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Effect of Monomeric Sequence on Mechanical Properties of P(VP-co-HEMA) Hydrogels at Low Hydration Seung Geol Lee,‡ Giuseppe F. Brunello,† Seung Soon Jang,*,† J. Hannah Lee,‡ and David G. Bucknall‡ School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0245, and School of Polymer, Textile and Fiber Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0295 ReceiVed: July 4, 2008; ReVised Manuscript ReceiVed: March 1, 2009
We have used molecular modeling of both random and blocky hydrogel networks of poly (N-vinyl-2pyrrolidone-co-2-hydroxyethyl methacrylate) with VP:HEMA ) 37:13 composition to investigate the effect of the monomeric sequence on the mechanical properties. The degrees of monomer sequence randomness for the random and the blocky copolymers were 1.170 and 0.104, respectively, and the degree of polymerization was set as 50. The equilibrated density of the dry gel network was 0.968 ( 0.007 and 0.911 ( 0.007 g/cm3 for the random and the blocky sequences, respectively. In the partially hydrated state with 10 wt % water content, the effect of the monomeric sequence causes more distinct differences in density of 1.004 ( 0.007 and 0.916 ( 0.009 g/cm3 for the random and the blocky copolymer network, respectively. We observed that in such networks, the water molecules are associated more closely with the N-vinyl-2-pyrrolidone than with the hydroxyethyl methacrylate moieties, which is consistent with results from quantum mechanical solvation free energy calculations. By simulating a compressive deformation of the dry gels up to 80% strain, we found that the random sequence network develops higher stress levels than the blocky network. We also found that stress reduction occurs in the random sequence network due to the hydration, which is not evident in the blocky sequence network. This difference in stress reduction between the random and the blocky sequence networks is due to the difference in the structural rearrangement of monomers in the presence of water during deformation. The random sequence network is able to undergo much more efficient rearrangement of HEMA units than in the blocky sequence network. 1. Introduction A hydrogel is a three-dimensionally cross-linked hydrophilic polymer network that can absorb and retain a large amount of water up to a thousand times its dry weight.1 Associated with this high degree of hydration, gels that are composed of bioinert or biocompatible polymers have therefore been studied intensively over the past 50 years as a promising biomaterial for medical and pharmaceutical applications, such as drug delivery and tissue engineering.2-7 Indeed, to comply with rapidly increasing demands in medical treatment and health care, a large variety of hydrogels have been made and tested so far on the basis of recent progresses in organic synthesis techniques that can realize exactly tailored molecular architectures according to the suggested design.3,8 Of the various hydrogels, we are particularly interested in the poly (N-vinyl-2-pyrrolidone-co-2-hydroxyethyl methacrylate) (P(VP-co-HEMA)), which is a network copolymer composed of varying proportions of VP and HEMA monomers (Figure 1). Although both PHEMA and PVP homopolymers have individually been used as biomedical materials for artificial skin,9,10 drug release,11-13 microcapsules,14 and DNA isolation,15 P(VP-co-HEMA) provides a way to control the properties of interest because PVP is more hydrophilic and therefore swells the most, but PHEMA has a higher mechanical strength.16-20 * To whom correspondence should be addressed. E-mail: seungsoon.jang@ mse.gatech.edu. † School of Materials Science and Engineering. ‡ School of Polymer, Textile and Fiber Engineering.
Figure 1. Chemical structures of VP, HEMA, poly(VP-co-HEMA), and MBA.
10.1021/jp8058867 CCC: $40.75 2009 American Chemical Society Published on Web 04/09/2009
Mechanical Properties of P(VP-co-HEMA) Hydrogels Thus, the hydrophilicity and swelling behavior of P(VP-coHEMA) hydrogel can be controlled as a function of VP:HEMA composition at various temperatures and pH conditions.16,17,19,21-28 Surprisingly, despite all of these intensive efforts on the P(VPco-HEMA) hydrogel, there has been no systematic study and therefore understanding of the effect of monomeric sequence on the properties of the hydrogel at a molecular level. In this study, our primary objective is to elucidate the effect of monomeric sequence on the mechanical properties of P(VPco-HEMA) hydrogel in its equilibrium state. The water content in these simulations was deliberately set relatively to only 10 wt %. At high water content (>∼40 wt %), the water molecules in the polymer network can form a percolated continuous phase and consequently tend to dominate the overall properties of the hydrogel. At low water content ( ∼1000). Considering the DP of our model chain is 50, which might be too small to meet true statistical requirements, consequently we intentionally designed the monomeric sequence to have two extremes (random and blocky sequences). It is assumed that the realistic sequence would lie somewhere between these two extremes. To form a three-dimensional network structure as shown in Figure 2c, we placed a cross-linker molecule (N,N′-methylenebisacrylamide (MBA)) at one end of each P(VP-co-HEMA) chain and then arranged all chains to participate in the network structure through periodic boundary conditions. Although experimental samples potentially have structural variations such as free dangling chain ends and self-looping,53 we assumed a perfect model network structure leaving no free dangling chain ends or self-loops. Here, it should be noticed that the topology of our model network is purely theoretical in terms of the number of chain ends at the cross-linking junction. Although the usual number of junctions in experiments involves 3-4 chain ends, we deliberately chose the current junction connecting 6 chain ends to build a three-dimensional grid structure, which
was used in the previous study.36,37 This is supposed to have an identical mechanical behavior along each axis direction. We think that the current theoretical topology is sufficient for the scope of our investigation regarding the effect of monomeric sequence between random and blocky sequence. Once the polymer network system has been constructed (Figure 2c), 110 water molecules were added to partially hydrate the system to an equivalent of 10 wt % water content. Starting from the initial structure (Figure 2c), the initial cell was gradually compressed to the target density, F0 ) 1.1 g/cm3, ahead of the annealing cycles. Energy minimization was performed to relax the stress on the chains during this compression procedure. In addition, to clarify the effect of water molecules on the properties of hydrogel, dry polymer network systems with 0 wt % water content were also constructed. Model Equilibration. It should be emphasized that generally the initial structures prepared by molecular mechanics have highly strained local configurations with unstable energies. However, the time scales for relaxation of polymers are very slow for standard equilibrium MD simulations to evolve to the equilibrium state. To obtain well equilibrated structures for complex amorphous polymers with a minimum of effort, we applied an annealing procedure that accelerates the equilibration by driving the system repeatedly through sequential thermal (between 300 and 600 K) and pressure (between densities of 0.5 and 1.1 times the expected density) annealing cycles. This
Mechanical Properties of P(VP-co-HEMA) Hydrogels
Figure 3. Equilibrated random poly(VP-co-HEMA) network with (a) 0 wt % of water content; (b) 10 wt % of water content; and equilibrated blocky poly(VP-co-HEMA) network with (c) 0 wt % of water content, (d) 10 wt % of water content. Blue, orange, and green colors denote VP, HEMA, and MBA, respectively. The oxygen of water molecule is enlarged 2 times to see its distribution clearly.
procedure aims to help the system quickly escape from various local minima and thereby efficiently reach an equilibrated structure. The steps in the annealing procedure are summarized next: (a) Starting from the initial structure, gradually expand the initial cell by 100% over a period of 30 ps while the temperature is simultaneously increased from 300 to 600 K. (b) Equilibrate at 600 K for 30 ps at a half-density of the original target density (F ) 0.5F0, F0 ) 1.1 g/cm3) using NVT MD. (c) Gradually compress the system back to the original target density over 30 ps while cooling the temperature to the target temperature (T ) 300 K). (d) Repeat steps (a)-(c) four times. (e) At the original target density, we equilibrate for 100 ps NVT MD at 300 K. (f) Finalize the equilibration by running a NPT MD for 10 ns at 1 atm and 300 K. During this step, the density of the system is optimized by changing the simulation cell parameters. This annealing equilibration procedure has been used successfully in the studies of polymer membrane for fuel cell39-41 to achieve equilibrated systems at the target temperature and pressure. After the building and equilibration steps described above were completed, data collection from all of the systems was obtained by running a 5 ns NPT MD simulation. 3. Results and Discussion 3.1. Equilibrated Structures. Density. The 3D structures from the final 5 ns NPT data collection MD simulations are shown in Figure 3. The spatial distribution of VP and HEMA monomers in the random and blocky structures is clearly different. As expected, the HEMA monomers (orange beads) are dispersed throughout the structure for the random P(VPco-HEMA), while in the blocky systems the HEMA clearly forms segregated domains. As shown in Table 1, the bulk density of the system also depends on the monomeric sequence, showing that the random sequence gel is ∼6% denser than the blocky sequence. This density difference is more distinct for
J. Phys. Chem. B, Vol. 113, No. 19, 2009 6607 the hydrated system with the random sequence hydrogel ∼10% denser than the equivalent blocky hydrogel. To investigate this density difference further, a 5 ns MD simulation was run for a single isolated P(VP-co-HEMA) chain in a vacuum for each monomeric sequence. Each simulated single chain has the same degree of polymerization (DP ) 50) and the same composition (VP:HEMA ) 37:13) as shown in Figure 2a and b. It was found that the root-mean-square radius of gyration of a single P(VP-co-HEMA) chain is 10.92 ( 0.33 Å for the random and 12.03 ( 0.08 Å for the blocky sequences, indicating that the blocky sequence chains have a larger dimension than the random sequence by ∼10%. This can be understood by considering steric interactions between the bulky branches made up from large blocks of HEMA (Figure 2b), which make the blocky sequence P(VP-co-HEMA) chains more expanded than those with random sequences. Therefore, the sequence-dependent chain dimension would be a reason for the density difference between the two monomeric sequences. Another potential source of this density difference is associated with the cross-linking. Figure 2c shows that all chain ends in our systems are tied up at the cross-linking point, a situation that does not change during either the long MD simulations or the severe annealing procedure. This means that once the crosslinking is established, the polymer network structure is topologically invariant, and any large-scale conformational relaxation is seriously restricted by this chemical cross-linking point. Therefore, it would be reasonable to expect that the restricted relaxation of sterically expanded chains in the blocky P(VPco-HEMA) network retards the efficient packing between chains and thereby results in lower density in comparison with the random P(VP-co-HEMA) network. Hydrophilicity of VP and HEMA. To quantify the difference in hydrophilicity between the VP and HEMA moieties, the quantum mechanical (QM) water solvation free energies were calculated using the Poisson-Boltzmann self-consistent reaction field model56,57 using B3LYP/6-31G** in Jaguar.58 The solvation free energy is defined as the energy required to move a specific molecule in a vacuum into a specific solvent medium. Consequently, a negative energy indicates that the solvation of the solute is favorable for that particular solvent.59,60 From these calculations (Figure 4), it was found that the solvation free energies of VP and HEMA monomers were similar to each other and equal to -7.60 and -7.56 kcal/mol for VP and HEMA, respectively. By contrast, the polymerized units have more favorable solvation free energies equal to -9.30 kcal/mol for PVP and -8.22 kcal/mol for PHEMA. The difference in hydrophilicity between VP and HEMA being more evident in the polymers as compared to in the monomers could be due to the high electron density at the double bond of monomer vinyl group reducing the polarity of the molecule, especially for the VP. These QM computations of water solvation free energies are consistent with the experimental observations,16-20 which show that PVP is more hydrophilic than PHEMA. Distribution of Water. Experimental studies using small-angle neutron scattering of in situ swelling of PVP-co-PMMA hydrogels have shown that the distribution of water in the early stages of swelling is nonuniform in the hydrated regions.61 This is thought to be due a nonuniform distribution of the two monomers, which have different hydrophilicity. To characterize the water distribution through such hydrophilic polymer networks, the pair correlation function of water with these monomers has been evaluated. The pair correlation function,
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TABLE 1: Characteristics of Hydrogels from 5 ns of NPT MD Simulations monomeric sequence
random VP ) 37 and HEMA ) 13 3 5804.16
mumber of monomers per chain number of chains per system cross-linking molecular weight, Mc degree of randomness
1.170
water content 3
density at 298 K (g/cm ) simulated cell size (Å) number of water molecules mesh size (ξ) (Å, simulation) elastic modulus (GPa) a
blocky
0.104
0 wt %
10 wt %
0 wt %
10 wt %
0.968 ( 0.007 31.30 ( 0.08 0 31.30 ( 0.08 5.32 ( 1.54 (6.48 ( 0.17)a
1.004 ( 0.007 32.03 ( 0.08 110 32.03 ( 0.08 4.44 ( 0.72 (6.06 ( 0.23)a
0.911 ( 0.007 31.94 ( 0.08 0 31.94 ( 0.08 4.05 ( 1.15 (5.75 ( 0.15)a
0.916 ( 0.009 33.02 ( 0.11 110 33.02 ( 0.11 3.49 ( 1.21 (5.45 ( 0.10)a
The values in the parentheses are obtained from the 8 times larger systems.
Figure 4. Quantum mechanical water solvation free energy of monomer and model molecule for segment in polymer using B3LYP/ 6-31G**.
gA-B(r), is the probability density of finding atoms A and B at a distance r (Figure 5a) averaged over the equilibrium trajectory as in eq 3.
gA-B(r) )
(
nB 2
4πr ∆r
)( ) /
NB V
(3)
where nB is the number of particle B located at the distance r in a shell of thickness ∆r from particle A, NB is the number of B particles in the system, and V is the total volume of the system. Using this pair correlation function, it is possible to determine in what environment the water molecules are located. Figure 5b shows the change of the pair correlation for the O (water) and N (VP) pair (gO(water)-N(VP)(r)), and the O (water) and C (HEMA) pair (gO(water)-C(HEMA)(r)). The C (HEMA) is the carbon directly attached to the backbone as shown in Figure 5a. To directly compare intensities, the product of the pair correlation and the number density (Fg(r)) is used instead of g(r). As shown in Figure 5b, the intensity of FgO(water)-N(VP)(r) is larger than that of FgO(water)-C(HEMA)(r), which means that the water molecules are more likely to be located closer to the VP moieties rather than the HEMA. For the system composition (VP:HEMA ) 37:13), with no difference in hydrophilicity between VP and HEMA, the probability that a water molecule is located next to a VP group is predicted to be ∼2.8 times larger than being next to HEMA. By integrating the first peak of the pair correlation function, the average number of VP units surrounding one water molecule is obtained, giving 1.20 and 1.10 for the random sequence and the blocky sequence,
Figure 5. Pair correlation function of water with the nitrogen (VP) and the carbon (HEMA): (a) the concept of pair correlation function; (b) the change of Fg(r) as a function of the distance between oxygen and another atom from our simulations. To directly compare intensities, the number density F was used for the nitrogen of VP and the carbon of HEMA, respectively.
respectively. These values are ∼5.7 times larger than that of HEMA (0.21 and 0.19 for the random sequence and the blocky sequence, respectively), and larger than the value of 2.8 based purely on the composition alone. These MD simulations describing the difference in hydrophilicity of the monomers are entirely consistent with the QM solvation free energy and the experimental observations. Another point of interest in Figure 5b is the effect of the monomeric sequence on the water distribution. The effect of
Mechanical Properties of P(VP-co-HEMA) Hydrogels
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Figure 7. Compression of hydrogels up to 80%: (a) random poly(VPco-HEMA) with 10 wt % water content; (b) blocky poly(VP-co-HEMA) with 10 wt % water content. We observed the same features from the compression of the dehydrated poly(VP-co-HEMA) network.
Figure 6. Pair correlation function (a) for the pair of N (VP) and N (VP) and (b) for the pair of C (HEMA) and C (HEMA).
monomeric sequence is distinctly seen in the second peak of the pair correlation function. However, that effect appears to be contradictory in that the FgO(water)-C(HEMA)(r) for the blocky sequence has more intensity than the random sequence, whereas the FgO(water)-N(VP)(r) of the blocky sequence has less intensity than that of the random sequence. To understand this observation, both of the pair correlations for the N (VP)-N (VP) pair (FgN(VP)-N(VP)(r)) and the C (HEMA)-C (HEMA) (FgC(HEMA)-C(HEMA)(r)) pair were analyzed. It is expected that the blocky sequence may have more intensity than the random sequence because the correlation between the same type of monomers should be stronger in the blocky sequence. As shown in Figure 6, this is indeed what is observed, with the blocky sequence having more intensity than the random one for both FgN(VP)-N(VP)(r) and FgC(HEMA)-C(HEMA)(r). Therefore, what we expect from these monomeric sequences is that if one water molecule is located in the network, the number of monomers surrounding the water molecule is larger in the blocky sequence because the same type of monomers has a higher population within close proximity. However, the FgO(water)-N(VP)(r) in Figure 5b behaves in the opposite way to the results in Figure 6. To understand this behavior, it is necessary to consider the packing of the monomers in the systems. As the monomers in the blocky sequence are close together, it is possible that the monomers segregate together to form their own phase in which a certain number of monomers are buried inside the phase. This possibility seems consistent with the observation in Figure 5b because those buried monomers are not available for contact with the water molecules
at these hydration levels. This explanation has been confirmed by checking the solvent accessible surface area (SASA) of the monomers. The calculated SASA values for the VP and HEMA in the random sequence hydrogel are 8905 ( 45 and 4557 ( 37 Å2, respectively, and 7590 ( 99 Å2 for VP and 3628 ( 32 Å2 for HEMA in the blocky sequence hydrogel, clearly indicating that both VP and HEMA segments have a smaller SASA in the blocky sequence as compared to the random sequence hydrogel. 3.2. Mechanical Properties. To assess the mechanical properties of the hydrogels, the hydrogels were deformed by uniaxial compression up to 80% strain over a period of 2 ns at 300 K. The initial and deformed structures for random and blocky sequence hydrogels in the presence of 10 wt % water content are shown in Figure 7. The deformation was performed by continuous application of strain of 4.0 × 10-5% per simulation step (1 fs) uniformly across the simulation box, in addition to rescaling all atom coordinates to the new box dimensions. The stress (σxx) was calculated from the uniaxial compression in the x-axis direction using the virial equation: N-1
σxx )
N
∑∑
1 V i)1
rx,ijfx,ij
(4)
j)i+1
where V, rx,ij, and fx,ij are the volume, the position vector between atom i and j (x component), and the force (x component) on the atom i exerted by j, respectively. The engineering strain is also represented by the following equation:
ε)
∆L L0
(5)
where ∆L and L0 are the deformed length and the original length of material, respectively. The y- and z-axes directional compressions were also carried out independently and averaged statistically. A reference system was simulated for comparison where there are no cross-links between the random P(VP-co-HEMA) chains, so that each chain can move freely without constraint. The differences between the reference and cross-linked random P(VP-co-HEMA) network are shown in Figure 8, where the dehydrated random sequence network has 2-3 times higher stress than the reference free chain system above 50-60% strain. Clearly, this enhanced mechanical strength of the random
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Figure 8. Change of stress as a function of strain.
sequence network is due to the cross-linking among the chains as normally observed in real systems,62 justifying the validity of our simulation protocol. Using the initial slope of the stress-strain curves, the elastic modulus (E) for each system was calculated. As summarized in Table 1, for the random sequence systems, E ) 5.32 ( 1.54 and 4.44 ( 0.72 GPa with 0 and 10 wt % water content, respectively. By comparison, for the blocky sequence systems, E ) 4.05 ( 1.15 GPa with 0 wt % water content and 3.49 ( 1.21 GPa for 10 wt % water content. Before doing the simulations, we expected that the presence of water reduces the elastic modulus in both network systems because the elastic energy in the system might be dissipated by water molecules during deformation at low stress levels. However, it turns out that the precision of our simulation was not high enough to see the difference due to the large standard deviation of our simulated values, even though the average values of elastic moduli obtained were in accordance with our expectation. Thus, we performed independent simulations using 8 times larger systems by making a superstructure of 2 × 2 × 2 of the originally equilibrated structure, giving E ) 6.48 ( 0.17 and 6.06 ( 0.23 GPa with 0 and 10 wt % water content, respectively, for the random sequence systems, while E ) 5.75 ( 0.15 and 5.45 ( 0.10 GPa with 0 and 10 wt % water content, respectively, for the blocky sequence systems. We believe that this result confirms the softening role of water in the amorphous polymeric network system. Although the pair correlation functions for larger system are identical to the given results in Figures 5 and 6 due to such nature of making a larger system, we also expect that our short-range structure analyses within 10 Å such as pair correlation of monomers and water molecules are not significantly affected by the finite size effect because usually the finite size effects are shown from the long-range correlation phenomena. The random sequence system is shown to have a higher stress level than the blocky one in the dry state (see Figure 8), which is clearly distinct at greater than 60% strain. Because the density is one of the primary factors affecting the mechanical properties of the condensed matter, our simulated stress-strain curves present a common behavior of the material, which is that more dense random sequence material is mechanically stronger than less dense blocky material as discussed in the previous section above. However, the density of the partially hydrated system is not directly compared to that of the dehydrated system because
Figure 9. Strain dependency of pair correlation function. FgN(VP)-N(VP)(r): (a) the random sequence and (b) the blocky sequence. FgC(HEMA)-C(HEMA)(r): (c) the random sequence and (d) the blocky sequence. The left-hand side is for 0 wt % water content, and the righthand side is for 10 wt % water content. The blue, cyan, magenta, and red colors denote the deformation of 0-20%, 20-40%, 40-60%, and 60-80% of strain, respectively.
the hydrated material phase has heterogeneous features and the water regions in the system retain liquid-phase characteristics. The stress of the dehydrated random sequence network is higher than the hydrated random one (see Figure 8). By contrast, the stress in blocky sequence material does not depend on hydration. These results have been analyzed through the change of FgN(VP)-N(VP)(r) and FgC(HEMA)-C(HEMA)(r) during the deformation. For this, we segmentized the entire 2 ns long MD simulation trajectory file into four 500 ps long trajectory files and then calculated the pair correlation functions from each segmental trajectory file. Because the total strain during the 2 ns MD simulation was 80%, each partition with 500 ps of length corresponds to 20% of strain. As shown in Figure 9a and b, all FgN(VP)-N(VP)(r) undergo a similar change during the compressive deformation. The first peak increases in intensity, while the second peak decreases in intensity. The growth of the first peak is thought to be due to the structural packing in the compression direction, while the reduction of the second peak is due to the increasing dimension of the structure perpendicular to the compression direction. This indicates that the structures of the polymer networks experience dynamic rearrangement as the deformation proceeds. By contrast, the FgC(HEMA)-C(HEMA)(r) shows different behavior depending on the monomeric sequence (see Figure 9c), where the first peak of the FgC(HEMA)-C(HEMA)(r) curves for the hydrated random sequence decreases significantly in comparison with that of the dehydrated random sequence. On the other hand, the
Mechanical Properties of P(VP-co-HEMA) Hydrogels FgC(HEMA)-C(HEMA)(r) of the blocky sequence (Figure 9d) does not seem to change during the compressive deformation either with or without water. These different features of the pair correlation functions are in good agreement with the stress-strain behavior (Figure 8). In general, when materials deform due to an external stress, the structures of the materials change in response to the stress buildup due to the deformation, and thereby the stress in the material can be resolved to become smaller. With respect to the structural relaxation, the VP monomers for both monomeric sequences are deformed regardless of the presence of water. However, the HEMA monomers clearly show sequence-dependent rearrangement unlike the VP. For the hydrated random sequence system (Figure 9c), the reduction in the first peak intensity during the deformation is thought to be due to structural relaxation among the nearest neighboring monomers, which are very critical to the reduction of the stress in compressive deformation. It is inferred that the water molecules play an important role as lubricants between the HEMA monomers and promote their structural rearrangement. As noted in the stress behavior of the system in Figure 8, this inference seems consistent with the observation that the hydrated random sequence has lower stress than the dehydrated random one. On the other hand, such a relaxation of the nearest neighboring HEMA monomers is not observed from the FgC(HEMA)-C(HEMA)(r) for the blocky sequence system in Figure 9d, where the curves are very similar for both systems with and without water. This means that the HEMA monomeric units in the blocky sequence do not undergo structural relaxation as effectively in response to the deformation. Indeed, this result is directly reflected in its mechanical property, whereby the stress level of the hydrated blocky sequence is comparable to the dehydrated blocky one regardless of water content. Therefore, it can be concluded from our simulations that the monomeric sequence determines the distribution and structural relaxation of HEMA monomers, which in turn affects the mechanical properties of the system. Although the present study focuses on a low level of hydration of the polymer network, further work is addressing increased hydration levels, as well as different comonomer compositions and network topology. 4. Conclusions Poly (N-vinyl-2-pyrrolidone-co-2-hydroxyethyl methacrylate) network structures have been simulated using atomistic MD modeling with 0 and 10 wt % water content. The effect of monomeric sequence of the constituent copolymer chains has been investigated with random and blocky VP-HEMA sequences, and degrees of randomness are 1.170 and 0.104, respectively. From the equilibrated models, it is observed that both with and without water, the random sequence network is denser than that of the blocky sequence system. This sequence-dependent density of the P(VP-co-HEMA) is thought to be due to the difference in expansion of chain conformation and restricted conformational relaxation. Using quantum mechanical computation with B3LYP and 6-31G**, the solvation free energies of VP and HEMA were determined, which showed that water solvation of VP is more favorable than that of HEMA, and this confirms that VP is more hydrophilic than HEMA. In addition, from 5 ns MD simulations, and resulting analysis of the pair correlation functions, the water molecules in the network are shown to have a greater tendency to be in the vicinity of VP rather than HEMA, confirming the greater hydrophilicity of the VP as compared to that of HEMA.
J. Phys. Chem. B, Vol. 113, No. 19, 2009 6611 The compressive deformation of P(VP-co-HEMA) networks has been simulated in the absence or presence of water. The dehydrated systems have larger calculated moduli than does the comparative hydrated system for both monomeric sequences. The simulated stress-strain curves were obtained up to 80% strain, showing that in the dehydrated state, the random sequence has higher stress levels than does the blocky one. This difference in stress level is most probably related to the different monomeric sequence-dependent densities of the systems. On the other hand, for the hydrated networks with 10 wt % water content, the stress of the random sequence was seen to be reduced in comparison to the dehydrated system. By contrast, the blocky sequence system shows no change in stress between the dry and hydrated system. By analyzing the pair correlation between monomeric units, it was shown that the HEMA monomers in the random sequence rearrange more efficiently during the compressive deformation in the presence of water molecules, whereas such structural rearrangements are not observed in the blocky sequence under the same condition. Therefore, it is believed that the stress reduction behavior observed in the random sequence system is consistent with the structural change the HEMA monomers in the random sequence undergo. From this study focusing at a low level of hydration, it was found that the properties of the P(VP-co-HEMA) such as density and mechanical strength are directly affected by the monomeric sequence of copolymer. References and Notes (1) Lowman, A. M.; Peppas, N. A. Hydrogels. In Encyclopedia of Controlled Drug DeliVery; Mathiowitz, E., Ed.; John Wiley & Sons: New York, 1999; Vol. 2, p 397. (2) Peppas, N. A. Curr. Opin. Colloid Interface Sci. 1997, 2, 531. (3) Peppas, N. A.; Huang, Y.; Torres-Lugo, M.; Ward, J. H.; Zhang, J. Annu. ReV. Biomed. Eng. 2000, 2, 9. (4) Lee, K. Y.; Mooney, D. J. Chem. ReV. 2001, 101, 1869. (5) Byrne, M. E.; Park, K.; Peppas, N. A. AdV. Drug DeliVery ReV. 2002, 54, 149. (6) Langer, R.; Peppas, N. A. AIChE J. 2003, 49, 2990. (7) Langer, R.; Tirrell, D. A. Nature (London) 2004, 428, 487. (8) Tanaka, Y.; Gong, J. P.; Osada, Y. Prog. Polym. Sci. 2005, 30, 1. (9) Young, C. D.; Wu, J. R.; Tsou, T. L. J. Membr. Sci. 1998, 146, 83. (10) Young, C. D.; Wu, J. R.; Tsou, T. L. Biomaterials 1998, 19, 1745. (11) Trigo, R. M.; Blanco, M. D.; Huerta, P.; Olmo, R.; Teijon, J. M. Polym. Bull. 1993, 31, 577. (12) Gokce, M.; Akata, R. F.; KiremitciGumusderelioglu, M. Biomaterials 1996, 17, 941. (13) KiremitciGumusderelioglu, M.; Gokce, M.; Akata, R. F. J. Biomater. Sci., Polym. Ed. 1996, 7, 857. (14) Hwang, J. R.; Sefton, M. V. J. Membr. Sci. 1995, 108, 257. (15) Kim, C. S.; Lee, C. H.; Shin, J. S.; Chung, Y. S.; Hyung, N. I. Nucleic Acids Res. 1997, 25, 1085. (16) Hong, Y.; Chirila, T. V.; Cuypers, M. J. H.; Constable, I. J. J. Biomater. Appl. 1996, 11, 135. (17) Blanco, M. D.; Trigo, R. M.; Garcia, O.; Teijon, J. M. J. Biomater. Sci., Polym. Ed. 1997, 8, 709. (18) Davis, T. P.; Huglin, M. B. Makromol. Chem., Rapid Commun. 1988, 9, 39. (19) Davis, T. P.; Huglin, M. B. Macromolecules 1989, 22, 2824. (20) Mabilleau, G.; Aguado, E.; Stancu, I. C.; Cincu, C.; Basle, M. E.; Chappard, D. Biomaterials 2008, 29, 1593. (21) Cifuentes, A.; Diez-Masa, J. C.; Montenegro, C.; Rebuelta, M.; Gallardo, A.; Elvira, C.; San Roman, J. J. Biomater. Sci., Polym. Ed. 2000, 11, 993. (22) Gallardo, A.; Fernandez, F.; Bermejo, P.; Rebuelta, M.; Cifuentes, A.; Diez-Masa, J. C.; San Roman, J. Biomaterials 2000, 21, 915. (23) Gallardo, A.; Fernandez, F.; Cifuentes, A.; Diez-Masa, J. C.; Bermejo, P.; Rebuelta, M.; Lopez-Bravo, A.; Roman, J. S. J. Controlled Release 2001, 72, 1. (24) Alissa, M. A.; Davis, T. P.; Huglin, M. B.; Rego, J. M.; Rehab, M. M. A. M.; Yip, D. C. F.; Zakaria, M. B. Makromol. Chem., Macromol. Chem. Phys. 1990, 191, 321. (25) Gallardo, A.; Lemus, A. R.; Roman, J. S.; Cifuentes, A.; DiezMasa, J. C. Macromolecules 1999, 32, 610.
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