This study aims to produce amidoxime-modified poly(acrylonitrile-co-acrylic acid) using an optimized method and to investigate the performance of amidoxime-modified poly(acrylonitrile-co-acrylic acid) on the adsorption of boron ions in batch operations. Batch adsorption was conducted at the physiochemical parameters of pH, adsorbent dosage, and initial boron concentration. The isotherms and kinetics of adsorption data were studied at various initial boron concentrations. The renewed synthesis process gave a production yield of 77%, and the conversion of nitrile group to amidoxime was 78%. The adsorption reached its optimum point at pH = 8, adsorbent dosage = 4 g·L−1, and initial adsorbent concentration at 40 ppm. The best model fits for isotherm adsorption was the Sips model with heterogeneity factor (n) = 0.7611. In the kinetic study, the adsorption data fitted best with pseudo-second-order model. The synthesized polymeric adsorbent could be recycled with little decline in its boron entrapment capacities. Hence, amidoxime-modified poly(acrylonitrile-co-acrylic acid) exhibited high adsorption capacity and could be potentially explored as an alternative to commercial resin in the removal of boron from wastewater.

  • Poly(AN-co-AA) was synthesized via redox polymerization and functionalized with amidoxime.

  • AO-modified poly(AN-co-AA) adsorbent possessed multi-functional groups.

  • Boron adsorption unto AO-modified poly(AN-co-AA) was high.

  • Equilibrium and kinetic models were used to delineate adsorbent-adsorbate interactions.

  • The adsorption-desorption study revealed the stability and reusability of the functionalized polymer.

Boron is typically released into the environment from wastewater sources, and it can be detected mainly in the form of borate salts or boric acid. Boron originates from a wide range of activities; thus, it can be in the form of chemical products casted in the agriculture sector (Halim et al. 2013; Theiss et al. 2013; Nasef et al. 2014). Boron also exists in the form of boron carbide which is frequently utilized in nuclear applications as neutron radiation absorbent (Domnich et al. 2011). Besides, the isotope boron-10 is mainly used in the nuclear industry to prevent explosion by controlling the nuclear reaction rate (Wang et al. 2014). This results in a heavier dispatch of boron as nuclear residues along with the progress of nuclear industry. Boron has negative effects on human and animal reproductive systems, and it causes impairments on the nerves. In addition, long term exposure to boron has a negative effect on cardiovascular and coronary systems (Cengeloglu et al. 2008; Wolska & Bryjak 2013; Guan et al. 2016). As recommended by the World Health Organization (WHO), the concentration of boron in the drinking water should be kept below 0.3 mg/L (World Health Organisation 2009). Meanwhile, the legislation condition stated by the Department of Environment (DOE) Malaysia is to reduce boron concentration to lower than 1 and 4 mg/L for Effluent Discharge Standards A and B, respectively (Department of Environment 2010).

Several studies have focused on ways to overcome the problem of boron released into the environment. The use of multi-pass reverse osmosis membrane (RO) with pH modification (Tu et al. 2011; Teychene et al. 2013) and the application of ion exchange using boron selective resins (BSRs) (Guan et al. 2016) have been considered as effective methods for the removal of boron. Besides, a hybrid process, known as an adsorption membrane filtration (AMF), has received attention as an emerging technology for boron removal due to its high efficiency and low operating costs (Blahušiak et al. 2015). In addition to these methods, adsorption using synthesized polymeric material is also a good selection for boron treatment (Harada et al. 2011; Li et al. 2011; Nasef et al. 2014).

Amidoxime (AO) groups have a high tendency to form strong complexes with a wide range of heavy metal ions such as lanthanides, actinides, transition metals, and poor metals (Alakhras et al. 2005). However, amidoxime adsorption rates are frequently restricted due to the hydrophobic characteristic of its supporting matrix (Ji et al. 2016). To improve hydrophilicity, myriad of chelating polymers have been manufactured through the copolymerization of acrylonitrile with rather hydrophilic monomers such as methyl acrylate (Liu et al. 2010) and acrylic acid (Xing et al. 2013; Oyola & Dai 2016). PAN is selected due to the high mechanical strength and chemical properties of poly(acrylonitrile) in having bundles of nitrile group (C ≡ N), which in turn has high conversion ability into new functional groups (Chen et al. 2019). Meanwhile, acrylic acid (AA) was selected to copolymerized with AN to add carboxyl group (COOH) into the PAN chain. The incorporation of carboxyl group minimises the nitrile-nitrile interactions and hydrophobicity, and thereby yields antifouling and pervaporation characters (Mishra et al. 2011). A lot of efforts have been put on amidoxime chelating adsorbent to remove heavy toxic elements and/or selective-recovering of precious elements from different sources such as the adsorption of uranium from sea water (Gunathilake et al. 2015), cadmium and lead (Zahri et al. 2015) together with copper, manganese, and nickel from aqueous solution (El-Bahy & El-Bahy 2016). Thus, it is proven that AO-AN-AA has never been used to capture boron, a metalloid which exhibits the properties of both metals and non-metals.

As adsorbent, the AO-modified poly(AN-co-AA) has a wide range of physicochemical properties that enable it to be particularly attractive as a reactive and separation medium for wastewater treatment and water purification (Choi et al. 2003; Zahri et al. 2015). These adsorbents have a relatively large surface area to mass ratio coupled with dual functional groups (amidoxime and carboxylic groups) which provide the polymer with the ability to selectively adsorb chemical and biological toxicants on its surface. It was reported that AO-modified polyacrylonitrile fiber has better adsorption efficiency than ordinary activated carbon (Huang et al. 2013).

The copolymerization of acrylonitrile and acrylic acid is illustrated in Figure 1(a), and the functionalization of polymer into AO-modified poly(AN-co-AA) is shown in Figure 1(b). The reactivity ratios of AN and AA were determined by the Kelen-Tudos method and reported by Bajaj et al. (1993) as follows: r1(AN) = 0.34 and r2(AA) = 3.25.

Figure 1

(a) Copolymerization of acrylonitrile and acrylic acid to form poly(AN-co-AA); (b) functionalization of poly(AN-co-AA) into AO-modified poly(AN-co-AA) by reaction with hydroxylamine hydrochloride.

Figure 1

(a) Copolymerization of acrylonitrile and acrylic acid to form poly(AN-co-AA); (b) functionalization of poly(AN-co-AA) into AO-modified poly(AN-co-AA) by reaction with hydroxylamine hydrochloride.

Close modal

The values of reactivity ratios for AN (r1) is less than unity in above system; which indicates that the AN growing radical prefers to combine with the comonomer (AA) unit. Meanwhile, the reactivity ratio of AA (r2) is greater than unity; which suggests that the AA growing radical prefers to bind with its own monomer unit. Considering the r1r2 value (1.1), the AN/AA copolymer system tends to obtain large blocks of AA unit and broken by individual AN monomer unit. Hence, the poly(AN/AA) system prefers to form block copolymer (Bajaj et al., 1993).

The present study encompasses the development of functionalized polymer-based adsorbent for boron-containing effluent treatment. The conditions for boron separation are optimized using one variable at time. Isotherm and kinetic analyses of adsorption data are also delineated.

Polymer synthesis

Redox polymerization of AN and AA was previously reported by several researchers (Huang et al. 2013; Zahri et al. 2015; Ji et al. 2016). In this research, the redox polymerization of poly(AN-co-AA) was performed under N2 gas inside a three-necked round-bottom flask, fitted with water condenser. The reaction was carried out at varied temperatures to determine the temperature that could yield the optimum weight of polymer. In 200 mL deionized water, 18.6 mL of AN and 1.4 mL of AA were added, followed by 2.09 g of sodium bisulphate (SBS) and 2.16 g of potassium persulphate (KPS) as initiators. The chemicals reacted at different temperatures, i.e. 40 °C, 48 °C, 55 °C, and 60 °C. The polymerization was allowed to proceed for 2 h and mechanically stirred at 200 rpm. The polymer produced was precipitated in methanol for 1 h, filtered, and washed several times with deionized water and methanol. Finally, the polymer was dried in a vacuum oven at 45 °C until a constant weight was obtained. The polymer yield, percentage was given by Equation (1) (Zahri et al. 2015):
formula
(1)
where is the weight of poly(AN-co-AA) after drying while is the total weight of monomers in feed.
There are several methods employed to functionalize polymer with amidoxime groups (Saeed et al. 2008; Liu et al. 2010; Horzum et al. 2012). In the present work, the functionalization method is refined as follows. 11.20 g of hydroxylamine hydrochloride (HH) was dissolved in 320 mL of deionized water. The pH of the solution was adjusted to pH 7 by sodium bicarbonate. The mixture was heated at 70 °C and stirred at 80 rpm for 60 min. Then, 1 g of poly(AN-co-AA) was added and allowed to undergo amidoximation for 1 h. Finally, the modified polymer was filtered, washed, and dried in a vacuum oven at 60 °C for 24 h. The conversion (,%) of poly(AN-co-AA) nitrile group into amidoxime was calculated using Equation (2) (Saeed et al. 2008):
formula
(2)
where is the dry weight of AO-modified poly(AN-co-AA); is the total molecular weight of AN (53 g·mol−1) and AA (72 g·mol−1); and is the molecular weight of amidoxime group (33 g·mol−1).

Instrumentation

Fourier-transform infrared spectroscopy (FTIR) was recorded on Perkin Elmer 1750X spectrometer (UK) using potassium bromide (KBr) pellet that operated within the resolution range of 4,000–400 cm−1 under atmospheric circumstances with a resolution of 1 cm−1. In Elemental Microanalysis (CHNS analysis), the contents of the element (carbon, nitrogen, hydrogen and sulphur) were calculated using Cahn C-31 Microbalance (USA). The combustion of sample of was carried out using LECO CHNS-932 spectrometer (South Africa). Scanning electron microscope (SEM) micrographs were acquired using a Hitachi S-3400N instrument (Japan). Samples were coated in Au/Pd film prior to analysis. The spherical diameter of adsorbent was measured by taking the average diameter of 30 different beads from the micrograph using ImageJTM (USA) – an image processing program. The thermogravimetric analysis (TGA) was evaluated using Perkin Elmer Simultaneous Thermal Analyzer (STA 6000) instrument (UK) from 50 °C to 1,000 °C at 10 °C·min−1 under nitrogen atmosphere. Analysis by using GPC was carried out to determine the molecular weight of polymer. The sample was prepared by diluting 0.01 g of polymer in 10 mL of dimethylformamide (DMF). The solution was sonicated for 1 h to facilitate the dilution of sample in DMF. The instrument that was used for molecular weight analysis was Waters 2414 Gel Permeation Chromatography (GPC) Waters system (USA). The remaining boron content in the aqueous solution after adsorption was assessed using Inductively Coupled Plasma (ICP) – Optical Emission Spectrometer (OES) through VARIAN VISTA-PRO (USA). The specific surface area of poly(AN-co-AA) before and after the adsorption process was determined by applying the Brunauer-Emmett-Teller (BET) method according to the N2 adsorption-desorption isotherm data, which was retrieved from Gemini 2390 VII at 333 K.

Adsorption experiment

Stock solution of 100 ppm boron ions (B3+) was prepared from boric acid (H3BO3) through dilution of 0.5719 g boric acid in 1,000 mL deionized water. The effects of physiochemical parameters which comprised the effects of pH, adsorbent dosage, and initial boron concentration were investigated. To investigate the effects of pH, 50 mL of 50 ppm boron solution and 2 g·L−1 of adsorbent were added in a conical flask. The pH was adjusted by adding diluted hydrochloric acid (0.1 M) or sodium hydroxide (0.1 M). The adsorption was carried out by shaking the mixture using Wise Shake SHO-2D (UK), a digital orbital shaker. The rotation speed was set at 150 rpm, and the adsorption period was carried out for 90 min. All experiments were conducted at room temperature.

To investigate the effects of adsorbent dosage, 50 mL of 50 ppm boron solution at default pH (pH = 7.4) was added into a conical flask. Different dosages of adsorbent (0.5 g·L−1 to 4 g·L−1) were then applied to the solution. The effect of initial boron concentration was examined by studying the concentration ranging between 10 and 100 ppm. The change in boron concentration after the adsorption process was determined using ICP-OES instrument.

The adsorption capacity was calculated by utilizing Equation (3) (El-Bahy & El-Bahy 2016):
formula
(3)
where (mg·g−1) is the adsorption capacity at equilibrium; and (mg·L−1) are the initial and final concentrations of boron ions in solution; (L) is the volume of boron solution; and (g) is the amount of adsorbent.

Isotherm and kinetic study

2 g·L−1 of resin and 50 mL of various concentrations of boron ion solution were continuously shaken at default pH (pH = 7.4). The experimental adsorption data were studied with several isotherm models which included Langmuir, Freundlich, and Sips Isotherm. The isotherm parameters and maximum adsorption capacity of each model were computed and tabulated.

The kinetics studies were conducted to describe the batch adsorption dynamic behaviour of boron uptake. The samples of the aqueous solution were withdrawn and analyzed at the interval of every 2 min for the first 15 min and later at every 10 min until 90 min of reaction time. The four mathematical models used were pseudo-first-order, pseudo-second-order, Elovich, and intra particle diffusion. The model performance was justified using statistical parameters, the coefficient of determination (R2) and sum of squares error (). was calculated using Equation (4) (Riahi et al. 2017):
formula
(4)
where is the calculated equilibrium adsorption capacity while is the experimental equilibrium adsorption capacity at different initial boron concentration.

Reusability and desorption study

The B3+-AO-modified poly(AN-co-AA) (originally from 40 ppm boron solution, pH 7.2 and 4 g·L−1 adsorbent during adsorption) was dried and treated with HNO3 for desorption. The concentration of HNO3 varied among 0.2 mol·L−1, 0.5 mol·L−1, 1.0 mol·L−1 and 1.5 mol·L−1. The mixture of B3+-AO-modified poly(AN-co-AA) and HNO3 was shaken continuously for 1 h at 150 rpm. The process was repeated using different concentration of HCl and H2SO4 solutions. The desorption efficiency () was calculated after the ICP test with Equation (5):
formula
(5)

Copolymerization of acrylonitrile and acrylic acid

The polymerization of poly(AN-co-AA) via the redox method utilized lower energy and less consumption of organic solvent compared to other methods such as radical copolymerization (Sabzroo et al. 2018) and co-graft polymerization (Liu et al. 2014). In this study, the reaction medium used was deionized water. In addition, the only energy expense was heating at moderately high temperature (55 °C) and stirring agitation.

As reported in a previous study on polymerization of poly(AN-co-AA) (Zahri et al. 2015; Rapeia et al. 2015), the polymerization process between acrylonitrile and acrylic acid was conducted at 40 °C under continuous purging of nitrogen. In the present study, the polymerization method was improved by yielding higher percentage of poly(AN-co-AA), which was 77% at 55 °C. This reflected 13% and 5% increments, compared to 64% and 72% of percentage yield produced in (Zahri et al. 2015) and (Rapeia et al. 2015), respectively. As shown in Table 1, the yield percentages increased with the increase in temperature. However, further increase in temperature beyond 55 °C did not contribute to higher yield percentage.

Table 1

Yield percentage of poly(AN-co-AA) at different operating temperatures

Temperature (°C)Yield (%)
40 °C 72.0 
48 °C 74.7 
55 °C 77.0 
60 °C 77.0 
Temperature (°C)Yield (%)
40 °C 72.0 
48 °C 74.7 
55 °C 77.0 
60 °C 77.0 

Amidoximation of poly(AN-co-AA)

As shown in Figures S1(a) and (b), the color of the copolymer changed from white to light brown, and the fine powder structure became hard and brittle after chemical modification with amidoxime. It was reported that amidoxime-modified PAN nanofibers demonstrated better mechanical strength and toughness compared to the unmodified PAN nanofibers (Huang et al. 2013).

The molecular weight of poly(AN-co-AA), AO-modified poly(AN-co-AA) and B3+-AO-modified poly(AN-co-AA) were shown in Table 2.

Table 2

Molecular weight results from GPC

Name of samplesMw, × 105
Polyacrylonitrile 9.37 
Poly(AN-co-AA) 2.61 
AO-poly(AN-co-AA) 2.53 
Name of samplesMw, × 105
Polyacrylonitrile 9.37 
Poly(AN-co-AA) 2.61 
AO-poly(AN-co-AA) 2.53 

The conversion percentage of nitrile group into amidoxime group was calculated using Equation (2). It was found that the conversion percentage of nitrile into amidoxime group was 78.2%. This result indicates that conversion percentages in the present study were 5.4% and 38.2% higher compared to the conversion percentage using the modification methods in (Zahri et al. 2015) and (Saeed et al. 2008), respectively. This is due to the present work that applied pH of 8 during the chemical modification process. In contrast, (Zahri et al. 2015) and (Saeed et al. 2008) reported the application of pH ∼6 during the chemical modification process with hydroxylamine hydrochloride. These results were in line with (Huang et al. 2013), in which the nitrile conversion into amidoxime was higher with reaction at higher pH (up to pH 8) since alkaline condition promoted the amount of free hydroxylamine. However, at higher alkaline condition (more than pH 8), the hydroxylamine molecules became unstable, which resulted in low nitrile conversion. This explains the higher conversion percentage of nitrile into amidoxime group in the present work.

Characterization of synthesized polymer and modified-polymer

In FTIR characterisation, Figure 2 demonstrated the functional groups appeared in both poly(AN-co-AA) and modified poly(AN-co-AA). The C = O stretching appeared in poly(AN-co-AA) spectra was denoted by bands at 1,726 cm−1 (Venkatesan & Pari 2016). This indicates that AA has successfully copolymerized with AN. After modification with hydroxylamine hydrochloride, the bands that were allocated to the O-H stretching (2,941 cm−1) in unmodified poly(AN-co-AA) were shifted to higher wavenumber (3,390 cm−1) and overlapped with N-H2 stretching bands (Petit & Puskar 2018). In addition, the absorption bands of nitrile stretch which were originally present in unmodified polymer at 2,245 cm−1 were thoroughly vanished in AO-modified poly(AN-co-AA). The nitrile stretching was swapped by the presence of the bands in 1,647 cm−1 that were assigned to the overlapping stretching of C = N and C = O functional groups (Hamza et al. 2018; Wang et al. 2018). The appearance of a band at 941 cm−1 corresponded to the stretching vibrations of N-OH, denoting a successful incorporation of amidoxime functional group (Wang et al. 2018) into copolymer system. The identical remark of characteristic bands on AO-modified adsorbent was reported beforehand (Zhuang et al. 2018; Yan et al. 2019).

Figure 2

IR Spectra of poly(AN-co-AA) before and after modification by amidoxime group.

Figure 2

IR Spectra of poly(AN-co-AA) before and after modification by amidoxime group.

Close modal

The elemental microanalysis of poly(AN-co-AA) in Table 3 shows the relative compositions of carbon, hydrogen, and nitrogen that were 57.49%, 5.42% and 19.89%, respectively. After the modification by hydroxylamine hydrochloride, the percentages for C, H, and N changed to 36.04%, 6.57%, and 21.90%, respectively. The 2% increase in nitrogen evidently demonstrates the efficiency of modification. This indicates that there is a substitution of nitrile group, which is the attachment of NH2 to C ≡ N group (Sabaqian et al. 2017).

Table 3

Composition of carbon, hydrogen, nitrogen, and sulphur elements in synthesized polymer

C (%)H (%)N (%)S (%)
Unmodified poly(AN-co-AA) 57.49 5.42 19.89 2.16 
AO-modified poly(AN-co-AA) 36.04 6.57 21.90 1.21 
C (%)H (%)N (%)S (%)
Unmodified poly(AN-co-AA) 57.49 5.42 19.89 2.16 
AO-modified poly(AN-co-AA) 36.04 6.57 21.90 1.21 

Figure 3(a) and 3(b) show the surface morphologies of poly(AN-co-AA) and AO-modified poly(AN-co-AA), respectively. There are plentiful of loose pore structure scattered on the surface of both polymers, indicating that AO-modified poly(AN-co-AA) has retained the porous structures even after hydroxylamine modification. Agglomerated beads were also seen on both poly(AN-co-AA) and AO-modified poly(AN-co-AA) SEM images. The same observations were described in the amidoxime-functionalized polymers (Ji et al. 2016; Wang et al. 2018). The presence of pores on the surface was significantly important for ions adsorption (El-Bahy & El-Bahy 2016). The average particle size of poly(AN-co-AA) was 132 nm while that of AO-modified poly(AN-co-AA) was 305 nm. This shows that the size of the particles increased as amidoxime group was functionalized to nitrile group of polymers. The identical sign of an increase in particle size was reported when enhancing AO-functional groups into poly(acrylonitrile-methyl acrylate) (Liu et al. 2010). The surface morphology of AO-modified poly(AN-co-AA) after boron adsorption is shown in Figure 4(c). The appearance of loose pores structure disappeared in the case of B3+-AO-modified poly(AN-co-AA). This is because the pore cavities are filled with boron ions after the adsorption process.

The BET test has been carried out to determine the difference in the pore conditions for AO-modified poly(AN-co-AA) and B3+-AO-modified poly(AN-co-AA). As tabulated in Table 4, the pore size of adsorbent was greatly reduced to a percentage of 57.2% after the adsorption process. The surface area and pore volume also reduced, which indicated the success of adsorption of boron onto AO-modified poly(AN-co-AA).

Table 4

The BET surface area, pore volume and pore size of adsorbent before and after adsorption

PolymerSurface area (m2/g)Pore volume (cm3/g)Pore size (nm)
AO-modified poly(AN-co-AA) 2.474 0.1849 299 
B3+- AO-modified poly(AN-co-AA) 1.269 0.1228 127 
PolymerSurface area (m2/g)Pore volume (cm3/g)Pore size (nm)
AO-modified poly(AN-co-AA) 2.474 0.1849 299 
B3+- AO-modified poly(AN-co-AA) 1.269 0.1228 127 
Figure 3

Morphology of (a) unmodified poly(AN-co-AA), (b) AO-modified poly(AN-co-AA) and (c) B3+- AO-modified poly(AN-co-AA).

Figure 3

Morphology of (a) unmodified poly(AN-co-AA), (b) AO-modified poly(AN-co-AA) and (c) B3+- AO-modified poly(AN-co-AA).

Close modal
Figure 4

TG and DTG profiles of (a) poly(AN-co-AA) from 50 °C to 1,000 °C; (b) AO-modified poly(AN-co-AA) from 50 °C to 1,000 °C.

Figure 4

TG and DTG profiles of (a) poly(AN-co-AA) from 50 °C to 1,000 °C; (b) AO-modified poly(AN-co-AA) from 50 °C to 1,000 °C.

Close modal

A comparison made on TG curves of poly(AN-co-AA) in Figure 4(a) and that of AO-modified poly(AN-co-AA) in Figure 4(b) showed that AO-modified adsorbent experienced slightly faster degradation compared to the unmodified adsorbent. This indicates that the existence of amidoxime groups within the polymer chains might have interrupted the stability of copolymer chains (Zahri et al. 2015). As shown in the DTG profiles of AO-modified poly(AN-co-AA) (Figure 4(b)), 27% of weight loss occurred before 190 °C. This was due to the evaporation of water molecules from the external surface and inside the cavities of the AO-modified copolymer. The appearance of degradation peaked in the range of 190 to 400 °C was attributable to immigration of the hydroxyl functional groups (on the oxime) from hydroxylamine hydrochloride to the nitrile groups to form amidoxime functional groups. This resulted in a high rate of cyclization which resulted in chains breakdown. Gradual weight loss occurred starting from 400 °C afterwards, and it was associated to the decomposition of the poly(AN-co-AA) chains and additional weight loss. The results are consistent with previous reports on thermal degradation of amine-containing polyacrylonitrile (Kiani et al. 2011) and polyamidoxime chelating resin (El-Bahy & El-Bahy 2016).

Uptake of boron ions by batch adsorption

Effects of pH on boron adsorption

The initial pH of the solution was considered to be a remarkable factor in influencing the amount of boron ions being adsorbed by adsorbents. The acidity or alkalinity of the solution will stipulate and regulate the ion charges on the surfaces of the adsorbent (Sepehr et al. 2014). Figure S2(a) shows that the highest removal of B3+ occurs at pH 8, and the removal percentage showed a general increasing trend from pH 2 until it peaked at pH 8, which resulted in the adsorption capacity of 10.7 mg/g. The adsorption capacity decreased beyond pH 8.

Boron has various optimum adsorption pH ranging from acidic to alkaline environment, depending on the type of adsorbent (Halim et al. 2013; Nishihama et al. 2013; Polowczyk et al. 2013). The observation from the present work indicates that the adsorption of boron ions by amidoxime-modified poly(AN-co-AA) was rather favourable in neutral conditions (pH 6.5 to 7.5). Similar observations were recorded (Wang et al. 2007; Xu & Peak 2007; Liu et al. 2010; Wei et al. 2011). Although the optimum adsorption was marked at pH = 8, there might be precipitation of boron ions on adsorbent at alkaline condition (Ozturk & Kavak 2005; Irawan et al. 2011; Ruiz-Agudo et al. 2012). The precipitation, which caused more boron ions to be removed, should not be counted as part of adsorption process.

The pH dependent boron uptake is mostly related to the surface functional groups of AO-modified poly(AN-co-AA). Boron can only be removed in the form of negatively charged borate ions or neutral boric acid (B(OH)3) (Wei et al. 2011). The sorption mechanism can be explained in reactions (a) in Figure 5. Under the acidic condition, the surface of adsorbent became positively charged due to protonation of hydroxyl functional groups while the partial neutral adsorbent species R*OH was still present. In acidic and neutral environment, the predominant species of boron was neutral boric acid B(OH)3. Boric acid could form complex molecules with R*OH or R*O to release H2O or H+ as shown in reactions (b) and (c) (of Figure 5). As pH increased (up to 7.5), the amount of hydrogen ions decreased, and this reaction shifted (b) and (c) to the right, which formed more boron-adsorbent complexes and increased adsorption rate.

Figure 5

Proposed boron adsorption reaction mechanism.

Figure 5

Proposed boron adsorption reaction mechanism.

Close modal

On the other hand, the adsorption capacity reduced as the basicity was increased to more than pH 7.5. At high pH, boron exists mainly as borate ions (B(OH)4−); thus, electrostatic repulsion occurred between the B(OH)4− ions and the anionic adsorbents. This weakens the forces of attraction between the B(OH)4− and the negatively charged functional groups on the adsorbents, leading to a decrease in adsorption (Kiani et al. 2011).

Effects of adsorbent dosage

The influence of varying adsorbent dosage in the boron solution on the adsorption capacity was evaluated at different values which were 0.5, 1.0, 2.0, 4.0, 6.0, and 8.0 g·L−1. As shown in Figure S2(b), the removal capacity rose from 2.5 mg/g to 13.25 mg/g with an increase in the dosage from 0.5 g·L−1 to 3 g·L−1. Afterwards, there was only a marginally upward trend until the adsorption capacity reached its constant at 14 mg/g at 4 g·L−1 of adsorbent dosage. At this point, the equilibrium concentration between the bounded ions to the adsorbent and unbounded ions was achieved (Igberase et al. 2014).

Effects of initial boron ion concentration

The influence of changing initial boron concentration on adsorption of boron was evaluated at myriad values of 10, 20, 40, 60, 80, and 100 ppm. As shown in Figure S2(c), the removal generally increased as the concentration of boron solution was increased from 10 to 40 ppm. Afterwards, the curve showed no sign of increment. This result reveals that the active sites of adsorbents were occupied and bounded with B3+ at 40 ppm of boron solution.

Isotherms study

The isotherm studies were conducted to investigate the interaction between the adsorbent and adsorbate particles. This involved the application of monolayer or multilayer adsorption, heterogeneity degree on adsorbate surfaces, and maximum adsorption capacity. The isothermal studies were also carried out to evaluate the adsorption behaviour either physisorption or chemisorption and/or both process. The graphs for Langmuir, Freundlich, and Sips isotherm were plotted in Figure 6, and their respective model parameters were summarized in Table 5.

Table 5

Isotherm parameters for Langmuir, Freundlich, and Sips models

Langmuir
Freundlich
Sips
 10.82  0.7078  11.92 
 1.1811  4.3538  1.4568 
 0.9710    0.7611 
 0.9720  0.8834  0.9889 
 0.2403   1.1361  0.2589 
Langmuir
Freundlich
Sips
 10.82  0.7078  11.92 
 1.1811  4.3538  1.4568 
 0.9710    0.7611 
 0.9720  0.8834  0.9889 
 0.2403   1.1361  0.2589 
Figure 6

Isotherm model plot for removal of boron ions at different initial concentrations of adsorbate (Ad = 2 g·L−1, V = 50 mL and pH = 7.2).

Figure 6

Isotherm model plot for removal of boron ions at different initial concentrations of adsorbate (Ad = 2 g·L−1, V = 50 mL and pH = 7.2).

Close modal
The Langmuir equation bounds to be valid to homogeneous adsorption in which the attachment of each adsorbate molecule onto the surface possesses the same sorption activation energy. This isotherm is represented by its linear form of expression as Equation (6) (Langmuir, 1916):
formula
(6)
(L·g−1) and (mg·g−1) are the constant of Langmuir equilibrium and monolayer saturation capacity, respectively. The monolayer saturation capacity computed was 10.82 mg/g. Besides, the important feature of Langmuir isotherm can be stated in a dimensionless constant termed separation factor, which is shown by Equation (7) (Hall et al. 1966):
formula
(7)

The value of shows the trend of the isotherms to be either favourable (0 < < 1), unfavourable ( > 1), linear ( = 1) or irreversible ( = 0). As shown in Table 5, the data of boron adsorption at different initial concentrations fit well with the Langmuir isotherm, showing R2 = 0.9720. It was found that for all initial concentrations were between 0 and 1, indicating that the adsorption process was favourable.

The most essential isotherm for multisite adsorption isotherm on heterogeneous surfaces is the Freundlich isotherm. Its linear form is expressed as Equation (8) (Freundlich 1906):
formula
(8)
where (L·g−1) is the Freundlich constant while (g·L−1) is the Freundlich exponent. Therefore, a pre-plotted graph of against , allows the constant and exponent to be computed. From Table 5, it was inferred that the value of was between 1 and 10, which again verified that the adsorption process is favourable. The adsorption fitted the Freundlich isotherm at value of 0.8834, which is less than that of Langmuir isotherm.
The Sips isotherm is a model considering both Langmuir and Freundlich isotherms. The model is applicable for localized adsorption without interactions among adsorbate. Sips parameters are computed by a linearization method. The linear equation can be expressed as Equation (9) (Sips 1948):
formula
(9)

(L·mg−1) is the Sips constant, and represents the surface of the heterogeneity. When n equals 1, the Sips isotherm reduces to the Langmuir isotherm and is expected to perform homogeneous adsorption. In contrast, deviation of value from the unity shows heterogeneous adsorption. As shown in Table 5, the value of ns deviated partially from unity at 0.7611, which denotes the presence of heterogeneity of the adsorbent surface. This in turn indicates that the adsorption process on the surface of AO-modified poly(AN-co-AA) occurred by both physisorption and chemisorption (Húmpola et al. 2013). Among the three models, Sips isotherm devotes the best fit for experimental data, at of 0.9889. An agreement with Sips model proves that the adsorption involves monolayer adsorption (Saadi et al. 2015). The maximum adsorption capacity, was found to be 11.92 mg boron per g adsorbent. As a result, both Langmuir and Sips provide good estimation for adsorption isotherm (with >0.90) with relatively low .

As compared with other adsorbent report in boron adsorption (Table 6), the maximum adsorption capacity in the current study has a high performance among all. Nevertheless, this shows amidoxime-functionalized polymer as a potential alternative polymer to remove boron while the chemical structure can be further modified and improved in future research to enhance the adsorption capacity.

Table 6

Comparison of boron uptake using various adsorbents

Adsorbent(mg/g)Reference
Palm bark activated carbon 2.38 Melliti et al. (2020)  
Nano-magnetite 8.44 Abba et al. (2021)  
Crypocrystalline magnesite 6.00 Masindi & Gitari (2017)  
Dialon CRB02 resin 13.18 Recepoğlu et al. (2017)  
N-methyl-D-glucamine grafted HDPE 15.63 Du et al. (2019)  
AO-modified poly(AN-co-AA) 15.23 Current study 
Adsorbent(mg/g)Reference
Palm bark activated carbon 2.38 Melliti et al. (2020)  
Nano-magnetite 8.44 Abba et al. (2021)  
Crypocrystalline magnesite 6.00 Masindi & Gitari (2017)  
Dialon CRB02 resin 13.18 Recepoğlu et al. (2017)  
N-methyl-D-glucamine grafted HDPE 15.63 Du et al. (2019)  
AO-modified poly(AN-co-AA) 15.23 Current study 

Kinetic study

The kinetic study of adsorption uptake of boron ions was carried out at room temperature and at pH 7.4 with variation of initial concentrations of boron ions. According to Figure 7, 20 ppm of boron ions solution reached its half-load time (t1/2) in less than 10 min while 60 ppm, 80 ppm, and 100 ppm reached their half-load time in less than 15 min. All concentrations of solution gradually reached their equilibrium within 60 to 70 min. The steep increase in uptake rate at the initial stage shows that the adsorption of boron ions occurs mainly on the polymer surface (El-Bahy & El-Bahy 2016).

Figure 7

The adsorption of boron ions over reaction time (Ad = 2 g·L−1, V = 50 mL and pH = 7.2).

Figure 7

The adsorption of boron ions over reaction time (Ad = 2 g·L−1, V = 50 mL and pH = 7.2).

Close modal
The applied kinetic mechanisms used to define the boron ions adsorption onto the adsorbent were Lagergren's pseudo-first-order, pseudo-second-order, Elovich, and intra particle diffusion. The Lagergren's pseudo-first-order portrayed the adsorption mechanism related to adsorption capacity. It was plotted in Figure S3, and the model was given by Equation (10) (Lagergren 1898):
formula
(10)
where and (mg·g−1) represent the amount of ions uptake at equilibrium and at given time t (min), respectively. Parameter is the Lagergren rate constant (min−1) for the sorption process. Lagergren's pseudo-first-order is based on a few assumptions in which sorption solely occurs on localized sites and does not interact with the sorbed ions. Secondly, the energy of adsorption is independent of surface coverage. Thirdly, the maximum adsorption was represented by saturated monolayer of adsorbate on the surface of adsorbent (Largitte & Pasquier 2016).

The experimental results were also analysed by applying the pseudo-second-order kinetic model. The pseudo-second-order model could be expressed as several linearized form as shown in Table 7 (Robati 2013; Rout et al. 2015):

Table 7

The linearized equation of pseudo-second-order model

CategoryLinearized equationPlotEquation no.
Linear model-1  vs.  11 

Linear model-2 
 
vs.  

12 


Linear model-3 
 
vs.  
13 

Linear model-4 
 
vs.  

14 
CategoryLinearized equationPlotEquation no.
Linear model-1  vs.  11 

Linear model-2 
 
vs.  

12 


Linear model-3 
 
vs.  
13 

Linear model-4 
 
vs.  

14 

where (g·mg−1·min−1) is the second-order rate constant. The values for each linearized equation was computed from the graph plotted in Figure S4 and tabulated in Table S1. Among four linearized second order equation, model-2 provides the maximum , minimum and has reasonable match between and . The computation of linear model-2 gave at values of 0.00745 ± 0.0024. All of model-2 values were above 0.98 and close to 1. These values were higher compared to the values that were obtained from the first-order kinetics. The predicted equilibrium adsorption capacity was of 1.233 which corresponded to their differences with the experimental results. The result was relatively lower than that of pseudo-first-order. Thus, pseudo-second-order kinetic model is more appropriate than the first-order in describing the behaviour of boron adsorption.

The Elovich model indicates a chemical sorption mechanism, and its linearized form is expressed as in Equation (15) (Largitte & Pasquier 2016). Figure S5 shows the Elovich kinetic model plot for the removal of B3+. By generating a linear trend line, and values can be calculated from the slope and y-intercept. Constant is linked to the rate of chemisorption while is represented by the surface coverage. The positive values of α and β parameters for B3+ at all concentrations indicates that chemisorption occurred during respective adsorption (Uzunova et al. 2013).
formula
(15)
Intraparticle diffusion model was depicted by Weber and Morris involving the uptake of boron ion using resin which includes both immediate surface sorption and intraparticle diffusion steps. The model can be expressed by Equation (16) (Weber & Morris 1963).
formula
(16)
where (mg·g−1·min−0.5) is the intraparticle diffusion rate constant. The value of was calculated from the gradients of model plots. As shown in Figure S6, the intra-particle diffusion model provides a decent fit to the experimental data with at 0.9299 ± 0.0110.

In the requirement of values should reasonably match and possessed similar trend (Markandeya et al. 2015), linearized pseudo-second-order (model-2) was a better fit than other pseudo-first-order, Elovich and intra particle diffusion models. This was supported by closed values between the experimental equilibrium () and calculated equilibrium adsorption capacity () in pseudo-second-order (model-2) (Table 8). A good agreement is able to be further supported by highest values in the pseudo-second-order (model-2) among all. Otherwise, the pseudo-first-order, Elovich, and intra particle diffusion provide appropriate fit to the adsorption mechanism with values >0.90. This boron sorption mechanism was best represented by pseudo-second-order as suggested by highest value and lowest error analyses. This implies that the interaction of boron ions with the modified poly(AN-co-AA) is mostly chemisorption dominated. Although, the influence of intraparticle diffusion on the boron sequestration onto polymer surface is also notable according to high values.

Table 8

Kinetic parameters for adsorption mechanism of boron ions AO-modified poly(AN-co-AA)

Initial concentration (mg·L−120 60 80 100 
(mg·g−17.000 10.428 10.560 10.400 
Lagergren pseudo-first-order 
(mg·g−16.108 10.629 8.563 7.111 
(min−10.0497 0.0424 0.0374 0.0310 
 0.9582 0.9189 0.9138 0.9092 
 15.644    
pseudo-second-order 
(mg·g−18.046 10.293 10.881 10.269 
(g·mg−1·min−10.00984 0.00565 0.00613 0.00816 
 0.9930 0.9930 0.9858 0.9914 
 1.233    
Elovich 
 1.613 2.019 2.260 2.797 
 0.629 2.526 2.321 2.162 
 0.9634 0.9705 0.9528 0.9611 
 4.0723    
Intra particle diffusion 
(mg·g−10.936 1.061 1.276 1.709 
(mg·g−1·min−10.738 1.144 1.078 1.016 
 0.9409 0.9348 0.9392 0.9188 
 13.854    
Initial concentration (mg·L−120 60 80 100 
(mg·g−17.000 10.428 10.560 10.400 
Lagergren pseudo-first-order 
(mg·g−16.108 10.629 8.563 7.111 
(min−10.0497 0.0424 0.0374 0.0310 
 0.9582 0.9189 0.9138 0.9092 
 15.644    
pseudo-second-order 
(mg·g−18.046 10.293 10.881 10.269 
(g·mg−1·min−10.00984 0.00565 0.00613 0.00816 
 0.9930 0.9930 0.9858 0.9914 
 1.233    
Elovich 
 1.613 2.019 2.260 2.797 
 0.629 2.526 2.321 2.162 
 0.9634 0.9705 0.9528 0.9611 
 4.0723    
Intra particle diffusion 
(mg·g−10.936 1.061 1.276 1.709 
(mg·g−1·min−10.738 1.144 1.078 1.016 
 0.9409 0.9348 0.9392 0.9188 
 13.854    

In addition, Figure S7 depicts the spectral transformation in the functional groups present on the modified polymer surface. The adsorption bands NH2 and N-OH in AO-modified poly(AN-co-AA) have shifted from 3,382 cm−1 and 937 cm−1 respectively to 3,387 cm−1 and 935 cm−1. This implied boron ion interaction with AO-modified poly(AN-co-AA) feasibly occurred through ion exchange method. Post adsorption process, the transmittance was significantly decreased to 6.7% and 13.7% for NH2 and N-OH groups, respectively. The complex of B3+-AO-modified poly(AN-co-AA) had less intense peaks for NH2 and N-OH, which indicated the functional groups had been occupied by adsorbed metal. The FTIR results asserted the transformation of adsorption peaks of adsorbent at different stages which in turn addressed the successful adsorption of boron on AO-modified poly(AN-co-AA). Besides, Table S2 indicates that the pore size of adsorbent was greatly reduced to a percentage of 57.2% after the adsorption process. The surface area and pore volume also reduced, which showed the success of adsorption of boron onto AO-modified poly(AN-co-AA).

Desorption and reusability study

Apart from adsorption, the recyclability of an adsorption is also assessed through desorption process. The adsorbent should be easily regenerated in order to reduce manufacturing and chemical waste. In this research, B3+-AO-modified poly(AN-co-AA) was regenerated by washing the loaded adsorbents with different concentrations of acidic desorbing agents at 0.1 M, 0.5 M, 1.0 M and 1.5 M, respectively. The desorbing agents are HNO3, HCl and H2SO4. The efficiency of desorption was displayed in Figure S8. Among three desorbing agents, nitric acid (HNO3) portrayed the highest performance at 79% desorption efficiency. Meanwhile, HCl and H2SO4 gave similar results at 75% desorption efficiency. The maximum desorption reached around 1.0 M for all agents and did not show any sign of increment beyond 1.5M of desorbing agent.

For reusability study, AO-modified poly(AN-co-AA) was reused five times, under same operating condition. The result was shown in Figure 8. It was found that from 15.25 mg/g adsorption efficiency at the first time, the figure dropped to 9.91 mg/g in the second usage, which is about 65% of the former. The efficiency dropped to 50% at the third usage at 7.63 mg/g. This has proven the reusability of AO-modified poly(AN-co-AA) in boron adsorption up to 2–3 times.

Figure 8

Reusability study of AO-modified poly(AN-co-AA). (Co = 40 ppm, pH = default = 7.2, adsorbent dosage = 4 g·L−1).

Figure 8

Reusability study of AO-modified poly(AN-co-AA). (Co = 40 ppm, pH = default = 7.2, adsorbent dosage = 4 g·L−1).

Close modal

The synthesis of AO-modified poly(AN-co-AA) was conducted for the preparation of adsorbent to remove boron ions from an aqueous solution. The improved synthesis method produced 77.0% of yield for copolymerization of AN and AA. The conversion of nitrile groups into amidoxime was found to be 78.2% in the AO-modified poly(AN-co-AA). The uptake of boron from liquid phase onto AO-modified poly(AN-co-AA) adsorbent in batch mode was investigated at different experimental parameters. The adsorption of boron ions was influenced by pH solution, concentration of boron ions, and adsorbent dosage. AO-modified poly(AN-co-AA) showed effective adsorption in a slightly alkaline environment (pH = 8). A linearized pseudo-second-order (model-2) mathematical equation fits well to describe the experimental kinetics of boron sequestration. The Sips model was more qualified than the Langmuir and Freundlich models to describe the isothermal adsorption data. Heterogeneity of adsorbent surface was confirmed by the constant of Sips (ns=0.7611), and the favourability of the investigated adsorption process was proven by the separation factor (RL) of the Langmuir isotherm which was 0 < RL < 1. The consecutive sorption-desorption experimentation reveal that the exhausted AO-modified poly(AN-co-AA) could be used multiple times with slight reduction in adsorption capacity. The findings of this investigation suggested that AO-modified poly(AN-co-AA) could be applied successfully to remove boron ions from aquatic environment.

The authors would like to express gratitude to the Ministry of Higher Education Malaysia for the financial support provided under the Fundamental Research Grant Scheme (FRGS) with the project number 5524296. Thanks are due to Chemistry Department, Faculty of Science, Universiti Putra Malaysia and Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia for providing the research facilities.

The authors declare that there is no conflict of interest regarding the publication of this article.

All relevant data are included in the paper or its Supplementary Information.

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