Translate this page into:
A six-channel fiber optic in-situ detection technique for simultaneous monitoring of desorption kinetics of quercetin from HPD300 resin
* Corresponding authors: E-mail addresses: turghunm@xju.edu.cn (T Muhammad) and akbarphd@126.com (A Rehemana)
-
Received: ,
Accepted: ,
Abstract
Desorption, is a critical and equally important phase of the entire adsorption process. The study of quercetin desorption kinetics is of great significance in guiding the adsorptive separation of bioactive compounds. Conventional methods for plotting desorption kinetic curves require manual sampling at different time points and offline tests. These methods are time-consuming, labor-intensive, yield limited data, and introduce significant error due to manual handling and variation in solution volume. Furthermore, conducting multi-throughput desorption operations simultaneously is challenging. Herein, a six-channel fiber-optic sensing in-situ detection technique was developed for the simultaneous, real-time monitoring of quercetin desorption process in multi-throughput, addressing these inherent issues. The established quercetin standard curves using the six-channel fiber-optic sensing system all demonstrated excellent linearity (R2 ≥ 0.9998), exploiting the ability of this technique to obtain six desorption curves in a single cycle. The macroporous adsorption resin (MAR), specifically HPD300, was selected as the optimal adsorbent for the adsorptive separation of quercetin. Additionally, this technique was used to obtain the optimal desorption conditions: using 80% ethanol as the desorption solvent, an initial adsorption concentration of 25 mg L-1, and a temperature of 298 K. Kinetic studies of desorption revealed that the pseudo-second-order (PSO) model was more suitable for describing the desorption of quercetin from HPD300. This technique can offer significant application potential in the adsorptive separation of bioactive compounds and greatly improve operational efficiency.
Keywords
Desorption kinetics
Fiber-optic in-situ detection
Macroporous adsorption resins
Quercetin
Simultaneous monitoring
1. Introduction
Quercetin, a typical flavonoid, has garnered significant attention due to its potent antioxidant and anti-inflammatory properties, as well as its potential anticancer and antiviral activities [1]. Several methods have been utilized for the isolation and purification of flavonoids, among which the macroporous resin adsorption method stands out for its good selectivity, operational simplicity, affordability, and reusability [2,3]. However, to the best of our knowledge, most studies have merely focused on the characterization of the adsorption process, while the desorption process has received comparatively less attention. As a critical phase of the overall adsorption process, desorption is equally important. A key aspect of characterizing the desorption process lies in the study of desorption kinetics. Therefore, studying the desorption kinetics of quercetin is crucial for guiding the adsorption and separation of flavonoids.
Adsorption/desorption kinetic studies typically require the measurement of analyte concentrations at different time points [4]. The conventional method relies on periodic manual sampling, which is subsequently analyzed with a UV-vis spectrophotometer [5]. This method, however, is not only labor-intensive and time-consuming but also yields limited data and can introduce considerable errors [6]. Another non-negligible issue is ensuring a consistent solution volume during adsorption/desorption experiments, as frequent sampling can lead to deviations of experimental results from the actual situation [7]. To address these issues, in-situ monitoring of the adsorption process has been proposed [8,9]. However, unlike adsorption, desorption typically occurs rapidly, especially in the initial stages, making it challenging to capture concentration changes before reaching desorption equilibrium. This limitation results in incomplete desorption curves, which adversely affect the study of desorption kinetics [10]. Furthermore, the complexity of the conventional method makes it challenging to perform multiple desorption processes simultaneously. Therefore, there is an urgent need for an in-situ characterization technique that can simultaneously monitor adsorbate concentration in real-time multi-throughput desorption processes.
Fiber-optic sensing technology provides an in situ fast analytical approach. This technology has extensive applications in environmental monitoring, pharmaceutical analysis, and food safety [11-13]. However, to date, no studies have reported its use in monitoring desorption processes. The novelty of this study lies in the development of a six-channel fiber optic sensing technique for the simultaneous, in-situ characterization of multiple desorption processes. By integrating the fiber-optic sensor directly into the desorption system, in-situ monitoring of adsorbate concentration can be achieved, thereby avoiding the issues of solution volume changes and external contamination that arise from conventional methods [14]. Using fiber-optic sensing technology to detect adsorbate concentration enables simultaneous, real-time monitoring of multiple desorption processes, thus overcoming the limitations of conventional methods. This approach not only significantly minimizes errors introduced by manual operation but also saves time and labor, thereby enhancing the accuracy and reliability of experimental data. This study aims to propose an effective method to address the limitations of conventional methods and to enrich the understanding of flavonoid desorption kinetics.
In this study, a six-channel fiber-optic sensing in-situ detection technique was developed and applied to investigate the desorption process of quercetin from macroporous adsorption resins (MARs). The species of MARs were screened, and adsorption isotherms were examined. Additionally, the effects of desorption solvent, initial adsorption concentration, and temperature on the desorption process were analyzed. Ultimately, the desorption data were fitted to the pseudo-first-order (PFO), pseudo-second-order (PSO), Elovich, and intra-particle diffusion (IPD) models for further analysis.
2. Materials and Methods
2.1. Materials
AB-8, ADS-17, D101, HPD300, HPD500, and NKA-9 MARs (physical parameters have been listed in Table S1) were purchased from Bon Adsorber Technology Co., Ltd (Cangzhou, China) and Lanxiao Technology New Material Co., Ltd (Xi’an, China). Quercetin, methanol, and ethanol were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China).
2.2. Procedure
For details on the establishment of the six-channel fiber-optic sensing detection method, please refer to our previous work [15]. Each of the six probes was submerged in desorption vessels containing 80% ethanol to measure the absorbances of the blank solutions. Using the paddle method, adsorption bags containing saturated MARs were placed into each vessel, while stirring was maintained at a speed of 100 rpm. The detection wavelength was set to 374 nm, and the end time could be adjusted for automatic operation. Subsequently, the desorption test was initiated, and the desorption curves of multiple vessels were simultaneously monitored in real-time by the six-channel fiber-optic sensing in-situ detection system. Desorption data were calculated using the standard curves.
2.3. Analytical methods
Quercetin solutions were accurately prepared with 80% ethanol at concentrations of 0.5, 2, 5, 10, 20, 30, 40, and 50 mg L-1. The experiment was initiated when the absorbance of the six spectra at the absorption spectral interface stabilized within the range of 0 ± 0.005. The absorbance of the quercetin solutions at different concentrations was measured at 374 nm using the UV fiber-optic sensor, and six-channel fiber-optic sensing standard curves for quercetin were constructed. Additionally, quercetin solutions were accurately prepared with 5% methanol at concentrations of 5, 8, 10, 15, 20, and 25 mg L-1, and their absorbance at varying concentrations was measured using a UV-vis spectrophotometer to generate a standard curve.
2.4. Batch adsorption and desorption kinetic tests
2.4.1. Batch adsorption
The MARs were pretreated according to our previous work [16]. The adsorption capacity of different MARs was investigated by placing adsorption bags containing 0.1000 g of activated MARs (dry weight: AB-8, ADS-17, D101, HPD300, HPD500, NKA-9) into separate 250 mL conical flasks. Then, 200 mL of quercetin solution (5% methanol) at a concentration of 25 mg L-1 was added to each flask. Similarly, the adsorption capacity of MARs at different quercetin concentrations was examined. For this, adsorption bags containing 0.1000 g of activated HPD300 MARs (dry weight) were placed into 250 mL conical flasks, and 200 mL of quercetin solution (5% methanol) was added to each flask at concentrations of 5, 8, 10, 15, 20, and 25 mg L-1. The conical flasks were then placed in a thermostatic water-bath oscillator set to 25°C and oscillated at a constant speed. Batch adsorption experiments were conducted until equilibrium was reached, after which the adsorption process was stopped. The absorbance of the equilibrium solution was measured using a UV-vis spectrophotometer. The quercetin concentrations at equilibrium (Ce) were calculated from the standard curve equation: y = 0.0530x - 0.0136 (R2 = 0.9997). The equilibrium adsorption capacity (qe) of quercetin on MARs was calculated according to Eq. (1) and used as the standard for subsequent desorption experiments [17].
where C0 (mg L-1) represents the initial concentration of the adsorbed solution, Ce (mg L-1) represents the concentration of the solution after adsorption reaches equilibrium, V1 (L) represents the volume of the adsorption solution, and m (g) represents the mass of the adsorbent.
The adsorption data were analyzed using the Langmuir and the Freundlich models. Detailed information on the adsorption isotherms can be found in the Supplementary Material Table S2 [18,19].
2.4.2. Desorption kinetics
In the desorption experiment, six fiber-optic probes were each immersed in a desorption vessel containing 100 mL of 80% ethanol for a blank measurement. Once the absorbance values at the interface of all six absorption spectra stabilized at 0 ± 0.005, the saturated adsorption bags from Section 2.4.1 were simultaneously placed into each desorption vessel. The desorption process was carried out continuously for 70 min at a temperature of 298 K and a rotational speed of 100 rpm. Changes in each solution absorbance during the desorption process were monitored in real-time using the six-channel fiber-optic sensing in-situ detection system. The desorption capacity and desorption ratio of quercetin from MARs were calculated according to Eq. (2) and Eq. (3) [20].
where Cd (mg/L) represents the concentration of the desorption solution, and Vd (L) represents the volume of the desorption solution.
The desorption data were analyzed using the PFO model, PSO model, Elovich model, and IPD model. Detailed information on the equations and parameters for these kinetic models can be found in Table S3 [21,22].
2.5. Experimental temperature setting
The adsorption bags containing 0.1000 g of HPD300 MARs were first saturated with 25 mg L-1 quercetin solution and then thoroughly rinsed with deionized water. To investigate the effect of temperature on the desorption ratio of quercetin from HPD300 MARs, desorption was performed at different temperatures (298, 308, and 318 K) at a mixing speed of 100 rpm and using 100 mL of 80% ethanol as the desorption solvent. During this process, it is crucial to ensure that the water level in the thermo bath remains slightly higher than the solution level in the desorption vessel. The instrument should not be operated if the water level is insufficient, as this will adversely affect the experimental results, damage the pump and heater, and reduce the lifespan of the apparatus.
3. Results and Discussion
3.1. Analytical methods
The absorbance of quercetin solution (80% ethanol) was measured at 374 nm over a concentration range of 0.5-50 mg L-1 using the six-channel fiber-optic sensing in-situ detection system. The standard curves for quercetin have been illustrated in Figure 1. The data demonstrated an excellent linear relationship between absorbance and quercetin concentration within the range of 0.5-50 mg L-1, with all determination coefficients (R2) not less than 0.9998. This strong linear correlation indicates that the method is highly suitable for the simultaneous and precise quantitative analysis of quercetin in multiple desorption solutions.
- (a-f) Quercetin standard curves obtained using the six-channel fiber-optic sensing in situ detection system. (solvent: 80% ethanol, concentration range: 0.5-50 mg L-1, detection wavelength: 374 nm).
3.2. Resin screening
In adsorption and desorption experiments, adsorbents with high adsorption capacity and efficient desorption ratios are crucial for the effective separation of target compounds. Thus, the selection of an appropriate adsorbent plays a pivotal role in separating target substances from the solution. The adsorption/desorption performance of MARs is influenced by several factors, including the polarity and size of the target molecules, as well as the polarity, pore size, and specific surface area of the MARs. In general, weakly polar molecules are more effectively separated using weak-polar or non-polar MARs, while strongly polar molecules are more effectively separated using strong polar MARs [23].
Batch adsorption experiments were conducted using six MARs and a 25 mg L-1 quercetin solution under identical conditions, which yielded the adsorption capacity and desorption ratio of quercetin on each MAR, as shown in Figure 2(a). The adsorption capacity of quercetin on the MARs ranked as follows: HPD300 > HPD500 > D101 > NKA-9 > ADS-17 > AB-8. Notably, HPD300, HPD500, D101, and ADS-17 MARs exhibited excellent desorption performance, with desorption ratios exceeding 90% for all.
- Adsorption/desorption behavior of quercetin on six types of MARs: (a) adsorption capacity and desorption ratio; (b) desorption curves obtained using the six-channel in-situ detection technique; (c) desorption curves during the first 10 min. (C0: 25 mg L-1, desorption solvent: 80% ethanol, temperature: 298 K, desorption time: 70 min, agitation: 100 rpm, detection wavelength: 374 nm).
Desorption capacity and desorption rate are key indicators for selecting MARs [24]. Figure 2(b) illustrates the desorption curves of quercetin from the six MARs, clearly depicting the desorption performance of quercetin from each MAR. The fastest increase in desorption rate was observed in the initial 10 min, followed by a sharp decline during the second phase (10-30 min), after which the desorption rate gradually reached a relatively constant value, with the slowest desorption rate observed in the third phase (30-70 min). Figure 2(c) indicates that the desorption rates of quercetin from all six MARs were rapid in the initial 10 min, resulting in overlapping desorption curves, which highlights the need for in situ characterization techniques. The desorption capacity of quercetin from the different MARs ranked as follows: HPD300 > HPD500 > D101 > ADS-17 > NKA-9 > AB-8. In conclusion, the HPD300 MARs demonstrated the optimal adsorption/desorption performance for quercetin, making it an excellent adsorbent for the adsorption of quercetin. This can be attributed to the fact that HPD300 resin exhibits the smallest average pore size, the largest specific surface area, and non-polar characteristics among the six resins (Table S1). Similar conclusions have been reported by Li et al [25]. Consequently, the HPD300 MARs were selected for further studies. Notably, the developed six-channel in situ detection technique allows for the acquisition of six desorption curves in a single cycle, significantly enhancing characterization efficiency. Moreover, the desorption curves were complete and continuous, which is highly beneficial for studying desorption kinetics.
3.3. Adsorption isotherms
The adsorption behavior of quercetin on HPD300 MARs at different concentrations was investigated. Adsorption bags containing 0.1000 g of activated HPD300 MARs were immersed in 200 mL of quercetin solutions with initial concentrations of 5, 8, 10, 15, 20, and 25 mg L-1. The equilibrium concentration of quercetin was measured using a UV-vis spectrophotometer, and the adsorption capacities of quercetin on HPD300 MARs across the different initial concentrations were determined. As shown in Figure 3(a), the adsorption capacity of quercetin on HPD300 MARs increased with the initial concentration of the quercetin solution, reaching its maximum when the initial concentration reached 25 mg L-1.
- Adsorption behavior of quercetin at different concentrations on HPD300 MARs: (a) adsorption capacity; (b) Non-linear fitting of the Langmuir model; (c) Non-linear fitting of the Freundlich model.
Langmuir (Figure 3b) and Freundlich adsorption isotherms (Figure 3c) were plotted at 298 K, with the equilibrium concentration of quercetin on the x-axis and the adsorption capacity of quercetin on HPD300 MARs on the y-axis. As shown in Table S2, the Langmuir model (Eq. S1) yielded a high determination coefficient (R2 = 0.9973), surpassing the Freundlich model’s coefficient (R2 = 0.9692). This suggests that the adsorption process of quercetin on HPD300 MARs follows the Langmuir model, indicating monolayer adsorption on the adsorbent. Furthermore, the separation factor (RL) calculated from the Eq. (S2) ranged between 0 and 1, confirming that the adsorption process of quercetin on HPD300 MARs is favorable [26,27]. In addition, the Freundlich model yielded an n value greater than 1 (n=1.331), further supporting the conclusion that the adsorption process is favorable [28].
By substituting the qmax and KL values from Table S2 into the Langmuir model Eq. (S1), the resulting Eq. (4) is:
By substituting the n and KF values from Table S2 into the Freundlich model Eq. (S3), the Eq. (5) obtained is:
3.4. Effect of ethanol concentration on desorption
Batch adsorption experiments were performed using quercetin and HPD300 MARs under identical conditions. The effect of ethanol concentration on the desorption of quercetin from HPD300 MARs was investigated by using 40%, 60%, and 80% ethanol as desorption solvents, respectively. As shown in Figure 4, both the desorption rate and desorption ratio increased progressively with an increase in the ethanol concentration. This indicates that increasing ethanol concentration significantly improved the desorption capacity and desorption efficiency of quercetin from HPD300 MARs [29]. After 60 min of desorption, the desorption ratios for both 60% and 80% ethanol exceeded 80%. Therefore, to reach equilibrium and improve the desorption ratio within 70 min, 80% ethanol was selected as the optimal desorption solvent.
- Desorption curves of quercetin from HPD300 MARs at different ethanol concentrations obtained using the six-channel in-situ detection technique: (a) absorbance curves at 374 nm and (b) desorption ratios. (desorption conditions: 298 K, 100 rpm).
3.5. Effect of initial adsorption concentrations on desorption
Batch adsorption experiments were conducted using quercetin solutions at concentrations of 5, 8, 10, 15, 20, and 25 mg L-1, with HPD300 MARs as the adsorbent. In-situ desorption was performed after the adsorption equilibrium was reached to investigate the effect of the initial quercetin concentration on the desorption kinetics. The desorption kinetic curves of quercetin from HPD300 MARs have been presented in Figure 5. Findings revealed that the desorption capacity of quercetin from HPD300 MARs increased with higher initial concentrations of quercetin at 298 K. This stemmed from the enhanced mass-transfer driving force at higher initial quercetin concentrations, which increased the adsorption capacity and, consequently, the desorption capacity.
- Desorption curves of quercetin from HPD300 MARs at different initial adsorption concentrations (5-25 mg/L) obtained using the six-channel in situ detection technique. (desorption conditions: 80% ethanol, 298 K, 100 rpm; detection wavelength: 374 nm).
3.6. Effect of temperature on desorption
Temperature is a key factor influencing the desorption behavior. Higher temperatures can accelerate the thermal motion frequency of adsorbate molecules and reduce the interaction between them and the active sites of the resin. The effect of temperature on the desorption capacity and desorption ratio of quercetin from HPD300 MARs was investigated at normal temperature 298K, and at elevated temperatures of 308 K and 318 K, respectively. A 10K uniform gradient is set to precisely quantify the "proportion of change in desorption rate for every 10K increase in temperature." The entire desorption process of quercetin from HPD300 MARs was monitored using the six-channel fiber-optic sensing system, and desorption ratio-time curves were generated (Figure 6). The results indicated that the desorption capacity increased with rising temperature, suggesting that higher temperatures promote the desorption of quercetin from HPD300 MARs within a certain temperature range. This is consistent with findings from adsorption isotherm studies. In other words, the adsorption of quercetin onto HPD300 resin follows a monolayer adsorption, where lower temperatures enhance adsorption efficiency, while higher temperatures favor desorption efficiency [23].
- Desorption curves of quercetin from HPD300 MARs at different temperatures obtained using the six-channel in-situ detection technique. (C0: 25 mg L-1, desorption solvent: 80% ethanol).
3.7. In-situ desorption kinetic modeling
3.7.1. Kinetic modeling of quercetin desorption from different MARs
The study of desorption kinetics primarily aimed to explore the desorption rate during the desorption process, which is crucial for the overall efficiency of desorption. The fitting results of the linear Pseudo-First-Order Kinetics Model (PFO), Pseudo-Second-Order Kinetics Model (PSO), and Elovich kinetic models have been shown in Figures 7(a-c), with the relevant fitting parameters detailed in Table 1. The results indicated that the PSO model exhibited the highest R2 value, suggesting that it is best suited for describing the desorption of quercetin from the six MARs [21]. Additionally, the fitting results for the nonlinear PFO, PSO, and Elovich kinetic models have been presented in Figure S1 and Table S4. Figure 7(d) displays the fitting results of the IPD model, where it is evident that the entire desorption data are not linear. None of the fitted curves intersect the origin point, and the desorption process can be categorized into three distinct stages (R2 > 0.9000) [30]. Table 2 lists the IPD model parameters for quercetin desorption from the six MARs. The results reveal significant differences in the desorption rates among the three stages. In the first stage (Kid1), the desorption rate was the highest, controlled by liquid film diffusion. The second stage (Kid2) reflected a gradual desorption stage, influenced by IPD. The third stage (Kid3) is the final equilibrium stage, characterized by the slowest desorption rate, suggesting that IPD poses the primary resistance in the overall desorption process [31].
- Linear fitting curves of kinetic models for quercetin desorption from six types of MARs: (a) PFO model, (b) PSO model, (c) Elovich model, and (d) IPD model.
| MARs | qexp (mg g-1) | PFO | PSO | Elovich | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| qcal (mg g-1) | k1×10 (min-1) | R2 | qcal (mg/g) | k2×10 (g mg-1 min-1) | R2 | a (mg g-1 min-1) | b (g mg-1) | R2 | ||
| HPD300 | 43.37 | 16.49 | 1.1277 | 0.9477 | 44.74 | 0.1315 | 0.9994 | 122.22 | 0.1474 | 0.9119 |
| HPD500 | 42.51 | 17.41 | 1.0630 | 0.8344 | 42.66 | 0.1599 | 0.9999 | 60.30 | 0.0451 | 0.9297 |
| D101 | 40.88 | 144.90 | 0.7875 | 0.4406 | 41.25 | 0.1316 | 0.9992 | 93.59 | 0.1552 | 0.9176 |
| NKA-9 | 32.00 | 23.64 | 0.9035 | 0.6989 | 20.55 | 0.0472 | 0.9985 | 4.78 | 0.2372 | 0.9932 |
| ADS-17 | 23.74 | 5.60 | 0.7518 | 0.9596 | 5.60 | 0.7518 | 0.9596 | 540.85 | 0.4364 | 0.9298 |
| AB-8 | 15.56 | 3.63 | 0.6046 | 0.9390 | 3.63 | 0.6046 | 0.9390 | 37.92 | 0.6533 | 0.9430 |
| MARs | Kid1 (mg mL-1 min-1/2) | R2 | Kid2 (mg mL-1 min-1/2) | R2 | Kid3 (mg mL-1 min-1/2) | R2 |
|---|---|---|---|---|---|---|
| HPD300 | 16.5857 | 0.9635 | 3.3190 | 0.9636 | 0.2334 | 0.9077 |
| HPD500 | 20.4760 | 0.9919 | 2.6178 | 0.9874 | 0.3744 | 0.9305 |
| D101 | 17.9582 | 0.9951 | 3.4615 | 0.9538 | 0.2284 | 0.9667 |
| NKA-9 | 7.0887 | 0.9768 | 2.9899 | 0.9346 | 1.1632 | 0.9727 |
| ADS-17 | 4.1827 | 0.9900 | 0.9605 | 0.9936 | 1.1632 | 0.9799 |
| AB-8 | 3.3976 | 0.9760 | 0.5795 | 0.9785 | 0.2182 | 0.9865 |
3.7.2. Desorption kinetics modeling of quercetin at different adsorption concentrations on HPD300 MARs
As shown in Figures 8(a-c), the desorption data at 298 K were fitted to the linear PFO, PSO, and Elovich models, with the corresponding model parameters and determination coefficients (R2) values listed in Table 3. The results indicate that the R2 of the PSO model is significantly higher than that of the PFO and Elovich models. Additionally, among the several models, the theoretical adsorption capacities calculated from the PSO model agree best with the experimental results. Thus, the PSO model provides a more accurate description of the desorption behavior of quercetin from HPD300 MARs [32]. The fitting results for the nonlinear PFO, PSO, and Elovich kinetic models have been shown in Figure S2 and Table S5.
- Linear fitting curves of kinetic models for quercetin desorption from HPD300 MARs at different adsorption concentrations: (a) PFO model, (b) PSO model, (c) Elovich model, and (d) IPD model.
| C0 (mg L-1) | qexp (mg g-1) | PFO | PSO | Elovich | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| qcal (mg g-1) | k1×10 (min-1) | R2 | qcal (mg g-1) | k2×10 (g mg-1 min-1) | R2 | a (mg g -1 min-1) | b (g mg-1) | R2 | ||
| 5 | 8.58 | 3.73 | 0.9525 | 0.9628 | 8.20 | 0.5156 | 0.9996 | 10.93 | 0.7209 | 0.8551 |
| 8 | 14.54 | 6.70 | 1.0093 | 0.9458 | 14.51 | 0.2591 | 0.9992 | 14.53 | 0.3860 | 0.8741 |
| 10 | 17.86 | 7.31 | 0.9126 | 0.9147 | 17.33 | 0.2297 | 0.9993 | 29.10 | 0.3451 | 0.8845 |
| 15 | 27.12 | 15.53 | 1.0966 | 0.9516 | 28.00 | 0.0946 | 0.9974 | 15.63 | 0.1780 | 0.8899 |
| 20 | 35.56 | 12.87 | 1.1408 | 0.9368 | 35.64 | 0.1608 | 0.9996 | 122.30 | 0.1954 | 0.8335 |
| 25 | 42.83 | 20.79 | 1.2102 | 0.9691 | 42.94 | 0.0974 | 0.9990 | 51.88 | 0.1347 | 0.8409 |
Both the PFO model and PSO model account for the effects of liquid film diffusion, IPD, and their interactions during the desorption process. The plot of qt versus t1/2 (Figure 8d) shows multiple linear segments. This can be attributed to the porous structure of HPD300 MARs, featuring a wide distribution of pore sizes, including macropores, mesopores, and micropores. Quercetin can be adsorbed on the surface of HPD300 MARs particles and penetrate their internal pores as well. According to the IPD model, the desorption process of quercetin from HPD300 MARs can be categorized into three distinct stages: (i) a rapid desorption stage on the surface of the resin particles, (ii) a diffusion stage within the particle interior mesopores, and (iii) a final diffusion stage within the micropores until desorption equilibrium is reached [33].
The data presented in Table 4 clearly demonstrate that the Kid value increases during desorption with an increase in initial quercetin concentration in the batch adsorption. This suggests that the diffusion rate of quercetin into the macropores is enhanced. Additionally, the entire desorption data are not linear, and none of the fitted straight lines pass through the origin point. These results may be attributed to the combined influence of both liquid film diffusion and IPD, which affect the desorption process of quercetin from HPD300 MARs. This implies that liquid film diffusion is not the sole rate-controlling step in the desorption process, and IPD also influences the desorption process [34].
| C0 (mg L-1) | Kid1 (mg mL-1 min-1/2) | R2 | Kid2 (mg mL-1 min-1/2) | R2 | Kid3 (mg mL-1 min-1/2) | R2 |
|---|---|---|---|---|---|---|
| 5 | 4.8347 | 0.9973 | 0.9319 | 0.9411 | 0.0948 | 0.9161 |
| 8 | 8.3077 | 0.9815 | 2.0424 | 0.9325 | 0.0783 | 0.9126 |
| 10 | 9.9912 | 0.9608 | 2.4786 | 0.9226 | 0.1253 | 0.9103 |
| 15 | 13.4421 | 0.9987 | 4.6150 | 0.9420 | 0.1821 | 0.8102 |
| 20 | 23.6389 | 0.9528 | 3.8596 | 0.9361 | 0.1528 | 0.8450 |
| 25 | 25.7239 | 0.9921 | 5.4206 | 0.9448 | 0.2398 | 0.8431 |
4. Conclusions
Simultaneous, real-time monitoring of desorption processes in multi-throughput was achieved by applying the developed six-channel fiber-optic sensing in-situ detection technique to the desorption kinetic studies of quercetin from MARs. The technique enables accurate measurement of quercetin. By harnessing its real-time and simultaneous characteristics, complete and continuous desorption curves were plotted, and optimal conditions for quercetin desorption from MARs were effectively optimized. Additionally, the technique generated a large amount of valuable data for kinetic studies. With its ability to monitor multiple processes simultaneously and in real-time, this technique shows significant potential for practical applications in the adsorptive separation of bioactive compounds, as well as in environmental monitoring, significantly enhancing operational efficiency.
Acknowledgment
This work was supported by the National Natural Science Foundation of China (22064015 and 22464017), the Open Fund of Key Laboratory of Biotechnology and Bioresources Utilization (Dalian Minzu University), Ministry of Education (KF2024005) and Fujian Natural Science Foundation (2022J011228).
CRediT authorship contribution statement
Gaowei Guo: Writing – original draft, Validation, Investigation, Formal analysis, Data curation. Turghun Muhammad: Writing – review & editing, Supervision, Resources, Methodology, Funding acquisition, Conceptualization. Jingjing Yang: Writing – review & editing, Validation, Investigation, Formal analysis. Aikebaier Rehemana: Writing – review & editing, Supervision, Resources, Funding acquisition. Dengbin Yu: Writing – review & editing. Janar Jenis: Review & editing Formal analysis. Guiyang Yan: Review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper
Declaration of generative AI and AI-assisted technologies in the writing process
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript, and no images were manipulated using AI.
Supplementary data
Supplementary material to this article can be found online at https://dx.doi.org/10.25259/AJC_245_2025.
References
- Insight into the binding mechanism between soy protein isolate-oat β-glucan extrudate and quercetin in nanoparticles by multi-spectroscopic techniques. Food Chemistry. 2025;471:142723. https://doi.org/10.1016/j.foodchem.2024.142723
- [Google Scholar]
- Highly robust, compressible, anisotropic, and fire-retardant polyimide/hydroxyapatite nanowires/reduced graphene oxide aerogel for rapid adsorption of viscous oil assisted by sunlight. Research (Washington, D.C.). 2024;7:0512. https://doi.org/10.34133/research.0512
- [Google Scholar]
- An efficient measure for the isolation of chenodeoxycholic acid from chicken biles using enzyme-assisted extraction and macroporous resins refining. Poultry Science. 2025;104:104573. https://doi.org/10.1016/j.psj.2024.104573
- [Google Scholar]
- Advancing phosphate batch adsorption: Comprehensive modeling and scalability with granulated clay adsorbent in single and binary systems. Journal of Water Process Engineering. 2025;70:106996. https://doi.org/10.1016/j.jwpe.2025.106996
- [Google Scholar]
- Classical and bayesian computational statistics applied to acetylsalicylic acid mitigation in aqueous solutions: Study of batch scale, kinetic modeling, and fixed-bed column adsorption. Industrial & Engineering Chemistry Research. 2024;63:9943-9954. https://doi.org/10.1021/acs.iecr.4c00050
- [Google Scholar]
- Fixed-bed adsorption kinetics study of auramine O dye on non-imprinted polymers based on a real-time monitoring system. Journal of Water Process Engineering. 2025;71:107161. https://doi.org/10.1016/j.jwpe.2025.107161
- [Google Scholar]
- Sequestration of contaminants from wastewater: a review of adsorption processes. ChemBioEng Reviews. 2023;10:491-509. https://doi.org/10.1002/cben.202200050
- [Google Scholar]
- Precise in-situ detection of adsorption kinetics based on fiber-optic sensing with a Y-shaped batch vessel. Instrumentation Science & Technology. 2021;49:201-215. https://doi.org/10.1080/10739149.2020.1811985
- [Google Scholar]
- In-situ kinetic and thermodynamic study of 2,4-dichlorophenoxyacetic acid adsorption on molecularly imprinted polymer based solid-phase microextraction coatings. Sensors and Actuators A: Physical. 2020;313:112190. https://doi.org/10.1016/j.sna.2020.112190
- [Google Scholar]
- FIA online spectrophotometric determination of total flavonoids in plants and its application for batch adsorption kinetics. Industrial & Engineering Chemistry Research. 2023;62:14224-14233. https://doi.org/10.1021/acs.iecr.3c01295
- [Google Scholar]
- Citrate polymer optical fiber for measuring refractive index based on LSPR sensor. Scientific Reports. 2024;14:18637. https://doi.org/10.1038/s41598-024-69083-2
- [Google Scholar]
- In situ liquid-phase-adsorption measurement system based on fiber-optic sensing with the aid of membranes. ACS Omega. 2018;3:10891-10897. https://doi.org/10.1021/acsomega.8b01059
- [Google Scholar]
- Molecularly imprinted polymers based optical fiber sensors: A review. TrAC Trends in Analytical Chemistry. 2022;152:116608. https://doi.org/10.1016/j.trac.2022.116608
- [Google Scholar]
- Thermal self-regulation of flexible asymmetric supercapacitor assisted by fiber optic sensing system. Journal of Power Sources. 2025;629:235991. https://doi.org/10.1016/j.jpowsour.2024.235991
- [Google Scholar]
- Monitoring dissolution rate of amiodarone tablets by a multiple fiber-optic sensor system. Dissolution Technologies. 2008;15:22-27. https://doi.org/10.14227/dt150108p22
- [Google Scholar]
- Precise evaluation of batch adsorption kinetics of plant total polyphenols based on a flow-injection online spectrophotometric method. Analytical Methods : Advancing Methods and Applications. 2024;16:589-598. https://doi.org/10.1039/d3ay02023a
- [Google Scholar]
- Anchoring nanoscale zero-valent iron within bacterial cellulose particles for boosting efficient adsorption of Co(II) and Sr(II) from seawater: Dual system and varying adsorption mechanisms. Journal of Environmental Sciences (China). 2025;154:457-469. https://doi.org/10.1016/j.jes.2024.09.005
- [Google Scholar]
- Lignin and black liquor based composite hydrogels for the enhanced adsorption of malachite green dye from aqueous solutions: Kinetics, rheology and isotherm studies. International Journal of Biological Macromolecules. 2025;296:139613. https://doi.org/10.1016/j.ijbiomac.2025.139613
- [Google Scholar]
- ANN Modeling for rhodamine B adsorption using pristine and NaOH-activated mesoporous sewage sludge biochars: Kinetic, isotherm, thermodynamic, and regeneration studies. Industrial & Engineering Chemistry Research. 2025;64:3288-3316. https://doi.org/10.1021/acs.iecr.4c02105
- [Google Scholar]
- Adsorption and desorption of phenanthrene and 1-hydroxyphenanthrene by goethite-coated polyvinyl chloride. Journal of Environmental Sciences (China). 2025;154:833-846. https://doi.org/10.1016/j.jes.2024.09.020
- [Google Scholar]
- Enhanced adsorption removal of levofloxacin using antibacterial LDH-biochar cross-linked chitosan/PVA beads through batch and column approaches; Comprehensive isothermal and kinetic study. Desalination. 2025;599:118452. https://doi.org/10.1016/j.desal.2024.118452
- [Google Scholar]
- Kinetic adsorption mechanism of cobalt(II) ions and Congo red on pristine and Schiff base-surface-modified MIL-101(Fe)-NH2. Microporous and Mesoporous Materials. 2025;386:113493. https://doi.org/10.1016/j.micromeso.2025.113493
- [Google Scholar]
- Sea buckthorn flavonoids: Purification, identification, and in vitro anti-inflammatory effects. Journal of Chromatography. A. 2025;1750:465885. https://doi.org/10.1016/j.chroma.2025.465885
- [Google Scholar]
- Preparation of silymarin enriched extract (Silybum marianum) using macroporous resins: Adsorption/desorption characteristics, quantitative analysis by HPLC and UPLC. Microchemical Journal. 2024;207:112006. https://doi.org/10.1016/j.microc.2024.112006
- [Google Scholar]
- Purification of quercetin-3-O-sophoroside and isoquercitrin from Poacynum hendersonii leaves using macroporous resins followed by Sephadex LH-20 column chromatography. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences. 2017;1048:56-63. https://doi.org/10.1016/j.jchromb.2017.01.041
- [Google Scholar]
- Electrospun nanofiber chitosan/polyvinyl alcohol loaded with metal organic framework nanofiber for efficient adsorption and removal of industrial dyes from waste water: Adsorption isotherm, kinetic, thermodynamic, and optimization via Box-Behnken design. International Journal of Biological Macromolecules. 2025;299:140086. https://doi.org/10.1016/j.ijbiomac.2025.140086
- [Google Scholar]
- Elimination of Ni(II) from wastewater using metal-organic frameworks and activated algae encapsulated in chitosan/carboxymethyl cellulose hydrogel beads: Adsorption isotherm, kinetic, and optimizing via Box-Behnken design optimization. International Journal of Biological Macromolecules. 2025;299:140019. https://doi.org/10.1016/j.ijbiomac.2025.140019
- [Google Scholar]
- Adsorption and eliminating of diquat herbicide using layer double hydroxide enclosed in double layer hydrogel beads of carboxymethyl cellulose and alginate: Synthesis, characterization, adsorption isotherm, kinetics, thermodynamics and optimization via box-behnken design. International Journal of Biological Macromolecules. 2025;303:140564. https://doi.org/10.1016/j.ijbiomac.2025.140564
- [Google Scholar]
- Adsorption and desorption characteristics of a phenolic compound from Ecklonia cava on macroporous resin. Food Chemistry. 2021;338:128150. https://doi.org/10.1016/j.foodchem.2020.128150
- [Google Scholar]
- Superior adsorption and removal of toxic industrial dyes using cubic Pm3n aluminosilica form an aqueous solution, Isotherm, Kinetic, thermodynamic and mechanism of interaction. Journal of Molecular Liquids. 2023;379:121672. https://doi.org/10.1016/j.molliq.2023.121672
- [Google Scholar]
- One-step enrichment of phenolics from Chaenomeles speciosa (Sweet) Nakai fruit using macroporous resin: Adsorption/desorption characteristics, process optimization and UPLC-QqQ-MS/MS-based quantification. Food Chemistry. 2024;439:138085. https://doi.org/10.1016/j.foodchem.2023.138085
- [Google Scholar]
- Effects of aging processes on spent mushroom substrate-derived biochar: Adsorption characteristics of Cd(II) and Cr(VI) Arabian Journal of Chemistry. 2024;17:105926. https://doi.org/10.1016/j.arabjc.2024.105926
- [Google Scholar]
- Reaction mechanism study of calcium carbide residue with graphene oxide in aqueous environment: Adsorption properties and mechanical potentials. Arabian Journal of Chemistry. 2024;17:106038. https://doi.org/10.1016/j.arabjc.2024.106038
- [Google Scholar]
- Highly rapid and efficient removal of heavy metals, heavy rare earth elements, and phenolic compounds using EDTA-cross-linked MXene polymer composite: Adsorption characteristics and mechanisms. Chemical Engineering Research and Design. 2023;194:497-513. https://doi.org/10.1016/j.cherd.2023.04.048
- [Google Scholar]