Outstanding Adsorption of Reactive Red 2 and Reactive Blue 19 Dyes on MIL-101 (Cr): Novel Physicochemical Analysis of Underlying Mechanism Through Statistical Physics Modeling

Abstract

An outstanding adsorbent, such as the metal–organic framework (MOF) MIL-101 (Cr), was employed to study the adsorption of two dyes, namely reactive red 2 (RR2) and reactive blue 19 (RB19). Experimental adsorption data were retrieved at T = 25, 35 and 45 °C and analyzed to define the adsorption mechanism of these dyes. A modeling approach based on a double-layer model derived from statistical physics was used. The maximum adsorption capacity (MAC) was found to be 875, 954 and 1002 mg/g for RR2 and 971, 1093 and 1148 mg/g for RB19, at T = 25, 35 and 45 °C, respectively. These values indicate that MIL-101 (Cr) exhibits outstanding performance in removing potential water pollutants such as the RR2 and RB19 dyes. The possible orientations of the RR2 and RB19 dyes upon adsorption were determined by analyzing the number of dye molecules bound per MIL-101 (Cr) active sites during the adsorption process. It was found that the RR2 dye was removed via a mixed parallel and non-parallel orientation on MIL-101 (Cr), while RB19 was removed via an inclined orientation at higher temperatures. The adsorption mechanism suggested that MIL-101 (Cr) site density was reduced due to an exothermic effect, which decreases the number of active sites participating in dye adsorption, even though the reduction in water adsorption may be attributed to the overall endothermic behavior. From the adsorption energy (AE) and the chemical structure of MIL-101 (Cr) and both dyes, it was concluded that hydrogen bonds, Van der Waals forces and π-π stacking are involved in the dye removal process. This research provides new physical insights into the adsorption mechanism of two relevant dyes on an outstanding adsorbent such as the MIL-101 (Cr) MOF.

1. Introduction

Water contamination by synthetic organic dyes is a growing concern as it generates serious environmental problems if not adequately managed. This environmental problem can cause deep damage to both aqueous ecosystems and human health [1,2,3,4,5,6]. Due to the development of industrial activities such as those of pharmaceuticals, foods, textiles, cosmetics, paper and plastics, more than 10,000 various dyes have been used. The widespread use of these dyes during the production and finishing processes, coupled with the incorrect management of the resulting discharges, is the main source of the contamination of industrial wastewater [7,8,9]. It is estimated that about 700,000 to 1,000,000 tons of dyes is annually produced worldwide, and the textile industry alone accounts for the greatest share. It is also estimated that, due to incomplete utilization and incorrect disposal, about 280,000 tons of synthetic dyes is discharged annually into various water bodies [10]. Dyes are chemically diverse compounds, often categorized into classes such as acids and bases, each with distinct physical and chemical properties that influence their diffusion and persistence in aquatic environments. Some dyes, such as the azo type, are known for their vivid colors and great resistance and durability to degradation, which is advantageous during their industrial use but presents a critical issue for natural degradation processes and, more in general, for their impact when released into the environment. In fact, once dispersed into aquatic systems, they can significantly hinder oxygen solubility and sun light penetration, thus affecting photosynthetic aquatic organisms and the entire ecosystem, with significant impacts on the whole food chain. Beyond the ecological impact, dyes can directly affect human health due to their toxic, mutagenic and carcinogenic properties, which can also be derived from breakdown products originating from the interactions between the original dyes and the aquatic environment. Therefore, significantly reducing the impact of these dangerous contaminants has become necessary to ensure good water quality and to protect human health. To achieve this environmental objective, various technologies have been explored such as advanced oxidation, photocatalytic degradation, membrane separation and adsorption [11,12,13,14,15]. Yet, an effective and economical solution remains a pressing challenge. Comparatively, adsorption has been applied more on different systems [12,14,16,17,18,19,20,21], yielding good results in terms of limiting the impact of industrial activities using dyes in their production cycles. Adsorption is widely considered as an effective option among those available for the thorough removal of dyes from contaminated water, due to its general simplicity, wide applicability and efficiency across different categories of water pollutants [22]. It does not require complex equipment and does not necessitate high energy inputs, ensuring high performances in the removal of different categories of dyes, if the appropriate adsorbent is used in terms of physical and chemical affinity with the specific target molecule. The first step toward the better treatment of dye-contaminated water is the selection of a high-performance adsorbent to obtain significant water pollutant removal. In this regard, various adsorbents have been employed to remove dyes [23,24,25]. The high versatility of this technology allows both low-cost waste materials and high-specific commercial adsorbents to be exploited, depending on the required performance level [26,27]. Additionally, this process is easy to implement, and the pollution generated during its application is limited, as many adsorbents can also be regenerated and reused cyclically [22]. This characteristic makes adsorption a highly attractive technology for sustainable wastewater treatment, especially in those areas where resources are limited or environmental regulations are particularly stringent.

Examples of dyes that can generate risks to human health include reactive red (RR2) and reactive blue (RB19) [28]. Their widespread use across various applications means that they are often found in wastewater due to improper disposal. Various adsorbents can potentially be applied for their removal. As the thorough selection of a suitable material significantly influences the successful elimination of these dangerous compounds, it should be remarked that the proper choice should be based on a thorough experimental analysis of potential candidates’ behavior. Indeed, a full understanding of the dynamics of adsorbate–adsorbent interactions, taking into consideration the properties of both at the molecular level, can lead to a more informed selection and higher chances of success. To understand the mechanism of dye removal, several research steps are necessary, including the preliminary determination of dye adsorption data, the adsorbent characterization and a final modeling approach, which serves as a valuable tool for analyzing the collected experimental data.

Among the available options for the adsorption of these dyes, metal–organic frameworks (MOFs) have emerged as a prominent class of high-specific and -performing adsorbents, characterized by high porosity and, consequentially, large adsorption capacity. The adsorption of RR2 and RB19 dyes using MIL-101 (Cr) as an adsorbent was formerly analyzed by Cheng et al. [29]. Note that the effects of Cobalt-containing wastewater treatment were also studied [30]. However, the modeling of dye adsorption isotherms was based on classical models such as Langmuir, Freundlich and Temkin, which, despite their widespread use, do not go beyond a phenomenological interpretation of the adsorption data and lack a defined physical meaning. The investigation of RR2 and RB19 dye adsorption mechanisms can be extended to gain new details at the molecular level by the application of statistical physics models. These advanced models represent a new frontier for interpreting adsorption data involving MOFs, as they allow for a detailed description of how dye molecules interact with MOF surfaces and pores at the molecular scale. In this context, the selected dyes can be considered as “probe molecules” for defining and validating a modeling methodology, which can be later extended to the study of other adsorption systems. The insights obtained are comparable to those from molecular simulation tools (e.g., COSMO-RS) but require lower computational efforts [31]. Specifically, useful information can be retrieved from the fitting parameters such as the adsorption energy distribution, site occupancy and the number of adsorption sites, all based directly on the experimental evidence and helpful for quantifying the strength and dynamics of adsorption. Moreover, statistical physics models are valuable for estimating some key thermodynamic properties of the adsorption system, including enthalpy and entropy changes, which are essential for understanding the stability and efficiency of MOFs as adsorbents under different conditions. Therefore, the objective of this paper is the application of a physical model to RR2 and RB19 adsorption data on the MIL-101 (Cr) MOF to gain a deeper understanding of their adsorption mechanisms at the molecular level. Overall, new physical findings based on steric, energetic and thermodynamic considerations are presented, which could support the practical application of this adsorbent for a real adsorption device.

2. Experimental Section

2.1. Materials and Methods

The MIL-101 (Cr) MOF was obtained starting from the use of PET plastic bottles as a raw material and using chromium (III) nitrate nonahydrate as a metal cluster, following the procedure described by Cheng et al. [29]. The adsorbent has a microporous structure, with a large pore volume (order of 1 cm³/g) and good BET surface area (1922 m²/g) [29]. A release test in deionized water was carried out, and the absence of Cr ion release was verified. A detailed characterization of the obtained adsorbent can be found in Cheng et al. [29].

Adsorption tests of RR2 and RB19 on the MIL-101 (Cr) adsorbent were carried out with the conventional batch procedure, using a volume of 100 mL, a mass of 10 mg and different concentrations of dyes in the range of 80–350 mg L⁻¹. Experimental runs were carried out at constant pH = 7 and by varying the temperature at 25, 35 and 45 °C.

2.2. RR2 and RB19 Adsorption Data Results

Figure 1 illustrates the RR2 and RB19 adsorption capacity on the MIL-101 (Cr) MOF as a function of their equilibrium concentration and for the different investigated temperatures. For both the adsorbates, adsorption isotherms show a typical trend, with a significant increase in adsorption capacity as the dye concentration increases. However, for RR2, the trend is more gradual, while RB19 exhibits a steeper increase at low concentrations and a more pronounced plateau at higher concentrations. Moreover, both the graphs show a clear tendency toward saturation, which may indicate the formation of one or more adsorption layers. The experimental findings indicate that MIL-101 (Cr) has a high affinity for removing both the RR2 and RB19 dyes with good experimental adsorption capacities, demonstrating that this adsorbent performs excellently. Finally, both the adsorbates display an endothermic behavior, as their adsorption capacities increase with temperature.

2.3. Statistical Physics Model Set-Up

For the interpretation of the observed experimental results, different models deriving from statistical physics were tested, namely a monolayer model with single energy, a double-layer model with two energies and a multilayer model with saturation. The modeling results indicated the physical double-layer model as the best-fitting model, and it was used to extend the analysis of the experimental data and to provide a non-traditional explanation of the adsorption mechanism of these dyes. This model assumes that the total number of layers formed on the adsorbent surface is fixed at 2, characterized by two different interaction energies RR2-MIL-101 (Cr) and RR2-RR2 for the RR2 dye and RB19-RB19 and RB19-MIL-101 (Cr) for the RB19 dye. The model equation is formulated as follows [32,33]:

$$Q_e=n{N}_m{\displaystyle \frac{{\left(\frac{C_e}{C_1}\right)}^n+2{\left(\frac{C_e}{C_2}\right)}^{2n}}{1+{\left(\frac{C_e}{C_1}\right)}^n+{\left(\frac{C_e}{C_2}\right)}^{2n}}}$$

(1)

The n parameter represents the number of bound RR2 and RB19 molecules by the MIL-101 (Cr) site, while its density is represented by the N_m parameter. C₁ and C₂ are the concentrations at half-saturation, two energetic parameters that can be adopted to determine the adsorption energies (ΔEs). They are expressed as follows [34,35]:

$$\Delta E_1=RT\ln \left({\displaystyle \frac{C_s}{C_1}}\right)$$

(2)

$$\Delta E_2=RT\ln \left({\displaystyle \frac{C_s}{C_2}}\right)$$

(3)

Equations (2) and (3) are related to the interactions of dye–MIL-101 (Cr) and dye–dye molecule, respectively. R is the constant of ideal gas, and C_S is RB19 or RR2 water solubility.

This adopted model shows a good correlation with dye experimental data, and the values of the determination coefficient are very close to unity in some cases (see

Table 1. Fitting parameter values of double-layer model for adsorption of RR2 and RB19 dyes onto MIL-101 (Cr) adsorbent.

T, °C	R2	n	Nm (mg/g)	C1 (mg/L)	C2 (mg/L)	MAC (mg/g)
RR2
25	0.995	0.64	684.25	8.18	22.48	875.84
35	0.997	0.81	589.19	10.56	17.98	954.48
45	0.997	0.86	582.98	13.28	25.18	1002.72
RB19
25	0.946	0.74	656.66	10.19	24.29	971.85
35	0.977	1.12	488.26	15.58	35.17	1093.70
45	0.956	1.55	370.36	18.98	52.52	1148.116

) Table 1 summarizes the calculated values of this model, parameters are summarized, and the data fitting is illustrated in Figure 1.

Figure 1. RR2 and RB19 dye adsorption experimental data at 25, 35 and 45 °C with double-layer model fitting at different temperatures.

Figure 1. RR2 and RB19 dye adsorption experimental data at 25, 35 and 45 °C with double-layer model fitting at different temperatures.

3. Discussion

The adsorption mechanisms of the RR2 and RB19 dyes can be elucidated through an analysis of the fitting parameters obtained from the adopted statistical physics model, which are linked with specific physicochemical aspects of adsorption such as steric and energetic interactions. Specifically, the steric aspects of adsorption are related to the interpretation of the parameters n, N_m and Q_s, while the energetic aspects are based on the assessment of the adsorption energy (ΔE). Moreover, thermodynamic parameters such as entropy and free enthalpy complete the analysis.

3.1. Steric Aspect of Dye Adsorption Mechanisms

As mentioned in the model description, the n parameter represents the number of dye molecules adsorbed per MIL-101 (Cr) active site. At higher equilibrium dye concentrations, saturation can be reached, leading to the filling of the MIL-101 (Cr) sites that can be examined through the N_m parameter. Specifically, N_m represents the density of occupied MIL-101 (Cr) sites. Both parameters synergistically contribute to the definition of the adsorption mechanism. The values of the n parameter, which are summarized in Table 1, highlight that n (RR2-MIL-101 (Cr) site) is lower than unity at T 25, 30 and 45 °C and lower compared to those of the RB19-MIL-101 (Cr) system. It is possible to infer that the RR2 dye binding level is weaker, thus preventing aggregation among molecules during adsorption. For the RB19 dye, the n values are below unity at lower temperatures, but at higher temperatures (T = 35 and 45 °C), the n (RB19-MIL-101 (Cr)) parameter increases to values between 1 and 2, reaching a maximum of n = 1.55 at 45 °C. This estimated value indicates that this dye tends to aggregate at higher temperatures, leading to the formation of both monomers and dimers on the adsorbent surface. To the authors’ knowledge, the orientation of dyes on MIL-101 (Cr) has not been previously described. Indeed, the fitted value of the n parameter at different temperatures provides useful insights into the inclination of the dyes during adsorption. Based on our previous works [33,36,37], three orientation modes can be inferred: if the n value is less than 0.5, the orientation is parallel; if greater than 1, it is non-parallel; and if between 0.5 and 1, a mixed parallel/non-parallel orientation is assumed. For the RR2-MIL-101 (Cr) system, n values fall between 0.5 and 1, indicating that RR2 was captured by the adsorbent surface in a mixed orientation. For the RB19–MIL-101 (Cr) system, the dye showed the same orientation as RR2 at lower temperatures, while at higher temperatures, it shifted to a non-parallel orientation. The evolution of the dye molecules captured per MIL-101 (Cr) site is depicted in Figure 2, which clearly shows that temperature plays a relevant role in detecting both pollutants. This evidence can be attributed to the reduced adsorption capacity of water molecules at higher temperatures, which frees up space for dye adsorption and promotes the aggregation of molecules for a hydrophobic effect [38]. This confirms that the adsorption of both dyes is an endothermic process, driven by complex interactions with water.

The evolution of the N_m parameter as a function of temperature is depicted in Figure 3. Overall, an inverse trend in this parameter was observed as compared to the number of dye molecules per MIL-101 (Cr) active site (n parameter). The reduction in N_m with temperature experienced by both the adsorbates appears to be attributable to a typical exothermic effect, which reduces the number of active sites along with an increase in temperature. However, the hydrophobic effect previously highlighted likely counterbalances this effect, resulting in an overall endothermic phenomenological effect.

The study of the maximum adsorption capacity (MAC) provides insights into the performance of the adsorbent used and its relevance for various applications in industrial sectors. The MAC values are 875, 954 and 1002 mg/g for the RR2 dye and 971, 1093 and 1148 mg/g for RB19 at the different investigated temperatures. Comparatively, MAC (RB19-MIL-101 (Cr)) > MAC (RR2-MIL-101 (Cr)), at each temperature. This result indicates that the MIL-101 (Cr) adsorbent is more effective in removing RB19, probably due to its higher surface affinity. These elevated MAC values clearly demonstrate that this adsorbent exhibits outstanding performance in removing these dyes and potentially other relevant pollutants. The remarkable increase in the MIL-101 (Cr) adsorbent’s performance with temperature can be attributed to reduced water adsorption, despite the reduction in available active sites (Figure 4). This likely led to an increase in the adsorbate–adsorbate hydrophobic interactions confirmed by the observed aggregation, which in turn resulted in higher adsorption capacity.

3.2. Energetic Aspects

The adsorption energy (ΔE) was estimated via Equations (2) and (3). Equation (2) relates to the interactions between dyes and the adsorbent surface (RB19-MIL-101 (Cr) and RR2-MIL-101 (Cr)), while Equation (3) corresponds to the RB19-RB19 and RR2-RR2 interactions. All ΔE values are positive, indicating an endothermic process, as also confirmed by a previous study using a different modeling approach [29]. Since the ΔE values are lower than the 40 kJ/mol threshold, the process could be likely interpreted as physisorption. When analyzing the chemical structure of both dyes and the MIL-101 (Cr)) adsorbent [29], hydrogen bonding, Van der Waals forces, hydrophobic interactions and π-π stacking are the main interactions expected to occur in the adsorption of these dyes on the investigated MOF. The impact of temperature on the ΔE of both systems is negligible, as the slight differences observed are not considered statistically significant (Figure 5). Given this behavior and returning to the temperature impact on the n and N_m parameters, it is clear that the MAC is primarily governed by the n parameter, since it follows the same trend as the MAC in contrast to the N_m parameter.

3.3. Analysis of Entropy and Free Enthalpy

The elucidation of the RR2 and RB19 dye adsorption mechanisms can be further enriched through the examination of thermodynamic parameters such as entropy (S_a) and free enthalpy (G_a). It is important to note that both thermodynamic functions were derived from the model adopted in this study. Additional insights can be retrieved through this thermodynamic analysis, providing an advanced macroscopic understanding of the adsorption process. The entropy and free enthalpy expressions are provided below [39]:

$${\displaystyle \frac{S_a}{K_B}}=-N_m\left\{{\displaystyle \frac{\left({\left(\frac{Ce}{C_1}\right)}^n\times {\mathit{ln}\left(\frac{Ce}{C_1}\right)}^n+{\left(\frac{Ce}{C_2}\right)}^{2n}\times {\mathit{ln}\left(\frac{Ce}{C_2}\right)}^{2n}\right)}{1+{\left(\frac{Ce}{C_1}\right)}^n+{\left(\frac{Ce}{C_2}\right)}^{2n}}}-\mathit{ln}\left(1+{\left({\displaystyle \frac{Ce}{C_1}}\right)}^n+{\left({\displaystyle \frac{Ce}{C_2}}\right)}^{2n}\right)\right\}$$

(4)

$${\displaystyle \frac{G_a}{K_{B}T}}=n{N}_m\times \mathit{ln}\left({\displaystyle \frac{Ce}{z_v}}\right)\times {\displaystyle \frac{{\left(\frac{Ce}{C_1}\right)}^n+2{\left(\frac{Ce}{C_2}\right)}^{2n}}{1+{\left(\frac{Ce}{C_1}\right)}^n+{\left(\frac{Ce}{C_2}\right)}^{2n}}}$$

(5)

where k_B is Boltzmann’s constant, and z_v is the partition function of translation (per unit of volume).

3.3.1. Entropy

Positional entropy describes the randomness of the position of the dye molecules distributed on the adsorbent surface. In turn, this depends on the density of adsorption sites and on the number of molecules bound per active site. The relationship between the Sa parameter and dye concentration is depicted in Figure 6. A brief analysis of the resulting trend identifies three different behaviors: At low dye concentrations, there is an increase in entropy as a function of dye concentrations that confirms the increase in available space for dye molecules and their spread over the large adsorbent surface. This indicates that the possibility of finding an empty MIL-101 (Cr) site is high.

At high dye concentrations, the opposite behavior is observed, with a decrease in entropy indicating a reduction in the available space. This means that, at higher dye concentrations, the possibility of finding an empty MIL-101 (Cr) site is reduced.

Furthermore, for the RR2 dye, the effects of temperature reflect the trend in adsorption site density, as a slight decrease with temperature does not imply a reduction in the number of available adsorption sites and, consequently, in the randomness of adsorption binding. Conversely, for RB19, the temperature effect appears more pronounced, leading to a corresponding decrease in entropy.

3.3.2. Free Enthalpy

The free enthalpy (G_a) of adsorption provides important information about the spontaneity of the adsorption process and the strength of the adsorbate–adsorbent interactions.

The relationship between the G_a parameter and dye concentration is depicted in Figure 7.

The computed values of G_a are negative, indicating that the adsorption of dyes is spontaneous. An increase in temperature determines a higher value of the free enthalpy (absolute value), confirming the establishment of stronger interactions at higher temperature. Moreover, RB19 was confirmed to be bound with higher strength on the adsorbent surface.

4. Conclusions

In this work, the adsorption of two dyes, namely reactive red 2 (RR2) and reactive blue 19 (RB19), onto a metal–organic framework (MIL-101 (Cr)) was accurately studied by means of a double-layer model formulated on the principles of statistical physics. Experimental adsorption data at different temperatures were fitted with the selected model, and the retrieved fitting parameters were analyzed in order to define an adsorption mechanism. For both the adsorbates, adsorption isotherms followed the typical trend, with a significant increase in adsorption capacity with liquid concentration. However, for RR2, the trend is more gradual, while RB19 shows a steeper shape for low concentrations and a more pronounced flat trend for higher concentrations. Moreover, both the adsorbates exhibited an endothermic behavior, as their adsorption capacity increases with temperature, likely attributable to a reduction in water adsorption and to a hydrophobic effect. The number of dye molecules bound per adsorbent active site indicates the presence of an aggregation process for RB19. The RR2 dye was captured by the adsorbent surface assuming a mixed parallel and non-parallel orientation, while for RB19, at a higher temperature, the non-parallel orientation prevailed. The density of active sites decreased with temperature for both the systems, indicating a typical exothermic effect, which reduces the number of active sites along with an increase in temperature. However, other effects prevailed, as previously indicated, and the insights from adsorption energy confirmed phenomenological endothermicity. Finally, the retrieved thermodynamic parameters allowed for a more complete description of the adsorption mechanism, indicating a higher affinity of RB19 for the adopted adsorbent.