1 Introduction

Because of the rapid increase in global population and industrialization, water quality is in grave danger. The discharge of hazardous compounds into the water environment without sufficient treatment is a hot topic of discussion. In general, dyes are synthetic compounds that cannot be removed or dissolved over time. Especially, methylene blue a cationic dye is unwanted in the aquatic environment due to its poisonous, carcinogenic, and toxic effects [1, 2]. The annual production of synthetic dyes is over 700,000 tons and more than 15% of this amount is discharged into water every year [3]. The removal of dye from the water environment is important for ecological systems.

The development of effective and cost-effective treatment technologies is an ongoing and continual effort. A variety of treatment techniques has been developed to remove synthetic dyes from wastewater. With adsorption [4], biosorption [5], aerobic and anaerobic treatment [6], coagulation/flocculation [7], and electro/photochemical [8] technologies, it is possible to effectively reduce synthetic dyes from wastewater and improve water quality.

Biosorption, an biosorption method in which waste biomass has been employed as a sorbent material in recent years, is an effective, cheap, simple, and environmentally friendly treatment technology for removing methylene blue from the aquatic environment [9]. Every year, huge amounts of waste are produced from all biomass-based industries. Recycling these wastes into valuable products can have a huge impact on the environment. Instead of creating problems, such as waste buildup and pollution, this practice can lead to significant economic and ecological benefits. By reusing and recycling materials, we can make a big difference in the health of our planet.

Fish scales are one of the most common wastes from this industry [10]. It should also be emphasized that, currently, fish scale waste produced in the fishing industry is not used economically. Storing fish scale wastes in landfills can cause significant environmental problems and loss of resources. As a result, recycling waste fish scales into various useful products can reduce environmental pollution while also having significant economic potential [11].

Although fish scales may differ in form and pattern depending on different factors (such as species, structure, age, and size), they have similar characteristics in general structure [12]. Such a regular and natural structure of fish scales may inspire the creation and production of various functional materials from them [13].

In this study, it was produced as a novel biosorbent for use in biosorption technology for the recycling of fish scales. The biosorbent material produced from waste fish scales was used in the biosorption of methylene blue synthetic dye from the aquatic environment. In this study, the effects of different initial pH values and initial solution concentrations will be investigated as experimental parameters influencing biosorption. Moreover, to elucidate the biosorption behavior of the biosorbent towards methylene blue, kinetic, thermodynamic, and equilibrium models have been analyzed.

The integration of statistical methods in experimental studies is a commonly used approach to determine the necessary optimal experimental conditions for the optimal performance of the biosorbent and to reduce the number of tests [14]. In order to achieve optimal outcomes from the process of biosorption, it is imperative that the impact of all pertinent parameters be thoroughly evaluated. The manual evaluation of these parameters can prove to be burdensome, which underscores the need for a methodical approach to developing an experimental matrix for the manipulation of these parameters. This matrix must encompass a range of variables in order to optimize the process and ultimately enhance the efficacy of biosorption [15].

One of the techniques used for optimization is response surface methodology (RSM), wherein the best combination of factors that produces an optimal response is determined [16]. In this study, RSM based on a central composite experiment design was applied to optimize the solution’s initial concentration (ppm), time (min), and biosorbent amount (mg), which are effective parameters of the biosorption process. The effect of the determined parameters on the dye biosorption capacity (qe) was investigated. According to the results obtained, it was shown that the initial solution concentration had the greatest effect on the methylene blue biosorption capacity (qe).

This study serves to illustrate that the goals of pollution remediation and environmental conservation can be achieved and, further, that effective waste management and the creation of cost-efficient and eco-friendly biosorbents are attainable.

2 Material and method

2.1 Preparation of biosorbent

Waste fish scales (Cyprinus carpio) were obtained from local fish markets in Sanliurfa, Türkiye, for the preparation of biosorbent samples. Initially, the collected fish scales underwent thorough washing with tap water to eliminate superficial debris and impurities. This step was followed by a secondary wash using distilled water to ensure the removal of soluble impurities. Post-washing, the fish scales were dried in a laboratory oven at 80 °C for 24 h to remove any residual moisture.

The waste fish scales were ground and sieved to a size of 0.5 mm. Then a treatment was applied to enhance the biosorption capacity of the fish scales. Specifically, 1 g of the dried fish scales was immersed in 100 ml of a 0.3 M sodium hydroxide (NaOH) solution. This treatment lasted for 24 h, modifying the surface properties of the fish scales to improve their biosorption efficiency. After the NaOH treatment, the modified fish scales were thoroughly rinsed with deionized water to remove residual NaOH and other impurities. This washing process was repeated multiple times until the wash water reached a neutral pH, confirming the complete removal of alkali residues.

The final step involved re-drying the treated fish scales in an oven at 80 °C for another 24 h to ensure the complete removal of moisture, resulting in a stable, dry biosorbent material ready for experimental applications (Fig. 1).

Fig. 1
figure 1

Production of biosorbent and the methylene blue biosorption process

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2.2 Characterizations

The raw material was obtained at a wavelength of 400–4000 cm−1 by using a Fourier transform infrared spectrometer (FT-IR, PerkinElmer Spectrum 400) device to determine the functional groups of the biosorbent before and after the biosorption process. The surface analysis scanning electron microscope (SEM, ZEISS-EVO 50 instrumentation) was used to characterize the surface properties of the biosorbent after the biosorption process of raw material, biosorbent, and dye.

2.3 Preparation of dye solution

The methylene blue dye (CAS No: 122965–43-9) was procured from Sigma-Aldrich. A stock solution of methylene blue dye (1000 mg L⁻1) was prepared for subsequent use in the biosorption experiments. Experimental solutions with concentrations ranging from 50 to 250 mg L⁻1 were prepared by diluting the stock solution with distilled water. For accurate pH adjustment of the test solutions, we employed 0.1 mol L⁻1 solutions of sodium hydroxide and hydrochloric acid. Sodium hydroxide (NaOH) and hydrochloric acid (HCl) were obtained from Scharlau, Sinopharm Chemical Reagent Co., and Sigma-Aldrich, respectively.

2.4 Biosorption experiments

To achieve the best possible outcomes, we used only high-quality analytical-grade materials in our biosorption research. The biosorption process involves numerous variables that can influence its effectiveness. To optimize the removal efficiency of methylene blue dye from water, a one-variable-at-a-time experimental method was implemented to fine-tune critical factors such as the initial methylene blue concentration (Co) and pH. The experiments were conducted in a series of Erlenmeyer flasks, each containing a specific combination of methylene blue solution and biosorbent. These mixtures were agitated using an orbital shaker set at a constant speed of 150 revolutions per minute (rpm). The removal process was performed, and the initial concentrations of methylene blue in the solutions were measured using UV spectroscopy at a wavelength of 664 nm. The amount of methylene blue adsorbed by the biosorbent at equilibrium (qe) was calculated using Eq. (1):

$${q}_{e}=\frac{\left({C}_{0}-{C}_{e}\right)}{w}V$$
(1)

The equilibrium concentration of methylene blue (Ce (mg L−1)) is a key factor in evaluating the biosorption process’s efficiency. By determining the initial methylene blue concentration (Co (mg L−1)), the solution volume (V (ml)), and the amount of biosorbent used (w (g)), we can precisely calculate the equilibrium concentration of methylene blue. This calculation allows us to assess how well the biosorbent interacts with methylene blue molecules, providing insights into the effectiveness of our biosorption experiment.

2.5 Kinetics of biosorption

To investigate the kinetics of biosorption, a series of experiments was performed using Erlenmeyer flasks, each containing 100 mL of methylene blue solution and 10 mg of biosorbent. This study aimed to quantify the rate and extent of biosorption interactions between the biosorbent and methylene blue. Samples were periodically collected over the course of the experiment, spanning from 0 to 250 min. At each sampling point, the biosorbent was separated, and the concentrations of methylene blue and biosorption capacity were measured. The kinetic data obtained were then analyzed using several established kinetic models: the pseudo-first-order (PFO) model [17], the pseudo-second-order (PSO) model [18], the intra-particle diffusion (IPD) model [19], and the Elovich model [18]. These models are instrumental in elucidating the biosorption rate and the underlying mechanisms of the biosorption process. The equations of the models used are as Eqs. (2, 3, 4, 5):

$${q}_{t}={q}_{e}\left(1-e^{-k_{1}t}\right)$$
(2)
$${q}_{t}=\frac{\left({k}_{2}{q}_{e}^{2}t\right)}{\left(1+{k}_{2}{q}_{e}t\right)}$$
(3)
$${q}_{t}={k}_{id}{t}^\frac{1}{2}+C$$
(4)
$${q}_{t}=\frac{1}{\beta }\text{ln}\left(\alpha \beta t+1\right)$$
(5)

where qe (mg g−1) and qt (mg g−1) represent the biosorption capacity at equilibrium and at a specific time t (min), respectively. The rate constants for the PFO, PSO, and IPD models are expressed as k1 (min−1), k2 (g mg−1 min−1), and kid (mg g−1 min−1/2), respectively, while C (mg g−1) corresponds to a constant associated with the boundary layer thickness. The parameter α (mg g−1 min−1) indicates the initial rate of the biosorption process, and β (g mg−1) is the desorption constant related to this process.

2.6 Isotherm of biosorption

The isotherm study of biosorption was conducted to gain a deeper understanding of the biosorption mechanism. This investigation aimed to determine the biosorption capacity of the biosorbent material. Multiple Erlenmeyer flasks, each containing 100 mL of methylene blue solution and 10 mg of biosorbent, were prepared for this purpose. The experiment was carried out with varying concentrations of methylene blue to evaluate the effect of different initial concentrations on the biosorption process. The mixtures were agitated at a constant temperature, optimized for maximum efficiency. After the designated time, samples were taken from the solution, and the biosorbent was removed to measure the final equilibrium concentration of methylene blue. This allowed for the assessment of the biosorption performance at equilibrium and provided insights into its potential applications. The obtained data for the biosorption isotherm was rigorously evaluated using three well-known isotherm models; the Freundlich [20] the Langmuir [21], the Temkin [22], and Dubinin and Radushkevich (DR) [23] a four-equation (Eqs. 6, 7, 8, 9). These models are extensively used in the field to describe the physical and chemical interactions of biosorbents, providing a comprehensive understanding of the biosorption isotherms.

$${q}_{e}=\frac{({q}_{m}{K}_{L}{C}_{e})}{(1+{K}_{L}{C}_{e})}$$
(6)
$${q}_{e}={K}_{F}{C}_{e}^{1/{n}_{F}}$$
(7)
$${q}_{e}={B}_{T}ln{A}_{T}+{B}_{T}ln{C}_{e} , {B}_{T}=\frac{RT}{b}$$
(8)
$${q}_{e}= {q}_{m}{e}^{{-B\varepsilon }^{2}}$$
(9)

In this context, qe (mg g−1) and qm (mg g−1) denote the equilibrium and maximum dye biosorption capacities of the biosorbent, respectively, while Ce (mg L−1) indicates the equilibrium concentration of the solution. The Langmuir equilibrium constant, KL (L mg−1), relates to the biosorption energy. For the Freundlich model, KF (mg g−1 (L mg−1)1/nF) and nF are constants representing the biosorption capacity and intensity, respectively. The Temkin isotherm constant BT (L g−1) measures the biosorption capacity, and AT (mg L−1) represents the equilibrium binding constant, indicating the strength of adsorbate binding to the biosorbent surface. The Temkin constant b (J mol−1) provides insight into the temperature dependency of the biosorption process. Two critical parameters for assessing biosorption efficiency are B (mol2 kJ−2) and ε (RT ln(1 + 1/Ce), where B represents the biosorption energy, and ε, known as the Polanyi potential, is used to evaluate the thermodynamics of binding. This is crucial for predicting changes in adsorption with varying temperatures. The gas constant R (8.314 J mol−1 K−1) plays a vital role in the ideal gas law, linking gas pressure to temperature and molecular quantity. T (K) represents the absolute temperature, indicating the thermal energy available in the system.

2.7 Thermodynamic of biosorption

The thermodynamics of biosorption were investigated in a controlled laboratory environment using a series of Erlenmeyer flasks. Each flask contained 100 mL of methylene blue solution and 10 mg of precisely measured biosorbent material. These mixtures, prepared with varying methylene blue concentrations, were vigorously agitated under optimized conditions. Upon reaching biosorption equilibrium, samples were taken from the solution, and the biosorbent was separated. The equilibrium concentrations of methylene blue in both the liquid phase and adsorbed on the biosorbent were then measured and recorded. The thermodynamic properties of the absorption of methylene blue into a biosorbent made from waste fish scales were examined, by calculating the thermodynamic parameters such as the change in Gibbs free energy (\(\Delta G^\circ\)), enthalpy (ΔH°), and entropy (ΔS°) (Eqs. 10, 11, 12).

$$\Delta G^\circ =-RT\text{ln}{K}_{\text{D}}$$
(10)
$$\Delta G^\circ =\Delta H^\circ -T\Delta S^{o}$$
(11)
$$\text{ln}{K}_{\text{D }}=\frac{\Delta S^\circ }{R}-\frac{\Delta H^\circ }{RT}$$
(12)

The temperature, T, is measured in Kelvin (K). The gas constant, R (J mol−1 K−1), is a crucial physical constant that relates the energy of a thermodynamic system to its temperature. The distribution coefficient (KD = Ceb/Ces) represents the ratio of the dye amount adsorbed on the biosorbent to the dye amount present in the solution. Ceb and Ces (mg L−1) are essential parameters used to determine the equilibrium concentration of a synthetic dye on a biosorbent in each system.

2.8 Modeling of biosorption by experimental design

The process of methylene blue biosorption onto activated carbon has been extensively studied, revealing a significant relationship between various independent variables and the amount of dye adsorbed (qe) at equilibrium. Key factors include biosorption time (min), initial dye concentration (ppm), and the amount of biosorbent (mg). Table 1 summarizes the parameters investigated and their respective levels.

Table 1 Biosorption parameters and optimization values
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3 Results and discussion

3.1 Characterization of the biosorbent

3.1.1 Scanning electron microscopy (SEM) analysis

As demonstrated in Fig. 2a, the scanning electron microscope (SEM) image of the raw material used in our study for biosorbent production reveals a smooth and void-free surface. This indicates that the material was in a dense and compact state prior to undergoing the biosorbent production process. In contrast, Fig. 2b shows that the produced biosorbent has a significantly different surface morphology compared to the raw material. The surface is now heterogeneous, with large folds and porosity present. This can be attributed to the physical and chemical changes that occurred during the production process. Figure 2c shows that the porosity is partially closed, which also allows for better mass transfer of target molecules into and out of the biosorbent structure. The results show that the surface morphology of biosorbents such as fish scales changes and becomes more porous after chemical treatment. For example, Zayadi et al. [24] reported similar surface morphology changes in their study.

Fig. 2
figure 2

SEM images of a raw material, b biosorbent, c biosorbent after biosorption

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3.1.2 Fourier transform infrared (FT-IR)

Upon analyzing the given wave numbers, it can be deduced that the peaks at 3375, 2980, 1620, and 1050 are indicative of specific functional groups present in the compound. The first peak at 3375 cm−1 is associated with N–H bonds, while the peak at 2980 cm−1 represents C-H bonds. Similarly, the peaks at 1620 cm−1 and 1050 cm−1 correspond to C = O and C–O–C functional groups respectively. These findings are in accordance with previous studies conducted by researchers [25,26,27,28]. Furthermore, it should be noted that the presence of peaks below 1000 cm−1 is a strong indication of the existence of functional groups bonded to aromatic rings [29]. This information adds significant value to the analysis as it provides insight into the structural composition of the compound (Fig. 3). According to the FT-IR analysis results, it is seen that some functional groups, which are not present in raw fish scales, appear in the biosorbent obtained as a result of chemical treatment. Additionally, some functional groups disappeared at the end of the dye biosorption process. This shows similar results to the study conducted by Onwordi et al. [30] on fish scales.

Fig. 3
figure 3

FTIR spectra of the a raw material, b biosorbent before biosorption, c biosorbent after methylene blue biosorption

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3.2 Methylene blue biosorption

3.2.1 Effect of pH

The initial pH has a very important effect on the biosorption effectiveness of biosorbents due to the functional groups and surface chemistry on the biosorbent surface [31]. Firstly, the effect of different initial pH (2–10) values on methylene blue biosorption was investigated. The investigation was carried out in a shaking water bath at 150 rpm with a constant solution temperature of 25 °C, an initial dye concentration of 100 ppm, a solution volume of 100 mL, and an amount of 0.1 g of biosorbent. The change in the initial pH and the biosorption capacity is shown in Fig. 4.

Fig. 4
figure 4

Effect of pH (T: 250C, V: 100 ml, m: 0.1 g, C: 100 ppm)

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Figure 4 depicts the impact of pH (2–10) on the dye biosorption technique. The biosorption capacity of the biosorbent increased as the initial pH increased from 2 to 8. At low pH values, the level of H+ ions in the solution is considerable, which causes protonation on the biosorbent surface [32]. Therefore, electrostatic attraction formed between the dye particles and the biosorbent surface, which decreased the biosorption performance. In addition, at a basic pH, excess OH− ions in solution form a complex compound with cationic molecules of methylene blue and decrease biosorption [33]. Optimal biosorption capacity at pH 8 aligns with several studies, such as Chakraborty et al. [34] and Barka et al. [35].

3.2.2 Effect of dye concentration

Following the determination of the initial pH level of the solution, a range of starting dye concentrations (50–250 ppm) was examined, as they are significant factors in methylene blue biosorption. The plot presented in Fig. 5 illustrates the correlation between various initial concentrations (ppm) and the corresponding biosorption capacities (qe) for methylene blue biosorption onto the biosorbent material.

Fig. 5
figure 5

Effects of dye concentration and biosorption time (T: 25 °C, V: 100 ml, m: 0.1 g, pH: 8)

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With increasing initial concentrations, the biosorbent’s dye removal performance improved. This increasing trend in biosorbent material performance can be explained by the large concentration gradient, which creates a larger driving force for the mass transfer between biosorbent and dye molecules at high dye concentrations [36]. The biosorption capacity increases rapidly with the progressive filling of the pores of the biosorbent and slows to almost an equilibrium condition [37]. This trend was also observed in the study by Daneshvar et al. [38].

3.2.3 Determination of the biosorption kinetic model

The kinetics of biosorption and the dynamics of the reaction are assessed using rate constants. Models of biosorption kinetics serve as effective tools for evaluating and expounding upon the fundamental characteristics of a biosorbent [39]. The graphs of the investigated models are shown in Fig. 6.

Fig. 6
figure 6

IPD kinetic model plot

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Table 2 presents the regression coefficients and standard deviation values of the kinetic models studied in the biosorption process of methylene blue onto the biosorbent.

Table 2 Kinetics assessment findings for methylene blue biosorption
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The correspondence of the statistical parameters derived from the kinetic models to the experimental data was assessed using the regression coefficient (R2), adjusted regression coefficient (AdjR2), and root mean square error (RMSE) tests. This analysis indicated that the experimental kinetic data for dye biosorption fit the pseudo-second-order (PSO) kinetic model most accurately (R2 0.99, AdjR2 0.99, and RMSE 0.026). The study fits the pseudo-second-order kinetic model best, indicating chemisorption as the primary mechanism [40]. This is corroborated by multiple studies, including Tural et al. [41]. The influence of dye molecules on the biosorption rate was evaluated using the intra-particle diffusion (IPD) kinetic model. Figure 6 presents the graph of this kinetic model, which does not pass through the origin and does not form a straight line. This observation suggests that the biosorption mechanism of the dye is controlled by multiple rate-determining steps [42].

3.2.4 Biosorption isotherms

The equilibrium values for biosorption were studied by analyzing isotherms. The experimental data on the biosorption was assessed using isotherm models, as shown in Table 3.

Table 3 Isotherm constants of the models
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Based on the regression coefficients displayed in Table 3, it can be observed that the biosorption equilibrium data effectively align with the Langmuir isotherm (R2 0.94, AdjR2 0.92, and RMSE 0.0069). According to this model, it proposes a monolayer biosorption process that occurs at homogeneous locations within the biosorption [43]. This aligns with Maurya et al. [44], who found that different biomass had a similar high biosorption capacity. It is not enough to simply look at R2 values when choosing the best model. To make the best decision, we must compare the equilibrium data with the calculated maximum biosorption capacity (qmax) [45]. The maximum biosorption capacity (qmax) was found to be 344.82 mg g−1, which represents the highest observed value.

The abbreviation “nF” used in the Freundlich model refers to the biosorption density. This value is classified as 1/ nF ≥ 1, indicating a challenging biosorption process [46]. The present study has revealed a specific nF value of 1.72, which suggests that the biosorption process is mainly physical in nature. Additionally, the calculated 1/ nF value of 0.58 indicates a high level of efficiency in this process. These values obtained in our study show that the adsorption capacity increases with concentration and the surface is heterogeneous. These results are consistent with the findings in the literature [4, 38].

The Temkin model suggests a distribution of monolayer biosorbates on heterogeneous sites, characterized by a uniform binding energy distribution and consistent interactions between the biosorbent and solute, similar to the Langmuir model. The parameters obtained from the Temkin model show that the heat of biosorption (BT) was 34.30 J mol−1, the heat of adsorption decreases linearly and intermolecular interactions are important. This is in agreement with the findings in our study [47, 48].

The mean free energy of biosorption (EDR) was calculated to be 3.075 kJ mol−1, indicating that the biosorption process may be driven by physical mechanisms (EDR = 1/√2B). This value is lower than the typical range for physical biosorption of 0–8 kJ mol−1, indicating that this is likely the controlling factor for this process [49].

3.3 Biosorption thermodynamic models

The thermodynamic analysis provided critical insights into the methylene blue biosorption process, including its spontaneity, feasibility, and underlying physical and chemical properties. The standard Gibbs free energy change (ΔG0) is an indicator of the spontaneity and feasibility of a process. A negative ΔG0 value signifies that the process is energetically favorable and can occur spontaneously. Generally, a negative ΔG0 value denotes an exothermic process, while a positive value indicates an endothermic process. Specifically, if ΔG0 lies between − kJ mol⁻1 and 0 kJ mol⁻1, it suggests that physisorption has occurred [50, 51]. The determination of the free energy value ΔG0 for the adsorption process of methylene blue dye at a temperature of 298 K was achieved through thermodynamic modeling. This analysis revealed a negative value, as shown in Table 4. Furthermore, the negative values of ΔH0 correspond to the exothermic nature of dye biosorption, whereas the negative values of ΔS0 are very low, indicating that there is no significant change in entropy [52]. This indicates a strong affinity between the dye molecules and the sorbent surface, signifying a successful sorption process. The findings demonstrated that the biosorption of the synthetic dye was spontaneous, feasible, and primarily physical in nature. Furthermore, the research indicated that the process was not dependent on chemical reactions, making it suitable for the effective removal of synthetic dyes from wastewater.

Table 4 Results of thermodynamic modeling
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3.4 Experiment design

The research investigated the process of methylene blue biosorption onto the biosorbent using response surface methodology and the central composite design model. Detailed experimental conditions are summarized in Table 5.

Table 5 Biosorption parameters and experimental design results
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The efficacy of the modeling was assessed using regression (R2) coefficients, which measure the degree of correlation between the independent variables and the dependent variable. These coefficients are crucial for evaluating the model's fit to the data, with higher values indicating better performance. The obtained regression coefficients are listed in Table 6.

Table 6 Experimental design model statistics applied for dye biosorption
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The regression coefficient is a crucial statistical measure for evaluating how well our model fits the experimental data. The R2 value indicates how effectively the model explains the variance in the data. An R2 value closer to 1 signifies a model with superior predictive capabilities. Among the four models tested, the quadratic model proved to be the most accurate, evidenced by its highest R2 value.

The quadratic model was employed to derive an equation that demonstrates the influence of varying time, temperature, and initial concentration on the biosorption capacity qe. This equation incorporates a combination of mathematical functions and variables to elucidate the relationships between these factors. Understanding these relationships allows researchers to better predict changes in biosorption capacity under different conditions (Eq. 13).

$${q}_{e}=+102.37+30.18A+4.72B-7.84C+5.82AB-6.57AC+8.18BC-2.55{A}^{2}-8.53{B}^{2}-4.40{C}^{2}$$
(13)

The variables A (ppm), B (min), and C (mg) represent the initial concentration of the solution, the time elapsed, and the amount of biosorbent used, respectively. To evaluate the quadratic model and examine the effects of these process parameters on the biosorption capacity, ANOVA (analysis of variance) diagrams were utilized. This method offers valuable insights into the impact of each parameter on the biosorption capacity, as well as the interactions between all parameters, as detailed in Table 7.

Table 7 The analysis of variance (ANOVA) for the quadratic model will be conducted
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The significance of the model is evident through its high Model F-value of 62.67, indicating a statistically significant result with only a 0.01% probability that this value is a result of chance. Similar findings are reported in studies using response surface methodology (RSM) for biosorption processes, where high F-values indicate robust models with significant explanatory power [53]. The significant model terms, as identified by P-values less than 0.0500, include A, B, C, A2, B2, and C2. Any terms with P-values greater than 0.1000 are considered insignificant and may be excluded from the model for the purpose of simplification, unless necessary for maintaining a hierarchical structure. These terms are critical for the model, as supported by previous research that emphasizes the importance of these parameters in biosorption studies. Insignificant terms, those with P-values greater than 0.1000, can generally be excluded to simplify the model without compromising its integrity, unless they are necessary for maintaining hierarchical structure [54]. Furthermore, the significant lack of fit F-value of 13.26 indicates a discrepancy between the model and the data with a 0.66% chance that this result is due to random variability. This suggests that further refinement is necessary to improve the model’s fit. Similar issues are often addressed in the literature, where models are refined through additional experimental runs or alternative modeling approaches to reduce lack of fit and enhance predictive capability [55] Overall, the Model F-value of 62.02 confirms the robust explanatory power of the model. The significance of model terms is determined by their respective P-values. Any P-value below 0.0500 signifies a significant term that should be included in the model. On the other hand, terms with P-values above 0.1000 are deemed insignificant and may be omitted. The noteworthy lack of fit F-value suggests an apparent inadequacy in the model’s accuracy, highlighting the need for additional adjustments.

The investigation determined that the capacity for biosorption at a consistent temperature is positively influenced by an increase in solution concentration and duration. Likewise, the value for qe increases with an escalating interaction of the initial concentration and duration. In cases where duration is held constant, the rate of growth is directly related to the initial concentration of the solution; however, it has been observed that this correlation diminishes as the quantity of biosorbent is augmented. Furthermore, the effectiveness of biosorption is enhanced with higher initial solution concentrations and increasing quantities of biosorbent. The efficiency of biosorption displayed an elevation over time with a constant concentration; however, when there was an increase in the quantity of biosorbent employed, there was a decline observed. Furthermore, as illustrated in Fig. 7, there was a decrease in the biosorption efficacy with an increase in both duration and quantity of biosorbent.

Fig. 7
figure 7

Contour and 3D response surface graphics

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After conducting a response surface methodology (RSM), the optimal levels for the parameters of initial concentration, duration, and biosorbent quantity were determined and depicted in Fig. 8. The analysis concluded that, under optimal conditions, the biosorbent demonstrated a maximum capacity of 102.367 mg g−1 for methylene blue.

Fig. 8
figure 8

Optimum levels of selected experimental parameters and maximum biosorption capacity

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4 Comparison study and future research directions

Table 8 represents the maximum biosorption capacities (qmax) of biosorbents derived from diverse raw materials, as per the Langmuir isotherm model for the adsorption of methylene blue. The biosorbent synthesized in this study demonstrates a higher methylene blue biosorption capacity when compared to various other biosorbents recently documented in published works.

Table 8 Maximum biosorption capacities of different biosorbent
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In addition, apart from those summarized in the table above, using waste fish scales, Marrakchi et al. [63] performed methylene blue removal with carbon material prepared by using Labeo rohita fish scales. They reached a maximum dye removal capacity of 184.4 mg g−1 with the adsorbent they obtained. Zhe et al. [64] found the maximum adsorption capacity as 555.55 mg g−1 in the removal of methylene blue dye with the carbon material they produced with the scales of Tilapia nilotica fish. Neves et al. [65] used Orechromis niloticus fish scales as biosorbent for the removal of reactive blue dye. They calculated the maximum dye removal capacity as 291 mg g−1. Ribeiro et al. [66] have carried out the removal of reactive blue 5G dye with the sorbent they prepared using Oreochromis niloticus fish scales. They achieved a maximum dye removal capacity of 241.2 mg g−1 with the sorbent they obtained.

The promising results of this study open up several avenues for future research in the field of biosorption and wastewater treatment. One potential direction is the exploration of other low-cost and biodegradable biomaterials similar to fish scales for their efficacy in removing various contaminants. Investigating alternative sources, such as agricultural residues or other types of biowaste, could provide a broader range of effective biosorbents. Further research could also focus on enhancing the modification techniques of biomaterials to improve their biosorption capacities. For instance, the use of different chemical treatments or the combination of multiple modification methods may yield biomaterials with superior properties for pollutant removal. Another significant area for future studies is the application of the developed biosorbents in real-world scenarios. Conducting pilot-scale studies and field trials will help in understanding the practical challenges and effectiveness of the biosorption process in various wastewater treatment contexts. This can provide valuable insights into scaling up the process and integrating it into existing wastewater treatment systems.

5 Conclusions

In this research, the extraction of methylene blue dye from a biosorbent created using waste fish scales has been thoroughly investigated in the context of water pollution and treatment. Characterization findings reveal that the produced biosorbent exhibits a heterogeneous surface morphology, characterized by numerous protrusions and voids, and a rich array of functional groups. The biosorption process begins with an examination of pH (2–10) and initial solution concentration (50–250 ppm) parameters, identifying pH 8 as optimal for effective biosorption. Kinetic and equilibrium modeling studies demonstrate that the PSO and Langmuir models best explain the dye removal behavior of the biosorbent, with the Langmuir isotherm indicating a qmax of 344.82 mg g−1. Thermodynamic results suggest that the biosorption of methylene blue on various surfaces is spontaneous and occurs via physisorption, signifying a natural, positive, and physical process. Additionally, the maximum biosorption capacity was determined to be 102.367 mg g−1 based on parameters of initial solution concentration (112.5 ppm), time (180 min), and biosorbent amount (75 mg), as designed using response surface methodology. The innovative biosorbent material derived from waste fish scales has proven highly effective in removing synthetic dyes from wastewater. This biosorbent presents a potential solution to wastewater pollution, demonstrating high efficiency in eliminating various pollutants, including heavy metals, pharmaceuticals, and organic compounds. Utilizing this material can substantially reduce environmental pollutants, contributing to a cleaner and healthier future.