Sustainable adsorption of methylene blue (MB) dye using individual and combined ratios of Trigonella foenum-graecum (F) seed galactomannan and Linum usitatissimum (L) seed

Environmental issues are drawing researchers’ attention nowadays due to their adverse effects on public health and the environment (Pal et al. 2014). Several kinds of diseases are caused by prolonged exposure to contaminants that are emerging mainly because of anthropogenic activities, including rapid industrial growth (Miyah et al. 2018). These contaminants are responsible for affecting the key mediums of life on Earth such as air, soil, and water (Heibati et al. 2015; Munagapati et al. 2018; Mannan et al. 2022). Among all kinds of pollutants, dyes are the main constituents of waste emerging mainly from the industrial sector (Mittal et al. 2010; Uddin et al. 2017; Mondal & Kar 2018) and are accountable for affecting both the environment and life on Earth due to their carcinogenic and mutagenic nature (Haik et al. 2010; Ai et al. 2011; Anastopoulos & Kyzas 2014). Methylene blue (MB) dye is one of the cationic dyes having the molecular formula of C₁₆H₁₈N₃SCl and molecular weight of 319.85 g/mol (Khan et al. 2022). This dye is noxious in nature and is responsible for causing numerous health issues including eye burn, cardiac disorder, fever, headache, and anemia. The non-biodegradable nature of this dye makes its removal from wastewater very difficult, which poses a serious threat to the environment and all life forms on Earth (Ghzal et al. 2023). In view of this, for ensuring the well-being of our ecosystem and sustaining life on this planet, it is crucial to find an appropriate way to treat polluted water (Konicki et al. 2015).

When it comes to treating wastewater, numerous water treatment procedures have been developed and are in use today. These include traditional physicochemical or biological methods for dye removal from wastewater like photochemical degradation, adsorption, reverse osmosis, membrane separation, oxidation, coagulation/flocculation (Gupta 2009; Idrissi et al. 2014; Duta & Visa 2015; Miyah et al. 2017) and biological treatment using some microorganisms (Room & Center 2004). However, each of the aforementioned methods has its own merits and demerits such as the high cost associated with the operation and toxic by-product formation (Zhou et al. 2018) that limit their uses for treating wastewater (Zhou et al. 2018). Among all currently available techniques, adsorption is one of the most effective methods for treating dye-loaded wastewater because of its low cost, remarkable efficiency, and easy operation (Jain et al. 2014; Naushad et al. 2016; Ahmad et al. 2017; Daraei & Mittal 2017; Arora et al. 2020; Kumar et al. 2020; Soni et al. 2020; Arora et al. 2021; Haddad et al. 2021; Patel et al. 2021; Saharan et al. 2021; Mariyam et al. 2021a, 2021b, 2021c; Mittal et al. 2021a, 2021b, 2021c, 2022). In the adsorption treatment, the selection of an appropriate adsorbent for maximum removal of the pollutant plays a crucial role (Azhar-ul-Haq et al. 2022). To date, numerous adsorbents have been studied for treating wastewater such as Cedrus deodara sawdust (Batool et al. 2021), walnut wood (Hajati et al. 2016), coconut husk (Foo & Hameed 2012), loofah sponge (Li et al. 2018), orange peels (Oyekanmi et al. 2019), sugarcane bagasse (Noreen et al. 2020), rice husk (Bhatti et al. 2020), peanut hull (Tahir et al. 2017; Yang et al. 2020), potato peels (Chidi & Kelvin 2018), algae (Kumar et al. 2006), soy waste (Jawad et al. 2020), stone of mango (Shoukat et al. 2017), activated carbons (Pereira et al. 2003), zeolites (Bosso & Enzweiler 2002), silica beads (Krysztafkiewicz et al. 2002), industrial by-products (Garg et al. 2003; Netpradit et al. 2003), agricultural wastes (Robinson et al. 2002a, 2002b), polymeric materials (Lord et al. 2022; Mashkoor et al. 2023), and others (Gupta 2009; Salleh et al. 2011; Miyah et al. 2015, 2016; Miyah et al. 2017).

However, some of these adsorbents are costly and their adsorption efficiency is low in most cases, which can be improved by some physical or chemical treatments, for example, modification or by making composites with other materials (Miyah et al. 2018). Therefore, the use of some non-modified, abundant, low cost, and waste materials as an adsorbent, such as Trigonella foenum-graecum (F) and Linum usitatissimum (L), were considered for efficient MB dye removal, giving an extra economical interest to technical adsorption studies. Linseed (L. usitatissimum L.) crop is commonly cultivated in India. Activated carbon obtained from deoiled cakes finds extensive uses in treating wastewater having numerous metals and dyes in it (Khan & Khan 2016). Fenugreek (T. foenum-graecum) is another valuable crop in India and is commonly known as Methi and is widely available all over the world. Once the leaves of fenugreek are cut for cooking, the residual stems and roots are discarded as waste products that can be employed as adsorbent for treating wastewater (Jain et al. 2020). Upon mixing F and L adsorbents equally (1:1 or 2:2) and in variable (2:1 or 1:2) ratios, adsorptive removal of MB dye can be improved, which is the main focus of the study.

Keeping in view the aforementioned discussion, current research aims to investigate the efficiency of individual F seeds and L as adsorbents for MB dye adsorption, and to investigate their combined effects in four different ratios, i.e., 1:1, 1:2, 2:1, and 2:2, respectively, for MB adsorption, to optimize the adsorption parameters including solution pH, adsorbent dose, dye concentration, contact time, and temperature for maximum dye removal, to apply concentration and contact time data to different isotherm and kinetic models for determining the best fitted model, to explore the adsorption process thermodynamically via the Van't Hoff plot, to investigate the mechanism of MB removal on studied adsorbents and to compare the adsorption capacity of studied adsorbents with already reported adsorbents toward MB dye removal. It is noteworthy to mention here that two different (1:2 and 2:1) and two equal ratios (1:1 and 2:2) of adsorbents were used and the ratio 2:2 is just the double amount of 1:1, but this variation in amount used was done to better understand the effect of doubling the amount of adsorbent. Although many other researches have already been reported in the literature that involve the study of MB adsorption (Mahmoud et al. 2016; Basrur & Ishwara Bhat 2017a, 2017b; Gopalakrishnan et al. 2020; Kuang et al. 2020; Ahmad & Ansari 2021; Işık & Uğraşkan 2021; Sharma et al. 2022; Taweekarn et al. 2022; Zeghioud et al. 2022; Kumari et al. 2023), the current work is novel in a sense that to the best of our knowledge it is the first ever report on studying the individual and combined adsorptive efficiency of F and L in six different forms (i.e., F, L, F + L (1:1), F + L (2:2), F + L (1:2) and F + L (2:1)) for MB dye removal.

The analytical-grade chemicals utilized in the current study include sodium hydroxide and nitric acid (for investigating the effect of solution pH on dye adsorption). The dye used here is MB that was purchased from a chemical drug house (CDH). Further, distilled water was used as a solvent throughout the research work. The percentage purity of the dye used was 99.99%. The instruments used were a Fourier transform infrared (FTIR) spectroscope, an X-ray diffractometer (XRD), a scanning electron microscope (SEM), a Brunauer–Emmett–Teller (BET) analyzer, a UV-visible spectrophotometer, a pH meter, a weighing balance, a centrifuge machine, and a hot plate.

A standard MB solution of 1,000 mg/l concentration was prepared by dissolving stoichiometric amount of dye, i.e., 1 g in enough distilled water to make total volume of 1,000 ml. Solutions of required dilute concentrations were then obtained by diluting the stock solution with distilled water.

For optimization of experimental conditions for maximum dye removal, batch study was conducted by varying one parameter at a time while keeping others as constant. The physicochemical parameters studied included solution pH (2–12), dose of each adsorbent (0.1–1.2 g adsorbent/0.02L of dye solution), dye concentration (10–120 mg/l), contact time (10–120 min), and temperature (10–50 °C). Totally, 20 ml of dye solution having concentration of 40 mg/l was used for investigating the effect of solution pH and adsorbent dose. For subsequent trials, i.e., contact time and temperature experiment, solution concentration of 80 mg/l was used. Dose of each adsorbent used during all experiments was 1 g of adsorbent/0.02L of dye solution. Each experiment was conducted at 12 pH except for the pH study where the solution pH varies from 2 to 12. A contact time of 40 min was applied to each experiment while studying the effect of solution pH, adsorbent dose, and dye concentration, while for the study of contact time, adsorption time was varied from 10 to 120 min for its optimization where maximum results could be achieved. At the end, temperature study was carried out at the optimized time period of 60 min. All experiments were performed at 313 ± 1 K unless otherwise specified.

Herein, and are initial and final absorbance of dye solution, and refer to the initial and equilibrium concentration of the dye, V refers to volume (ml) of the dye solution, and M refers to the mass (g) of adsorbent used. Experimental data from dye concentration and contact time experiment were applied to three different isotherm and kinetic models correspondingly, while a thermodynamic study was carried out on the results of the temperature study.

For characterization of the prepared adsorbents, different analyses techniques were employed as mentioned previously, including FTIR, XRD, and SEM for determining the functionalities present in adsorbents (Batool et al. 2022; Shah et al. 2024), their crystallinity or amorphous nature (Batool et al. 2022), and morphological analysis of the prepared adsorbents, respectively (Yusuff 2019; Batool et al. 2021).

Characterization results of all six studied adsorbents have been summarized as follows.

For the better understanding of the pH effect on MB dye adsorption, point of zero charge (pH_pzc) was determined according to the methodology adopted by Taqui et al. (2023) and was 6.6 for fenugreek and 5.2 for linseed. Based upon this pH_pzc, it is observed that when the solution pH is higher than pH_pzc, it makes the surface of the adsorbent negatively charged, which favors the adsorption of the cationic species (MB dye in this study), while on the contrary, when the solution pH is less than pH_pzc, it imparts positive charge on the adsorbent surface, which would then favor adsorption of anionic species (Dada et al. 2013). It is obvious from the pH study that all the studied adsorbents show maximum adsorption percentage at higher pH, i.e., 12, where the removal percentage of F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2) were 66.9, 66.3, 68.2, 66.9, 68.8, and 71.6%, respectively. From these observations, a solution pH of 12 was selected as the optimum pH in subsequent experiments for all studied adsorbents.

For investigating the nature of MB dye adsorption on the studied adsorbents, data from concentration experiments were applied to different isotherm models, namely, Langmuir, Freundlich, and the Dubinin–Radushkevich (D–R) isotherm model, discussed as follows.

A comparison of parametric values obtained from each model for all studied adsorbents is provided in Table 6. It is clear from the table that each adsorbent shows physical adsorption of MB dye as each adsorption process fits well to the Langmuir isotherm model because the regression coefficient value of each adsorbent is the greatest among other studied isotherm models. Further, the maximum adsorption capacity of the studied adsorbent is the highest, i.e., 31.98 mg/g when both F and L are mixed in the ratio 2:2, showing the effectiveness of the F + L (2:2) composition for MB dye adsorption.

Table 6

Comparison of parameters of different isotherm models for all studied adsorbents

Model .	Parameter .	F .	L .	F + L (1:1) .	F + L (1:2) .	F + L (2:1) .	F + L (2:2) .
Langmuir model	Qo (mg/g) experimental	1.21	1.26	10.98	16.46	29.42	32.29
	Qo (mg/g) calculated	1.06	1.18	10.66	15.99	29.08	31.98
	b	0.164	0.1552	0.018	0.010	0.004	0.0081
	R2	0.773	0.790	0.8406	0.909	0.928	0.955
Freundlich model	n	0.308	0.313	0.336	0.266	0.188	0.332
	Kf (mg g−1)	1.01 × 107	1.01 × 106	9.90 × 105	1.04 × 106	1.03 × 106	1.00 × 106
	R2	0.551	0.565	0.599	0.562	0.720	0.704
D–R model	β (kJ2 mol−2)	3 × 107	3 × 107	3 × 107	2 × 107	2 × 106	4 × 107
	ε2 (kJ mol−1)	4.08 × 10−4	4.11 × 10−4	4.22 × 10−5	5 × 10−4	1.6 × 10−3	3.5 × 10−4
	R2	0.546	0.561	0.593	0.559	0.720	0.703

Model .	Parameter .	F .	L .	F + L (1:1) .	F + L (1:2) .	F + L (2:1) .	F + L (2:2) .
Langmuir model	Qo (mg/g) experimental	1.21	1.26	10.98	16.46	29.42	32.29
	Qo (mg/g) calculated	1.06	1.18	10.66	15.99	29.08	31.98
	b	0.164	0.1552	0.018	0.010	0.004	0.0081
	R2	0.773	0.790	0.8406	0.909	0.928	0.955
Freundlich model	n	0.308	0.313	0.336	0.266	0.188	0.332
	Kf (mg g−1)	1.01 × 107	1.01 × 106	9.90 × 105	1.04 × 106	1.03 × 106	1.00 × 106
	R2	0.551	0.565	0.599	0.562	0.720	0.704
D–R model	β (kJ2 mol−2)	3 × 107	3 × 107	3 × 107	2 × 107	2 × 106	4 × 107
	ε2 (kJ mol−1)	4.08 × 10−4	4.11 × 10−4	4.22 × 10−5	5 × 10−4	1.6 × 10−3	3.5 × 10−4
	R2	0.546	0.561	0.593	0.559	0.720	0.703

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To better understand the adsorption mechanism and kinds of forces involved, different kinetic models, namely, pseudo-first-order, pseudo-second-order, and intra-particle diffusion models, were applied to the experimental data. The results obtained from each model are discussed as follows.

Table 7 shows a comparison of all the studied kinetic parameters for each adsorbent. It is observed from the table that for the pseudo-second-order kinetic model, the variation between experimental and calculated for all studied adsorbents is less in comparison with the other studied kinetic models. Also, the R² value of each adsorbent in case of the pseudo-second-order model is close to unity. All these results show the fitness of experimental data to the pseudo-second-order kinetic model. However, for the pseudo-first-order and intra-particle diffusion models, the results are also good (not too much variation between experimental and calculated and R² values close to 1) revealing the fitting of data to these models as well. In general, all three kinetic models studied here are good in explaining the mechanism of MB dye adsorption on each studied adsorbent, i.e., F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2).

Table 7

Comparison of parameters calculated from different kinetic models for MB dye adsorption on F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2

Model .	Parameter .	F .	L .	F + L (1:1) .	F + L (1:2) .	F + L (2:1) .	F + L (2:2) .
	Experimental	1.071	1.100	1.134	1.153	1.190	1.230
Pseudo-first-order	Calculated	2.13	2.22	3.66	2.68	2.32	3.09
		0.023	0.024	0.022	0.028	0.036	0.029
	R2	0.916	0.951	0.958	0.936	0.911	0.982
Pseudo-second-order	Calculated	1.92	1.70	1.46	1.43	1.39	1.38
		0.006	0.008	0.016	0.021	0.034	0.042
	R2	0.898	0.919	0.946	0.949	0.988	0.992
Intra-particle diffusion	Calculated	0.114	0.119	0.106	0.101	0.082	0.076
		0.196	0.189	0.023	0.080	0.331	0.428
	R2	0.986	0.985	0.981	0.968	0.984	0.988

Model .	Parameter .	F .	L .	F + L (1:1) .	F + L (1:2) .	F + L (2:1) .	F + L (2:2) .
	Experimental	1.071	1.100	1.134	1.153	1.190	1.230
Pseudo-first-order	Calculated	2.13	2.22	3.66	2.68	2.32	3.09
		0.023	0.024	0.022	0.028	0.036	0.029
	R2	0.916	0.951	0.958	0.936	0.911	0.982
Pseudo-second-order	Calculated	1.92	1.70	1.46	1.43	1.39	1.38
		0.006	0.008	0.016	0.021	0.034	0.042
	R2	0.898	0.919	0.946	0.949	0.988	0.992
Intra-particle diffusion	Calculated	0.114	0.119	0.106	0.101	0.082	0.076
		0.196	0.189	0.023	0.080	0.331	0.428
	R2	0.986	0.985	0.981	0.968	0.984	0.988

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Adsorption capacity of studied adsorbents (F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2)) for MB dye is compared with some already reported adsorbents in the literature as summarized in Table 9. It is clear from the table that some adsorbents show maximum affinity toward MB dye adsorption, while others adsorb MB dye to lesser extents. However, in comparison with the literature, the studied adsorbents possess good adsorption affinity toward MB dye and this can be improved when both fenugreek and linseed are mixed together in equal and higher proportion, i.e., 2:2. Overall, the results show the effectiveness of the studied adsorbents for maximum MB dye removal without any modification.

MB dye is a cationic dye and its adsorption is highly favored when the adsorbent surface possesses some kinds of negatively charged functionalities that attract dye molecules and help in adsorption. From the FTIR study it is clear that all the studied adsorbents, namely, F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2), possess several functional groups (already mentioned in sub-section 3.1.1) that become highly negatively charged when basic pH is added to the system. This can be attributed to the fact that at higher basic pH, functional groups of the studied adsorbent's surface become negatively charged owing to deprotonation, which favors cationic dye adsorption. Main functionalities that contribute majorly to MB dye adsorption include groups. These functional groups are responsible for the adsorption of MB dye via electrostatic forces and hydrogen bonding (El-Shafey et al. 2016; Zhang 2018; Batool et al. 2021).

The current research focused on the adsorptive removal of MB dye from aqueous solution using non-modified biosorbents that are easily available, low cost, and meeting the aspects of green chemistry. The biosorbents used in this research include fenugreek galactomannan, linseed, and four combinations of fenugreek and linseed, i.e., 1:1, 1:2, 2:1, and 2:2 in a batch mode. The characterization study reveals the presence of various functionalities in the adsorbents that are amorphous and possess highly rough and heterogeneous surfaces. BET surface area of the adsorbent (F + L combination) was found to be 394 m²/g. The results of the adsorption study reveals the effectiveness of the studied adsorbents as nearly 86.62, 86.94, 88.04, 88.24, 88.56, and 89.09% of MB dye adsorption takes place with F, L, F + L (1:1), F + L (1:2), F + L (2:1), and F + L (2:2) under optimized conditions (pH of 12, adsorbent dose of 1.2 g, dye concentration of 80 mg/l, contact time of 60 min at 40 °C). The isothermal study shows the fitness of the experimental data to the Langmuir isotherm model, while the kinetic modeling shows that both physical and chemical interactions are involved in dye adsorption. Further, spontaneity, endothermicity, and feasibility of the process were also confirmed from the thermodynamic study. Overall, it was observed that the studied adsorbents are effective and promising adsorbents for maximum MB dye removal.

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

The authors declare there is no conflict.