Delonix regia seed pod—an efficient biosorptive candidate toward the removal of Rhodamine B from simulated wastewater: characterization, kinetics, and equilibrium approach

Abstract This study focused on the comparative analysis of biosorption performance of Delonix regia seed pod toward the removal of Rhodamine B (RB) from simulated solution using native (DRSP) and chemically treated form (ADRSP). The surface morphology, structural analysis, textural properties, and thermal analysis of DRSP and ADRSP were examined using scanning electron microscopy (SEM), BET analysis, Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), respectively. FTIR analysis concluded that surface functional groups like hydroxyl –OH stretching, C–N stretching, and C = C stretching of the aromatic ring were largely responsible for the attachment of RB. The chemical treatment enhanced the surface morphology of D. regia seed in terms of heterogeneity, distinct depth cavities, and irregular pores responsible for RB biosorption. The biosorption of RB was investigated using parametric analyses such as solution pH, biosorbent dosage, contact time, initial RB concentration, and operating temperature. The obtained equilibrium data were fitted with different isotherm and kinetic models. Langmuir isotherm model and pseudo-second-order kinetic were well suitable for the biosorption of RB using DRSP and ADRSP. The maximum monolayer biosorption capacities (mg/g) of DRSP and ADRSP were predicted to be 39.37 and 60.61, respectively. Using thermodynamic principles, the removal of RB was found to be thermodynamically feasible, endothermic, and spontaneous process. The results of the present study proved that DRSP and ADRSP can be identified as promising biosorbents for the removal of RB. NOVELTY STATEMENT The potential utilization of Delonix regia seed pod (native and chemically treated forms) for the removal of Rhodamine B (RB) from simulated water. Surface morphology, surface area, functional analysis, and thermal analysis of both native (DRSP) and treated forms (ADRSP) to understand materials properties before biosorption of RB. Parametric effects of dosage, initial pH, initial pollutant concentration, and temperature on biosorption capacity and biosorption (%) using native and treated forms of bisorbents. Implantation of different kinetic models and two-parameter isotherm models to examine the feasibility and type of biosorption. The maximum biosorption capacity (mg/g) of DRSP and ADRSP is predicted to be 39.37 and 60.61 using the Langmuir isotherm model, respectively. Identification of possible biosorption mechanism using the functional group analysis. Negative values of Gibbs free energy change ( and positive values of entropy change ( enthalpy change ( demonstrating the thermodynamic feasibility, increase in randomness at the solid-liquid interphase and endothermic biosorption


Introduction
Previous literature reported that about 36,000 L of water consumed by different industrial sectors for the production of 20,000 lbs of fabric per day (G€ uyer et al. 2016). About 40,000 industrial synthetic dyes are actively involved in various dyeing sectors namely textile, paper, plastic, rubber, plastic, and cosmetic containing different synthetic dyestuffs namely methylene blue, malachite green, Rhodamine B (RB), etc. As per the statement of the United States Environmental Protection Agency (USEPA), the disposal of wastewater from dyeing industries is classified into four categories: (i) high volume of effluent, (ii) dispersible, (iii) hazardous wastes, and (iv) hard to treat (Dasgupta et al. 2015). The discharged effluent creates a pollutant load of 450,000 tons per annum (Forgacs et al. 2004) in various processing/ industrial units are the primary factor responsible for causing societal threats in the ecological system (Shen and Gondal 2017). The discharged wastewater containing even a trace quantity of dyestuff create a contamination in both aquatic system and human beings (Fazal et al. 2018).
Rhodamine B (RB) is an organic salt dye which is belonging to the category of neurotoxic and carcinogenic dye. It is widely applied in various industrial fields due to the excellent water solubility, high stability, and non-biodegradability (Hamdaoui 2011). It is used in the preparation of paints, ball pens, dye lasers, leather, stamp pad inks, carbon sheets, fireworks, and crackers (Imam et al. 2020). It can be employed as a tracer to understand the direction and flow rate of fluid flow. It is also used as a probe in various biotechnological applications because of its amphoteric role in shifting fluorochromes to fluoroprobes, histological nature, and cost-effectiveness. Even though the increase in applications of RB in the various industrial sector, the discharge of effluent containing RB has greater chemical/biochemical oxygen demand, intense color constituents, and toxic aromatic components which could adversely affect both aquatic and human health (Selvakumar and Rangabhashiyam 2019). The maximum allowable concentration quality standard of RB in the discharged wastewater was reported to be 140 mg/L (Skjolding et al. 2021). It causes a severe damage to the reproductive system, irritation in the eyes, infection in the respiratory tract and gastrointestinal tract, etc. for both animals and human beings (Hamdaoui 2011;Ahmad Bhat et al. 2020). The presence of high organic loading in the discharged RB effluent provides a minimum quantity of dissolved oxygen requirement lowering the critical level for respiration and also reducing the intensity of sunlight penetration for the growth of the aquatic living system (Aksu 2005). Therefore, the discharge of untreated industrial effluent containing RB from various industrial sectors must be properly treated before the discharge (Selvakumar and Rangabhashiyam 2019).
In the last few years, there was an increase in technology development and promising strategies for the removal of pollutants from wastewater. Various treatment methods namely biosorption, filtration, coagulation, flocculation, advanced oxidation, filtration, and aeration have been tried for the removal of pollutants from the discharged effluent (Rangabhashiyam et al. 2018). Most of these treatment methods other than biosorption had several limitations for the removal of toxic pollutants due to more energy consumption, high treatment cost, formation of toxic sludge, less removal efficiency of pollutant, less selectivity, and increase in chemical consumption. These limitations can be overcome by the introducing a suitable cost-effective and feasible process with efficient technology for treating the effluent.
Nowadays, the biosorption technique has been attracted by various researchers for the removal of various pollutants from wastewater because of its intense removal of pollutants, cost-effective, simple process, less operating cost, re-usability of material, and negligible sludge generation (Mathivanan et al. 2021). The various bio sorbents namely agricultural residues, cost-effective ligno-cellulosic biomass, and microbial biomass were effectively utilized in the pollutant removal. Among these, cost-effective lignocellulosic biomass was predominantly chosen due to the following reasons: (1) easy availability; (2) excellent surface morphology containing porous, cavity, and rough structure; (3) essential functional groups namely hydroxyl, carboxyl, and other functional groups responsible for the effective attachment of pollutant on the surface of the bio sorbent; (4) after regeneration, it can be used as a fertilizer in the agricultural field due to biodegradability; (5) chemical composition (Wahab et al. 2010;Dai et al. 2018). Various forms of lignocellulosic biomass namely native, treated, char, activated carbon from biomass and commercial activated carbon were significantly involved in the treatment of wastewater during biosorption (Forgacs et al. 2004;Selvakumar and Rangabhashiyam 2019).
Different treatment methods namely (i) physical/mechanical method; (ii) thermal method; (iii) chemical method using alkali/acid/salt/other chemical substance; (iv) biological method and (v) combination of two (or) more treatment approaches involved in the surface modification of biomass before biosorption (Abegunde et al. 2020). This surface modification creates a suitable change in the surface of the material by altering the density, solubility, thermal degradation temperature, functional group distribution, surface charge, surface energy, roughness, cavity, heterogeneity, surface area, hydrophobicity, and reactivity to enhance the textural, thermal and structural properties for the better attachment of pollutants from simulated solution during the biosorption (Abegunde et al. 2020;Patra et al. 2021;Chandrasekar et al. 2022;Kumar et al. 2022;Shahnaz et al. 2022). Among the various treatment methods, chemical treatment could be preferred by largely in the modification of biosorbents since it directly interacts with the surface chemistry of the selected material (Abegunde et al. 2020). Also, it is used to remove the impurities and other non-cellulosic components from the surface of the material to provide a suitable surface area, surface morphology (cavities, porous, and heterogeneity), re-usability, and grater biosorption capacity (Abegunde et al. 2020). The various chemical agents including acid, alkaline, neutral solutions, salt and other chemical substances employed to improve the physico-chemical characteristics of biosorbents in recent years (Senturk et al. 2010;Vieira et al. 2010).
In this study, pretreatment was performed by introducing sulfuric acid into Delonix regia seed pod powder before the biosorption. The comparison of biosorption capability of native D. regia seed pod (DRSP) and chemically treated D. regia seed pod (ADRSP) were examined for the removal of RB during the biosorption. The material properties of DRSP and ADRSP namely functional group analysis, surface morphology, thermal properties, and surface area were evaluated by various instrumentation techniques. The parametric analysis namely solution pH, biosorbent dosage, initial concentration, and temperature on biosorption capacity and biosorption (%) was performed compared using DRSP and ADRSP and the obtained results were compared to check the better performance of the material. The thermodynamic analysis was employed to understand the feasibility, spontaneous and endothermic nature of the biosorption process. The possible biosorption mechanism was identified for the attachment of RB using functional group analysis. To the best of our knowledge, the comparative analysis of biosorptive performance of DRSP and ADRSP toward the removal of RB from an aqueous solution has not been previously demonstrated.

Biosorbent preparation and characterization
The matured and fallen D. regia seed pod, as lignocellulosic biomass used in this study was collected from SASTRA Deemed University, main campus, Thanjavur, Tamil Nadu, India (10 43 0 40.5 00 N 79 01 0 05.6 00 E). The collected sample was repetitively washed with distilled water to remove the impurity and dust particles. Afterward, the sample was converted into small pieces and sun-dried on the open terrace for 2 days. It was again subjected to oven drying at 70 C to remove the moisture content associated with it. Then the dried sample was ground into powder and passed through a laboratory sieve shaker to collect the desired range of average biomass particle size (BSS#-12 þ 14; average particle size: 1.3 mm). The portion of the powdered sample was stored in an air-tight container, called a native sample (DRSP). The remaining portion of the sample was subjected to the chemical treatment using sulfuric acid, in which the biomass was soaked with 1 M sulfuric acid at the concentration of 1:2 (w/v). The sample was kept in an orbital shaker for 2 h at room temperature. After treatment, the sample was drained using running water for a long time to remove the excess acid associated. It was continued till the drained water pH reaches the neutral pH. Finally, the sample was subjected to a hot air oven at 70 C for drying. Then dried sample after acid treatment is termed as ADRSP. Both samples were stored in an air-tight container for further studies.

Properties of biosorbent
The specific surface area, pore diameter, pore volume, and porous information of DRSP and ADRSP were evaluated using the BET apparatus (Make: Micrometrics, Model: ASAP 2020). The samples were subjected to degassing for 5 h at 200 C under vacuum conditions before conducting the analysis using nitrogen gas (Sivaraman et al. 2022).
The morphological characteristics of DRSP and ADRSP before and after biosorption were evaluated using Scanning Electron Microscopic analysis (VEGA3 XM, TESCAN USA, Inc.). The functional group distribution in the prepared biosorbent (before and after biosorption) was analyzed using Fourier Transformed Infrared Spectroscopy (PerkinElmer Spectrum, Version 10.03.09, Spectrometer, transmittance mode) with the KBr pellet method. For FTIR analysis, the spectrum was recorded in the transmittance mode with wavenumbers ranging from 4000 to 400 cm À1 . The thermal stability of both DRSP and ADRSP (before and after biosorption) was investigated using thermogravimetric analysis, TGA-DSC (SDT Q600 V20.9 Build 20). In this, the samples were subjected to the heat treatment under a nitrogen atmosphere from 25 to 900 C at a constant rate of 20 C per min. The data analysis for (%) weight loss of the sample as a function of operating temperature ( C) was used to understand the thermal stability (Mathivanan et al. 2021).

Zero-point pH charge (pHzpc)
The zero-point pH charge is used to examine the net electrically neutral charge on the surface of the biosorbent at a particular point of pH (Selvakumar and Rangabhashiyam 2019). In this, about 50 ml of potassium nitrate (0.1 M) was taken in a 250 ml conical flask. The initial pH of the working solution was adjusted from 2.0 to 10.0 using 0.1 N sulfuric acid/sodium hydroxide, followed by the addition of 0.1 g of DRSP and ADRSP in separate conical flasks. The sample was kept in an orbital shaker for 24 h with a shaking speed of 150 rpm and the final solution pH was determined for each sample. The difference in solution pH level (DpH ¼ pH final À pH initial ) was plotted against the initial solution pH. The data point at which the intersection of change in solution pH at X-axis (i.e., DpH ¼ 0) is zeropoint pH charge (pHzpc).

Preparation of sorbate
The stock solution was prepared by the addition of 1.0 g RB in 1 L distilled water with a stock concentration of 1 g/L. The different concentration of RB solution was made by the dilution of the stock solution by the addition of a suitable volume of distilled water. The chemical formula for RB is C 28 H 31 ClN 2 O 3 (IUPAC Name: 9-(2-Carboxyphenyl)-6-(diethylamino)-N,N-diethyl-3H-xanthen-3-iminium chloride; category: xanthene dye, molar mass: 479.02 g/mol, maximum wavelength: 555 nm; melting point: 210-211 C).

Batch biosorption experiment for RB removal
Batch experiments were investigated in 50 ml working volume in a 250 ml stopper conical flask, shaking in an orbital shaker at 120 rpm to explore the biosorption performance of DRSP and ADRSP toward the removal of RB from the simulated solution. After biosorption, the liquid sample was carefully withdrawn using a plastic pipette to avoid/minimize the carryover of biosorbent particles into the Eppendorf tube. The liquid sample was subjected to centrifugation (5000 rpm,10 min) and the collected supernatant was then filtered using Whatman filter paper (filter paper No. 42). The residual concentration of RB in the supernatant solution was evaluated by measuring the absorbance unit (A.U) using the spectroscopic method (UV-Vis Spectrophotometer, Systronics 2201) with characteristic wavelength (k max ¼ 555 nm) for RB. The obtained absorbance unit was converted into a concentration unit (mg/L) using calibration experiments. If the sample absorbance unit is more than unity, the sample was suitably diluted using distilled water, and the dilution factor was included for the determination of RB concentration.
The amount of biosorbate adsorbed over the biosorbent was determined using the component material balance. The equilibrium biosorption capacity and biosorption (%) for DRSP and ADRSP toward the removal of RB were determined by the followings (Selvakumar and Rangabhashiyam 2019): Where, C L, i ¼ Initial concentration of RB in the L-phase (mg/L); C L, eq ¼ Equilibrium concentration of RB in the Lphase (mg/L); M ¼ mass of biosorbent (g); V L ¼ working volume of sample (L) The biosorption efficiency (%) of RB was expressed as follows: (Mathivanan et al. 2021):

Factors affecting biosorption of RB
The different factors such as initial solution pH (2-10) and biosorbent dose (0.4-3.6 g/L) on biosorption capacity and biosorption (%) were investigated to identify the initial solution pH and dosage. The effect of contacting time on the biosorption capacity for both DRSP and ADRSP toward the removal of RB was performed using a different initial concentration of RB (10-50 mg/L) and temperature (30-50 C) to evaluate the kinetic and equilibrium parameters using kinetics and equilibrium models. To understand the fitness of experimental data with kinetic and equilibrium models, the residual RB concentration was measured as a function of time till the equilibrium has been attained. The kinetic models namely pseudo-first-order, pseudo-second-order, and intra-particle diffusion and equilibrium isotherm models such as Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich were employed to check the feasibility and type and controlling step of biosorption. Using the Langmuir model, the maximum possible biosorption capacity of DRSP and ADRSP were predicted for the removal of RB to know the suitable form of biosorbent.

Statistical analysis
All the experiments were carried out in triplicates and data were shown with mean ± SD. Using the statical software, Minitab (Version 15), the statistical significance of experimental data was analyzed by the Tukey test with one-way ANOVA and pairwise comparisons. A statistical significance test was performed with a significance level (a) of 0.01. If the probability value significance level (a), the difference between mean values was statistically significant and vice versa. The co-efficient of determination (R 2 ) was used to examine the accuracy of experimental data with the proposed model.

Results and discussion
Characterization

BET analysis
To examine the biosorption potential of DRSP and ADRSP, BET analysis was performed to determine specific surface area and average pore volume. The biosorption and desorption isotherm profile of nitrogen and differential pore volume (cm 3 /g nm) vs. pore diameter (nm) plot were illustrated in Figure 1 to the understand the presence of specific surface area and pore volume. The isotherm profile illustrated a type IV with H3 type hysteresis loop for both DRSP and ADRSP. Such kind of loop and characteristic isotherm is describing the possibility of mono and multi-layer biosorption on the surface with pore width ranging from 2 and 50 nm. Moreover, these results illustrated the presence of the aggregation of slit-shaped pores of platy particles containing slit-shaped pores (Shahnaz et al. 2022). Using BET analysis, the surface area analysis of DRSP and ADRSP were found to be 2.4121 and 21.6722 m 2 /g, respectively.
Biosorption average pore width (4 V/A by BET) using DRSP and ADRSP were determined 13.41125 and 10.355 nm, respectively. Using single-point adsorption analysis, the total pore volume of DRSP (<359.5699 nm diameter at P/P o ¼ 0.9946) and ADRSP (<375.3023 nm diameter at P/P o ¼ 0.9948) were found to be 0.008087 and 0.056109 cm 3 / g, respectively. Using t-plot, the microporous volume of DRSP and ADRSP were observed to be 0.000363 and 0.001984 cm 3 /g, respectively. The plot of differential pore volume vs. pore diameter ( Figure 1b) indicates that there were significant peaks appeared between 1 and 50 nm pore diameter demonstrating the presence of a huge number of micropores and mesopores in the materials. It is also noticed that the specific surface area of ADRSP is found to be 8.98-folds more than DRSP. Hence, the specific surface area was significantly improved by the chemical treatment of biomass residue. Table 1 presents the comparison of DRSP and ADRSP using BET analysis.
Thermal gravimetric analysis Thermal degradation profiles for both DRSP and ADRSP were examined using the residual mass of the sample as a function of temperature by the gravimetric method. Different stages of thermal degradation were observed due to the presence of moisture content, cellulose, hemicellulose, and lignin in the biomass (Paduraru et al. 2015). In addition, thermal degradation for biomass is also greatly influenced by chemical composition, particle size, degree of crystallinity, distribution of functional groups, and structural behavior (Mathivanan et al. 2021). Figure 2 illustrates the thermal gravimetric analysis of DRSP and ADRSP. It is noticed that the thermal degradation profile for DRSP and ADRSP were found to be slightly different. There are four stages of weight loss (%) visualized in TGA demonstrating (i) moisture removal, (ii) breaking of the polymeric component into monomeric form by the cleavage of glycosidic linkages, (iii) breaking of inner glycosidic linkages and backbone structure of the lignocellulosic contents, (iv) char forming residues (Mathivanan et al. 2021). Based on the findings, it is observed that the thermal stability of ADRSP using chemical treatment is greatly improved than DRSP due to the increase in char (%). The obtained results were comparable with previous findings (Rangabhashiyam and Selvaraju 2015a;Mathivanan et al. 2021).

Surface morphology
The surface morphology of biosorbent is an essential factor that could influence the biosorption process. Figure 3 shows the SEM images of both DRSP and ADRSP (before and after biosorption 10 kÂ magnifications (average particle size scale: 5 lm). It is noticed that SEM photographs for DRSP revealed a rough surface containing irregular shallow cavities with different shapes and sizes without an open pore structure. It is observed that the surface morphology of ADRSP (after chemical treatment) was significantly different from that of DRSP (native sample). The greater degree of heterogeneity and roughness with distinct depth cavities in ADRSP might be due to the release of trace amounts of pectin and other cellulosic components from the surface of biomass during the chemical treatment (Ali et al. 2016). The chemical treatment is the main factor that is responsible for the development of porosity and cavity on the surface of D. regia seed pod. The attachment of RB on the surface of DRSP and ADRSP was observed by the slight variation in surface morphology in terms of reduction in cavities, decrease in pore size, and accumulation of pollutants as shown in Figure 3.
Surface functional analysis by FTIR spectra Figure 4 demonstrates the distribution of functional groups on the surface of both DRSP and ADRSP before and after biosorption. It is observed that the strong and broad bands appeared at 3441 and 3423 cm À1 due to the presence of aliphatic -OH stretching in DRSP and ADRSP, respectively (Meng et al. 2014). The presence of -CH stretching vibration of methylene group in both DRSP and ADRSP were identified at 2926 and 2924 cm À1 , respectively (Mahalakshmi  and Saranaathan 2019). There was a new peak that appeared at 2855-2857 cm À1 in ADRSP indicating the CH stretching vibration indicating the presence of the methoxyl group (Oyekanmi et al. 2019). This might be possible due to the removal of lipids and lignin contents on the surface of biomass after the chemical treatment (Oyekanmi et al. 2019) and 1383 cm À1 describes the presence of CH bending of aldehyde and alkane (Selvakumar and Rangabhashiyam 2019). There was broadband available at 1643 cm À1 and 1600 cm À1 explaining the stretching of amid-I in the protein peptide bond in both DRSP and ADRSP (Rangabhashiyam et al. 2018). There was a new steep peak arrived at 1453-1455 cm À1 for ADRSP (before and after RB loading) demonstrating the presence of -COOin the carboxylate functional group (Rangabhashiyam et al. 2018). The presence of C-N stretching in both DRSP and ADRSP were identified between 1111 and 1114 cm À1 (Shahnaz et al. 2022). In addition, this band is completely disappeared due to the attachment of RB with ADRSP. During the acid treatment, pectin and some organic substances were removed (Thirumavalavan et al. 2011). It was noticed that a slight variation in FTIR spectra of DRSP was observed in terms of position, variation in intensity, and elimination of some functional groups in ADRSP as compared to DRSP (Table  2). By comparing the FTIR spectra of ADRSP with DRSP, the higher absorption intensity of -OH functional group identified in ADRSP than DRSP due to the presence of more carboxyl and hydroxyl groups after chemical treatment (Thirumavalavan et al. 2011). For further confirmation, presence of medium after treatment containing pectin extracted from biomass was confirmed by functional group  analysis (He et al. 2021). Figure S1 shows the FTIR spectra of extracted pectin in the liquid phase after chemical treatment of D. regia seed pod. The characteristic peaks around at 1632 and 1750 cm À1 corresponding to the stretching of free carboxylic groups and stretching of the methyl-esterified carboxyl groups (C¼O) indicate the presence of pectin (He et al. 2021).

Factors influencing biosorption capacity and percentage biosorption
Zero-point pH charge Figure 5 demonstrates the effect of initial pH on change in solution pH for both DRSP and ADRP to determine pH-Zero Point Charge (pH PZC ). The pH PZC values for DRSP and ADRP were found to be 7 and 6, respectively. If the solution pH is lower than pHzpc, the surface of biosorbent could be protonated that is favoring the attachment of anionic pollutants. Above the pHzpc, the surface could be negatively charged encouraging the binding of cationic pollutants from the aqueous solution (Rangabhashiyam and Selvaraju 2015a;Mathivanan et al. 2021).

Initial solution pH
Initial solution pH is the crucial parameter influencing the biosorption capacity and biosorption (%) for the removal of pollutants from the aqueous solution. It also affects the ionization potential of pollutant molecules, degree of   protonation/deprotonation on the surface of biosorbent, and distribution of functional groups, resulting in the variation of the affinity of the pollutant over biosorbent (Rangabhashiyam et al. 2018). Figure 6 illustrates the influence of initial solution pH (3.0-10.0) on biosorption capacity and biosorption (%) for RB removal using both DRSP and ADRSP. As the initial solution pH changed from 3.0 to 5.0, biosorption capacity and biosorption (%) were significantly increased to the maximum level till pH 5. It is also noticed that biosorption (%) is increasing to pH 5 followed by a slight reduction in the removal (%) at pH 6 and then slightly increased to pH 7. There is no significant variation in biosorption capacity and biosorption (%) for the removal of RB using both DRSP and ADRSP observed for the solution pH ranging from 7.0 and 8.0. Using Tukey pair-wise comparison test, the following results indicate the difference in the mean value of biosorption (%) between two different pH levels using a 99% level of significance with a two-sided confidence interval: (i) between pH 5 and 6 (adjusted p ¼ 0.032 for DRSP; adjusted p ¼ 0.215 for ADRSP); (ii) between pH 6 and 7 (adjusted p ¼ 0.574 for DRSP; adjusted p ¼ 1.000 for ADRSP); (iii) between pH 5 and 7 (adjusted p ¼ 0.662 for DRSP; adjusted p ¼ 0.381 for ADRSP). In the statistical analysis, the overall biosorption (%) varied within a 1% level of significance, which is also a 95% of confidence level between 5 and 7. In grouping analysis, the initial pH 5 was found to contain maximum biosorption (%) resulting in the maximum biosorption capacity. Under this condition, the maximum biosorption capacity of 2.38 mg/g (DRSP) and 3.98 mg/g (ADRSP) with corresponding biosorption (%) of 57.36 (DRSP) and 98.29 (ADRSP) were identified and used in the further studies. The binding forces namely electrostatic interaction, hydrogen binging, and p-p interaction are contributed to the attachment of pollutants on the surface during the biosorption. The slight reduction in biosorption (%) between 5 and 7 might be the possibility of a minimum contribution of electrostatic forces as compared to other binding forces since the solution pH was very close to pHpzc for DRSP and ADRSP and hence the entire biosorption process might not be controlled by electrostatic interaction in this region (Xiao et al. 2020). It is also noticed that the biosorption performance of ADRSP was found to be greater than DRSP. The obtained results were supported by previous findings. Ding et al. (2014) reported that the effect of solution pH on the RB biosorption process is a complex process. Largura et al. demonstrated that there was an increase in biosorption (%) of RB by increasing the solution pH with the existence of electrostatic interaction (Largura et al. 2010). Wang and Zhu demonstrated the minimum effect of solution pH on RB biosorption since it was induced also by the presence of different functional groups on RB (Wang and Zhu 2007). However, Jain et al. (2007) illustrated the increase in RB biosorption (%) by lowering the solution pH.

Biosorbent dosage
Dosage is an essential factor for the biosorption of pollutants from an aqueous solution. It also describes a chemical equilibrium between the liquid phase and the solid phase. To know the suitable dosage, conventional batch experiments were carried out by varying the dosage from 0.4 to 3.6 g/L, with a fixed initial RB concentration of 10 mg/L and pH 5.0. Figure 7 illustrated the effect of the dosage on biosorption (%) and biosorption capacity (mg/g). It is noticed that the biosorption (%) was found to be increased and then reached the maximum at 3.2 g/l for the removal of RB using DRSP and ADRSP. It was noticed that above 2 g/L, there was a slight reduction in biosorption capacity of DRSP and ADRSP for the removal of RB observed. When the dosage size varied from 0.4 to 2 g/L, the biosorption capacity rapidly decreased. In the final stage, there was a reduction in RB loading on the surface due to the following reasoning: (i) saturation of binding sites on the surface (ii) aggregation of biosorbent resulting in a decrease in total surface area and an increase in the diffusion distance for pollutant (Ansari and Malik 2007). Based on the maximum value of biosorption (%), the dosage of 3.2 g/L was identified for biosorption of RB using DRSP and ADRSP in successive batch biosorption experiments.

Effect of contacting time and RB concentration on biosorption capacity
Contacting time is an important factor in biosorption since the obtained experimental data is useful and employed in the various kinetic and equilibrium models to evaluate the kinetic constants and equilibrium parameters, respectively. The mechanism for the interaction of pollutants with the solid phase, the feasibility of the process, and the type of biosorption could be identified using the kinetic and isotherm models. The influence of contact time on biosorption capacity was investigated using different initial RB concentrations (10-50 mg/L), initial solution pH of 5.0, and dosage of 3.2 g/L. The biosorption capacity of RB was found to be rapidly increased in the early stage of biosorption of RB using DRSP and ADRSP, because of the availability of vacant active sites with several functional groups (Malakootian and Heidari 2018). In the second stage, the increase in contact time, biosorption capacity was slowly increased (except initial RB concentration of 40 mg/L using DRSP) and then reached equilibrium in the final state. The reduction in biosorption capacity might be due to the possible active sites occupied by RB. The equilibrium time for RB biosorption for both DRSP and ADRSP were found to be around 125 and 75 min, respectively. It is also noticed that the biosorption capacity of ADRSP is greater than that of DRSP. In addition, the equilibrium contacting time for the biosorption of RB using ADRSP is shortened as compared to that using DRSP under the same condition. This is possible with the appropriate surface morphology containing heterogeneous and rough surfaces with more cavities after acid treatment. Based on the experimental results, it is identified that the biosorption performance of ADRSP is remarkable as compared to DRSP.

Effect of RB concentration and temperature
Temperature is an another parameter influencing the performance of biosorption. To identify the suitable operating temperature, type of biosorption, and thermodynamic feasibility of the process, the temperature of the system was varied from 30 to 50 C with initial RB concentration (10-50 mg/L), initial pH 5.0, and dosage of 3.2 g/L ( Figure  8). It is noticed that the biosorption capacity of ADRSP was greatly improved as compared to that of DRSP toward the removal of RB in a given temperature range. Initial RB concentration could also affect the affinity and dynamic interaction of RB with both DRSP and ADRSP at a given temperature. The biosorption is the solid-liquid mass transfer operation and the rate of mass transfer is decreased by an increase in RB concentration. The reason might be the necessary driving force required to overcome the resistance to the movement of RB species from the liquid phase to the solid phase. At a low initial concentration of RB, the quantity of biosorbent available for RB molecules are large enough and hence resulting in higher removal efficiency (Rangabhashiyam and Balasubramanian 2019). However, at high RB concentration, there might be competition among the RB molecules which tried to bind over the surface of a defined quantity of biosorbent and hence explored the decrease in biosorption (%). The maximum biosorption capacity of DRSP and ADRSP were identified at 50 C, respectively (Figure 9). It is noticed that an increase in temperature increases the biosorption capacity to 50 C due to the increase in the number of the binding sites generated by breaking the internal bond near the edge of active sites of biosorbent (Panday et al. 1986;Ucun et al. 2008). This is also representing the diffusion-controlled endothermic biosorption process in the high-temperature range.

Equilibrium isotherm model
The isotherm studies for the removal of RB were investigated by varying the initial RB concentration from 10 to 50 mg/L. Using the experimental data, an equilibrium model was fitted to explain the isotherm model. Isotherm models describe the mechanisms associated with the biosorption for the removal of RB using different equilibrium concentrations corresponding to specific RB uptake. The equilibrium data for biosorption using both DRSP and ADRSP were fitted with various isotherm models namely Langmuir, Freundlich, Dubinin-Radushkevich (DR), and Temkin. The model parameters were evaluated using the linear form of the isotherm equations. The feasibility, direction, and biosorption capacity of biosorbent could be examined to design the batch biosorption process using the isotherm models (Rangabhashiyam et al. 2014).
Langmuir model. This model has the following assumptions: i. monolayer biosorption takes place on a uniform specific homogeneous surface with a finite number of active sites. ii. there is no movement of sorbate molecules occurring on the surface of the biosorbent. iii. biosorbent has a greater affinity with biosorbate molecules Langmuir isotherm model is expressed as follows: The linear form of expression is given by: Where, C e,L is an equilibrium RB concentration (mg/L) in the liquid phase, q e is equilibrium biosorption capacity that describes the quantity of pollutant adsorbed per quantity of the biosorbent @ equilibrium time (mg/g), q m is the maximum biosorption capacity, illustrating the quantity of RB biosorbed as a monolayer (mg/g), and b is the Langmuir model constant (L/mg).
The model parameters, such as q m and b were evaluated using the slope and intercept of linear plot C e /q e vs. 1/C e using Equation (4) (data not shown). An essential feature of the Langmuir isotherm is to determination of equilibrium dimensionless constant, separation (or) equilibrium parameter, R L which is used to define the feasibility of biosorption.
The separation factor is expressed as follows: The following feasibility criteria are used based on R L (Rangabhashiyam and Selvaraju 2015b): The experimental data were fitted with the proposed model, and the results are represented in Table 3. The maximum biosorption capacity (mg/g) for DRSP and ADRSP were found to be 39.370 and 60.606, respectively at 40 C. Based on the experimental data, it is noticed that ADRSP explored superior biosorption capacity than DRSP. The experimental data is well in agreement with the proposed model, indicated by higher ranges of coefficient of determination (R 2 ) (0.967-0.998 for DRSP; 0.896-0.991 for ADRSP). The ranges of R L values were found to be lower than unity  Freundlich isotherm model. Unlike the Langmuir model, it suggests the formation of multilayer pollutant molecules on the heterogeneous energy distribution of solid surfaces (Freundlich and Heller 1939). An empirical expression for this model is given below: The linear expression for the Freundlich model is given by: Where, K F is the model isotherm constant (L/g), indicating the biosorption capacity, and (1/n F ) is the exponential factor, illustrating the intensity and feasibility of biosorption. The model parameters such as K F and (1/n F ) were evaluated from the intercept and slope of the linear plot using Equation (7) (plot not shown). The ranges of K F (L/g) using DRSP and ADRSP were found to be 0.137-1.607 and 0.675-2.935, respectively (Table 3). Since the values of (1/n F ) were fractional values, less than unity confirming the feasibility of the biosorption.
Dubinin Radushkevich (DR) isotherm. This model is used to examine the mechanism of the biosorption process (physical (or) chemical (or) exchange of ions) using the model parameter of apparent energy (or) mean biosorption energy (Ghasemi et al. 2014). It has the following assumptions: (1) applicable to the porous structure of biosorbents; (2) does not illustrate the homogeneous surface with constant biosorption potential; (3) describes the penetration of sorbate through micro-porous of biosorbent; (4) does not explain the layer-by-layer biosorption on pore wall (Dubinin et al. 1947). The expression for the DR model is as follows: The linear form of the model is given by: Where q m is the maximum biosorption capacity in mg/g. k D is the activity coefficient, relating the biosorption energy (mol 2 /kJ 2 ) The Polanyi potential (e) involved in this model is determined by: Where, R is a gas constant (8.314 J/mol K), T is operating temperature (K), and C e is the equilibrium concentration. The mean biosorption energy E (kJ/mol) is given by The model parameters obtained from the slope and intercept for the plot of log q e vs. e 2 were listed in Table 3. According to the model, the nature of biosorption was examined by mean biosorption energy, E as follows: i. The biosorption might be governed by a chemical mechanism if the value of E lies above 16 kJ/mol ii. If the value of E is <8 kJ/mol, then physical biosorption prevails. iii. The value of E lies between 8 and 16, exploring the exchange of ions during the biosorption process (Ghasemi et al. 2014).
Using this model, the maximum possible biosorption capacity (mg/g) of DRSP and ADRSP for the removal of RB were found to be 3.303 and 6.641 mg/g at 30 C, respectively. It is noticed that there was a significant difference in maximum possible biosorption capacity q m (mg/g) observed for DRSP and ADRSP. In addition, the increase in q m for ADSRP might be due to the modification of surface morphology by chemical treatment. The range of coefficient of determination, R 2 for DRSP and ADRSP were determined to be 0.778-0.973 and 0.887-0.955. The range of biosorption energy E (kJ/mol) for both DRSP and ADRSP was found to be 0.158-0.5 and 0.707-0.845, respectively. Based on the value of biosorption energy, it is revealed the physical biosorption mechanism of RB for both DRSP and ADRSP (Zaheer et al. 2019).
Temkin isotherm. This model has the following assumptions: (i) the heat of biosorption of all the molecules in the layer linearly, other than logarithmically decreases with coverage of molecules due to the repulsive nature of sorbate-sorbate during the process; (ii) biosorbate molecules are not being organized themselves in an identical packed structure; (iii) biosorbent molecules are uniformly distributed over the surface of biosorbent (Temkin and Pyzhev 1940;Nunes et al. 2009). The non-linear expression of the model is expressed as: Where, a T ¼ Temkin model constant (L/g), k T ¼ RT b (kJ/mol) The linear form of the model is given by: The model parameters obtained are shown in Table 3. Temkin model parameter, k T (kJ/mol) is used to evaluate the heat of biosorption and the nature of the mechanism involved. It is noticed that the values of k T were observed within the range of 0.461-1.306 and 0.592-0.727 toward the biosorption of RB using DRSP and ADRSP, respectively. The range of coefficient of determination, R 2 using DRSP and ADRSP were found to be 0.842-0.941 and 0.902-0.943, respectively.

Suitability of the model
The experimental data were fitted with various isotherm models under equilibrium conditions. Model parameters were listed in Table 3 using the linear form of isotherm expressions.
In the overall analysis, experimental data fitted well with the Langmuir model followed by Freundlich isotherms with in high R 2 values, close to 1.0. This observation is the well agreement with previous reports (Ponnusami et al. 2008;Rangabhashiyam and Selvaraju 2015a). Therefore, the Langmuir isotherm model can be well demonstrated one to describe the homogeneous nature of the surface for the biosorption process.

Evaluation of kinetic parameters
Kinetic models are essential to the design of the biosorption process for the following reasons: (i) identification of rate governing step; (ii) determination of kinetic parameters; and (iii) screening the suitable mechanism. In addition, kinetics information is based on the principle of biosorption kinetics and convective mass transfer rate in solid-liquid mass transfer operation (Tang et al. 2018). The kinetics analysis is mostly dependent on the physical and chemical nature of the biosorbent selected (Alberti et al. 2012). The transient behavior of RB biosorption using both DRSP and ADRSP was examined using the pseudo-first-order, pseudo-secondorder, and intraparticle diffusion models.
Pseudo-first-order kinetics. The pseudo-first-order model is one of the models proposed by Lagergren (1898) for the prediction of kinetic analysis. Even though it is a simple kinetic model, it is applicable only in the initial stages of biosorption. The linear form of the model is expressed as follows: Àln q e À q t q e ¼ k 1 t Where q e and q t demonstrate the biosorption capacities of DRSP and ADRSP for the removal of RB at equilibrium and any time, respectively. k 1 is the pseudo-first-order rate constant (1/min), which was evaluated from the slope of the linear plot (14) Àln q e Àq t q e vs. t. The kinetic model parameters are listed in Table 4.
Pseudo-second-order kinetics. This model is first proposed by Blanchard et al. (1984) and later, it is modified by Ho and MacKay. This model is widely employed in different biosorption processes since data fitness is well-suitable for the entire range of contacting time. The pseudo-secondorder kinetic model (Ho and McKay 1999) is explained by: On integrating: Where k 2 is the second-order rate constant (g/mg-min); The model kinetic parameters namely predicted equilibrium biosorption capacity (q e, pre Þ and second-order rate constant (k 2 ) were determined from the slope and intercept of the linear plot using Equation (16), t q t vs. t and the results were listed in Table 4.
Intra-particle diffusion model. This model demonstrates the boundary layer thickness for the diffusion mechanism of biosorption. The various diffusion mechanisms involved in the biosorption process: (i) transfer of pollutant molecules from the aqueous phase to the outer surface of the solid phase by convective mass transfer (external mass transfer); (ii) intra-particle diffusion; (iii) diffusion of pollutant through pores/cracks (porous diffusion); (iv) attachment of pollutant on the surface of the solid material (surface diffusion). One of the slowest steps can be considered the rate-controlling step for biosorption (Ai et al. 2013). Mostly, the rate-limiting step that appears in the biosorption might be the diffusion of pollutants onto the biosorbent layer, called intra-particle diffusion. This model was developed by Weber and Morris, in 1963 to identify the diffusional limitation and also determine the diffusional parameter. The rate of intraparticle diffusion can be expressed as a function of the square root of contacting time during the biosorption (Weber and Morris 1963): where k intra is the intra-particle diffusion constant (mg/g min 1/2 ) and F (mg/g) is the intercept. The model parameters namely k intra and F were evaluated using the slope and intercept of the plot of q t vs. t 1 2 and results are listed in Table 4.

Selection of kinetic model
The kinetic model parameters and co-efficient of determination for both DRSP and ADRSP for the removal of RB are listed in Table 4. The pseudo-first-order model is not wellsuitable for illustrating the experimental data, since the ranges for R 2 values using DRSP and ADRSP were found to be 0.92-0.998 and 0.895-0.972, respectively. For the intraparticle diffusion model, is also not suitable since the lower values of the coefficient are listed in Table 4. The range of intercept, F (mg/g) was found to be 0.264-0.685 and 1.558-2.61 using DRSP and ADRSP, respectively.
As the values R 2 were close to unity (0.928-0.996 for DRSP and 0.996-0.999 for ADRSP), the fitness for experimental data with the second-order kinetic model is a good agreement. In the overall analysis of experimental data with kinetic models, the pseudo-second-order model was identified as the suitable model among the others. The selection of the model is comparable with existing reports (Ponnusami et al. 2008;Miranda et al. 2010). However, in reality, the application of a single kinetic model to demonstrate the biosorption process on solid biosorbent might be still questionable due to the following reasons: (i) heterogeneity nature of biosorbent surfaces; (ii) diversity of biosorption phenomena (Ponnusami et al. 2008).
Thermodynamic study Thermodynamic parameters namely change in free energy (DG 0 ), enthalpy (DH 0 ) and entropy (DS 0 ) are used to examine the feasibility and spontaneous nature of biosorption. The positive and negative values of DH 0 are indicating the endothermic and endothermic nature of biosorption, respectively (Bhaumik et al. 2011;Khan et al. 2012). When the value of DG 0 is zero and distribution constant, K L is equal to unity, then the biosorption might be proceeding to a considerable extent before reaching the equilibrium. The negative value of DG 0 indicates the biosorption is quite favorable. However, the situation becomes quite unfavorable if the value of DG 0 increases in the positive direction (Narayanan 2004). The relationship between equilibrium constant (K L ) and Langmuir isotherm constant (b) was related using the following expression (Liu 2006;Ghosal and Gupta 2017) if equilibrium concentration, C e is in mg/L: Where, K L is the equilibrium constant (L/mol); b is the Langmuir constant (L/mg); M A is the molecular weight of RB (g/mol); c is the activity co-efficient; For diluted solution, activity co-efficient is considered to be unity.
The equilibrium constant and change in standard Gibbs free energy are related by the following expression (Mathivanan et al. 2021): Using equilibrium co-efficient (K L ), thermodynamic parameters such as enthalpy (DH 0 ) and entropy (DS 0 ) were determined using Van't Hoff equation: A perusal of Table 5 shows that biosorption of RB using DRSP and ADRSP explored negative values of DG 0 indicating the feasibility nature of the process. The positive values of DS 0 and DH 0 demonstrated the increase in disorder and randomness at the solid-liquid interphase, causing a better affinity of RB onto the surface and endothermic biosorption, respectively (except 50 C for DRSP and 30 C for ADRSP) (Bhaumik et al. 2011;Khan et al. 2012).

Biosorption mechanism
Since RB is an amphoteric and complex organic molecule containing two amino groups and one carboxylic group attached with aromatic rings, the overall affinity of RB onto DRSP/ADRSP is greatly influenced by the ionic form of RB (cationic/zwitterion) and the charge on the surface of the DRSP/ADRSP with respect to zero-point pH charge. It is reported that the pKa value of RB was found to be 3.7. Therefore, initial solution pH influence both RB and DRSP/ ADRSP. As the solution pH is below 3.7 (<pHzpc), there was a shifting of the ionic form of RB from zwitterion to cationic and also the surface of DRSP/ADRSP got positively charged. The cationic RB þ causes an electrostatic repulsion with protonated DRSP/ADRSP and hence shows the reduction in biosorption (%) of RB. As the solution pH was above 3.7 (<pHzpc), there was a shifting of the cationic form of RB into zwitterion form, RB - (Mohammadi et al. 2010). This might be strongly interacting with the positively charged surface of DRSP/ADRSP illustrating the increase in biosorption (%). Above pH 8.0 (>pHzpc), there was a reduction in biosorption (%) observed for both DRSP and ADRSP. It was due to the electrostatic repulsion of negatively charged RB with the deprotonated solid surface.
To evaluate the distribution of surface functional groups on DRSP and ADRSP after biosorption, FITR spectral analysis was performed as shown in Figure 4 and Table 2.
After RB loading, the location of -OH stretching was changed in both DRSP and ADRSP. In addition, -CN stretching in DRSP and -C¼C stretching in ADRSP were significantly shifted to a new location due to the biosorption of RB. It confirms that these functional groups were identified as the primary factors for the attachment of RB through electrostatic (or) hydrogen binding using FTIR analysis (Ahmad and Kumar 2010). The binding forces namely electrostatic attraction, hydrogen-bonding, p-p interaction, intermolecular gravity namely dispersion force (or) Vander Waals force, and di-pole interaction could be involved in the binding of the zwitterion form of RB molecules (RB -) with negatively charged DRSP/ADRSP. The following scheme is proposed using functional group analysis through electrostatic interaction (Oyekanmi et al. 2019):

Conclusion
The present work demonstrated a detailed comparison of biosorption capability of native and chemically treated forms of D. regia seed pod for the removal RB from simulated solution.
1. The surface morphology of DRSP and ADRSP revealed rough, cavity, and porous surface morphology, greater thermal stability, and distribution of different functional groups responsible for the attachment of RB from the simulated solution. 2. Chemical treatment of D. regia seed pod offered a significant variation in surface morphology, functional group distribution, specific surface area, and decomposition temperature.
3. Using BET analysis, the essential textural parameters namely specific surface area, pore diameter, meso, and microporous volumes of ADRSP were compared with that of DRSP. A specific surface area of ADRSP (21.6722 m 2 /g) offered the maximum biosorption (%) of 98.29%. By chemical treatment, the specific surface area of ADRSP was improved. i.e., 8.98 times more than that of DRSP. 4. The parametric analysis of different factors such as initial pH, dosage, initial concentration, and solution temperature for the removal of RB were investigated using DRSP and ADRSP. 5. The experimental evidence noticed that the pseudosecond-order model could be well-suitable as compared to other kinetic models proposed based on the coefficient of determination. Among the different isotherm models, the Langmuir isotherm was identified as the suitable model. 6. A maximum biosorption capacity of 60.606 mg/g for ADRSP and 39.37 mg/g for DRSP at 40C for the removal of RB and also the negative values of Gibbs free energy change and positive values of both enthalpy and entropy changes illustrated the thermodynamic feasibility, endothermic and spontaneous nature of biosorption process. 7. A possible biosorption mechanism was proposed using functional group analysis and the effect of solution pH on biosorption (%). Using FTIR analysis, the functional groups namely -OH stretching and -C¼C stretching were responsible for the attachment of RB on ADRSP. Along with -OH stretching, -CN stretching is also essential for the attachment of RB on DRSP. 8. To the best of our knowledge, the comparison of biosorption performance of D. regia seed pod in both untreated and treated forms for the removal of RB from simulated solution has not been extensively studied previously.
The results of the present study illustrated that DRSP and ADRSP can be used as effective biosorbent for the removal of RB.