Pick-up of fluoroquinolones from the aqueous phase via magnetically propeled microrobots: kinetics, thermodynamics, and site energy distribution analysis

1 Introduction

Fluoroquinolones (FQs) are extensively consumed for disease prevention and growth promotion in animal breeding and aquaculture (Coffie et al., 2021). Mariculture tailwater has drawn much attention, as it brings serious eutrophication offshore and damage to the surrounding estuary ecosystems (Gao et al., 2022). Also, some of the FQs were officially detected in the mariculture system around the world (Wang et al., 2022). Most of the FQs cannot be metabolized or absorbed by the body, and so enter into the environment instead (Oberoi et al., 2019). They have also been recognized as new toxic organic pollutants in the aquatic environment (Saya et al., 2022). Antibiotic residues in water may endanger the ecosystem and human health because they can cause central nervous system stimulation, convulsions, ocular problems, inhibition of the neurotransmitter gamma-aminobutyric acid, reproductive dysfunction, and gastrointestinal disturbances (Saya et al., 2022). It is imperative to develop a green and effective technology to remove antibiotic residues from the aquatic environment.

When FQs enter the environment, they undergo migration and transformation processes such as adsorption, hydrolysis, photolysis, and biodegradation (Sarmah et al., 2006; Patel et al., 2019; Yang et al., 2021). While FQs are relatively stable in water they are not particularly suitable for hydrolysis (Van Doorslaer et al., 2014; Patel et al., 2019). The photolysis process is much easier to carry out (Wammer et al., 2013; Lakshmi Prabavathi and Muthuraj, 2019), but will produce active free radicals and cause secondary pollution. Therefore, adsorption is the primary way of removing FQs in land-based mariculture tailwater since the biodegradation rate of FQs is very low (Oberoi et al., 2019; Saya et al., 2022). Many absorbents have been confirmed to remove FQs from aqueous media, such as clay minerals (Hacıosmanoglu ˘ et al., 2022), biochar (Cheng et al., 2021), activated carbon (Kah et al., 2017) and other carbonaceous materials (Scaria et al., 2022), plastic polymers (Rai et al., 2022), graphene-based nanomaterials (Wang et al., 2019a), and Fe-oxide-based composites (Chu et al., 2022). Some green materials, such as plant leaves, fruit, algae, fungi, and bacteria, were employed to achieve energy-efficient, cost-effective, and environmentally friendly removal of organic pollutants (Altaf et al., 2021). Moreover, the favored adsorption has some strengths, such as a simple operation process, high treatment efficiency, rich adsorbent materials, and no highly toxic by-products (Fang et al., 2021b; Hacıosmanoglu ˘ et al., 2022).

Magnetic substrate-loaded adsorbent has been employed in the removal of FQs with easy regeneration (Fang et al., 2021a). Magnetic micro/nanorobots have piqued the interest of researchers because of their enormous potential for use in biomedicine and environmental remediation (Zhou et al., 2021). In addition to their bio-friendliness, recoverability, and toxin-free nature due to magnetic manipulation, they can actively swim around aquatic contaminants and remove them via capture (adsorption/absorption) or degradation (Zhang et al., 2018). Owing to the strong dynamic intermixing, also known as the magnetic stirring function, the magnetic fields can also be used to speed up reaction kinetics or increase recognition efficiency. They can also be used to retrieve nano/microrobots after the cleaning process is finished (Ji et al., 2020). The magnetic micro/nanorobots will eventually be able to be recycled or reused without their parts being altered. To deal with oil spills, researchers designed a micromotor that moved like a walnut and was made of polycaprolactone, Fe3O4 nanoparticles, and catalase in a solution with H2O2. The micromotor could be navigated and recycled using an external magnetic field (Wang et al., 2019b). Porous biohybrid microrobots made of fungal spores and Fe₃O₄ nanoparticles were found to be very effective at removing heavy metal ions. The group behaviors and magnetically driven movement of the microrobots may enhance pollutant adsorption more than static microrobots (Zhang et al., 2018). Carbon soot-based micromotors were simultaneously activated by a magnetic field and oxygen microbubbles, allowing for efficient on-the-spot degradation of methyl blue (MB) dye contamination (Singh et al., 2020). Additionally, it has been reported that functional magnetic micromotors were powerful enough to absorb or remove antibiotics from contaminated water (Li et al., 2019b; Liu et al., 2019).

In a previous study, we made magnetic microrobots with iron (II, III) oxide nanoparticles (Fe₃O₄ NPs) based on hydrocarbon-degrading bacteria (Pi et al., 2022). The magnetic microrobot performed excellently for Congo red adsorption from the aquatic phase (Pi et al., 2022). Owing to FQs having a similar benzene ring structure to that of organic dye, the removal of FQs with the help of a magnetic microrobot was the goal of this work. Norfloxacin (NOR) and levofloxacin (LEV) are FQs that are used widely, and the concentration of ng/L to μg/L has been detected in different aqueous environments (Fang et al., 2021a, b; Yan et al., 2017a; Yan et al., 2017b). They were used as typical FQs in this work. Adsorption capacity, kinetics, isotherm equilibrium, site energy distribution analysis, and mechanism were used to investigate NOR’s and LEV’s removal potential. Adsorption parameters, which corresponded to a specific site energy distribution, were also determined using a variety of isotherm models. Owing to their magnetic characteristics, microrobots were easy to navigate and were recycled under a magnetic field.

2 Materials and methods

2.1 Materials

Without further purification, all chemicals are at an analytical grade. The bacteria were isolated from an antibiotic-producing pharmaceutical factory’s sewage outlet. Our previous research serves as a reference for the isolation procedure (Pi et al., 2015).

2.2 Synthesis of microrobots

The microrobot can be simply defined as a nanocluster magnetite (Fe₃O₄) attached to bacteria. The Fe₃O₄ was prepared in accordance with previous studies (Schwertmann and Cornell, 2000; Jiang et al., 2018; Jiang et al., 2020). The preparation of magnetic microrobots is referred to in the literature (Pi et al., 2022; Vaghasiya et al., 2022). The details of the characterization of bio-based materials were also demonstrated according to the field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), fourier transform infrared (FTIR), and X-ray diffraction (XRD), nitrogen adsorption-desorption isotherms, magnetic behaviors, and point of zero charges (Pi et al., 2022).

2.3 Adsorption experiments

All adsorption experiments were conducted using 50-mL glass tubes in accordance with our previous work (Wang et al., 2021; Pi et al., 2022). To investigate the adsorption isotherm equilibrium, 50.0 mL of a NOR/LEV solution was mixed with 5 mg Fe₃O₄ or a magnetic microrobot, with initial NOR/LEV concentrations ranging from 10 to 50 mg/L. In addition, 0.1 mol/L NaOH and/or 0.1 mol/L HCl solutions were used to adjust the NOR/LEV solutions’ pH. The tubes were shaken at 150 rpm at a controlled temperature using a shaker in the dark. Then, the pH value (4–10), the adsorbent dose, and the adsorption temperature were changed to obtain the adsorption capacity.

In the kinetics experiments, a 500-mL NOR/LEV solution was mixed with moderate adsorbents. The NOR/LEV solution was measured using high-performance liquid chromatography (HPLC) after being adsorbed for various amounts of time. To avoid light, all samples were shaken in the dark. Each experiment was replicated three times.

Ultraviolet-(UV-)HPLC (1260, Agilent Technologies) was utilized for the detection of NOR and LEV. With a mobile phase of 60:40 (v/v) acetonitrile anhydrous and formic acid at 1% in deionized water and a flow rate of 0.75 mL/min, the HPLC was equipped with a C18 column (2.7 m, 4.6 mm × 100 mm). The wavelengths used for UV detection were 278 nm (NOR) and 293 nm (LEV).

2.4 Methods of data analysis

2.4.1 Equilibrium adsorption capacity

The following formulae (1–3) were used to calculate the NOR/LEV removal efficiency (adsorption percentage), adsorption capacities at time t, and equilibrium:

$\begin{array}{ll}R=\frac{(C_0-C_e)}{C_0}\times 100& (1)\end{array}$

$\begin{array}{ll}{q}_t=\frac{(C_0-C_t)}{w}V& (2)\end{array}$

$\begin{array}{ll}{q}_e=\frac{(C_0-C_t)}{w}V& \text{, (3)}\end{array}$

where R is the NOR/LEV’s removal efficiency; C₀ (mg/L), C_e (mg/L), and C_t (mg/L) are the concentrations of the initial, equilibrium, and time t of the NOR/LEV, respectively; the NOR/LEV’s adsorption capacities at time t and equilibrium are q_t (mg/g) and q_e (mg/g); and the adsorbent’s mass is w (g) and V (L) is the volume of the solution (Pi et al., 2022).

2.4.2 Fitting of adsorption isotherms

The empirical relationships between adsorption capacities of NOR/LEV on Fe₃O₄ and the magnetic microrobots with the equilibrium concentration in the liquid phase were fitted with Langmuir, Freundlich, Temkin (Pi et al., 2022), and Langmuir–Freundlich (Yan et al., 2017a; Yan et al., 2017b) isotherm (Carter et al., 1995) equations (4–7):

$\begin{array}{ll}\frac{C_{\text{e}}}{q_e}=\frac{C_e}{q_m}+\frac{1}{K_L{q}_m}& (4)\end{array}$

$\begin{array}{ll}\ln q_e=\ln K_F+\frac{1}{n_F}\ln C_e& (5)\end{array}$

$\begin{array}{ll}{q}_e=(\frac{RT}{b_T})\ln (K_T{C}_e)& (6)\end{array}$

$\begin{array}{ll}{q}_e=\frac{{\text{q}}_{\text{m}}{\mathrm{bC}}_e^n}{1+{\mathrm{bC}}_e^n}& \text{, (7)}\end{array}$

where K_L (L/mg), K_F [(mg/g) (L/mg)^1/n], and K_T (L/mg) are the adsorption coefficients for the Langmuir, Freundlich, and Temkin models, respectively. q_m (mg/g) was the calculated maximum value of the adsorbents’ NOR/LEV adsorption capacity. The 1/n_F indicates the Freundlich model parameter, while b_T (L/mg) is the equilibrium constant for the adsorption of the Temkin model (Yan et al., 2017a; Yan et al., 2017b). b (L/mg) is the equilibrium constant for the adsorption of the Langmuir–Freundlich model.

2.4.3 Fitting of adsorption kinetics

The pseudo-first-order, pseudo-second-order, and Elovich kinetic models were used to establish the rate-governing adsorption process, as shown below (8–10) (Sun et al., 2022):

$\begin{array}{ll}\ln (q_e-q_t)=\ln q_e-k_{1}t& (8)\end{array}$

$\begin{array}{ll}\frac{t}{q_t}=\frac{1}{k_2{q}_e^2}+\frac{t}{q_e}& (9)\end{array}$

$\begin{array}{ll}{q}_t=\alpha +\beta \ln t& \text{, (10)}\end{array}$

where k₁ (h^–1) and k₂ (g/mg·h) are the pseudo-first-order and pseudo-second-order rate constants, respectively. In the Elovich model, α and β are constants.

2.4.4 Mass transfer mechanisms

The adsorption process’s speed-limiting steps were investigated using intraparticle diffusion (IPD) (Wang et al., 2010) and liquid film diffusion (LFD) models.

The LFD and IPD models were expressed as:

$\begin{array}{ll}-\ln (1-F)=k_{3}t& (11)\end{array}$

$\begin{array}{ll}{q}_t=k_{IPD}{t}^{1/2}+c& (12)\end{array}$

The constant for the diffusion rate of a liquid film is k₃ (min⁻¹), and F is the q_t/q_e. The IPD diffusion rate constant is k_IPD [mg/(g·min^1/2)], and the linear intercept c (mg/g) provides information about the thickness of the boundary layer (Foroutan et al., 2021).

2.4.5 Thermodynamic calculation

The following equations were used to calculate the thermodynamic parameters to ascertain the nature of the adsorption process (13–15):

$\begin{array}{ll}{K}_{\text{c}}=\frac{q_e}{C_e}& (13)\end{array}$

$\begin{array}{ll}\ln K_{\text{c}}=\frac{\Delta S}{R}-\frac{\Delta H}{RT}& (14)\end{array}$

$\begin{array}{ll}\Delta G=-RT\ln K_{\text{c}}& \text{, (15)}\end{array}$

where the coefficient of the adsorption distribution is K_c (L/g). Entropy, enthalpy, and Gibb’s free energy are represented by ΔS (J/mol), ΔH (J/mol), and ΔG (J/mol·K), respectively. The universal gas constant is R (8.314 J/mol K) and the temperature is T (K).

2.4.6 Approximate site energy distribution

The adsorbent’s adsorption site energy distribution was linked to the equilibrium adsorption capacity (Carter et al., 1995). Using the parameters of the Langmuir–Freundlich model, the following equations (16,17) were used to determine the magnetic microrobot’s site energy distribution:

$\begin{array}{ll}E*=E-E_{\text{s}}=RT\ln (\frac{C_s}{C_e})& (16)\end{array}$

$\begin{array}{ll}F(E*)=\frac{q_{m}nb{C}_s^n}{RT}•\frac{e^{-nE*/RT}}{{(1+b{C}_s^n{e}^{-nE*/RT})}^2}& (17)\end{array}$

where C_e = C_s, E_s is the adsorption energy, E* is the difference in adsorption energies between the adsorbate and solvent on the adsorbent surfaces, and F(E*) is an approximate site energy distribution function. The adsorbate’s maximum solubility is C_s (mg/L). The C_s value of NOR in water is 303.5mg/L, 400 mg/L, 522.1 mg/L, 678.2 mg/L, and 872.5 mg/L at 293.15 K, 298.15 K, 303.15 K, 308.15 K, and 313.15 K (pH=7), respectively (Ross and Riley, 1990; Blokhina et al., 2016). The C_s value of LEV in water is 46, 50, 54, 58, and 62 mg/mL at 293.15, 298.15, 303.15, 308.15, and 313.15 K, respectively (Ross and Riley, 1990; Blokhina et al., 2016).

The adsorption site energy distribution, which can be calculated using the following equation, was used to determine the average site energy:

$\begin{array}{ll}u(E*)=\frac{{\displaystyle {\int }_0^{\infty }E*F(E*)d(E*)}}{{\displaystyle {\int }_0^{\infty }F(E*)d(E*)}}& (18)\end{array}$

Incorporating the above equation with Eq. (16) and Eq. (17), the average site energy could be determined as follows:

$\begin{array}{ll}\mu (E*)=\frac{RT}{\text{n}}\ln (1+b{C}_s^n)& (19)\end{array}$

3 Results and discussion

3.1 Adsorption property for norfloxacin and levofloxacin

3.1.1 Effect of initial norfloxacin and levofloxacin concentration

The impact of the initial concentrations of NOR and LEV on the relative adsorption capacity and removal efficiency on the magnetic microrobot is illustrated in Figures 1A, B. The relative adsorption capacity increased with the initial concentration until 40 and 50 mg/L for NOR and LEV, respectively. The concentration gradient is a vital driving force between the liquid adsorbate and solid adsorbent. When it overwhelmed the resistance to bulk transfer between the adsorbate and adsorbent, the adsorption was enhanced as if the initial concentration of the adsorbate had increased (Altaf et al., 2021). Also, the limited adsorption site of the adsorbent reached a saturation state with the increase of the initial concentration. Thereafter at this point, the absorbent achieved the equilibrium, with the adsorption capacity up to 63.8 and 49.4 mg/g for NOR and LEV, respectively. The removal efficiency of NOR and LEV decreased gradually with the increase of the initial concentration. This can be attributed to the fixed amount of adsorbent dosage in this experiment.

FIGURE 1

Figure 1 The adsorption properties and removal percentage of norfloxacin (NOR) and levofloxacin (LEV) on Fe₃O₄ and the magnetic microrobot. (A, B) The initial concentrations of NOR and LEV, (C, D) the adsorbent dosages, (E, F) the initial pH of NOR and LEV, and (G, H) the adsorption temperature. Note: the columns represent the adsorption capacity and the lines represent the removal efficiency.

3.1.2 Effects of adsorbent dosage

The effect of the adsorbent dose on the adsorption capacity and removal efficiency is presented in Figures 1C, D. When the dosage increased from 3 to 30 mg, the removal efficiency increased significantly due to the increase in the number and surface area of the active adsorption sites (Altaf et al., 2021; Fang et al., 2021). Also, the aggregation of the adsorbents resulting from a high dose of nanoparticles enhanced the removal efficiency (Altaf et al., 2021), while aggregation led to a decrease in the total surface area of the adsorbent (Fang et al., 2021b). The adsorption capacity increased with the increasing dosage, from 3 to 5 mg, peaking at 5 mg. The high adsorption capacity at 5 mg could be attributed to the fulfillment of most binding sites and an increase in total surface area (Zhou et al., 2018). Then, there was a decline when the adsorbent dosage was larger than 5 mg, indicating that the absorbent achieved equilibrium. While the capacity was calculated using the relative adsorption dose, the value declined according to the increased dose of the adsorbent.

3.1.3 Effect of pH

The pH of the solution, which plays a crucial role in the adsorption process, can alter the adsorbents’ surface charges and adsorbate ionization, affecting the adsorption capacity even more (Fang et al., 2021a). Because they have two distinct acid dissociation (pKa1 and pKa2) from the carboxyl group and the amino group,respectively, the form and adsorption effects of NOR and LEV were determined by the pH value of the solution, as shown in Figure 2. If the solution pH was< pK_a1, -COOH and -NH_2⁺- existed in the molecular of the cationic form. When the solution pH was > pK_a2, -COO^- and -NH- existed in the molecular in anionic form. When pK_a1< pH< pK_a2, then NOR and LEV were in the zwitterionic form with -COO^- and -NH_2⁺- existed in the molecular form.

FIGURE 2

Figure 2 Molecular structure and pH-dependent speciation of (A) NOR (norfloxacin) and (B) LEV (levofloxacin).

Figures 1E, F depict the adsorption capacity and removal efficiency onto a magnetic microrobot at various initial pH levels, from 4 to 10. It can be seen that the adsorption limit and expulsion proficiency under similar circumstances were NOR > LEV. The adsorption capacity and removal efficiency of the capacity increased with the pH ranging from 4 to 7 for NOR, peaking at pH = 7. The LEV adsorption had a similar trend to that of NOR, with the highest adsorption capacity at pH = 6. The removal capacities were 63.8 and 49.2 mg/g, respectively. The adsorption capacity and removal efficiency significantly declined as the pH increased from 7 to 10. In general, the adsorbents’ uptake of FQs was higher under pK_a1< pH< pK_a2 than acid or alkaline conditions, which was related to the properties of the FQs in zwitterionic form. The results are consistent with the studies conducted by Altaf et al. (2021). The adsorption capacity reached its maximum value at a pH of approximately 7, which is consistent with the structural characteristics of zwitterionic FQs (Yan and Niu, 2017; Yan and Niu, 2018), and the quantity of zwitterionic FQs gradually increased with pH, implying that FQ adsorption results from complementary ion–pair interactions (Jiang et al., 2021). According to the research, Fe₃O₄ makes a passive oxide layer by coating on the surface when the pH is > 7 and reduces the FQ adsorption from the magnetic microrobot (Rezaei and Vione, 2018).

3.1.4 Effect of temperature

The adsorption performances of NOR and LEV by magnetic microrobot at various temperatures are presented in Figures 1G, H, respectively. The highest adsorption capacity and removal efficiency were achieved at 30°C for NOR and at 25°C for LEV. The interaction between FQs and absorbents was enhanced due to the active site expansion, when the adsorption temperature increased from 20°C to 30°C for NOR and 25°C for LEV (Altaf et al., 2021). While the adsorption temperature continued rising, the updraft movement of FQs was enhanced, which weakened the attraction between active adsorption sites and themselves, leading to the decline of the adsorption capacity and removing efficiency (Chen et al., 2011).

3.2 Adsorption isotherms

The experimental data and model-fitted findings for NOR and LEV adsorption from a magnetic microrobot are shown in Table 1. The non-linearity of the NOR and LEV adsorption isotherms on the absorbents suggests that the NOR and LEV concentrations and distributional effects were related to the magnetic microrobot’s adsorption capacity (Sun et al., 2022). At various temperatures, the R² values of the Langmuir isotherm model were greater than those of the Freundlich, Temkin, and Langmuir–Freundlich isotherm models, indicating that NOR and LEV mostly adsorb onto the absorbents in monolayers. In the Freundlich model, n_F is the parameter relating to the mean energy of adsorption. If n_F> 1, it is preferred that adsorption is chemisorption in nature, and a strong adsorbent/adsorbate interaction occurs (Lv et al., 2020; Gaho et al., 2022). The calculated values of n_F were all larger than 1, indicating the chemisorption of NOR and LEV on the absorbents.

TABLE 1

Table 1 Adsorption equilibrium isotherm models on norfloxacin (NOR) and levofloxacin (LEV) using a magnetic microrobot.

Many different adsorbents were listed in the comparison of the adsorption capacity with magnetic microrobots. As shown in Table 2, the Q_m for NOR was 698.6 mg/g by FRMB consisting of SDS (Li et al., 2019a). The Q_mof Fe₃O₄-based adsorbents (5-IOW and 14-IOW) for NOR (8.64 and 6.48 mg/g) were significantly lower than those of the magnetic microrobot. The Q_m,exp of the magnetic microrobot for NOR was much larger than for most other adsorbents (Table 2). The Q_m for LEV was 298.43 mg/g by PCS-KOH (Yang et al., 2020), which was much higher than for the other absorbents. The Q_mof the Fe₃O₄-based adsorbent (Fe₃O₄-gINPs) for LEV was 22.47 mg/g, which was much lower than that of the magnetic microrobot. Compared with other adsorbents, a magnetic microrobot can be used as one of the markedly superior adsorbent materials in wastewater treatment containing NOR or LEV.

TABLE 2

Table 2 Comparison of the adsorption capacities of different adsorbents for the removal of norfloxacin (NOR) and levofloxacin (LEV) at ambient temperatures (25°C).

3.3 Adsorption kinetics

The kinetic data of NOR and LEV fitted with three kinetic models are presented in Figure 3 and Table 3. Based on Figure 3 and the high R² values in Table 3, the adsorption of NOR fitted the Elovich kinetic model well, while the adsorption of LEV fitted the pseudo-second-order model well. The Elovich model was suitable for simulating the adsorption of NOR, showing that it is the valence electron, rather than just the electrostatic attraction, that causes the adsorption of NOR on to magnetic microrobots (Sun et al., 2022). The main process involved in LEV kinetic adsorption was chemisorption due to the pseudo-second-order model (Sun et al., 2022).

FIGURE 3

Figure 3 (A, B) Pseudo-first-order kinetic model, (C ,D) Pseudo-second-order kinetic model, and (E, F) Elovich kinetic model for norfloxacin (NOR) and levofloxacin (LEV) adsorption.

TABLE 3

Table 3 Adsorption kinetic models on norfloxacin (NOR) and levofloxacin (LEV) using Fe₃O₄ and a magnetic microrobot.

3.4 Mass transfer mechanisms

According to temperature, pressure, and the types of adsorbent and adsorbate, varied mass transfer resistances may be able to limit the adsorption rate, which was evaluated using a kinetic analysis. The solid material was characterized by two primary resistances: protection from outer dissemination (interparticle), connected with mass exchange from mass liquid to the outside surface, and intraparticle dispersion, connected with mass exchange from an outside surface to an internal permeable construction. To investigate mechanisms and the potential rate-determining steps, several models have been proposed. Piecewise and linear regressions were used to fit the adsorption data using the IPD and LFD models to investigate the specific adsorption processes of NOR and LEV. The results are shown in Figure 4 and Table 4. The IPD model was better suited to represent the mass transfer process of NOR and LEV adsorption by Fe₃O₄ and a magnetic microrobot based on the statistical parameter (R² > 0.90). From Figures 4A, B, the fact that the connection between q_t and t^1/2 is non-linear and does not pass through the origin point indicates that there are other rate-limiting steps besides IPD and that the rate of adsorption may potentially be controlled by an external diffusion mechanism. IPD and equilibrium are the two steps of the adsorption process. The adsorption rate of NOR and LEV was k_IPD1 > k_IPD2. The first stage was relatively slow, and the second stage represented the equilibrium condition for the adsorption–desorption process. The internal mass transfer restriction of the magnetic microrobot was stronger than that of Fe₃O₄ based on the fact that the R² of the magnetic microrobot for NOR adsorption was higher than that of Fe₃O₄ (Yu et al., 2021). In conclusion, NOR and LEV were adsorbed on magnetic microrobots by a chemical process that was regulated simultaneously by internal and exterior diffusion processes.

FIGURE 4

Figure 4 The particle diffusion model (A ,B) and LFD model (C, D) of norfloxacin (NOR) and levofloxacin (LEV) adsorption by Fe₃O₄ and a magnetic microrobot.

TABLE 4

Table 4 Adsorption kinetic models on norfloxacin (NOR) and levofloxacin (LEV) using Fe₃O₄ and a magnetic microrobot.

3.5 Adsorption thermodynamics

To examine the adsorption thermodynamics of NOR and LEV on a magnetic microrobot, a range of temperatures, including 298, 303, 308, 313, and 318 K were chosen. It is clear from Table 5 that the adsorption of NOR had a negative ΔH value, which indicates that the process was exothermic and involved the adsorption of both chemical and physical substances. LEV adsorption by the magnetic microrobot was an endothermic process (ΔH>0), which shows that chemisorption may have occurred. ΔS was positive, demonstrating that the solid/solution interface contains additional unpredictability. It might be connected to the fact that the molecules of the displaced solvent (like water) gained more translational energy than the molecules of the adsorbate lost (de Andrade et al., 2018).

TABLE 5

Table 5 Adsorption thermodynamic parameters of norfloxacin (NOR) and levofloxacin (LEV) adsorption by a magnetic microrobot.

To investigate the adsorption thermodynamics of NOR and LEV on magnetic microrobots, a range of temperatures, including 298, 303, 308, 313, and 318 K, were chosen. It can be seen in Table 5 that the ΔH of the adsorption of NOR was negative, demonstrating that both physical and chemical adsorption was involved in the exothermic process. For the LEV adsorption by a magnetic microrobot, it is an endothermic process (ΔH), which suggests that chemisorption may have occurred. Since ΔS was positive, the solid/solution interface must have had additional randomness. It could be related to the fact that the adsorbate molecules lost less translational energy than the displaced solvent molecules (like water) (de Andrade et al., 2018). ΔG< 0, which means that adsorption was advantageous and spontaneous at any temperature.

3.6 Adsorption site energy analysis

Based on Equation (17), the equilibrium NOR and LEV adsorption capacities q_e are plotted as a function of the magnetic microrobot’s site energy E^* values in Figure 5. The E^* values decreased dramatically as the amount of NOR and LEV adsorbed on adsorbents increased. These findings demonstrated that NOR and LEV molecules occupied the magnetic microrobot’s high-energy adsorption sites first, and then the low-energy adsorption sites. After the adsorbate occupied the high-energy sites, low-energy sorption sites interacted with the NOR and LEV molecules as the solution concentration rose. This was in line with the earlier NOR adsorption on carbon nanotubes (Wang et al., 2010). On a magnetic microrobot, the values of NOR’s site energy E^* were significantly lower than those of LEV’s. The E^* values of NOR adsorbed on the magnetic microrobot fell in the range of 4.25 to 10.73 kJ/mol, and the E^* values of LEV ranged from 17.36 to 21.22 kJ/mol. Additionally, the plots of E^* showed an increase with temperature, indicating that the NOR and LEV adsorption on the magnetic microrobot benefited from higher temperatures. Temperature increased the rate of molecular diffusion, making it easier for NOR and LEV molecules to cross the magnetic microrobot’s external boundary layer and enter its internal pores.

FIGURE 5

Figure 5 Site energy of norfloxacin (NOR) and levofloxacin (LEV) adsorption. (A) site energy versus equilibrium NOR adsorption capacity; (B) site energy versus equilibrium LEV adsorption capacity.

Based on the Langmuir–Freundlich isotherm model, the approximate site energy distribution (F(E^*)) for the adsorption of NOR and LEV to the magnetic microrobot at various temperatures is depicted in Figure 6. For NOR and LEV, the site energy had unimodal distributions. Most of the NOR and LEV sorption occurred on the sites with energy over 4.0 kJ/mol and lower than 16.0 kJ/mol, indicating that NOR and LEV sorption on the biosorbent was a physical-chemical process. First, as the site energy (E*) increased, the frequency function F(E*) decreased until it was close to zero. The upward trend suggests that, at high concentrations, some NOR and LEV molecules were forced to occupy lower-energy sites. Conversely, at low-solution concentrations, NOR and LEV molecules were preferentially captured at the high-energy site (Zhang et al., 2021). Owing to the lower F(E*), however, the extremely high- or low- energy sites contributed very little to the maximum amount of adsorption (Liu et al., 2016).

FIGURE 6

Figure 6 Site energy distribution of norfloxacin (NOR) and levofloxacin (LEV) adsorption on a magnetic microrobot at various temperatures. (A) Site energy distribution of NOR; (B) site energy distribution of LEV.

4 Conclusion

The magnetic microrobot demonstrated outstanding NOR and LEV adsorption capacities. The static maximum adsorption capacities of NOR and LEV on the magnetic microrobot were 114.8 and 49.4 mg/g, respectively. The Langmuir isotherm model and Elovich kinetic models agreed well with the experimental data of NOR adsorption by a magnetic microrobot. The Langmuir isotherm model and the pseudo-second-order kinetic model might be able to adequately describe the LEV adsorption procedure. The IPD was not the only mechanism regulating the adsorption process, and the IPD model was better suited to describe the mass transfer process of the NOR and LEV adsorption by magnetic microrobot. Exothermic and spontaneous characteristics were verified through thermodynamics. The biosorbents’ heterogeneous surface was verified by the analysis of site energy distribution. Additionally, Figure 6 demonstrated that the majority of the NOR and LEV adsorption took place on sites with greater than 4.25 kJ/mol and less than 17.36 kJ/mol, supporting the notion that this adsorption was physical–chemical in nature. Based on the findings, the magnetic microrobot can potentially be employed to inexpensively and efficiently remove NOR and LEV from aqueous wastewater as a new-style green bio-adsorbent.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Author contributions

YT: resources, funding acquisition, writing—reviewing and editing. WJ: investigation, methodology, and data handling. MB: writing—reviewing and editing. SQ: funding acquisition, writing—reviewing and editing. YP: conceptualization, resources, writing—reviewing and editing, supervision, funding acquisition. CL: investigation, methodology. JZ: methodology, resources, data handling. All authors contributed to the article and approved the submitted version.

Funding

This research was financially supported by the Shandong Provincial Natural Science Foundation (ZR2022QD018); the National Key R&D Program of China (2018YFD0900802); the National Innovation and Entrepreneurship Training Program for College Students (202111066013); the Yantai University Doctoral Start-up Foundation (HX2018B32); and the Shandong Key Laboratory of Marine Ecological Restoration (201919).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2023.1169883/full#supplementary-material

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