58]

Yeast cells containing silver nanoparticles

Arsenic (V) ions

0.975

Aqueous solution

[59]

Activated carbon modified with silver nanoparticles

Methyl orange dye

27.5

Aqueous solution

[60]

Activated carbon modified with silver nanoparticles

Acid yellow 199 dye

30

Aqueous solution

[61]

Activated carbon modified with silver nanoparticles

Sudan red dye

90.9

Aqueous solution

[62]

k-Carrageenan beads modified with silver nanoparticles

Cationic crystal violet dye

243

Aqueous solution

[63]

Activated carbon modified with gold nanoparticles

Acid red 299 dye

20

Aqueous solution

[64]

Activated carbon modified with gold nanoparticles

Malachite green dye

172.41

Aqueous solution

[65]

Activated carbon modified with gold nanoparticles

Methyl orange dye

161

Aqueous solution

[66]

Activated carbon modified with gold nanoparticles

Congo red dye

71.43

Aqueous solution

[67]

Activated carbon modified with gold nanoparticles

Reactive orange 12 dye

714.3

Aqueous solution

[68]

Activated carbon modified with gold nanoparticles

Albumin

109.54

Aqueous solution

Gold Nanoparticles

CHAPTER 4  Mechanism of Adsorption on Nanomaterials

Reference

100

Table 4.2  Recent Reported Examples of Nanoparticle-Based Adsorption Systems

Reference

Adsorbent Composition

Adsorbate

Adsorption Capacity (mg g−1)

Sample

[69]

Fe3O4 nanoparticles modified with gold nanoparticles and 2-Mercapto-5-benzimidazolesulfonic acid

Lysozyme

360

Egg white

[70]

Layered double hydroxide modified with gold nanoparticles

Hemoglobin

42.5

Aqueous solution

Zinc Oxide Nanoparticles Urea-formaldehyde film modified with ZnO nanoparticles

Copper (II) ions

10

Aqueous solution

[72]

Zinc oxide nanoparticles

Copper (II) ions Cadmium (II) ions Lead (II) ions Nickel (II) ions

137.5 119.1 112.7 48.6

Aqueous solution

[73]

Zinc oxide nanoparticles

Zinc (II) ions Cadmium (II) ions Mercury (II) ions

357 387 714

Aqueous solution

[74]

Zinc oxide nanoparticles

Victoria blue B dye

163

Aqueous solution

[75]

Zinc oxide nanoparticles

Basic red 12 dye Acid orange 7 dye Acid blue 1 dye

15.64 6.78 6.38

Aqueous solution

[76]

Zinc oxide nanoparticles

Malachite green dye Acid fuchsin dye Congo red dye

2963 3307 1554

Aqueous solution

[77]

Activated carbon modified with zinc oxide nanoparticles

Brilliant green dye

142.9

Aqueous solution

[78]

Activated carbon modified with zinc oxide nanoparticles

Uric acid

345.8

Aqueous solution

Magnetic Fe3O4 Nanoparticles [79]

Magnetic Fe3O4 nanoparticles modified with tannic acid

Lead (II) ions Mercury (II) ions

1115.3 279.4

Aqueous solution

[80]

Magnetic Fe3O4 nanoparticles modified with thiol groups

Mercury (II) ions

344.82

Aqueous solution

101

( Continued )

2 Adsorption mechanism

[71]

Adsorbent Composition

Adsorbate

Adsorption Capacity (mg g−1)

Sample

[81]

Magnetic Fe3O4 nanoparticles coated with poly(glycidylmethacrylate-maleic anhydride) polymer

Lead (II) ions Cadmium (II) ions

53.33 48.53

Aqueous solution

[82]

Magnetic Fe3O4/SiO2 nanoparticles modified with lanthanum oxide

Phosphate

27.8

Aqueous solution

[83]

Activated carbon modified with magnetic Fe3O4 nanoparticles

Aniline

90.91

Aqueous solution

[84]

Magnetic Fe3O4 nanoparticles modified with phenyl groups

Methylparaben Ethylparaben Propylparaben

0.60 3.28 3.54

Aqueous solution

[85]

Magnetic Fe3O4/MgO nanoparticles

Amaranth dye

37.98

Aqueous solution

[86]

Magnetic Fe3O4 nanoparticles coated with copolymer of catechol and polyethylenimine

Methyl blue dye Orange G dye Amaranth dye

344.8 192.3 146.2

Aqueous solution

[87]

Magnetic Fe3O4 nanoparticles modified with sodium dodecyl sulfate

Safranin O dye

769.23

Aqueous solution

[88]

Magnetic Fe3O4 nanoparticles coated with carbon

Methylene blue dye

141.3

Aqueous solution

CHAPTER 4  Mechanism of Adsorption on Nanomaterials

Reference

102

Table 4.2  Recent Reported Examples of Nanoparticle-Based Adsorption Systems (cont.)

2 Adsorption mechanism

103

of bisphenol AF to activated carbon-based composite adsorbent is well fitted to the pseudo-second-order model. The maximum adsorption of the prepared activated carbon-alginate composite beads was found as 284.6 mg g−1. In another reported study [90], l-phenylalanine was successfully removed from aqueous solutions by using activated carbons. For this purpose, two different activated carbons were prepared. One of them was activated by NaOH and the other was activated by ZnCI2. Both adsorbents exhibited high adsorption capacity (183.3 and 133.3 mg g−1, respectively). The data from the thermodynamic studies and adsorption isotherms showed that the adsorption process was exothermic and well demonstrated by the Langmuir model. The group of Saleh reported the use of waste tire-based activated carbon having polyethyleneimine for the Hg (II) adsorption from aqueous samples [91]. The prepared adsorbent exhibited good adsorption behavior toward the target Hg (II) ions. The results from the adsorption thermodynamic and kinetic experiments confirmed that the adsorption of Hg (II) ions to the activated carbon-based adsorbent is an exothermic process and well demonstrated by the pseudo-second-order model. The maximum adsorption capacity was determined as 16.39 mg g−1. The removal of carbamazepine, an antiepileptic pharmaceutical compound, from wastewater sampled was successfully achieved by using magnetic-activated carbon including Fe3O4 [92]. The obtained kinetic data indicated that the adsorption process is exothermic and spontaneous. The prepared magnetic nanocomposite adsorbent exhibited high adsorption capacity (182.9 mg g−1) toward target carbamazepine.

2.4.2  Carbon nanotubes In 1991, Japanese physicist Sumio Iijima discovered CNTs [93]. Since then, many scientists have been working on the different applications of CNTs. CNTs are composed of graphene sheets that are rolled into a cylindrical shape and categorized into two groups, which are single-walled CNTs (SWCNTs) and multiwalled CNTs (MWCNTs). SWCNTs are composed of one graphene layer while MWCNTs have two or more layers (Fig. 4.5). CNTs have been widely applied as efficient nanoadsorbents for the removal of various contaminants (e.g., metal ions, dyes, phenolic compounds, and drug substances) from aqueous solutions. In a study, Yang et al. [95] prepared MWCNTs for the adsorption of Ni (II) ions in aqueous solutions. The adsorption kinetic studies showed that the Ni (II) adsorption to the MWCNTs is well demonstrated by the pseudo-second-order model. Lu and Chiu [96] compared the adsorption behaviors of the activated carbon, SWCNTs, and MWCNTs toward Zn (II) ions in water samples. The adsorption capacities were found to be 13.04, 43.66, and 32.68 mg g−1, respectively. The wall of the CNTs exhibit hydrophobic feature due to the π electron density. Thus, hydrophobic interactions could occur between the dye molecules and the wall of the CNTs. Considering this, MWCNTs were also applied for the removal of dye compounds such as direct blue 86 and direct dye 224 dyes [97]. The maximum adsorption capacity values of the prepared MWCNTs toward direct blue 86 and direct dye 224 were 56.2 and 61.3 mg g−1, respectively. The obtained results from the isotherm models and thermodynamic studies indicated that the Freundlich model well demonstrates the adsorption process and the adsorption type is physical adsorption. In another study, Sadegh et al. proposed MWCNTs modified with carboxylate groups for the efficient removal of textile dye malachite green from aqueous solutions [98]. The results showed that the

104

CHAPTER 4  Mechanism of Adsorption on Nanomaterials

FIGURE 4.5  The Schematic Representation of SWCNT and MWCNT. Reproduced with permission from J.M. Schnorr, T.M. Swager, Emerging applications of carbon nanotubes, Chem. Mater. 23 (2011) 646–657.

­ echanism of the adsorption process follows the Langmuir isotherm model and the adsorption capacity of m the prepared MWCNTs having carboxylate groups toward malachite green was obtained as 49.45 mg g−1. Magnetic CNTs are also a great choice for the adsorption processes due to the easy separation of the magnetic adsorbent from the sample solutions. Magnetic MWCNTs were successfully applied for the adsorption of janus green, crystal violet, methylene blue, and thionine dye [99]. The obtained adsorption capacities of the prepared magnetic adsorbent toward target dyes were found to be 250, 227.7, 48.1, and 36.4 mg g−1, respectively. The group of Yan prepared magnetic MWCNTs grafted with guar gum for the removal of dye compounds methylene blue and natural red [100]. The obtained results from the kinetic studies showed that the adsorption of dyes is well described by the pseudo-second-order model. The maximum capacity of the prepared magnetic nanoadsorbent was found to be 89.85 and 61.92 mg g−1 for natural red and methylene blue, respectively. In another study carried out by Zhang et al. [101], magnetic molecularly imprinted polymer-based MWCNT composite material was developed for the extraction of bisphenol A (BPA) from water samples. The obtained results from rebinding experiments for BPA in batch mode showed that the prepared magnetic MIP-based MWCNT composite shows high affinity and selectivity for BPA. The maximum binding capacity of the composite was found to be 49.26 µmol g−1.

2.4.3  Graphene oxide GO is another carbon-based material that displays excellent features such as large surface area, high stability, and layered structure. GO is prepared by the oxidation of graphene. Graphene shows ­hydrophobic property that leads to agglomeration problems in aqueous solutions. The oxidation of

2 Adsorption mechanism

105

graphene to GO enhances the dispersion behavior due to the polar groups such as hydroxyl, carboxyl, and epoxide. GO and GO-based composites have already been used as efficient nanoadsorbents for the removal of metal ions [102], dye compounds [103], and pharmaceutical compounds [104] from environmental samples. For example, Raghubanshi et al. prepared GO for the efficient removal of Pb (II) ions from aqueous solutions [105]. The maximum adsorption capacity of the prepared GO adsorbent was obtained as 120 mg g−1 and the adsorption kinetic was well described by the pseudosecond-order model. In a study reported by Jiang et al., removal of 17β-estradiol from aqueous solutions was successfully carried out by using GO nanosheets [106]. The expected interactions between GO nanosheets and 17β-estradiol is schematically depicted in Fig. 4.6. The obtained results showed that the adsorption of 17β-estradiol to GO nanosheets is well demonstrated by the Langmuir adsorption model and the thermodynamic studies confirmed that the adsorption process is spontaneous. The maximum adsorption capacity of the prepared nanoadsorbent toward 17β-estradiol was found to be 149.9 mg g−1, which is the highest value compared to other reported studies. Another interesting study was published by Wu et al. [107]. In their study, a graphene-based nanoadsorbent was developed for the efficient removal of textile dye Congo red from aqueous solutions. For this purpose, p-phenylenediamine was incorporated into the nanolayers of graphene as shown in Fig. 4.7. The maximum dye removal was achieved at pH 3.0 and the adsorption capacity of the prepared nanoadsorbent was obtained as 892.8 mg g−1. The adsorption of Congo red dye to the prepared graphene-based nanoadsorbent was well demonstrated by the Langmuir model and the results obtained from the thermodynamic studies showed that the adsorption process is endothermic and spontaneous. In another study, zeolite-GO nanocomposite adsorbent was developed for the adsorption of Rhodamine B dye [108]. The maximum adsorption capacity of the nanocomposite was obtained as 64.47 mg g−1 and the adsorption process followed the Langmuir and Freundlich isotherm models. Magnetic GO nanocomposites were also successfully applied for the adsorption of dye compounds. Magnetic Fe3O4 nanoparticle-sulfonated GO nanocomposite adsorbent was prepared by

FIGURE 4.6  The Expected Interactions Between Graphene Oxide Nanosheets and 17β-Estradiol. Reproduced with permission from L.-H. Jiang, Y.-G. Liu, G.-M. Zeng, F.-Y. Xiao, X.-J.Hu, X. Huc, H. Wang, T.-T. Li, L. Zhou, X.-F. Tan, Removal of 17b-estradiol by few-layered graphene oxide nanosheets from aqueous solutions: external influence and adsorption mechanism, Chem. Eng. J. 284 (2016) 93–102.

106

CHAPTER 4  Mechanism of Adsorption on Nanomaterials

FIGURE 4.7  The Schematic Representation of the Prepared Graphene-Oxide Modified with p-phenylenediamine. Reproduced with permission from Z.-L. Wu, F. Liu, C.-K. Li, X.-Q. Chen, J.-G. Yu, A sandwich-structured graphene-based composite: preparation, characterization, and its adsorption behaviors for Congo red, Colloids Surf. A Physicochem. Eng. Asp. 509 (2016) 65–72.

Zhang et al. and was used for the removal of malachite green from aqueous solutions [109]. The results showed that the prepared GO-based magnetic nanoadsorbent exhibits high adsorption capacity toward the target dye compound. It has been reported that over 98% of malachite green could efficiently be removed by using a very small amount of the magnetic GO nanocomposite (48 mg) within a short time (20 min). Another research group [110] prepared magnetic GO nanocomposites for the removal of eriochrome black T and malachite green from wastewater. The prepared magnetic nanoadsorbent exhibited high adsorption behavior toward eriochrome black T and malachite green with a high adsorption capacity of 160.8 and 179.15 mg g−1, respectively. The results from the kinetic experiments indicated that the adsorption process follows the pseudo-second-order model. The antibacterial activities of the prepared magnetic GO nanocomposites were also tested on various bacteria such as Bacillus subtilis, Staphylococcus aureus, Salmonella typhimurium and Pseudomonas aeruginosa. The obtained results showed that the prepared magnetic GO nanocomposites could also be used as a promising antibacterial material for the treatment of contaminated water. Table 4.3 gives the reported examples of carbon-based adsorption systems.

3  CONCLUSIONS AND PERSPECTIVE The growing number of published research in which nanoadsorbents have been applied for different purposes shows that these unique materials are promising adsorbents for the adsorption of many target compounds such as heavy metals, textile dyes, pharmaceutical compounds, and organic and inorganic compounds. The demonstrated examples in this chapter highlight the recent progresses in adsorption processes using nanostructured materials over the past years. The designed novel adsorbents in nanoscale as promising materials provide a new approach for efficient adsorption processes in complex matrices such as environmental and biological samples. In this chapter, we have only focused on the recent reported examples in which nanomaterials were used for the adsorption processes. It is worth noting that these materials, which have superior features such as such as large surface area, small size, high stability, high reactivity, and versatile chemistry for the further functionalization, have recently been applied in many fields (e.g., catalysis, drug delivery, and biosensor systems).

Table 4.3  Recent Reported Examples of Carbon-Based Adsorption Systems Reference

Adsorbent Composition

Adsorbate

Adsorption Capacity (mg g−1)

Sample

[111]

Coal-based activated carbon

Cadmium (II) ions Lead (II) ions

27.3 20.3

Aqueous solution

[112]

Mango kernel-based activated carbon

Chromium (VI) ions

7.8

Aqueous solution

[113]

Palm oil mill effluent-based activated carbon

Lead (II) ions Zinc (II) ions

94.34 68.49

Aqueous solution

[114]

Activated carbon-gelatin composite

Rhodamine B dye

256.41

Aqueous solution

[115]

Activated carbon prepared from pomegranate peel

Direct blue 106 dye

58.14

Aqueous solution

[116]

Activated carbon prepared from coffee husk

Remazol brilliant orange 3R dye

66.76

Aqueous solution

[117]

Flamboyant pods-based activated carbon

Acid yellow 6 dye Acid yellow 23 dye Acid red 18 dye

673.68 643.04 551.79

Aqueous solution

[118]

Biomass-based activated carbon

Ciprofloxacin

244

Aqueous solution

[119]

Activated carbon prepared from walnut shell

Cephalexin

211.78

Aqueous solution

[120]

Guava seed-based activated carbon

2,4-Dichloro phenol

20.9

Aqueous solution

[121]

5,7-Dinitro-8-quinolinol-modified MWCNT

Copper (II) ions Zinc (II) ions Iron (II) ions Lead (II) ions

333.3 500 200 333.3

Aqueous solution

[122]

MWCNTs

Chromium (VI) ions

20.56

Aqueous solution

[123]

MWCNTs

Nickel (II) ions

49.26

Aqueous solution

[124]

MWCNTs

Lead (II) ions

91

Aqueous solution

[125]

MWCNTs

Eriochrome Cyanine R

95.2

Aqueous solution

[126]

Magnetic Fe3C-MWCNTs

Acid red 88 dye

99.8

Aqueous solution

Activated Carbon

107

( Continued )

3 Conclusions and perspective

Carbon Nanotubes

108

Table 4.3  Recent Reported Examples of Carbon-Based Adsorption Systems (cont.) Adsorbent Composition

Adsorbate

Adsorption Capacity (mg g−1)

Sample

[127]

MWCNTs

Crystal violet dye

90.52

Aqueous solution

[128]

Chitosan-MWCNT nanocomposite

Direct blue 71 dye

29.32

Aqueous solution

[129]

MWCNTs

Alizarin red S dye Morin dye

161.29 26.24

Aqueous solution

[130]

SWCNTs

Reactive blue 29 dye

496

Aqueous solution

[131]

WO3-MWCNTs decorated with Pt nanoparticles

warfarin

141.2

Aqueous solution

[132]

CdS-MWCNT nanocomposite

Cefradine Cefotaxime Cefazolin

40.52 37.71 34.5

Aqueous solution

[133]

8-Hydroxyquinoline-modified graphene oxide

Chromium (VI) ions

11.9

Aqueous solution

[134]

2-Pyridinecarboxaldehyde thiosemicarbazonemodified graphene oxide

Mercury (II) ions

555

Aqueous solution

[135]

Dithiocarbamate-modified graphene oxide

Lead (II) ions

158.2

Aqueous solution

[136]

Polyamide-modified graphene oxide

Antimony (III) ions

21.28

Aqueous solution

[137]

Oxidized graphene oxide

Cesium (I)

40

Aqueous solution

[138]

Tannic acid-modified graphene oxide

Rhodamine B dye

201

Aqueous solution

[139]

Graphene oxide modified with polysaccharides

Metylene blue dye

789

Aqueous solution

[140]

Oxidized graphene oxide

Acid orange 8 dye Direct red 23 dye

29.1 15.3

Aqueous solution

[141]

Double oxidized graphene oxide

Acetaminophen

704

Contaminated water

[142]

Magnetic graphene oxide modified with nitrilotriacetic acid

Ciprofloxacin

230.57

Aqueous solution

[143]

Reduced graphene oxide

Bisphenol A

94.06

Aqueous solution

[144]

Titanium nanotube- graphene oxide composite modified with polyacrylic acid

Enrofloxacin

13.4

Aqueous solution

Graphene Oxide

CHAPTER 4  Mechanism of Adsorption on Nanomaterials

Reference

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