This study was designed to investigate the effectiveness of Musanga cecropioides wood sawdust as an adsorbent for the removal of eosin yellow dye from aqueous solution. Batch adsorption, FTIR and computational chemistry methods were used. A concentration of the dye was determined by spectrophotometry method. The results obtained confirmed that the wood sawdust is an efficient adsorbent for the removal of eosin dye from aqueous solution. The adsorption capacity of the wood sawdust is a function of concentration, adsorbent dosage, time and temperature. The adsorption isotherms of Langmuir, Freundlich, Temkin and Dubinin-Raduskevich fitted the adsorption data significantly. The fitness of the adsorption data to kinetic models was excellent for pseudo first order and pseudo second order models. FTIR study revealed that the adsorption of the dye is facilitated by some functional groups (that were missing in the original spectrum) while computational chemistry study gave values of electronic parameters that are comparable to those reported for good adsorbents. The molecular orbital, bonds and atoms associated with electrophilic and nucleophilic attacks were also analyzed through frontier orbital theory and Fukui function analysis and the results obtained agreed with each other.

Keywords: Water purification, Adsorption, Wood saw dust, Experimental and Theoretical studies

INTRODUCTION

Global environmental concern places more hope on the provision of portable water that is devoid of all forms of pollutants ranging from physicochemical (including color), organoleptic, heavy metals, etc. [1,2]. One of the major characteristics of portable water is that it must be colorless. Water acquired color when some substances dissolves in it. The textile, paint, leather and tanning industries use dyes of various forms in processing their products [3]. Most often, these dyes find their way into the water bodies (through direct discharge or surface runoff), consequently, the color of the water will be altered. Some dyes are toxic and could therefore be very harmful to aquatic life [4]. Also, the nontoxic dyes can also affect aquatic life because it can obstruct light penetration and consequently retard the primary photosynthesis process [5]. In view of the above listed (and others) impacts of dyes on aquatic system, several researches have been reported on ways of removing dye from water, including adsorption.

Several studies have also been conducted on removal of dyes from aqueous solution using different forms of adsorbents such as natural and artificial polymers, natural and chemical compounds such as limestone, Cao, ZnO, etc. [6] nano materials such as nano carbon tubes, nano graphene oxide [7-9] and plants or animals materials such as plant leaves, stems, etc [10,11]. The use of plant materials offers sustainable environmental hope because most of them are green and undergo biodegradation at ease. Therefore, the present study is aimed at using wood saw dust obtained from Musanga cecropioides wood as an adsorbent for removing eosine yellow dye from aqueous solution. The use of some wood sawdust for the removal of dyes from aqueous solution is not strange. For example, scientists found that [12] found that Tectonagrandis, Ceiba pentandraand Terminalia superbasawdusts were good adsorbents for the removal of dyes from aqueous solution. Scientists [13] investigated the capacity of Beech wood sawdust for the adsorption of some textile dyes (direct orange 26, acid orange 7 and acid green 20). The wood sawdust was an effective adsorbent for the removal of the studied dyes from aqueous solution [14]. Also found that some textile dyes can effectively be adsorbed by wood sawdust. The adsorption fitted pseudo first order, pseudo second order, Langmuir, Freundlich and Temkin adsorption models. Adsorption is a surface phenomenon that operates through mechanism of charge transfer or electron transfer. Charge transfer is native for physiosorption mechanisms while the transfer of electron from the adsorbate to the adsorbent or vice versa is in accord with the mechanism of chemical adsorption which is more sensitive to temperature and physiosorption [15-17].

MATERIALS AND METHODS

The IUPAC name of the dye (eosin yellow) is sodium 2-(2,4,5,7-tetrabromo-6-oxido-3-oxo-3H-xanthen-9-yl) benzoate. The dye and all other reagents were supplied by the Chemistry departmental store, Akwa Ibom State University. Wood saw dusts were produced from Musanga cecropioides wood. Experimental components of the work included batch adsorption experiment, spectrophotometric determination of concentration and FTIR analysis of functional groups. The theoretical components included semiempirical calculations and Fukui function analysis.  calculations.

Batch adsorption experiment

Batch adsorption process as reported elsewhere was used to study the effect of concentration, contact time, adsorbent dosage and temperature of the adsorption of the dye unto the wood saw dust [11]. Amount of dye adsorbed at equilibrium was calculated using equation 1

                q_e=  (C₀- C_e/C₀ )  ×  V/m                            (1)

where C₀ is the initial concentration of the dye, C_e is the equilibrium concentration of the dye, V is the volume of solution and m is the mass of the adsorbent.

Spectrophotometric determination of dye concentration

All spectrophotometric analyses were carried out using 721, P/N: A003 UV-visible spectrophotometer. In spectrophotometric analysis, wavelength of maximum absorption of EY dye was measured. The measured wavelength was used as a reference wavelength for all analysis and determination of the concentrations using extrapolation method according to Beer-Lambert’s law of spectrophotometry.

FTIR analysis

FTIR analysis of the dye, adsorbent (before and after adsorption) was carried out using Agilent FTIR spectrophotometer (Located in Chemistry Department of the Bayero University, Kano, Nigeria). The samples were prepared with KBr powder and the scan range was 650 to 4000 cm^-1. The system status was good while the Apolization was Happ-Genzel. The Agilent Technologies software also provided provision for display of analytical output.

Computational chemistry calculations

All computational calculations were performed with a Hewett Parker (HP) core i4 laptop having with processor speed and hard disc capacity of 8 GB and I TB respectively. Computational chemistry calculations were performed using DFT and ab initio methods in hyperchem package. Full geometry optimization was achieved using the same software. ChemBio 2018 was used to develop molecular graphic and input files for ORCA package Semiempirical parameters were calculated using molecular orbital package (WinMOPAC).

RESULTS AND DISCUSSIONS

Batch adsorption study

Beer-Lambert’s law of spectrophotometry was applied to convert absorbance measurements to concentrations through extrapolation from the calibration plot. Effect of concentration was studied for various concentrations of EY dye adsorbed under similar experimental conditions (temperature, adsorbent mass, pH, period of contact, etc). Figure 1 shows plot for the variation of equilibrium amount of dye adsorbed at various concentrations, C (mg/L), adsorbent mass (in mg), temperatures (in Kelvin) and period of contact (in min).

From Figure 1, it is observed that the adsorption of EY dye increases with increase in concentration, which indicate that as the concentration of the dye increases, there is a corresponding increase in the amount of EY dye approaching the adsorption sites of the adsorbent through mass transfer. At low concentration, the mass transfer force is low hence the number of molecules approaching the adsorbent surface is reduced and vice versa. However, the observed steady rate of adsorption above certain concentration suggest that there was an onset of desorption or complete occupancy of all the adsorption sites in the adsorbent. When all the available and activated adsorption sites are occupied, further diffusion of the adsorbate’s molecules unto the adsorbent may not increase adsorption [1].

The equilibrium amount of EY dye adsorbed first decreases with increase in the mass of the adsorbent (i.e. adsorbent dosage) before increasing. This implies that, at low adsorbent dose, the adsorption capacity of the adsorbent was not fully explored but as the dosage increases, the adsorption sites and adsorption capacity increase (due to greater accessibility of surface binding sites and interactions). Consequently, the equilibrium amount of EY dye adsorbed increased with adsorbent dosage.

Adsorption isotherm

The adsorption characteristics of EY dye onto wood saw dust was consistent with the Langmuir adsorption model which can be written according to equation 2 [17].              

          C_e / q_e =  1/(q_m b)+  C_e / q_m                                           (2)

where C_e is the equilibrium concentration of adsorbate (mg/l), q_e is the amount of adsorbate adsorbed per unit mass of the adsorbent (mg/g), b is the Langmuir adsorption constant which is related to affinity between the adsorbate and the adsorbent while q_m is the theoretical monolayer saturation capacity. From the Langmuir equation, a plot of    versus C_e should be linear if the Langmuir assumptions are valid. Figure 2 presents the Langmuir isotherm for the adsorption of EY dye from aqueous solution onto wood saw dust. Langmuir adsorption parameters calculated from the slope and intercept of the plot were q_m = 14.29 mg/g and b = 0.044. The calculated q_m value is comparable to those reported for other dyes. For example, [20] reported q_m value of 12.83 mg/g for the adsorption of crystal violet dye onto Moroccan pyrophyllite, Banerje and Chattopadhyaya [21] obtained q_m value of 3.39 mg/g for terazine dye adsorbed on activated carbon, obtained q_m values of 8.947 mg/g for methyl green adsorbed on regia resin.

dust is spontaneous and support the mechanism of physiosorption.

In adsorption study, the equilibrium amounts adsorbed (q_e) andequilibrium concentration (C_e) are related to the equilibrium constant according to the following equation,              

                k_c=  q_e/C_e                                                                   (13)

Also, from thermodynamics,

    ∆G^*=  ∆H^* - T∆S^*                                                      (14)

Therefore,

   -2.303RTlogk_p=  ∆H^*- T∆S^*                                   (15)

   -Tlnk_p=  ∆H^*- T∆S^*                                                   (16)

    lnk_p =  ∆S^*/R - ∆H^*/RT                                                             (17)

Therefore, a plot of  is expected to be linear with slope and intercept equal to  and  respectively.

The plot obtained (plot not shown) indicated R² value of 0.965 while slope and intercept were -0.007 and -0.055 respectively. . Estimated values of  and  were -0.0582 J and -0.4572 J indicating that the adsorption of EY dye onto the surface of wood saw dust is exothermic and occurs in the direction of increasing degree of orderliness.

Kinetic Study

Pseudo first order and pseudo second order kinetics models can be expressed according to equations 18 and 19 respectively [27].

  ln(q_e-q_t ) = lnq_e- k₁ t                                                         (18)

   t/q_t   =   1 / (k₂ q_e²)+  t/q_e                                                                 (19)

Agreement of the present adsorption data with pseudo first and second order kinetics was established through  linear plots of  versus t and  versus t for pseudo first and second order kinetics respectively (as shown in Figure 3). Calculated adsorption kinetic data (Table 1) are k₁= 0.096/m and k₂= 2.3 x 10⁵ /m respectively while lnq_e (pseudo first order plot) and q_e (pseudo second order plots were 0.009 and 6666.67 respectively. Perfect degree of fitness was obtained for the pseudo first order kinetics (R² = 1.000) compared to R² = 0.9462 obtained for pseudo second order kinetics. Consequently, adsorption of EY dye onto wood saw dust best fitted the pseudo first order kinetics than pseudo second order kinetics. Also, from the pseudo second order kinetic data, the initial adsorption rate (i.e. h) and half adsorption time (t_0.5) were calculated using the formula,

   and  respectively [28].

The Elovich equation is a kinetic model that is most suitable for explaining chemisorptions and for adsorption process that does not approach equilibrium at ease due to low surface coverage. Expression for the Elovich equation [29] can be written as:

    q_t = (1/β) ln (αβ)  +  1k_Deslnt                                             (20)

where  is the initial adsorption rate in mg/g/min,  is desorption constant and is related to the activation energy of a chemisorption process and the extent of surface coverage. The adsorption of EY dye on the surface of wood saw dust fitted the Elovich adsorption model (R² =0.870) as shown in a linear plot (Figure 3) of q_t versus t. Therefore, the mechanism of adsorption of EY dye partly involves chemisorptions. Estimated   value was 370. 37 whiles   was 58.95 mg/g/min.The Weber-Morris adsorption model (expressed as equation 21) is the most useful kinetic model for investigating intra particle diffusion [30].

    q_t = B + K_id√t                                                                     (21)

Kid is the intra particle diffusion constant (mg (g. min0.5) while B is the initial adsorption (mg/g). When B is zero, intra particle diffusion is the rate controlling step. The Weber-Morris plot for the adsorption of EY dye (Figure 3) indicated a non-zerointercept (i.e. B = 10.44 mg/g) which implies that other mechanism also contributes to the adsorption of EY dye on wood sawdust (in addition to intra particle diffusion). Estimated kid value was 0.010 (mg (g. min0.5).

FTIR study

FTIR spectra of EY dye and that of the wood saw dust before and after adsorption were analyzed (spectra not shown). Frequencies and intensities of IR adsorption deduced from the FTIR of wood saw dust before and after adsorption of EY dye (spectra not shown) are presented in Table 1. The FTIR spectrum of EY dye indicated the presence of OH stretch at 3335 cm-1 (42.76 %), C0H stretch at 2117 (95.72 %), C=C stretch at 1640 (64.87 %) and C-N stretch at 1242 (88.535 %).

From Table 1, it can be deduced that the wood saw dust possess several functional groups that aided the adsorption of EY dye.

 After adsorption of ET dye, some functional groups were missing in the spectrum including C-Br stretch, C-O stretch at 1286 cm^-1 and C=C=C stretches at 1990, 1961 and 1905 cm^-1 respectively. The missing functional groups might have been used for the formation of new bonds [31]. However, new functional groups formed were C=C stretch at 2218 cm^-1, C=C=N stretch at 2009 cm^-1 and C-H bend at 899 cm^-1. The OH stretch at 3320 was shifted to 3339 cm^-1 after adsorption of EY dye other included C-H stretch at 2988 shifted to 2895 cm^-1, C=C stretch at 2106 shifted to 2117cm^-1 and the C=O stretch shifted from 1655 to 1640 cm^-1, The shift in frequencies of adsorption indicate that there is interaction between the adsorbent and the adsorbate [15, 16]. Functional groups that witness shift in intensity of adsorption (but not frequency) were C-Cl stretch at 836 cm^-1, C-OH stretch at 1033 cm^-1, C-O stretches at 1108 and 1160 cm^-1 respectively, S=O stretches at 1324 and 1369 cm^-1 respectively, OH bend at 1424 cm^-1, C=C stretch at 1482 cm^-1, C=O stretch at 1503 cm^-1C=N stretch at 1596 cm^-1 and C=O stretch at 1737 cm^-1. Bathochromic and hypsochromic shifts in intensity confirms that the absorption strength of the adsorbent has been altered by the interaction between the dye and the adsorbent [17].

COMPUTATIONAL CHEMISTRY STUDY

Semiempirical parameters

Semiempirical parameters calculated for EY dye were E_HOMO (-7.787021 eV), E_LUMO (-1.107504 eV), total energy (-193.1411 eV), binding energy (-4197.2663 eV), isolated atomic energy (-117000.6061 eV), electronic energy (-902517.1837 eV), core interaction (781319.3113 eV) and heat of formation (-10.3993 kCal). The calculated semiempirical parameters are not at variance with those reported for good adsorbent for other dyes. For example [11] reported -8.4071 and -1.6856 eV as values of E_HOMO and E_LUMO for methylene blue and malachite green respectively (that were excellently adsorbed on neem leaves). However, their calculated electronic energies were -528,742.2598 and -885,289.2176 eV respectively (which is significantly less than that of EY dye). Other parameters were also relatively comparable [11] In EY dye, 29%, 25%, 22% and 23% of the HOMO electron population resides in the S, P_x, P_y and P_z orbitals. Adsorption is a surface phenomenon that involves charge or electron transfer or sharing. According to the frontier molecular orbital theory, the formation of adsorption bond (i.e. van der Waal for physical adsorption or chemical bond for chemisorption mechanism) involves interaction between the HOMO and LUMO molecular orbitals and the extent and readiness of the transfer depends on the energy gap [32] E_HOMO is an index that reflects tendency toward adsorption while E_LUMO indicates tendency toward desorption [33,34]  Calculated energy gap is relatively low and suggest ease of adsorption governed by the proposed physical adsorption [34] Fukui function.

A neutral atom having N number of atoms can align in two different ways, either by losing or gaining electron. Such attacks lead to either nucleophilic or electrophilic attack respectively. Losing of one electron leaves the system as N-1 while gaining of one electron changes it to a N-1system. Apart from variation of electron, there is also variation of charge since donation or acceptance of electron also affects the charge of the molecule. Adsorption occurs via the transfer of charge from charged adsorbate to charge adsorbent surface (physical adsorption) or through the transfer of electron from the adsorbate to the adsorbent and vice versa (chemical adsorption). The Fukui function originates from the concept of considering the reactivity of a molecule in terms of the individual atom as it gains or loses electron. The finite difference approximation defines the three different types of Fukui function [33-35] as follows:

       f_x⁺ = q_(N+1) - q_N                                                           (22)

        f_x^-= q_N - q_(N-1)                                                          (23)

          f_x⁰  =  [(q_(N+1) )  - (q_(N-1) )] / 2                          (24)

In analyzing the results obtained from Fukui function calculations, it is necessary to consider the most favorable behavior that will favor each atom on the molecule. The difference between nucleophile and electrophilic Fukui functions (equation 25) is an index that allows the prediction of the location where nucleophilic or electrophilic Fukui function resides [32,36-39]:

    ∆f_x = f_x⁺- f_x^-                                                               (25)

Consequently, if , the site is favourable to nucleophilic attack but if , the site is favourable to electrophilic attack. Calculated values of , ,  and  for both Ab initio and DFT levels are recorded in Table 2. The results expose various sites with positive values of  for both Ab initio and DFT calculations. However, highest values of  for ab initio (0.0132) and DFT (0.0099) were obtained for O (26) which indicate that nucleophilic attack is likely located in this site [32, 40-43]. The Mayer bond order for this bond is also less than unity. Similarly, both ab initio and DFT predictions for the site for electrophilic attack did not prefer any other side but C(15) which has the highest positive values of  and highest negative value of for both ab initio and DFT levels of theory. All the valence electron in C (15) are bonded suggesting that the attack will certainly involves a bond or functional group associated with C (15). Also, the total nuclear charge for O (26), Muliken atomic charge, Mayer total valence and Mayer bonded valence (Table 2) are 8.0, -0.617, 1.9961 and 1.9961 respectively. This also suggests that nucleophilic attack will preferably involves a bond or functional group and not the atom alone [44-46].

CONCLUSION

The results and findings of this study revealed that wood saw dust from Musanga cecropiode is effective in the removal of EY due from aqueous solution. The removal efficiency of the wood saw dust depends on temperature, adsorbent dosage, concentration of the dye and period of contact. The adsorption behavior of the studied system conforms with some kinetic and isotherms models. The adsorption of the dye is spontaneous and exothermic. Quantum chemistry provides good information on the atoms/functional groups associated with the adsorption of the dye. Missing functional groups and the formation of new bonds also confirmed that the dye molecules are removed from the aqueous solution through adsorption.

ACKNOWLEDGEMENT

Technical staff of Akwa Ibom State University and staff of computational Chemistry Unit of the University of Nigeria are strongly acknowledged for their respective contributions.

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