Hierarchical approach towards adsorptive removal of Alizarin Red S dye using native chitosan and its successively modified versions

Dyes are inevitable constituents of many industries like textile, paper, rubber, leather, plastics, etc. and their presence in wastewater is a matter of great concern to environmentalists (Ho & Ching 2001). Many of the dyes are stable to light, oxidation and even resistant to aerobic digestion (Chen & Zhao 2009). Removal of dyes from water has been a major challenge and a number of methods have been adopted for this purpose, such as membrane filtration, photodegradation (Naushad et al. 2019), coagulation–flocculation, biological treatment, electro-chemical process and adsorption (Huang et al. 2015).

Adsorption (Vital et al. 2016), among all the other methods available, has been found to be highly useful because it is cost effective, simple, quick and applicable to large-scale effluents (Jeyaseelan et al. 2018). A variety of adsorbent materials are currently available, which include low-cost materials (Crini 2006; Bharathi & Ramesh 2013) such as alum sludge (Tripathy et al. 2006), clays (Fu et al. 2011; Komosińska et al. 2014; Adeyemo et al. 2017), chitosan (Ch) (Chatterjee et al. 2007; Saha et al. 2010; Kyzas & Bikiaris 2015), bio-composite (Nair et al. 2014; Saravanan et al. 2013; Dotto et al. 2016) and agricultural waste (Namasivayam & Kavitha 2002; Singh et al. 2003; Adekola & Adegoke 2005; Bulut & Aydin 2006; Mahmoodi et al. 2011; Salleh et al. 2011). Among these materials, bio-composites have attracted great attention because of their high adsorption capacities and good mechanical strength.

Ch, a well-known biopolymer, is obtained by deacetylation of chitin, which is a component of crustacean shells as well as fungal biomass. It has a wide range of applications in fields like food, cosmetics, medicine and pharmaceuticals. It is biodegradable, biocompatible and its degradation products are non-toxic. Due to its chemical stability, high reactivity and good chelation property, it can be used for the removal of dyes (Vital et al. 2016). Ch still has some disadvantages, including poor mechanical strength, easy agglomeration and its solubility in dilute acids. However, Ch is insoluble in sulphuric acid. The free amino groups react with acid to form salt, and because sulphuric acid is divalent, cross-linking occurs thus providing the necessary mechanical strength to the polymer chain. Kahu et al. has reported the synthesis of sulphate cross-linked chitosan (SCC) and its application in the removal of hexavalent chromium (Kahu et al. 2014).

Clay materials are generally made up of hydrous alumina-silicates, with high cation exchange capacity and large specific surface area. Furthermore, clay minerals are abundant in nature, cheaply available and mechanically stable making it an attractive immobilization material for Ch (Nesic et al. 2013). Among the mineral clays, bentonite has been highlighted for the preparation of composites because of its high cationic exchange capacity and the possibility of lamellar expansion (Anirudhan et al. 2010). Bentonite has proven to be a promising economic material for the removal of dyes due to its large abundance (Bellir et al. 2010).

In the present work, native Ch, cross-linked CH and Ch–bentonite composite have been employed as potential adsorbents for the removal of an anionic dye – Alizarin Red S (ARS). It is an organic sodium dye, commonly known as sodium alizarinsulphonate (Supplementary Figure 1). The molecular formula is C₁₄H₇NaO₇S and molecular weight is 342.253 g/mol. ARS is widely used in textile industries to impart colour to the fabrics, but it is known to cause skin, eye and respiratory tract irritation when exposed for a long duration.

Ch powder-652 (high density) was supplied by Meck Pharmaceuticals & Chemicals Pvt. Ltd, Ahmadabad, India. Sulphuric acid AR (98%) was supplied by SDFCL, Mumbai, India. Bentonite powder and Alizarin Red S AR (sodium alizarin sulphonate) were supplied by Loba Chemie Pvt. Ltd, Mumbai. Aqueous solutions were prepared using double distilled water. All reagents used were of analytical grade and no further purification was done.

Kahu et al. (2014) described in detail the preparation of SCC. It involves treating 5.0 g Ch with 250 mL 4% (v/v) sulphuric acid solution in a round-bottom flask and stirring for 1 h at room temperature. Resultant SCC was filtered and washed until the washings had a neutral pH. In order to prepare sulphate cross-linked chitosan-bentonite composite (SCC-B), 5.0 g of bentonite powder was added to the Ch–sulphuric acid solution after 1 h of stirring and was then stirred continuously for the next 12 h using a magnetic stirrer. The mixture was then filtered and the material washed several times with double-distilled water until the washings were completely free from acidity. It was dried in a hot air oven for 12 h at 50 °C, crushed using a mortar and pestle and sieved through 350 micron mesh a to obtain uniform particle size. The material obtained was SCC-B and was used as an adsorbent for ARS.

The pH point of zero charge (pH_PZC) is the pH value at which the net charge on the surface of the adsorbent material is zero (Jeyaseelan et al. 2018). The net charge on the adsorbent surface is positive below this pH, but is negative above this pH. Hence the value of pH_PZC can be used for the prediction of adsorbent–adsorbate interaction. For determining pH_PZC, 25 mL of 0.01M sodium chloride solution was taken in conical flask. The initial pH values were adjusted between 2.0 to 10.0 using dilute solutions of hydrochloric acid and sodium hydroxide. To each of the flasks, 0.1 g of the adsorbent was added, stirred for 24 h and the final pH values were noted after filtration. The values of pH_PZC were determined from the plot of change in pH as a function of initial pH.

For performing batch experiments, 50 mL dye solution (of known concentration) was equilibrated with a known amount of adsorbent (Ch, SCC or SCC-B) in a stoppered conical flask. Adsorption systems were stirred on a mechanical shaking machine at 170 rpm for the desired time at room temperature. The systems were then filtered and the absorbance value of the filtrate was recorded. Filter paper itself was found to adsorb some dye leading to decrease of about 0.4% in the absorbance value. This correction was applied in all the calculations. The absorption maxima (λ_max) and absorbance values were recorded using Equiptronics EQ-824 dual beam spectrophotometer in the range 350–1,100 nm using a set of matched cuvettes. The pH was adjusted using Equiptronics pH meter EQ-615. For uniform stirring of the dye solution with the adsorbents, a Remi RS-12R DX mechanical shaking machine was used (range 80–180 rpm).

Characterization was carried out by subjecting the adsorbents using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), X-ray diffraction (XRD), thermogravimetric-differential thermal analysis (TGA–DTA), and Brunauer–Emmett–Teller (BET) analysis surface area analysis. FT-IR spectra were recorded using a Bruker Alpha spectrometer in the range of 500 to 4,000 cm⁻¹. Surface morphology of adsorbents was studied using and SEM model TESCAN VEGA 3 SBH. EDX spectroscopy for elemental analysis was obtained using an X-ray analyser Oxford INCA Energy 250 EDS System during SEM analysis. The XRD spectra were recorded using an X-ray diffractometer system Righaku-Miniflex 300. The TGA–DTA analysis was carried out using Shimadzu DTG-60 simultaneous DTA–TG apparatus. The BET surface area analysis was carried out using a Surface Area Analyzer Model-SmartSorb 92/93.

The FT-IR spectrum of Ch (Figure 1(a)) shows characteristic broad peaks corresponding to O–H and N–H stretching vibrations in the region 3,300 cm⁻¹and 3,500 cm⁻¹, respectively (Savitri & Budhyantaro 2017; Jeyaseelan et al. 2018). The N–H bending vibrations were observed around 1,540 cm⁻¹. The C–H and the C–O stretching bands were obtained around 2,790 cm⁻¹ and 1,020 cm⁻¹, respectively. The FT-IR spectrum of SCC (Figure 1(b)) also shows the characteristic broad peaks that are analogous to that of Ch. Sharp peaks were found around 580–640 cm⁻¹, which corresponds to the presence of a sulphate group (Kahu et al. 2014; Jeyaseelan et al. 2018). In the FT-IR spectrum of SCC-B (Figure 1(c)), the region below 600 cm⁻¹ corresponds to the presence of quartz, i.e. Si–O–Si bonds. The bands appearing in the region around 678 cm⁻¹ refers to the presence of feldspar, i.e. Al–O–Si–O bonds, and those around 918 cm⁻¹ indicates the presence of Al–Al–OH bonds. The appearance of bands around 1,650 cm⁻¹ and 3,405 cm⁻¹ refer to the presence of adsorbed water (Grozdanov et al. 2016).

After adsorption of ARS (Figure 1(d), 1(f) and 1(e)) on these materials, the characteristic peaks of ARS were observed around 1,670 cm⁻¹, corresponding to the C=O group (Holmgren et al. 1997). The peaks of –NH₂ group has also been found to shift towards a higher wave number, indicating an interaction with the ARS molecule.

SEM micrographs (Figure 2) explore the surface morphology of the adsorbent material. The SEM image of pure Ch (Figure 2(a)) shows a degree of irregularity in the surface, as well as a denseness in the structure. After treatment with sulphuric acid (Figure 2(b)), a regular arrangement appears, with a smoothness and a rigidness in the structure that is maintained throughout. This may be due to the presence of cross-linking, which is responsible for the enhanced regularity and stability of the material. The SEM image of SCC-B (Figure 2(c)) shows the similar regularity and orderly structure with an illuminating layer above it. These bright areas are attributed to the alumina, silica and quartz groups present in the bentonite powder.

EDX spectrum of Ch (Figure 3(a)) clearly shows the peaks of three major components of Ch – carbon, nitrogen and oxygen. A peak of sulphur is clearly visible in the spectrum of SCC (Figure 3(b)), which confirms the cross-linking effect. The EDX spectrum of SCC-B (Figure 3(c)) shows the peaks of aluminium, silicon and sulphur along with that of carbon, nitrogen and oxygen, which indicates the formation of SCC- bentonite composite.

In the XRD pattern (Figure 4), the characteristic diffraction peaks of Ch (Figure 4(a)) were observed at 2θ = 10.94° and 21.8°, which are in accordance with the reported values (Kahu et al. 2014). The XRD spectra of SCC (Figure 4(b)) reveals the characteristic peaks at 2θ around 12.04° and 18.96°, which confirms the cross-linking effect of the sulphate group (Jeyaseelan et al. 2018). The peak at 2θ = 23.27° refers to structural change in the Ch polymer due to the formation of a cross-linked chain (Shekhawat et al. 2015). In the case of SCC-B, the XRD analysis helps to determine whether Ch has entered into the interlayer spacing of bentonite (Savitri & Budhyantaro 2017). The XRD pattern of pure bentonite exhibits a typical peak of montmorillonite at 2θ = 6.56°. After interaction of bentonite with Ch, there was a slight shift of peak towards the lower diffraction angle, thus obtaining a peak at 2θ = 5.94° (Figure 4(c)). This shift of peak may be attributed to a slight distortion of the intrinsic arrangement of the silicate layers and a decrease in the crystallinity of the molecule. These results confirm the incorporation of Ch into the interlayer spacing of bentonite (Huang et al. 2015). The peak at 2θ = 19.3° is a characteristic crystalline peak for the cross-linking phenomena (Huang et al. 2016), while the peak at 2θ = 24.93° is relative to Ch (Dotto et al. 2016).

Surface area analysis was carried out using the nitrogen adsorption–desorption method. The surface area of Ch, SCC and SCC-B were found to be 3.47 m² g⁻¹, 2.78 m² g⁻¹ and SCC-B was 6.01 m² g⁻¹. The decrease in surface area in SCC can be attributed to the cross-linking, leading to a reduction in cavities in the chitosan structure. The increase in surface area of SCC-B may be attributed to the binding of the bulky Si–O–Si groups and Al–O–Si–O groups to the surface of SCC. After adsorption of ARS, the surface area of each of the adsorbents was found to decrease. The surface area of chitosan and SCC were found to be below the detection limit of the instrument, while that of SCC-B was found to be 3.10 m² g⁻¹. This clearly indicates surface coverage of the materials by the adsorbent.

Thermal analyses of samples were carried out to study the thermal stability and decomposition temperature of the synthesized adsorbents. TGA–DTA analysis of Ch, SCC, SCC-B and pure bentonite was performed. The TGA curve of native Ch (Figure 5(a)) showed a two-step degradation, the first was around 50–100 °C, which corresponds to a loss of moisture, while the second degradation was at around 275 °C and continued up to 375 °C. The steep curve in this region indicates fast degradation, and above 400 °C the process slowed down with almost complete decomposition up to 1,000 °C. The DTA curve of Ch showed a strong and sharp exothermic peak at around 300 °C, which was attributed to its thermal decomposition. The TGA curve of SCC (Figure 5(b)) showed stepwise degradation, with a loss of moisture slowly up to 200 °C and two consecutive weight losses between 230 to 310 °C. The DTA curve shows two prominent endothermic peaks around 240 °C and 280 °C, respectively, which may be attributed to the degradation behaviour of the sulphate group and rearrangement reaction. In contrast to the exothermic peak obtained in the case of Ch, the SCC shows endothermic peaks, which indicate that SCC is less thermally stable due to the cross-linking effect of the sulphate group, which provides active sites for the uptake of dye molecules. Bentonite is thermally stable as an inorganic oxide and shows little degradation (Figure 5(c)), with a loss of moisture up to 100 °C and a loss of lattice water and removal of structural –OH groups at around 500 °C (Azzeddine & Abdelali 2014), with a small endothermic peak in the DTA curve. The TGA–DTA curves of SCC-B (Figure 5(d)) show characteristics of both SCC and bentonite. The degradation process involves a loss of moisture at around 100 °C. The composite prominently shows two endothermic peaks in the range 230–300 °C, which corresponds to the presence of SCC, and a small endothermic degradation around 500 °C, which corresponds to the presence of bentonite. This is a clear indication of the composite formation of the two materials.

The pH of the dye solution is an important parameter that significantly affects the adsorption mechanism and the interaction between the dye molecules and the adsorbent, especially when the dye under consideration is an indicator dye. The pH of solution also affects the surface charge of the adsorbent. The pH_PZC values for Ch, SCC and SCC-B were found to be 8.2, 4.6 and 5.3, respectively (Figure 7(a)). The pH of the dye solutions (Figure 7(b)) varied from 2.0 to 9.0, and all other parameters were kept constant in order to determine the pH for maximum removal efficiency of the adsorbent. For Ch, the removal efficiency was highest at pH 3.0 because the adsorbent surface has a positive charge and the adsorption of anionic dye is favoured at pH less than pH_PZC. However, the decrease in adsorption from pH 4.0 onwards clearly indicates that the electrostatic attraction is not the only interaction between Ch and ARS. In SCC, the surface positive charges are linked with sulphate groups and hence the adsorption efficiency has a negligible effect of pH over a wide range (Kahu et al. 2014). For SCC-B, maximum adsorption occurred at pH 8.0, indicating that the particles of the clay-building mineral (bentonite) possess negative surface charge. It was impossible to bond the dye by means of the electrostatic interaction with the mineral surfaces. The dyes were mainly bonded with the hydrogen bonds, in which the –OH, –NH and –NH₂ groups acted as the proton donors and the –SiO and –Al₂OH groups played the role of the proton acceptors. The studied dyes could also be bound due to the interactions of the hydrated interlayer Ca²⁺ ions. Similar observations have been reported for smectite clay (Kyzol-Komosińska et al. 2014). The proposed mechanism (Figure 6) for the uptake of ARS dye by Ch, SCC and SCC-B is depicted by the following scheme (Zhang et al. 2016).

The pH of 3.0 was selected for Ch, pH 8.0 was selected for SCC-B, but for SCC, the solution pH of dye (pH 6.5) was kept as it is. These pH conditions were used in all further studies.

The contact time (Figure 7(c)) of dye solution with adsorbent material was varied from 10 to 60 min. The optimum pH of the dye solution was set initially according to the type of adsorbent used, as discussed in the previous section. It was observed that, with an increase in contact time the adsorption efficiency of adsorbent increased, but the increase in adsorption became less significant later due to blocking of the available sites by the dye molecules. The equilibrium was attained at around 40 min for each adsorbent and hence the contact time of 40 min was fixed and further parameters were studied.

The adsorbent dose (Figure 7(d)) varied from 100 to 500 mg. It was observed that, with an increase in the amount of adsorbent, efficiency of adsorption increased due to more availability of active sites on the surface of the adsorbent. For Ch, SCC and SCC-B, equilibrium adsorption was attained at 200 mg dose and hence it was optimized for the further studies.

The adsorption studies were carried out by varying the initial concentration (Figure 7(e)) of the dye solution from 50 to 500 mg L⁻¹ for each of the adsorbents used and the optimized values of all other parameters. A steady decrease in the adsorption efficiency was observed with an increase in dye concentration for all the adsorbents used. This is due to the number of active sites on the surface of the adsorbent continuously being blocked by the incoming dye molecules and the number of sites becoming available is insufficient for the large number of dye molecules, and hence adsorption efficiency decreases.

Temperature studies (Figure 7(f)) were carried out by varying the temperature of the adsorbate–adsorbent system from 30 °C to 60 °C. There was a steady decrease in the adsorption efficiency with the rise in temperature from 30 °C to 60 °C for all three adsorbents studied. The results obtained were consistent with the observation that with an increase in temperature, adsorption decreases. Lower temperature favours adsorption, while higher temperature favours desorption.

Adsorption isotherms are essential in order to study the interaction between the adsorbate and adsorbent molecules. It describes the fraction of sorbate molecules that are partitioned between liquid and solid phases at equilibrium (Boparai et al. 2011). A number of adsorption isotherm models are available to understand the mechanism of adsorption, such as Langmuir, Freundlich, Redlich–Peterson, Halsey, Dubinin–Radushkevich etc. In the present work, four isotherms were studied quantitatively for each of the adsorbent used. The studies were carried out at optimum conditions by varying ARS concentrations from 50 to 500 mg L⁻¹.

The graphs for each of the adsorbent (Ch, SCC and SCC-B) showing the application of the above-mentioned isotherm models are provided in the supplementary materials (Supplementary Figures 2–4). The various constants associated with each of the above-mentioned isotherm models are listed in Table 1, along with the values of correlation coefficient.

From Table 1, it can be concluded that the Freundlich as well as the Halsey isotherm models were followed by all the adsorbents. Both of these models assume multilayer adsorption on heterogeneous adsorbent surface. The R–P isotherm also holds good for the adsorbents used. The R–P model is highly versatile because it can be used in both homogeneous and heterogeneous systems. The maximum adsorption capacity in accordance with the Langmuir isotherm was found to be 42.48 mg g⁻¹ for the ARS-Ch system, 109.12 mg g⁻¹ for the ARS-SCC system and 131.58 mg g⁻¹ for the ARS-SCC-B system. These observations are in correlation with the SEM micrographs shown in Figure 2 and the BET surface area analysis. For native Ch, the adsorbent surface was found to be dense with a relatively lower surface area. The morphology was found to become more folded in SSC. However, the surface area was found to decrease due to the cross-linking phenomenon. The adsorption capacity was found to increase due to the fact that cross-linking leads to trapping of dye molecules (Jeyaseelan et al. 2018) for SCC-B, the morphology became more porous with bentonite–Ch composite formation. This led to an increased surface area and an increased adsorption capacity.

In order to understand the mechanism of the adsorption process, two kinetic models, namely pseudo-first-order and pseudo-second-order, were used. The best-fit model was assessed on the basis of the value of linear coefficient of determination (R²). In order to check if diffusion process was involved, the Weber–Morris model of intra-particle diffusion was studied (Figure 8). These studies were carried out at optimized values of all parameters for the adsorbent applied.

Regarding the suitability of pseudo-first-order model, it is evident from the values of R² and the poor agreement between the q_e (exp) and q_e (cal) values that it is not the best-fit model (Table 2). On the contrary, the R² values obtained by pseudo-second-order model were 1.00 fit in case of all three adsorbents. The q_e (exp) and q_e (cal) were also in close association compared to the former model. This suggests that the pseudo-second-order model is best-fit for all three adsorbents.

It has been suggested that the overall rate of adsorption can be described by the following three steps (Boparai et al. 2011; Chingombe et al. 2006): (1) film or surface diffusion, where the sorbate is transported from the bulk solution to the external surface of sorbent, (2) intra-particle or pore diffusion, where sorbate molecules move into the interior of sorbent particles and (3) adsorption on the interior sites of the sorbent. Since the adsorption step is very rapid, it is assumed that it does not influence the overall kinetics. The overall rate of adsorption process, therefore, will be controlled by either surface diffusion or intra-particle diffusion. The Weber–Morris intra-particle diffusion model (Figure 8) has often been used to determine if intra-particle diffusion is the rate-limiting step (Kavitha & Namasivayam 2007; Taqvi et al. 2007; Wu et al. 2009).

As suggested by Ozcan et al. (2007) in his work, a plot of q_t versus t^1/2 should be linear if intra-particle diffusion is involved in the adsorption process, and if the plot passes through the origin then intra-particle diffusion is the only rate-limiting step. It has also been suggested that in instances when q_t versus t^0.5 is multi-linear, two or more steps govern the adsorption process (Unuabonah et al. 2007; Wu et al. 2009). The initial steeper section represents surface or film diffusion, the second linear section represents a gradual adsorption stage where intra-particle or pore diffusion is rate-limiting and the third section is the final equilibrium stage. As the plot did not pass through the origin, intra-particle diffusion was not the only rate-limiting step. Thus, apart from intra-particle diffusion, some degree of boundary layer diffusion also affected the adsorption process.

The effect of temperature on the adsorption process of ARS with different adsorbents was studied to obtain the thermodynamic parameters that decide the spontaneity and feasibility of the process. These parameters can be easily determined from the thermodynamic equilibrium constant, K.

With reference to Table 3, the negative values of ΔG for all three adsorbents indicate that the process of adsorption of ARS is spontaneous in nature. The negative values of ΔH for all three adsorbents shows that the process is exothermic and the negative values of ΔS indicates that the randomness in the moieties is decreasing as adsorption of dyes on the surface of the adsorbent molecules progresses. As can be seen from Table 3, as the temperature increases from 303 to 333 K, the ΔG values become less negative, indicating that adsorption capacity decreases with an increase in temperature.

Adsorption using column is one of the most common and efficient way for removal of pollutants from water (Gupta et al. 2016). However, it is worth noting that it may be helpful that before evaluating the feat of adsorbent in a fixed-bed adsorber, adsorption isotherm studies such as batch experiments were conducted to calculate the maximum adsorption capacity of the adsorbent (Al-Degs et al. 2009). Columns have an advantage over batch because a continuous flow is maintained over a fixed-bed, thereby increasing the adsorbent capacity, which is contrary to batch where the concentration gradient between adsorbent and adsorbate decreases with time (Anderson et al. 2012). A plot of C_C/C_o against volume of ARS solution (Supplementary Figure 7) eluted was plotted to determine the values of various column parameters.

It can be observed from Table 4 that the exhaustion capacities of all three materials are higher than adsorption capacities obtained in batch studies. Due to this, larger sample volumes (exhaustion volume) can be treated with column compared to batch studies.

ARS is a potent water pollutant. Three adsorbents, namely Ch, SCC and SCC-B were used for the removal of ARS using batch and column adsorption methods. All adsorbents were extensively characterized using various spectral techniques, such as FT-IR, SEM, EDX, XRD, BET and TGA-DTA analysis, to confirm the nature and presence of different active sites. Parameters such as pH_PZC of adsorbent, pH of dye solution, contact time, adsorbent dose and temperature were optimized to obtain a maximum removal efficiency. Four adsorption isotherms models were studied, namely Langmuir, Freundlich, Halsey, and R–P. Maximum adsorption capacity was found to be 42.48 mg g⁻¹ for Ch, 109.12 mg g⁻¹ for SCC and 131.58 mg g⁻¹ for SCC-B. This was the expected result because the introduction of new groups impart newer active sites on the surface of the polymer, which leads to binding of large numbers of dye molecules. For SCC-B, the surface is modified by both cross-linking by sulphate group and physical adherence of clay molecules, and hence it showed good adsorption properties with maximum removal capacity. Adsorption kinetics was best-fitted with the pseudo-second-order model and showed high correlation coefficients, R² ≥ 0.9999 for all the three adsorbents. An intra-particle diffusion model was also studied to determine the course of adsorption and its mechanism. Adsorption thermodynamics showed that the process occurs spontaneously, as shown by the negative values of change in free energy with release of heat (exothermic). Column studies were also carried out to evaluate the column parameters. From the values of exhaustion capacity, it was found that the column adsorption method is more suitable for large sample volumes compared to the batch adsorption method. A comparison of these three materials with other materials towards removal of ARS is presented in Table 5. It is clear from the table that SCC and SCC-B are excellent adsorbents for ARS, with higher adsorption capacities compared to most of Ch-based materials reported in literature.

The authors are thankful to RTM Nagpur University, Nagpur and PG Department of Chemistry for providing all the necessary facilities for the research work. Special thanks to Dr S. Kahu and Dr A. Shekhawat for helping in calculation work, writing style and proofreading.

This work was supported by Department of Science and Technology (DST), New Delhi under the DST INSPIRE Fellowship Program [Sanction order no. DST/INSPIRE Fellowship/2017/IF170496 dated 16 July 2019] and RTM Nagpur University under University Research Scheme.

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