Xin Zhaoa,
Zhengwu Wangb,
Shiling Yuanc,
Juan Lua and
Zhongni Wang*a
aCollege of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Shandong Normal University, Jinan 250014, P. R. China. E-mail: zhongniw@hotmail.com
bDepartment of Food Science Technology, Shanghai Jiaotong University, Shanghai 200240, P. R. China
cKey Laboratory of Colloid and Interface Chemistry, Institute of Theoretical Chemistry, Shandong University, Jinan 250100, P. R. China
First published on 7th April 2017
In this work, for the first time a coarse-grained model in a mesoscopic dynamic (MesoDyn) simulation for a pharmaceutical nonionic surfactant Brij97 was presented. By using this coarse-grained model, the morphology transition from oil in water (O/W) to a bicontinuous microemulsion formed in the Brij97/isopropanol/isoamyl acetate/H2O quaternary system was predicted. Furthermore, the effect of emulsifier/isoamyl acetate mass ratio, Brij97/alcohol mass ratio and alcohol structure on the droplets size and kinetic formation process of the O/W microemulsion were studied. These MesoDyn predictions were consistent with experimental measurements. This makes it possible to further predict the formation mechanism of complex drug-loaded aggregates of Brij97 by using this coarse-grained model.
Aiming to address the limitation of the experiments, computer simulations have been proven to be valuable tools for providing additional information at molecular11 or mesoscopic scale.12 In particular, mesoscopic dynamics (MesoDyn) simulation have become a powerful analytical approach for exploring the phase behaviour and dynamic evolution process of polymer or surfactant in solvents at real conditions (pressure and temperature). Li, Y. et al.13 used MesoDyn method to simulate the aggregation behaviour of pluronic copolymer L64 solutions in the presence of SDS. The kinetic process of micelles formation underwent transitions from three to two stages with the increase of L64 concentration, which was hard to be observed from the experiments. The necessity of the shear and the weak charge to the formation of hexagonal templates in the P123 copolymer were confirmed by Yuan, S. et al. through MesoDyn simulations.12
Microemulsions, usually consisting of surfactant, co-surfactant, oil and water, are defined as optically isotropic transparent and thermodynamically stable systems.14 Microemulsions have been extensive applied in various fields, such as separation,15 chemical reactions,16 nanomaterial preparation,17 and drug delivery.18 Microemulsions application are largely dependent on their different structures, namely, oil-in-water (O/W), bicontinuous (B.C.), and water-in-oil (W/O) structures. However, as far as we know, the effect of components on the aggregation process of microemulsion from the perspective of phase behaviour and nanostructure19 was rarely reported.
In present work, the coarse-grained model of Brij97 in MesoDyn simulation was presented for the first time. The morphologies of Brij97/isopropanol/isoamyl acetate/H2O were predicted by using the Brij97 model. The effect of water content, emulsifier/isoamyl acetate mass ratio, Brij97/isopropanol mass ratio and alcohol structure on the morphology and size of microemulsion were further studied by a combination of MesoDyn prediction and experimental measurements.
Fig. 1 The coarse-grained models of Brij97, alcohols, isoamyl acetate and H2O in the MesoDyn simulation. The molecular structure of Brij97 is divided into two types of beads: C and E. |
The interaction among various beads were represented by interaction parameters. The solvent–polymer interaction energy λij are related to the Flory–Huggins interaction parameter χij through the following equation:22
λij = χijRT | (1) |
The Flory–Huggins interaction parameter χij can be obtained by the expression:21
(2) |
The Flory–Huggins interaction parameter between the hydrophobic tail of Brij97 and isoamyl acetate χC–O was estimated to be 0.1 calculated from the eqn (2), consistent with similar dissolve mutually theory. However, the values of χE–W, χA–W and χE–A calculated from the eqn (2) were incorrect. The possible explanation to the trouble is that the hydrogen bonding between beads and solvent was neglected.23 Hence, the effective Flory–Huggins parameters were defined in Baulin and Halperin's work,24 = χeff + f(Φ). In general, the miscibility between polymer and solvent are dependent on the interaction parameter. Consequently, χE–W used in present study was defined as 0.3 on account of the hydrophilic properties of surfactant EO headgroup, and χC–W was estimated to be 5.0 due to the hydrophobic properties of surfactant alkyl chain tail. The effective Flory–Huggins interaction parameters between various beads used in this work were listed in Table 1.
Bead | E | C | A | O | W |
---|---|---|---|---|---|
a E, C, A, O and W represent hydrophilic group of Brij97, hydrophobic group of Brij97, alcohol, isoamyl acetate, and H2O, respectively. | |||||
E | 0 | 1.6 | 0.8 | 4.0 | 0.3 |
C | 1.6 | 0 | 1.0 | 0.1 | 5.0 |
A | 0.8 | 1.0 | 0 | 0.6 | 1.2 |
O | 4.0 | 0.1 | 0.6 | 0 | 5.0 |
W | 0.3 | 5.0 | 1.2 | 5.0 | 0 |
In MesoDyn simulation, the dimensionless parameters were chosen as follows: the size of cubic grid 32 × 32 × 32 nm, the bond length 1.1543, the bead diffusion coefficient 10−7 cm2 s−1, the noise parameter 100.0, the compressibility parameter 10 kT, the simulated temperature 298 K, the time step 0.5 ns. For each system, the total number steps of 20000 were carried out to reach a kinetic equilibrium. All simulations were carried out with MesoDyn module in a commercial software Materials Studio 4.4 from Accelrys, Inc,25 successful used to studied several surfactant22 or polymer26–28 solution systems.
The microstructural transition from W/O, B.C. to O/W in the microemulsion region was characterized by electric conductivity measurement using a model DDSJ-308A digital conductivity meter equipped with a DJS-1C platinum bright electrode (Shanghai INESA Scientific Instrument Co., Ltd., Shanghai, China).
Fig. 2(a) showed the dependence of simulated morphology of Brij97 assemblies on water content. The components of sample S1 and S2 were listed in Table 2. For S1 with 80 wt% H2O, the E beads isosurface formed several spherical droplets. In order to inspect the distribution of all compositions in the spherical droplets, a representative droplet marked by red cubic grid was segregated and analysed the radial density distribution. As shown in Fig. 2(b), the density distribution of O, C and W beads presented a single peak, broad peak and valley respectively, indicating the isoamyl acetate molecules and hydrophobic tails of Brij97 composed the core of spherical droplets without free water molecules. For hydrophilic beads E of Brij97, the density distribution presented two low peaks far from the centre of sphere, indicating a hydrophilic shell. This is a typical morphology of O/W microemulsion. While for S2 with 60 wt% H2O, the E beads isosurface formed several cylindrical channels. It is similar to a classical bicontinuous structure with water tank and oil pipe. The simulation results presented that the microemulsion underwent a transition from B.C. to O/W with water content increasing from 60 to 80 wt%. In order to further confirm the prediction obtained by MesoDyn simulation, the phase diagram of Brij97/isopropanol/isoamyl acetate/H2O (Km = 1:1) system at 25 °C was constructed.
Sample | K | Km | Alcohol | Water (%) | Size (nm) | PDI | Type |
---|---|---|---|---|---|---|---|
a K and Km represent the ratio of emulsifier/isoamyl acetate and Brij97/alcohol, respectively. The values of size and PDI were obtained by DLS measurement. | |||||||
S1 | 9:1 | 1:1 | Isopropanol | 80 | 14.81 | 0.150 | O/W |
S2 | 9:1 | 1:1 | Isopropanol | 60 | — | — | B.C. |
S3 | 8:2 | 1:1 | Isopropanol | 80 | 17.33 | 0.255 | O/W |
S4 | 9:1 | 3:1 | Isopropanol | 80 | 12.30 | 0.307 | O/W |
S5 | 9:1 | 1:1 | Ethanol | 80 | 15.52 | 0.189 | O/W |
S6 | 9:1 | 1:1 | 1,2-Propanediol | 80 | 16.02 | 0.216 | O/W |
Fig. 3 Pseudo-ternary phase diagram of EM/isoamyl acetate/H2O system at 25 °C. The insert is a representative curve of electrical conductivity (κ) vs. H2O (wt%) along dilution line a. |
In order to confirm the prediction of microstructural transition obtained from MesoDyn simulation, further experimental measurement was necessary. It is well known, by measuring the variations of electrical conductivity (κ) of microemulsion as a function of the water content, the microemulsion region was divided into three parts: W/O, B.C. and O/W (see in Fig. 3). A representative electric conductivity curve was shown in the insert of Fig. 3. It was obviously found that three different types of microstructure: W/O (below 54.9 wt%), bicontinuous (B.C., 54.9–71.7 wt%) and O/W (above 71.7 wt%) occurred in the present system along the water dilution line a (marked in Fig. 3). Comparing with the experimental phase diagram and electrical conductivity results, simulation results can reproduce corresponding microemulsion structure in certain water content, which indicates that the selection of coarse-grained models and interaction parameters is effective and reasonable.13
In order to further explore the aggregation behaviour of Brij97-based microemulsion, several samples were prepared and investigated by using a combination of MesoDyn prediction and experiment methods in the following research. The components and measurement results of all samples tested were listed in Table 2.
Fig. 4 (a) The density slice of beads E, C and O for microemulsion S1 and S3. (b) The droplet size distribution of S1 and S3. |
To confirm the MesoDyn prediction, the droplet size distribution of microemulsion S1 and S2 were measured by dynamic light scattering. As shown in Fig. 4 and Table 2, the DLS results showed that the value of both average size and polydispersity index (PDI) increased with the K value decreased. This is consistent with the MesoDyn prediction that beads E, C and O dispersed over a wider area. Moreover, it was obviously found that the droplet size presented in simulated cubic grid (32 × 32 × 32 nm) was slightly smaller than the DLS result. The similar result was found that the size of microemulsion droplets in electron microscopy (TEM) images was also smaller than the DLS results.31 This was due to the size obtained by DLS was hydrodynamic diameter rather than real diameter.
Fig. 5(a) showed the variation of the order parameters of beads W and O as a function of time steps for microemulsion S1 and S3, respectively. As we all known, the formation process of microemulsion is a self-assembling evolution from disorder to order. Hence, the order parameter of beads in system increased along with the aggregation process of microemulsion. It was clear seen from Fig. 5(a), the formation process of the O/W microemulsion can be divided into three stages. In the first stage, all of the order parameter of beads are close to zero, indicating that each component in the system is highly dispersed. In the second stage, the order parameter of each component increased dramatically, which indicated that the ordered aggregates began to form. The third stage is the formation and stabilization of microemulsion. In this stage, the value of order parameter is not constant but waved up and down in a small range. It is not surprising because the microemulsion is a dynamic equilibrium system.
Fig. 5 (a) Order parameter plot of beads W and O with increasing time steps for microemulsion S1 and S3. (b) Free energy density plot with time step for microemulsions S1 and S3. |
Comparing with the order parameters curves of bead E, C and A (not presented), the changes of beads W and O were obvious. As shown in Fig. 5(a), the time of first stage for sample S3 was shorter than that of sample S1. This indicated that the formation rate of microemulsion accelerated with the K value decreasing. The result may be due to the enhancement of hydrophobic interaction. Besides, the order parameter of isoamyl acetate and water increased significantly. The former may be result from the fact that more isoamyl acetate molecules embed into the hydrophobic chains of surfactant to arrange orderly. The latter may be due to the result that larger droplets permitted more water molecules to form hydrogen bond with EO chains of surfactant.
Apart from the size and formation rate of microemulsion, the practical application of microemulsion is also largely dependent on the thermodynamically stability. As we all know, the free energy change of system can reflect the stability. The MesoDyn simulation can provide the free energy change in the aggregation process of microemulsion, while it is hard to obtain from experiment. Fig. 5(b) showed the free energy density plots with time step for microemulsions S1 and S3. As shown, the free energy density decreased asymptotically to approach a stable value during the simulations when the system reaches dynamic equilibrium.32 This indicated that the aggregation process of microemulsion is spontaneous. It is worth mentioning that the comparison of the free energy density values between S1 and S3 is totally meaningless because it is not routinely calculated for real systems.33 While in this case, the value of free energy change (|ΔG|) before and after the aggregation could reflect the stability of microemulsion to some extent. As shown in Fig. 5(b), the |ΔG| value of S3 was higher than that of S1, indicating that the stability of microemulsion increased with the K value decreasing.
Fig. 6 (a) The beads E isosurface representations for microemulsion S4; (b) droplet size distribution of microemulsion S4. |
Fig. 7(a) showed the variation of the order parameters of beads W, E and C as a function of time steps for microemulsion S1 and S4, respectively. From the figure we can see, the formation process of the microemulsion with different Km can also be divided into three stages. While for S4, the first stage of microemulsion formation was remarkably shortened. This is because that the hydrophobic interaction between various components increased with alcohol content decreasing. Besides, the order parameter of surfactant and water increased significantly. Comparing with the hydrophilic headgroup E, the order parameter of hydrophobic tail C increased more significantly. This indicated that isopropanol could weaken the hydrophobic interaction of surfactant by mainly inserting into the hydrophobic tails of surfactant. Fig. 7(b) showed the free energy density plots with time step for microemulsions S1 and S4. As shown, the |ΔG| value of S4 was higher than that of S1, indicating that the stability of microemulsion increased when the Km value increased from 1:1 to 3:1.
Fig. 7 (a) Order parameter plot of beads W, C and E with increasing time steps for microemulsion S1 and S4. (b) Free energy density plot with time step for microemulsions S1 and S4. |
Fig. 8 S1, S5 and S6 showed the morphologies of microemulsion formed by isopropanol, ethanol and 1,2-propanediol, respectively. All microemulsion were typical O/W microstructure. It was obviously found that the droplets size increased by the order of S1, S5 and S6. The MesoDyn predictions were consistent with the DLS results listed in Table 2. This indicated that the droplets size were dependent on the polarity of co-surfactant alcohol. In order to understand clearly the mechanism of alcohol as a co-surfactant, the density slices of beads E and C of microemulsion with different alcohols were obtained. As we can see from A1, A5, and A6 in Fig. 8, the distribution of alcohol molecules in microemulsion were obviously different. For microemulsion S1, isopropanol mainly dispersed in oil to improve the polarity of oil. Ethanol mainly dispersed into surfactant molecules to adjust the hydrophile–lipophile balance for microemulsion S5. For microemulsion S6, 1,2-propanediol mainly dispersed in water phase to reduce the polarity. The different distribution of alcohol molecules may be the reason why the droplets size of microemulsion changes.
Fig. 8 The E beads isosurface representations (S1, S5, S6), density slice of E (E1, E5, E6) and A (A1, A5, A6) for microemulsion with different alcohols: isopropanol, ethanol and 1,2-propanediol. |
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