Ecofriendly and sustainable Sargassum spp.-based system for the removal of highly used drugs during the COVID-19 pandemic

2.1 Materials

Sargassum spp. referred it as Sargassum for the rest of the manuscript (59.3 % S. fluitans, 35.8 % S. natans I, 3.3 % benthic microphytes, and 1.4 % S. natans VIII (Vázquez-Delfín et al. 2021)) used in this work was collected in Puerto Morelos Quintana Roo (20°50′44.1″N, 86°52′35.5″W) in June 2021. Hydrogen peroxide (30 % w/w in H₂O) from Sigma Aldrich to treat Sargassum. The drugs paracetamol (acetaminophen, BioXtra, ≥99 %), diclofenac sodium (>98 %, TLC), and ibuprofen (>98 %, GC), all analytical grade, were purchased from Sigma-Aldrich. The pH was adjusted with NaOH (BioXtra, >98 %, pellets-anhydrous) from Sigma Aldrich. All reactants were used as received. All aqueous solutions were made with deionized water.

2.2 Chemical treatment of Sargassum.

The Sargassum was washed several times with deionized water to remove impurities, garbage, and sand. Subsequently, it underwent a treatment consisting of placing 500 g of Sargassum in a 20 % solution of hydrogen peroxide for 24 h. The Sargassum was then rewashed with deionized water and left to dry in the shade for a week. Finally, the Sargassum was stored under refrigeration for later use.

2.3 Synthesis of carbon dots (CDs)

Clean, and dry Sargassum was pulverized using a 1000 W domestic blender and passed through a 150-mesh sieve (106 µm). Then 1 g of the Sargassum powder was mixed with 50 mL of 50 % water/isopropanol using magnetic stirring at 60 °C for 30 min. Subsequently, the liquid phase was recovered by filtration using Whatman #41 filter paper. Following that, CDs have been synthesized by hydrothermal treatment using the Sargassum extract as a natural precursor. In the hydrothermal synthesis, the aqueous suspension was heated at 250 °C using a Teflon-lined autoclave for 12 h. After synthesis, the supernatant was collected and evaporated. Then, the dry solid was redissolved in deionized water and centrifugated at 5000 rpm for 10 min to remove larger particles. Pure CDs with blue fluorescence can finally be obtained through a 200 nm filter membrane. The product solution was lyophilized and stored until further use.

2.4 Drug removal

Drug removal was carried out using the system shown in scheme 1, which consists of a container with a constant agitation system. In the walls are the inlet and outlet pipes, which are connected to regulation valves. The removal process consisted of placing and mixing 3.0 g of Sargassum with 500 mL of PCT at 15 ppm inside the container. Then, 10 mL samples were taken at intervals of 10 min until completed 2 h. After this time, the Sargassum was removed and left to dry in the shade for later characterization. This process was repeated for IBU and DFS.

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Scheme 1

System used for the drug removal using Sargassum as biosorbent material.

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The Sargassum removal capacity was evaluated using the algae repeatedly. The same procedure was carried out for PCT, IBU, and DFS. The Sargassum used in the removal was recovered, washed with deionized water, and dried; later, this same Sargassum was used to carry out the removal of the drug. This process was repeated until completing the four cycles.

2.5 Drug quantification

Fluorescence spectrophotometry (from 400 to 700 nm) was obtained with a Varioskan Flash microplate reader (Thermo Fisher Scientific, Waltham, MA, United States) using 360 nm as excitation wavelength. DFS, IBU, and PCT concentrations from 0 to 15 ppm were mixed with 50 µg/mL of carbon dots (CDs) to perform the calibration curve. Then, the analysis was centered at 480 nm, where higher fluorescence intensity was found for each sample.

With the obtained data, the sorption capacity (amount of the selected drug per unit weight of Sargassum at time t) was estimated using the following expression:

where $C_i$ is the initial concentration of the selected drug, $C_t$ the drug concentration (mg/L) at a given time t, V the volume of the solution (L), and w the weight of Sargassum used as biosorbent (g).

Using the data collected, the remotion efficiency, R (%), was calculated using equation (2):

where $C_i$ is the initial concentration of the selected drug, $C_t$ the drug concentration (mg/L) at a given time t.

Moreover, the distribution coefficient (K_d) was calculating to observe the chemical affinity between the drug and the algae:

where $C_i$ is the initial concentration of the selected drug, $C_t$ the drug concentration (mg/L) at a given time t, V the volume of the solution (L), and w is the mass use of Sargassum for biosorption (g).

2.6 Determination of kinetic parameters

The kinetic parameters were calculated to evaluate the speed of motion; Likewise, they are very useful to suggest the possible mechanisms that take place in the removal process. The most and herby used models are the Lagergren pseudo-first-order (PFO, Eq. (4)), Ho & Mckay pseudo-second-order (PSO, Eq. (5)), and Elovich kinetic model (Eq. (6)).

where $q_e$ is the amount of drug sorption at equilibrium (mg·g⁻¹), $q_t$ is the amount of drug sorption at a given time $t$ (mg·g⁻¹), $k_1$ the equilibrium rate constant in the pseudo-first-order model (min⁻¹), $k_2$ the constant equilibrium rate of the pseudo-second-order model (g·mg⁻¹·min⁻¹), $h$ ( $k_2{q}_e^2$ ) the primary sorption rate, $\alpha$ the initial adsorption rate (mg·g⁻¹·min⁻¹), and $\beta$ the desorption constant (g·mg⁻¹).

Other factors involved in the adsorption process were evaluated using the equation (7) for the intraparticle diffusion model and the equations 8–10 for the Boyd diffusion models.

where $K_{\mathit{id}}$ (mg/g·min^1/2) is the model rate constant, $C_{\mathit{id}}$ the model constant, $t$ and $B_t$ are mathematical functions of $F$ .

Additionally, the initial adsorption factor ( $R_i$ ) of the intraparticle diffusion model was evaluated using the equation (11).

The last expression represents $R_i$ as the ratio of the initial adsorption amount ( $C_{\mathit{id}})$ to the final adsorption amount $q_{\mathit{ref}}$ .

2.7 Determination of molecular electrostatic potential (MEP)

Additionally, for further explanation of how the drugs interact with the biosorbent, the Molecular Electrostatic Potential (MEP) on the electron density surface of each drug was plotted by means of a DFT calculation using Gaussian 16 and later analyzed using GaussView 6 (Frisch et al. 2016). Geometry was fully optimized, assuming an ultrafine numeric integration cell, no symmetry restrictions, a temperature set at 278 K in the presence of water; using the range-separated functional ωB97XD, with the 6–311 g(d,p) basis sets and CPCM as the Self-Consistent Reaction Field (SCRF) method. Simulation conditions were maintained at every step of re-optimization, while convergence in force/displacement parameters in numeric and analytical hessian ensured a local energy minimum in the final structures.

2.8 Sargassum characterization

The Sargassum was characterized before and after the removal of the drugs. Diverse techniques were used to evidence the changes in the algae due to the presence of the drugs. The functional groups from Sargassum organic compounds and the changes caused by the presence of the drugs were evaluated by FTIR analysis. The spectrum was recorded from 400 to 4000 cm⁻¹ using a Spectrum Two FTIR spectrometer (Perkin Elmer, Waltham, MA, United States). Crystalline phases and structural changes in Sargassum were evaluated by X-ray diffraction using a Rigaku Ultima IV diffractometer with Cu Kα radiation in a range of 20 to 80°. The dry Sargassum samples were placed in copper sample holders and coated with gold for microscopy analysis. A SEM/STEM Hitachi SU8230 cold-field emission scanning electron microscope (Hitachi High-Tech, Tokyo, Japan) was employed to determine the Sargassum morphology. The chemical analysis was evaluated using an energy-dispersive X-ray spectrometer XFlash 6/60. Finally, a TGA/DSC Model 2 + StaRe System (Mettler-Toledo Intl. Inc., Columbus, OH, USA) thermal analyzer was used to determine the concentration of PCT, DFS, or IBU under a controlled nitrogen atmosphere. The analysis was performed from 30 to 700 °C using a 10 °C/min rate.

3.1 Removal of drugs

The monitoring of drug removal was carried out by fluorescence analysis using quantum dots (CDs), which are fluorescent materials with quasi-spherical form and are approximately 10 nm in size. CDs have been commonly used in a broad range of applications, including drug delivery (Yuan et al. 2017), bioimaging (Damarla et al. 2020), photocatalysis (Fernando et al. 2015), and as sensors (Cui et al. 2017) due to their unique optical properties, high photostability, low toxicity, biocompatibility, and inexpensive nature. Fluorescent sensors are often used to detect many ions owing to their simplicity and sensitivity. In the case of CDs, one of the most accepted fluorescence mechanisms is defined by their surface state, including the degree of oxidation and functional groups. By this mechanism, the protonation and deprotonation of the functional groups could result in the quenching/enhancement of CDs’ fluorescence.

The quenching-based drug detection feasibility was first assessing the interactions of CDs with each drug. DFS, IBU, and PCT concentrations from 0 to 15 ppm were mixed with 50 µg/mL of CDs to perform the calibration curve. Each solution was illuminated at 360 nm to excite the CDs and record their fluorescence spectra. Then, the analysis was centered at 480 nm because a higher fluorescence intensity was found there for each sample. Fig. 1a presents the calibration curves obtained after normalization. As can be noticed, the concentration is directly proportional to the fluorescence intensity, causing an enhancement in the fluorescence emission; therefore, the quantification of each drug could be made by monitoring fluorescence intensity variations.

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Fig. 1

a) Calibration curves to quantify DFS, IBU, and PCT concentrations. b) Effect of contact time on removing DFS, IBU, and PCT. Conditions: temperature (25 °C), pH (6), algal concentration (6 mg·mL⁻¹), and initial drug concentration (15 ppm).

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Taking advantage of this process, while the Sargassum removed each drug from water, every 10 min was taken a sample, mixed with 50 µg/mL of CDs, and analyzed through fluorescence. Again, the excitation wavelength was fixed at 360 nm and the emission wavelength at 480 nm to quantify the remotion efficiency using the calibration curve previously obtained. Fig. 1b shows the amount of each drug removed against time, where a decrease of each drug concentration is observed in each experiment, confirming the capabilities of the Sargassum to remove this kind of contaminants. The test was repeated three times, and in each one the remotion efficiency was around 98 % of DFS, 85 % of IBU, and 54 % of PCT with a standard deviation of 0.63 %, 0.77 %, and 0.84 %, respectively. As can be seen, DFS shows a more considerable remotion, followed by IBU and PCT. Then, it is easier for the Sargassum to adsorbed DFS and more difficult for PCT.

Changes in the sorption capacity of Sargassum against time are presented in Fig. 2a; as it is observed, as time increases, the drug sorption from the algae increases. The remotion takes place rapidly for DFS and IBU during the first 20 min of the experiment, while PCT uptake is more constant through time until all reach the equilibrium found at 120 min. The values obtained for sorption capacity coincide with the percentage of removal in equilibria since DFS sorption has both the highest removal (R = 98 %) and the highest sorption capacity (q_e = 2.4677). In contrast, PCT has the lowest removal (R = 54 %) and sorption capacity (q_e = 1.4151), and IBU is in between (R = 85 %, q_e = 2.0842). Furthermore, the remotion values are higher than those from other algae and microalgae reported elsewhere (Coimbra et al. 2018, Santaeufemia et al. 2018, Parus et al. 2020, Hifney et al. 2021). For example, in this work, the maximum adsorption capacities were approximately-two times less IBU than Santaeufemia et al. (Santaeufemia et al. 2018) (3.97 mg vs 1.7 mg), the same amount of PCT as Parus et al. (Parus et al. 2020), and five times the maximum adsorption capacities of DFS attained by Hifney et al. (0.429 mg vs 2.3 mg) per gram of algae. It is important to notice that the sorption capacity values obtained from fluorescence analysis with CDs are consistent and have similar values to those obtained from TGA analysis. Thus, the latest can be a handy tool when other characterization techniques for measuring drug removal such as HPLC are unavailable.

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Fig. 2

a) Time-dependent removal capacity for DFS, IBU, and PCT. b) Recycling (reuse) of Sargassum; change in remotion efficiency (%) after four cycles of the selected drugs at 25 °C.

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On the other hand, the capability of reusing the Sargassum, four cycles of remotion were performed with each drug, and the results are shown in Fig. 2b. As can be seen, even when the efficiency is lower, even after three cycles, the remotion of DFS and IBU reaches around 60 %. This implies that some active sites or pores remain occupied between each cycle, then the concentration of each drug is higher enough to totally saturate the active sites at a lower concentration than the previous cycle.

One of the parameters that can favor the biosorption of some pollutants is the temperature of the system. The Fig. 3 shows the removal of DFS, IBU, and PCT at different temperatures. As can be seen, the removal of drugs is favored when the temperature is increased to 30 and 40 °C. For the three drugs, 100 % removal is obtained with increasing temperature. This behavior has been previously reported (Khadir et al. 2020, Wu et al. 2021), showing that drug biosorption is an endothermic process. However, according to Sajid et al. (Sajid et al. 2022), the increase in high temperatures can become an exothermic process, decreasing their removal.

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Fig. 3

Removal percentage of DFS, IBU, and PCT at different temperatures (25, 30, and 40 °C).

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Previous results show that drug removal using sargassum as biosorbent material is an efficient process, even at room temperature. In this sense, different materials and processes have been used for the same purposes. Table 1 shows a compilation of various recent works in which the removal of drugs was carried out. As can be seen, in most reports, removal efficiency is high, in some very close to 100 %. However, in some cases sophisticated materials such as composites or nanostructures were used, whose synthesis is a complex process. Among the most used removal methods are adsorption and photodegradation. In addition, depending on the type of process, conditions such as temperature, pressure and energy are required. It should be noted that in this work the biosorbent material is a dead algae and the removal process does not require specific conditions. In addition, the use of sargassum is of great importance in some parts of the world, specifically on the coasts of the Caribbean Sea, due to the overpopulation of this algae in recent years, which has brought serious environmental and economic problems.

3.2 Analysis of drugs biosorption

Differences between the remotion of DFS, IBU, and PCT may be related to the physical properties and chemical affinity among the molecules and the biochemical composition of the algae cell wall. A distribution coefficient (sometimes so-called partition coefficient) is widely used to relate the concentration of a chemical solute in a specific phase related to that in another between which equilibrium is approached. The solute can be any inorganic/organic substance, and the phase of interest can be any media such as water, air, soil, sediment, etc. This parameter is often used in drug design as a proxy measure for membrane permeability.

The values of K_d are of great interest since they can be related to the biosorption of Sargassum from the perspective of their functional groups. Sargassum’s cell wall possesses a wide variety of functional groups, such as carboxyl, sulfhydryl, and hydroxyl, that could act as binding sites for the selected drugs (as already discussed from the FTIR analysis), and Fig. 4 shows the data obtained from K_d for each of the selected drugs. It is observed that there exist different behaviors of distribution coefficient for each drug against time; its values at the equilibrium time are consistent with the tendency obtained from both removal and sorption capacity (S-DFS > IBU > PCT). For PCT, it is observed that practically K_d is constant against time. This behavior is an indication that the drug does not interact entirely with the functional groups in the cell wall of the brown algae; unlike DFS, at the begging of the sorption K_d is constant. Still, after 80 min, an exponential increase reflects a higher drug interaction with the cell wall. It has been recently proposed that calcium is necessary for maintaining the fibrous layer in the cell walls of brown algae, composed mainly of alginate gels (Terauchi et al. 2016).

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Fig. 4

Distribution coefficient K_d obtained vs time of DFS, IBU, and PCT.

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Differences between DFS, IBU, and PCT remotion may be related to physical properties, the chemical affinity among the molecules, and the biochemical composition of the algae cell wall. Besides, it is known that pH alters the surface charge of the adsorbent due to functional group dissociation. Even more, the remotion is also influenced by the acid-base dissociation constant, pKa, defined as the pH at which the drug is 50 % ionized. Thus, to better understand the mechanism behind the remotion and efficiency between each contaminant, the remotion was evaluated by changing the pH of the DFS, IBU, and PCT solutions at 3.0, 4.0, 7.0, and 9.0. Then each solution was put in contact with Sargassum to evaluate the remotion.

Interestingly, the curves did not show important variations against pH, suggesting that the Sargassum, with all their functional groups, acts as a buffer that could maintain a stable pH in the peripheral solution without limiting the remotion efficiency. Thus, the pH of the solution was measured, resulting in pH = 6 in the three systems, corroborating the suggestion. Using absorbents with a negative charge, some researchers have reported that the adsorption efficiency of DFS decreases at pH values below its pKa (4.2) because it presents a neutral form. However, it carries a negative charge at pH values higher than 4.2. Additionally, sodium ions from DFS present an electrostatic interaction with carboxyl groups, resulting in higher adsorption efficiency at pH 6 (Hifney et al. 2021). Comparably, IBU is not charged at low solution pH, equal to or below to pKa (4.9). However, as the solution pH increases, the carboxylic group begins to dissociate. Almost all IBU molecules are negatively charged when the solution pH is above 7 (Santaeufemia et al. 2018), explaining why we have better remotion efficiency of DFS than IBU, even when their pKa is similar. In contrast, PCT has a pKa value between 9.0 and 9.50 (Parus et al. 2020). Therefore, solutions with 2.0 < pH < 9.0 present neutral PCT molecules, limiting the remotion by chemical means, suggesting a physical remotion.

3.3 Kinetic analysis of the drugs removal

The use of adsorption kinetics parameters can help to predict, evaluate and understand the sorption rate; it gives relevant information on the properties of the adsorbent for the target pollutants for assessing, designing, scaling, and modeling the process. Sorption kinetics are described by different models, where time-dependent changes in the adsorbate concentration until an equilibrium state is reached are observed. Therefore, the adsorption of the various drugs was fitted using the Pseudo First Order (PFO), Pseudo Second Order (PSO), and Elovich kinetic models; the kinetic parameters obtained from the described models are depicted in Table 2, and their correct fit to the experimental data was compared using the correlation values (R²).

The PFO kinetic model assumes that the sorption rate is proportional to the number of surface vacancy sites on the adsorbent (Borhan et al. 2019). The PSO kinetic model assumes that the sorption rate is linearly related to the square number of the vacancy sites available on the adsorbent (Borhan et al. 2019). Finally, the Elovich kinetic model describes activated chemical adsorption, assuming that the system has energetically heterogenous adsorbing surfaces; in other words, the adsorption rate decreases exponentially as the surface coverage increases by the adsorbent (Wu et al., 2009a), (Sahoo and Prelot, 2020).

The kinetics results showed that all the drugs are consistent with different kinetics models, as observed from the relation coefficient (R²) obtained for each. It is observed that in all drugs $R^2$ for the Elovich model are relatively high (>0.9). In particular, DFS presents the highest value (0.9842), suggesting that this model best represents its adsorption kinetics. For the PFO model, the correlation values for IBU and PCT (0.9570 and 0.9662, respectively) are reasonably good, indicating that the model described the results better than the Elovich model. Finally, the R² values for the PSO model from DFS and IBU (0.9646 and 0.9612, respectively) are pretty high to fit the model of both drugś adsorption by Sargassum. As observed, IBU is well fitted by the PFO and PSO models, but when analyzing the derivate $q_{cal2}$ from the PSO is observed, it is closer to the experimental data q_e than the $q_{cal1}$ from PFO model, suggesting the PSO model describes IBU kinetics.

In summary, S-PCT is governed by the PFO kinetic model, suggesting mainly surface adsorption and is consistent with the fact the $K_d$ behavior, discussed in Fig. 4, has the lowest value and is almost constant through time, indicating no chemical interaction. S-IBU agrees with the PSO and may be explained on the assumption that its rate-limiting step, as chemisorption, involves valency forces through sharing or exchanging electrons between adsorbent and adsorbate (Jellali et al. 2011, Riahi et al. 2017); which also explains why $K_d$ evolution through time is slow but has a higher equilibrium value than S-PCT. Finally, the data for S-DFS had a good agreement with the Elovich model; this involves a variation of the energies in the chemisorption with the active sites that are heterogeneous in Sargassum and therefore exhibit different activation energies for chemisorption because of cell walls composition (Riahi et al. 2017) and has consistency with the results obtained from $K_d$ .

These results imply that the chemisorption mechanism may play an essential role in the adsorption of DFS and IBU by Sargassum and are consistent with other studies (Coimbra et al. 2018, Santaeufemia et al. 2018, Parus et al. 2020, Hifney et al. 2021). For PCT is implied that adsorption occurs mainly by diffusion through the Sargassum interface (Krstić 2021). Despite these suggestions, the good fitting of the models for the rest of the drugs indicates that Sargassum is a highly heterogeneous system in which surface adsorption, chemisorption, and probably ion exchange, intraparticle diffusion, and precipitation co-occur.

Further analysis of the factors limiting the adsorption process, the adsorption curves of the different NSAIDs over time were fitted by intraparticle diffusion (eq. (7)) and the Boyd diffusion (eq. 8–10) models, as observed in Table 3.

Generally, the adsorption process is affected by both intraparticle/film diffusion, and more information on the mechanism involving the Sargassum in the presence of the different NSAIDs can be obtained by determining the rate-controlling step by using the proposed models. The results related to intraparticle and film diffusion can be observed in Table 3. It is observed that S-DFS and S-IBU have an excellent linear correlation with intraparticle diffusion. In contrast, S-PCT has a linear correlation with Boyd’s diffusion model, showing a different description of the adsorption process as already observed kinetics. It is observed in both cases a single, main controlling and rate-limiting stage of adsorption which can be related to slow adsorption in which the adsorption sites are bit by bit occupied, and the NSAID number increase inside Sargassum. During the process, differences between the potential energy and the NSAID in the solution gradually decrease or even exceeds the potential energy of the solution, so the adsorption rate is low in which a dynamic equilibrium cannot be reached before the drug completely occupies the adsorption sited. Moreover, from Table 3, the intercept of the fitting line is not 0 on the Y-axis in both models. It is shown that neither was the only rate-controlling step, and adsorption may be controlled by many factors (Shang et al. 2021) but mainly intraparticle diffusion for S-DFS and S-IBU, and film diffusion for S-PCT.

Additionally, the adsorption process can be further analyzed using an expression described by (Wu et al., 2009b), which after mathematical rearrangement can give a term defined as the initial adsorption factor ( $R_i$ ) of the intraparticle diffusion model (equation (11)). The $R_i$ values obtained for the adsorption of the NSAID onto de Sargassum are 0.92 for S-DFS, 0.94 for S-IBU, and 0.84 for S-PCT. These results suggest that the $R_i$ values for S-DFS and S-IBU are under zone 1 regiment in which weak initial adsorption takes place. S-PCT is under zone 2, meaning initial intermediate adsorption (Wu et al., 2009b, Pholosi et al. 2020). With the obtained data, it can be suggested that surface adsorption is not the dominant process as already described since Sargassum is a very heterogeneous matrix for the adsorption process of the NSAID.

3.4 Molecular electrostatic potential (MEP)

These observations are further confirmed by observing the MEP analysis of the drugs in the presence of water (pH 6), as seen in Fig. 5. MEP is an important study in molecule interactions since it can predict relative sites for nucleophilic and electrophilic attacks. The electrostatic surface potentials are presented using different colors. By convention, red is used for negative (electrophilic reactivity), green for zero, and blue for positive (nucleophilic reactivity) electrostatic potentials.

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Fig. 5

Schematic representation of MEP surfaces of a) DFS, b) IBU, and c) PCT.

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For DFS, it is observed that the molecule, in general, is slightly negatively charged, and the most negative electrostatic potential is localized in the carboxylate ion. For IBU, the molecule is more neutral charged (and thus has higher intermolecular interactions). The most negative potential is located on the carbonyl group’s oxygen molecule, which is next to a positive potential from the hydrogen in the hydroxyl group of the carboxyl. PCT has two positive potential regions in the aminophenol molecule, one from the hydrogen of the hydroxyl group and the other from the hydrogen of the nitrogen group, besides a slight negative potential from the oxygen present in the acetyl substituent of the amino molecule. These red regions in all drugs are potential sites for an electrophilic attack. When comparing the energy values obtained from MEP (DFS =  $\left|6.69\right|$ eV, IBU =  $\left|179.74\right|$ eV and PCT =  $\left|212.24\right|$ eV) considering calculations using water as a solvent, it is clear that DFS has the highest probability of an electrophilic attack since it has the lowest absolute energy value. In contrast, IBU and PCT have lower probability (lower absolute energy). These results can be related to pH, which is an important factor for the K_d values between Sargassum, drugs, the remotion, and the sorption capacity of Sargassum to these selected drugs.

3.5 Characterization of Sargassum

The Sargassum used for the drugs removal was recovered and dried to analyze it by the different characterization techniques and, in this way, determine the changes suffered during the removal of the drugs. X-ray diffraction (XRD) was used to identify the structures present in the pure Sargassum (S) and the Sargassum with absorbed IBU (S-IBU), DFS (S-DFS), and PCT (S-PCT) drugs. Fig. 6a shows the XRD patterns, confirming the presence of calcium carbonate “calcite” (CaCO₃) ICDD 00–005-0586, magnesium sulfide “iningerite” (MgS) ICDD 00–035-0730, and calcium oxalate hydrate (C₂H_4.5CaO_6.25) ICD 00–020-0233 phases in all the samples. It is important to mention that, unlike other reports (Paraguay-Delgado et al. 2020), in this particular case, the calcium oxalate phase was found in the pure Sargassum samples. However, this phase was removed when drugs were absorbed, decreasing the intensity of the peaks. This can be related to a change in the cell wall integrity of the Sargassum (Terauchi et al. 2016). In contrast, the intensity of the diffraction peaks of the calcium carbonate phase increases, which means a higher concentration in the samples, while the MgS phase is almost the same in all the samples. There are two diffraction peaks at 2θ values, 16.5°, and 22.2°, which are characteristic peaks of the alginate phase coming from the Sargassum (Helmiyati and M. Aprilliza, 2017), Kavitha et al. 2019). Considering the peak height intensity and the degree of crystallinity could diagnose the semi-crystalline nature of alginate (Dalal et al., 2021a). In addition, the structure of the diatoms, which is a random network of tetrahedral bond silicon atoms, is localized mainly between 2θ values 20° to 25° (Briceño et al. 2021). The diffraction peaks of the drugs are predominantly found at 2θ values lower than 25°. Slight differences can be observed in the XRD patterns between 2θ values 5 to 15°, which correspond to the effect of the different drugs compared to pure Sargassum.

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Fig. 6

Characterization of Sargassum before and after the removal of drugs: a) XRD patterns, and b) FTIR spectra.

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An FTIR analysis was carried out to support the results obtained by XRD. Fig. 6b shows the FTIR spectra of Sargassum before and after removing each of the drugs. Various signals can be observed in the spectrum corresponding to Sargassum. The strong band located at 3310 cm⁻¹ corresponds to the O—H bond of the hydroxyl groups of the aromatic compounds from the Sargassum. This type of compound is corroborated by the vibrations from the aromatic rings observed at 1523 cm⁻¹. The presence of non-aromatic compounds in Sargassum is demonstrated by the vibration at 2900 cm⁻¹, corresponding to C—H groups. The band centered at 1628 cm⁻¹ corresponds to COO vibrations from metal carboxylates and C⚌O bonds from alginates (Samir et al. 2016, Dalal et al., 2021a). The signal at 1410 cm⁻¹ is attributed to the vibrational band of the C—O group of calcite present in this type of algae (Paraguay-Delgado et al. 2020). The sulfates in brown algae, contained mainly in fucoidan, have been previously reported (Sinurat et al. 2016). In this case, the signals located at 1230 cm⁻¹ and 832 cm⁻¹ confirm the presence of S—O groups. Finally, the band located at 1030 cm⁻¹ is attributed to the C—O groups coming from the alginates in the Sargassum. By comparing the spectra, the same bands can be observed, with intensities variations due to the interaction of the drugs with the organic compounds of the Sargassum. Mainly, a notable decrease in intensity is observed in the band corresponding to the O—H group (3200 cm⁻¹), which can also be observed in the bands centered at 1628 cm⁻¹ (C⚌O) and 1030 cm⁻¹ (C—O), suggesting that O—H bonds are involved in the drug biosorption process.

The surface morphology of the pure Sargassum and S-IBU, S-DFS, and S- PCT was observed by scanning electron microscopy (SEM), displayed in Fig. 7. Fig. 7a shows the SEM images of the pure Sargassum where the surface morphology is irregular. Even diatoms, found in almost marine water with a siliceous skeleton, are presented. Also, besides diatoms, calcium oxalates were found. As mentioned in the methodology section, the samples were washed to eliminate waste from the marine environment; however, some structures are still present. Fig. 7b, 7c, and 7d show a totally different surface morphology than pure Sargassum. All the SEM images clearly show fibrils characteristic of alginate (Helmiyati and M. Aprilliza, 2017). In addition, some impurities have been removed because of the effect of the drugs, such as calcium oxalate; however, diatoms and calcium carbonate structures can still be observed. Fig. 7e shows the EDS spectra of the samples. As can be noted, all the spectra show calcium (Ca), sulfur (S), magnesium (Mg), oxygen (O), and carbon (C) elements from the Sargassum. Gold (Au) and aluminum (Al) elements are from the thin metallic coating and the holder used in the analysis, respectively. It is interesting to notice that the silicon (Si) element is present in all the samples, which is part of the structure of diatoms, indicating the presence of these structures in all samples.

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Fig. 7

SEM images of a) pure Sargassum, b) S-IBU, c) S-DFS, d) S-PCT, and e) EDS spectra of the samples.

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The presence and concentration of drugs can also be estimated by thermogravimetric analysis. Fig. 8a shows the TGA results obtained. The dry Sargassum, free of drugs (S), was subjected to treatment observing three different processes. In the range between 30 and 200 °C, a weight loss is observed, attributed to the evaporation of the water present in the Sargassum. Afterward, the decomposition and calcination of organic compounds occur between 200 and 600 °C, observing a significant decrease in weight. Finally, the event between 600 and 700 °C corresponds to the generation of CO₂ due to the decomposition of carbonates. Previous studies have already reported this behavior in this type of algae (Paraguay-Delgado et al. 2020, Alzate-Gaviria et al. 2021). At the end of the experiment, a remaining weight of 32.5 % is observed. This means that Sargassum loses 67.5 % of its weight. Subsequently, the Sargassum samples containing each drug were subjected to the same analysis. The results indicated a percentage of the remaining weight of 32.55 %, 32.58 %, and 32.59 % for PCT, IBU, and DFS, respectively (inset in Fig. 8a). In this way, it was estimated that the amount of DFS, IBU, and PCT per gram of Sargassum was 2.77, 2.46, and 1.54 mg, respectively.

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Fig. 8

a) Thermogravimetric analysis and b) Four derivative weight plots of Sargassum before and after the drug’s removal.

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On the other hand, the decomposition of these types of drugs by TGA analysis has been determined by the derivation process of the curve obtained (Higareda et al. 2019). Specifically, the second derivative has been used for these purposes, finding a peak between 250 and 300 °C. However, in this study, it was not possible to distinguish this signal due to the similarity between the composition of the Sargassum and the drugs. Therefore, the fourth derivative analysis was carried out, shown in Fig. 8b. As can be seen, in the curve corresponding to Sargassum, there are three peaks or intense signals located at 249, 343, and 389 °C due to the decomposition of organic compounds. These same signals can be observed in the curves corresponding to Sargassum containing the different drugs. However, shifts to the left are noticeably observed because of PCT, DFS, or IBU. Furthermore, an additional signal is observed between 260 and 290 °C, attributed to drug decomposition, as previously reported (Khanmohammadi et al. 2012, de Oliveira et al. 2017). These results corroborate the biosorption of drugs in the Sargassum.