Poly(acrylic acid) Mixed

Article pubs.acs.org/Macromolecules

Functional Poly(N‑isopropylacrylamide)/Poly(acrylic acid) Mixed Brushes for Controlled Manipulation of Nanoparticles Fabien Léonforte* and Marcus Müller Institut für Theoretische Physik, Georg-August-Universität, Friedrich-Hund-Platz 1, 37077 Göttingen, Germany S Supporting Information *

ABSTRACT: Molecular dynamics simulations of a coarse-grained model with soft, nonbonded interactions and implicit solvent are used to study the temperature- and pHsensitive response of mixed brushes composed of poly(N-isopropylacrylamide) [PNIPAm] and poly(acrylic acid) [PAA] polymers. The model is developed in order to address experimentally relevant, large invariant degrees of polymerization, and nonbonded interactions are expressed via a third-order virial expansion of the equation of state. The choice of interaction parameters for PNIPAm mimics the swelling behavior in water as the temperature increases toward the lower critical solution temperature, TLCST, and the model captures the pH-dependent response of PAA at fixed ionic strength (IS). For this case, the solvent-mediated Flory−Huggins parameter is adapted to reproduce the experimental pH swelling of the homopolymer brush. Mixed brushes incorporating various amounts of PAA are considered, and the effect of mixing polymers on the response of the mixed brushes to both temperature and pH changes is discussed. Additionally, nanoparticles (NPs) that preferably interact with the PAA portion of the polymers are considered. As a function of their radius and the size of the functional NP-attractive groups on PAA chains, the capability to capture NP and allow them to penetrate inside brushes is studied at various temperatures and fixed pH. Moreover, the kinetics of adsorption and release of NPs is investigated.

1. INTRODUCTION Polyelectrolyte brushes are promising candidates for immobilizing biophysical objects like cells or proteins1,2 as well as reactive ligands to locally tune friction and adhesion.3−7 They find applications in controlled release for drug delivery8−11 because they demonstrate significant variations in swelling as a function of pH and ionic strength (IS). For instance, poly(acrylic acid) [PAA]-based polymer brushes depict welladapted properties12 for biological purpose13−21 and/or modulate biofluid adsorption/desorption when mixed with tunable hydrophobic polymers.22−24 Combined with a polymer that exhibits temperature-dependent conformations, like poly(N-isopropylacrylamide) [PNIPAm], it has been shown that the resulting mixed, multiresponsive PNIPAm/PAA brushes exhibit complex and intricate pH-, ionic strength [IS]-, and temperature-sensitive swelling behavior25−27 that can be tailored by varying compositions, grafting density, and molecular weights of the species. PNIPAm molecules exhibit a lower critical solution temperature, TLCST ≈ 32 °C, below which the polymers are hydrophilic and above which they become hydrophobic.28−30 In particular, PAA added to PNIPAm brushes was shown to decrease the temperature sensitivity of the pure PNIPAm system. Conversely, adding PNIPAm to a pure PAA brush, one amplifies the IS and pH dependence of the resulting mixed brush.25,31 One of the possible applications of multiresponsive polymer brushes also appears in the field of nano-biotechnologies when combined with nanoparticles (NPs). In particular, they provide © XXXX American Chemical Society

a versatile platform to influence, select, and tune the uptake/ release of nanoparticles,32−36 with potential applications in dusty flow regeneration or regenerative medicine.37 Furthermore, the nanocomposite can be of practical interests in the fields of biosensors and actuators38−47 and can be used as hosting matrices to immobilize NPs. In that case, the choice of specific NPs could be useful to confer to the resulting material some particular optical, magnetic, and mechanical properties. Whereas such systems clearly need to be investigated, their complex environment-triggered response is difficult to model from a simulation point of view. In particular, accounting for the pH-dependent dissociation of the acid groups of the PAA components without explicitly including the solvent and electrostatics in the simulations, i.e., keeping computational efficiency by avoiding atomistic details and address experimentally accessible time and length scales, is a complex task. Despite recent progress using self-consistent field (SCF) theory48−55 and in the context of molecular mean-field theory56−59 and hybrid liquid-state theories,60−62 the difficulty to address systems with realistic invariant degrees of polymerization, spatial heterogeneities, and composition fluctuations still remains a challenge, and one often resorts to simplified, computationally efficient models that only describe the most relevant properties of the responsive polymers. Received: March 16, 2016 Revised: June 29, 2016

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DOI: 10.1021/acs.macromol.6b00535 Macromolecules XXXX, XXX, XXX−XXX

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polymerization N̅ ≈ 3000. The PAA polymers are discretized into NCG = 197 segments, whereas we segment PNIPAm A polymers of mass Mw(B) = 94K into NCG B = 123 interaction centers. Such a choice for the polymer weights have been shown to provide an optimal switching window between both species that may also allow for a cushion effect of the stimulated, switchable, polymer in regard to the complementary component.26,67 With this discretization, the statistical segment lengths of both polymers are identical, b = 0.77 nm. The lateral dimension of the simulation box is L∥ ≈ 90 nm. In our implicit-solvent model the quality of the solvent is encoded through the choice of the solvent-mediated interaction coefficients discussed in the Supporting Information. For PNIPAm polymers, they qualitatively reproduce the thermal response in an aqueous environment with a transition temperature TLCST ∼ 32 °C that marks the border between good and poor solvent conditions as T increases. In ref 64 PNIPAm homopolymer brushes have been studied in such a formalism, using an empirical model developed by Afroze et al.,68 and it was shown that the formalism succeeds in reproducing the experimentally observed, temperature-sensitive swelling behavior of brushes with different grafting densities, molecular weights, and polydispersity index. The same model will be employed in the following. In the case of PAA brushes, we require our model to reproduce the experimental pH-swelling behavior of a polymer brush with the same mass, polydispersity index PDI ∼ 1.1, and grafting density σ ≃ 0.2 nm−2. For this purpose, the average height, ⟨H⟩, of the brush in the simulations is defined by the first moment of the number density profiles ρ(r⊥) = L∥−2∫ dr∥ ρ(r∥,r⊥), namely ⟨H⟩ ≡ 2∫ r⊥ρ(r⊥) dr⊥/∫ ρ(r⊥) dr⊥, where the factor 2 ensures that ⟨H⟩ reduces to the layer thickness for a steplike density profile. In Figure 1, we plot the pH-dependent brush thickness obtained from null-ellipsometry measurements.66 It serves as reference data for the model parametrization. In the simulation the average brush height, ⟨H⟩, results from the effective pH-/ IS-dependent interaction of the brush with the implicit solvent. Using the formalism developed in the Supporting Information,

In previous studies,63,64 we have developed an implicitsolvent, particle-based model in the context of multiparticle dissipative particle dynamics that can efficiently capture, for instance, the temperature-induced swelling of PNIPAm polymers as well as solvent-quality effects through a thirdorder virial expansion of the equation-of-state of the polymers. In particular, this model allows us to reproduce the pH- and ISdependent quality of the solvent that acts on PAA-based brushes through the definition of effective Flory−Huggins compatibility parameters, χ. The aim of such a mapping is to devise a computationally efficient model that allows us to study biocompatible and multiresponsive mixed PNIPAm/PAA brush in contact with NPs of different sizes to select and optimize their uptake/ release under physiological-like environmental conditions. Under these conditions, PAA polymers are quasi-fully deprotonated and the resulting pure PAA-based brush in a swollen state. Given the protein-repellent nature of PNIPAm, a promising strategy to trigger a controlled uptake/release is to assign to PAA polymers the ability to capture NPs (through “functionalized” groups, E, that could either mimic fractions of undissociated sites, hydrophobic or chemically modified groups) whereas, in turn, the temperature-dependent conformations of PNIPAm polymers will control the release of NPs. Therefore, a suitable protocol for this system consists in capturing NPs at temperature T > TLCST and triggering their release by decreasing T. Our paper is organized as follows. In section 2, we provide details about the numerical modeling of responsive polymers and, in section 3, we study the multiresponsive properties of PNIPAm/PAA mixed brush at fixed grafting density and molecular weights. We vary the composition ratio f p of the species, the temperature and effective pH value, which will alter the solvent quality and the morphologies of the microphaseseparated structure of the mixed brush.63,65 In the following section 4.1, we incorporate NPs in our model and define their interactions with the polymer species. In section 4.2 we investigate how the size of the adsorbed NPs influences the morphology of a symmetric mixed brush. Section 4.3 describes the effect of varying the length η of the functional groups E on the dynamics of uptake and release of NPs. A brief summary in section 5 concludes the paper.

2. MODEL AND TECHNIQUE We employ an implicit-solvent, coarse-grained model with soft interactions in three-dimensional space. There are Gaussian polymer chains of type A (PAA) and type B (PNIPAm) exposed to solvent S. The mixed brushes are composed of n = ∑α=A,Bnα chains, where the molecular contour of a polymer chain is represented by Nα effective interaction centers (segments). We define the fraction of α-polymers in the mixed brush as fα = nα/n and ϕα = Nα/N̅ denotes the ratio of the chain lengths of species α to the reference chain length N̅ used in the model. The polymer chains are irreversibly, randomly, grafted to a hard, impenetrable substrate located at z = 0. Further details about the model and simulation technique are detailed in the Supporting Information. In order to relate the coarse-grained model to a specific polymer, one must account for the conformational differences between the PNIPAm and PAA compounds. Details about the method are given in ref 64 and summarized in the Supporting Information. In the following, we consider PAA polymers of mass Mw(A) = 57K, corresponding to an invariant degree of

Figure 1. Swelling of a polyanionic PAA brush of grafting density 0.2 nm−2 and ionic strength 0.001 M as a function of the bulk pH value. The mass of the polymer is Mw = 57K. Null-ellipsometry measurements66 serve as reference data, to which we match average height in our simulations by adapting the solvent-mediated Flory− Huggins parameter (cf. inset). B


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Figure 2. Top and side views of morphologies of PNIPAm/PAA mixed brushes with grafting density 0.2 nm−2. PNIPAm polymers are depicted in red and PAA in yellow. The fraction f p of PNIPAm varies between f p = 0.2, i.e. 20/80 mixed brush, f p = 0.5, and f p = 0.8. For each system, morphologies at T = 27 °C < TLCST and T = 57 °C > TLCST are presented, and the pH value also varies from low (collapsed PAA chains) and to high (good solvent for PAA).

Figure 3. Dependence of the height of each species on pH and temperature for a mixed PNIPAm/PAA brush with grafting density 0.2 nm−2 and different PNIPAm fractions, f p. Lines with symbols correspond to PAA and full lines to PNIPAm, whereas the dashed line depicts the height of a pure PAA brush (as shown in Figure 1).

we find the best value of χα(S) that minimizes the difference between experimentally observed brush thickness and the simulation data. The resulting Flory−Huggins parameters for salt concentration cs = 0.001 M is plotted in the inset of Figure 1.

and pH = 7, S(+ −) to T = 57 °C and pH = 7, S(− +) to T = 27 °C and pH = 4, and finally S(− −) to T = 57 °C and pH = 4. Because of the weak selectivity of S(+ +), both species are swollen, the solvent being slightly better for PAA than for PNIPAm. Laterally microphase-separated structures65 are formed that depend on the fraction f p. For small and large f p, dimples of the minority species emerge in a matrix formed by the majority species, whereas for a symmetric brush with f p = 0.5, bicontinuous ripples are preferentially formed. When the temperature increases, the solvent is still good for PAA but poor for PNIPAm. The selectivity of the solvent S(+ −) gives rise to similar lateral phase separation as the case of S(+ +), except that the bad solvent conditions for PNIPAms favor their collapse, and the dimples and ripples are more defined and located in the bottom half of the brush. Then, decreasing the pH value at this fixed temperature leads to a collapse of both species in a weakly selective, bad solvent S(− −). The latter is slightly better for PNIPAm; hence, increasing f p gives rise to dimple morphologies of PNIPAm in a PAA matrix, ripples, and finally dimples of PAA in a PNIPAm matrix. The final decrease of T at fixed pH = 4 leads to a large selectivity of the S(− +)

3. SWELLING BEHAVIOR OF THE MIXED BRUSH Our phenomenological approach presented in section 2 is well suited to investigate PNIPAm/PAA brushes because the pKa of PNIPAm is relatively high (∼11.3) and will not interfere, in the pH range of our study, with the IS-dependent dissociation of the weak polyelectrolyte PAA. In the following, we consider systems with increasing amount f p = {0.2; 0.5; 0.8} of PNIPAm that are added to the PAA brush. In the first part of this study, the total grafting density is fixed to 0.2 nm−2. Figure 2 shows top and side views of the different morphologies of the brushes as a function of the PNIPAm fraction f p. We denote the solvent quality by the abbreviation S(αβ), where α ≡ + (−) and β ≡ + (−) indicate good (bad) solvent conditions for PAA and PNIPAm, respectively. Specifically, S(+ +) corresponds to a temperature T = 27 °C C


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PNIPAm/PAA mixed brushes provide a suitable platform. We pointed out that a convenient strategy consists in capturing external nanoparticles at high temperature through ”functionalized” groups E of the PAA polymers (with a fixed length η) and to cool down the system toward the TLCST of PNIPAm to engage a release. This strategy, however, requires the understanding of a variety of different mechanisms. The overarching goal is to (1) estimate to which extent PAA molecules, through their modified ends E, can select nanoparticles of a specific size, (2) allow them to penetrate the brush at minimal cost upon decrease of temperature, and (3) optimize the release of the nanoparticles by tuning the competitive interactions between components of the brush via tailoring η. 4.1. Modeling of the NPs and Their Interactions in the Brush. In our effective-medium approach, the Flory−Huggins coefficients for PAA are assumed to reflect the behavior of the largely deprotonated polymers at pH ∼ 7.4. The functional groups E of length η that may capture NPs under such environmental conditions can therefore be conceived either as a small remaining amount of undissociated sites along the polymer backbones (in conjunction with NPs modified by chemical reduction of adequate redox couple40) or, more generally, as chemical anchors that may preferentially interact with the targeted objects.39,77−79 In our simplified and generic approach we assume the chemical integrity of the PAA polymers unaltered by the functional groups. We consider functional ends E of length η located at the top, nongrafted end of the PAA polymers, which physisorb onto the surface of NPs. These functional groups can participate in the capture of more than one NP. On the other hand, we consider NPs that are repelled by the other species (PNIPAm and nonfunctional blocks of PAA), and we define the interaction of the NPs with the different species by the distance-dependent potential80,81

solvent in favor of highly swollen PNIPAm polymers. PAA polymers are collapsed and shielded from the aqueous solvent by PNIPAms, which leads to a preferred vertical segregation that is coupled to a lateral one when f p varies. For small values, a dense PAA layer covers the bare substrate, whereas dimples of PAA in the PNIPAm matrix will form for high f p. Figure 3 presents the heights of each species as a function of the thermodynamic control parameters (pH, T) and for different brush compositions f p. The swelling of PNIPAm and PAA appears to strongly depend on the behavior of the other species. At low temperature, an increase of the swelling of PAA toward the pure system can be observed for high f p. This trend vanishes for small amount of PNIPAm. One also notes a shift of the pH, at which the PAA height reaches its plateau, toward larger values when f p decreases. Such a behavior was reported by Bittrich et al.25 and was attributed to the increase of the degree of deprotonation of PAA’s acid groups which, concomitantly to the preferential hydrogen-bonding interaction of PNIPAm with water, avoids interactions with amide groups of PNIPAm via hydrogen bonds. In our simulation model, however, deprotonation and hydrogen bonding are not explicitly taken into account. Nevertheless, the virial coefficients vAA and vBB of the pure species A and B aim to capture the effects related to the solvent (dissociation reaction of COOH groups for PAA and evolution of the solubility for PNIPAM due to the hydrogen bonding of amine groups). The additional term in the case of the mixture stems from the mixed secondorder virial coefficient vAB. As discussed in the Supporting Information, we assume a simple mixing rule that uses the Hildebrandt solubility parameters of each species. The mixed virial coefficient is therefore representative of their polarizalibility mediated by the solvent quality. Despite its apparent simplicity, our model seems to capture, in an effective way, the complexation of both species via hydrogen bonds69 outside the salted brush (SB) regime of the weak polyelectrolyte, i.e., below cs ≪ 0.1 M. (In the SB regime, additional contribution of salt bridges to the complexation of both species could be expected.70−76) Finally, when the temperature decreases, we observe that the fraction f p seems to influence the pHdependent swelling of PAA. For small f p, it depends both on the pH and on the temperature. This trend disappears upon decreasing f p. Additionally, the amount of PAA strongly alters the temperature dependence of PNIPAm conformations. In Figure 3c we find for low pH values, i.e., when PAA polymers are collapsed, a smaller variation of the height of PNIPAms with increase of T than in Figure 3a. This observation indicates a shift of the TLCST toward lower temperatures. Furthermore, a peak in the PNIPAms height appears in the pH-induced switching region of PAA that is broader for T < TLCST than for T ≥ TLCST. Because this peak is also present at high temperature, where PNIPAm is hydrophobic, it cannot be attributed to a solvent-penetration effect triggered by the swelling of PAA but rather arises from the fact that PAA molecules themselves provide better effective solvent conditions to PNIPAm molecules. This intricate effect is again a consequence of the peculiar hydrogen-bond-mediated interactions.

⎧ Λ −(r − R )2 /2d 2 p p , for R p < r < rc ⎪ e ⎪ dp ⎪ Unp(r ) = ⎨ kn 2 for r < R p ⎪ δn ⃗ , ⎪2 ⎪ 0, otherwise ⎩

(1)

where Rp is the core radius of the NP, δ is the overlap distance between the two interacting particles, and n⃗ is the unit vector along the line connecting their centers. In the following, we set |Λ| = 2.0, dp = bCG (see the Supporting Information), rc = 1.5dp, and kn ≡ 1.0. A sketch of the interaction scheme is depicted in Figure 4 where we illustrate the selective interactions of NPs with the polymer species through the sign of the interaction strength, Λ. NPs repel each other. Additionally, we emphasize that the “functionalized” groups E of the PAA polymers interact with the PNIPAm chains in the same way as the “nonfunctionalized” parts of the PAA segments do. Furthermore, for the sake of not introducing additional parameters, we reduce the complexity of the system by assuming that the E-units interact like A−A monomers even thought they behave differently with NPs. In the following, we only consider 50/50 mixed brushes of grafting density σ = 0.1 nm−2 at T = 37 and 57 °C. The same fitting procedure as illustrated in Figure 1 has been applied for the PAA brush at this grafting density to identify the interaction parameters. The systems are prepared such that initially, at t = 0, NPs are randomly distributed within a slab above the top of the brush;

4. ABSORPTION AND RELEASE OF NANOPARTICLES Next, we aim to design a strategy that (i) optimizes the uptake of nanoparticles of defined sizes and (ii) controls their release under external stimuli. As already mentioned in section 1, D


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4.2. Adsorption of NPs and Its Effect on the Brush Morphologies. One of the questions that arises from the inclusion of NPs in polymer-coated surfaces is their impact on the physical properties of the surface. For instance, early theoretical work82 based on free energy considerations of Alexander−de Gennes polymer brushes in contact with surfactants has shown that in the case of mixed solvent the brush height makes a discontinuous jump as the adsorption energy of the surfactants is varied; i.e., at a critical value of adsorption energy, it becomes energetically favorable to increase the brush height in order to adsorb more surfactants, while still keeping them sufficiently separated. Further investigations using self-consistent-field (SCF) theory83 conceived sufficiently small NPs as constituents of the solvent. In this context SCF theory could demonstrate discontinuities in the monomer density profiles and micelles that form in the upper region of the brush. The insertion of nanoinclusions of different shapes and sizes in a brush has been studied by a simplified SCF theory,84 and it was shown that small inclusions are able to totally penetrate and stay inside the brush, whereas for large nanoparticles, penetration was hindered and rejection will occur if the NP size is greater than the height-dependent blob size of the polymers in the brush. Additional studies investigated the effect of the size of the NPs on the adsorption and stability of inclusions85,86 or physical properties of the brush.87 Homopolymer brushes are often considered, and only recently SCF theory studied mixed responsive brushes, showing that a smart functional polymer−NP composite platform can be achieved by optimizing the brush design (e.g., grafting density, molecular weight) for the size and shape of the nanoparticles.88 In order to evaluate this capability, one first has to quantify the effect of the NPs on the postadsorption morphologies in equilibrium. This is presented in Figure 5 where we compile results from simulations of different systems. We plot snapshots of the top views of the brushes for two different lengths η of the functional groups and two different sizes Rp of the NPs. We compare the morphologies before and after adsorption, and for

Figure 4. Sketch of the interaction of NPs with the brush polymer species. A NP interacts with the other species using the potential defined in eq 1 where the parameter Λ provides the sign of interaction: (+) for attraction and (−) for repulsion. PNIPAm polymers are drawn in blue, PAA in yellow, and the functional groups E in red. The sketch mimics a functional E-groups of length η = 0.25.

i.e., NPs are dispersed in the solution. We considered three systems that differ in the sizes of the NPs, namely NPs of radius Rp = 0.8, 1.6, and 3.2 nm. In the first case, their size is smaller than the characteristic size of the brush morphologies (approximately 4 nm), whereas in the second and third cases, they become comparable or exceed the characteristic size, respectively. For each system, the adsorption process is observed during simulation runs over a period of 500τ− 2000τ, in which all NPs have been captured.

Figure 5. Top and three-dimensional views of the morphologies of mixed PNIPAm/PAA brushes of composition ratio f p = 0.5 before and after adsorption of NPs with different sizes. The length of the functional ends of the PAA polymers decreases from (a) η = 0.375 to (b) η = 0.125. The color code is the same as in Figure 4. E


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Macromolecules brushes at temperature T = 57 °C, well above the TLCST, and in its vicinity, T = 37 °C. In both cases and for all η, we observe in Figure 5 that for the smallest NPs with Rp = 1.6 nm, no significant changes in the structure of the brush’s top occur, whereas strong variations at the top of the brush are observed for NPs of sizes Rp = 3.2 nm. In particular, the brush structure can be drastically modified when the length η of the functional groups E is too short compared to the size of the NP, leading to a strong deformation of the PAA groups, highlighting the interplay between both entities. The concomitant effect of NP sizes and length η of the functional E groups also impacts the ability of the NPs to penetrate the brush. In Figure 6 we plot the difference between

highlights the encapsulation effect provided by the functional E groups that allows large NPs to penetrate the brush but, in turn, strongly modifies the structure of the brush. 4.3. Dynamics of Uptake and Release. Section 4.2 has investigated the role of η to facilitate NPs adsorption and inclusion through the encapsulation mechanism. In the following, we study its role on the kinetics of uptake and release. As previously, the systems are prepared such that at t = 0 the NPs are randomly placed in a slab slightly above the brush and are free to diffuse in the solution. In the main panels of Figures 7a and 7b, we plot the time evolution of the average height of NPs of different sizes at T ∼ TLCST and for large and small functional group lengths, i.e., η = 0.375 and η = 0.125, respectively. This quantity characterizes the ability of the brush to uptake NPs. In the corresponding insets, the same quantity is plotted at higher T ≫ TLCST. In the upper right insets of Figures 7a and 7b, we complement this * , at which the static information by the characteristic time tads average height of the NPs becomes smaller than the average height of the brush. These plots demonstrate that large functional ends enhance the uptake with a more pronounced efficiency at lower temperature when the size of the NPs is the smallest (i.e., small compared to the intrinsic lateral length scale * (T = 57 °C) of the morphologies); the deviation between tads * (T = 37 °C) at Rp = 0.8 nm and η = 0.375 is larger than and tads the one with η = 0.125. This effect could be attributed to the role of PNIPAm molecules that provide an additional (repulsive) guidance when NPs reach the top layer of the brush, i.e., at the lowest T, and direct the surface motion of NPs.89 For smaller “functionalized” block-end ratios, the situation is different: surface mobility effects can be strongly enhanced because, as the encapsulation effect is weaker, capturing NPs of small sizes becomes more difficult than for large sizes. The encapsulation effect can provide a flexible and wellsuited way to facilitate the capture and penetration of NPs of specific sizes (provided that the length η of the E groups of PAA is accordingly optimized), but its effect on the capabilities of the brush to allow for a fine control of uptake and release needs to be investigated. The first question we aim to address consists in quantifying the shielding effect provided by the “functionalized” E groups, in the framework of the uptake/ release strategy that we discussed at the beginning of section 4.

Figure 6. Average equilibrium location of the NPs relatively to the average brush height as a function of the length η of the functional E groups of PAA and for different NP sizes Rp. The two panels correspond to the temperatures considered in Figure 5.

the average height of the NPs and the average height of the brush as the length η of the functional E groups varies. The same temperatures, T = 37 and 57 °C, are considered for various size Rp of the NPs. First, Figure 6 shows that at high temperature most NPs do not penetrate the brush (or at least stay in the upper top layer in the vicinity of the brush/solvent interface) until a sufficiently large η is reached. Second, larger NPs have less ability to penetrate the brush, whereas smaller NPs can reach deeper regions. At T ∼ TLCST, even small functional groups allow the NPs to penetrate the brush, and increasing η facilitates their penetration. Again, larger NPs cannot reach deeper regions as smaller NPs do. Figure 6

Figure 7. Time evolution of the average height of NPs as a function of their size Rp for (a) η = 0.375 and (b) η = 0.125 and temperatures above (T = 57 °C) and close to (T = 37 °C) the TLCST. Upper right inset: uptake time to capture all NPs at both temperatures and different NPs radii, Rp. F


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Figure 8. (a−c) Average force exerted on the captured NPs by the nonfunctional species upon cooling from T ≫ TLCST to T ≪ TLCST, for different NP sizes and functional block ratios η. (d) Temperature dependence of the average height of NPs ⟨Hnp⟩ of size Rp = 3.2 nm is also provided.

= 50 °C)⟩ < ⟨Hnp(T = 5 °C)⟩, whereas this process is more difficult to achieve for smallest η. The encapsulation effect provided by the “functionalized” E groups of PAA appears to be a useful tool to improve the capture and penetration of NPs of specific sizes upon cooling, but its impact on their release also has to be addressed. In the following, we aim to develop an “alchemical transformation” that mimics the triggered release of NPs. The highly idealized protocol consists in simply switching off the preferential NP−E interaction of the functional groups of length η (e.g., such an effect could be achieved by an external stimulus like a photoinduced switch that either could act as chemical inhibitor on the E groups or directly alter the NPs as well as by any other methods like electric or magnetic field). Starting from a temperature regime below the TLCST of PNIPAm, we monitor the time evolution of the average height ⟨Hnp⟩ of the NPs and extract the characteristic time trel * , at which ⟨Hnp⟩ ≃ ⟨Hbrush⟩. In Figure 9, we plot this characteristic time as a function of the initial length η of the functional E groups (before the switching-off of their interaction with NPs) and for different NP sizes Rp. Data are obtained for a release engaged from a initial state of the composite at T = 15 °C (full symbols) and close to the TLCST, T = 30 °C. First, we observe that larger NPs are expelled faster than smaller particles and that for systems that had large η before the release, the characteristic time of expulsion increases. This is the counterpart of the encapsulation effect; it favors the penetration of NPs in the brush but slows down their release because NPs have to first escape from the shell provided by the initial functional E groups of PAA (that is, thicker for large η) before diffusing in the brush. It turns out that for small NPs the time needed to leave this first shell increases with η much stronger than for large NPs.

Hence, starting from a temperature above the TLCST after the capture of NPs, the solution temperature is gradually decreased to T = 5 °C whereas the forces, ⟨Fnp⟩, that act on NPs from the other species, i.e., without the contribution from the functional groups, are monitored. (At equilibrium, the total average force vanishes.) With this quantity we want to find the appropriate “functionalized” block ratio, η, that favors the capture of NPs, provides an efficient encapsulation effect and, simultaneously, allows for release, possibly triggered by the other species, PNIPAm. This problem is addressed in Figure 8a−c where we plot the temperature-dependent average force that acts on NPs of different sizes, starting from T ≫ TLCST and gradually cooling toward the low-temperature state T ≪ TLCST. Technically, the numerical protocol is implemented such that the cooling is achieved by decreasing T in ΔT = 5 °C steps, during which the system is allowed to equilibrate for a period of 1000τ (≈ 30τp, where τp is the Rouse relaxation time of a reference chain). We observe in Figure 8a−c that larger NPs experience more constraints than smaller ones and that for the shortest “functionalized” E groups, the forces exerted by the medium are always larger than for the longer end blocks. Additionally, in the swelling region T ∼ TLCST = 32 °C, the peak in the forces exhibits a magnitude that decreases with the increase of η, indicating that the functional groups indeed provide a surrounding shell that protects NPs from the swelling PNIPAm molecules and therefore facilitates their penetration into the brush. On the other hand, as shown in Figure 6c, if η is too short compared to the size of NPs, PNIPAm polymers will prevent NPs to stay in the brush. In addition, we provide in Figure 8d the corresponding temperature-dependent average height of NPs of size Rp = 3.2 nm as a function of the block ratio η of the functional E groups of PAA. It clearly appears that large η allow NPs to penetrate the brush, with an average NP height being smaller for η = 0.375 than for η = 0.0625. Additionally larger values of η allow NPs to deeper penetrate the brush at low T compared to the high-T regime, i.e., ⟨Hnp(T

5. SUMMARY AND CONCLUDING REMARKS In this study, we have explored the ability of functional mixed brushes composed of one thermoresponsive polymer species (PNIPAm) and another one that responds to a change in pH or G


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the nanoparticles by the functional PAA end-groups, E, on the kinetics of uptake and release was then investigated, and we show that large functional ends enhance the uptake time and penetration whereas increasing η too much compared to the size of the nanoparticles slows down their release. The model and methodology developed in this article provide an efficient and coherent way to design smart, multiresponsive, surfaces for a controlled manipulation of nanoparticles. For instance, it could give insights into finding the optimal length of functional groups that allows a preferential selection of nanoparticles of specific sizes and shapes (with respect to the physicochemical properties of the surface) and for which an efficient release or re-exposure of the nanoparticles is desired.

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Figure 9. Characteristic time of release, i.e., average time it takes for NPs to reach the brush top surface, as a function of the length η of the “functionalized” end-blocks E of PAA and for different NP sizes Rp. Full symbols correspond to a release at T = 15 °C and open symbols at T = 30 °C.

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.macromol.6b00535. Definition of the model for the polymer interactions and the multibody dissipative-particle-dynamics simulations; details about the coarse-graining procedure used to design the polymer species as well as the methodology for the implicit-solvent formalism (PDF)

ionic strength (PAA) to manipulate nanoparticles in contact with the brush surface. We first developed a simulation model based on a coarsegrained representation of the polymers with soft interactions and implicit solvent that is capable of capturing and the temperature-induced swelling of PNIPAm and the effect of a change in acidic concentration at fixed ionic strength of PAA through the mapping of a pH-dependent effective Flory− Huggins parameter. This mapping was obtained by matching the swelling of a pure PAA brush to the one observed in experiments.66 The second part of the study addressed the swelling behavior of the mixed brush in response to different (pH, T) conditions and, in particular, to characterize the interplay between each species when they respond to these environmental changes. In agreement with recent experiments, we observe a decrease in the temperature-induced responsiveness of PNIPAm when PAA polymers are added to the brush, accompanied by a shift of the lower critical solution temperature of PNIPAm to lower temperatures. On the other hand, we observe an amplification of the response of PAA to a change in pH when PNIPAm is added to the brush. However, although our effective medium approach cannot account for the local dissociation reaction of the acid groups, it seems to capture the essential ingredients that result from the pH- and temperature-sensitive swelling of each species. In the third part of this work, we adapted the multiresponsive mixed brush to investigate the capture of nanoparticles (NPs) of various sizes, at a temperature above the TLCST of PNIPAm, through the use of functional end-groups E of length η carried by the PAA polymers. First we show that for η that are short compared to the size of the selected nanoparticles, large modifications of the brush surface and morphologies can occur because of strong deformations of the “functionalized” PAA end-groups E, which hinders a proper inclusion and penetration of the nanoparticles. On the other hand, large fractions η allow the capture and penetration of large nanoparticles into the brush because they provide a protecting, encapsulating shell. This mechanism could allow to built smart surfaces with specific elastic or morphological properties (to prevent the penetration of undesired nanoparticles) and adapted functional end-groups in order to capture nanoparticles of a desired size out of a polydisperse mixture. The effect of the encapsulation of

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AUTHOR INFORMATION

Corresponding Author

*E-mail [email protected] (F.L.). Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS It is a great pleasure to thank S. Minko, I. Luzinov, A. Revzin, K. Hinrichs, P. Uhlmann, K. J. Eichhorn, and M. Stamm for stimulating discussions. Ample computer time at the Supercomputer Center (JSC), Jülich, HLRN Hannover and Berlin, as well as the GWDG Göttingen is gratefully acknowledged. Financial support has been provided by the German Science Foundation within the DFG-NSF Materials World Network (Mu1674/12).

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REFERENCES

(1) Hoy, O.; Zdyrko, B.; Lupitskyy, R.; Sheparovych, R.; Aulich, D.; Wang, J.; Bittrich, E.; Eichhorn, K.-J.; Uhlmann, P.; Hinrichs, K.; Müller, M.; Stamm, M.; Minko, S.; Luzinov, I. Synthetic Hydrophilic Materials with Tunable Strength and a Range of Hydrophobic Interactions. Adv. Funct. Mater. 2010, 20, 2240−2247. (2) Advincula, R., Brittain, W., Caster, K., Rühe, J., Eds.; Polymer Brushes Synthesis, Characterization, Application; Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, 2004. (3) Raviv, U.; Giasson, S.; Kampf, N.; Gohy, J.; Jérôme, R.; Klein, J. Lubrication by Charged Polymers. Nature 2003, 425, 163−165. (4) Cao, Q.; Zuo, C.; Li, L.; Zhang, Y. Modulation of Electroosmotic Flow by Electric Field-Responsive Polyelectrolyte Brushes: a Molecular Dynamics Study. Microfluid. Nanofluid. 2012, 12, 649−655. (5) Wei, Q.; Cai, M.; Zhou, F.; Liu, W. Dramatically Tuning Friction Using Responsive Polyelectrolyte Brushes. Macromolecules 2013, 46, 9368−9379. (6) Drechsler, A.; Synytska, A.; Uhlmann, P.; Elmahdy, M.; Stamm, M.; Kremer, F. Interaction Forces between Microsized Silica Particles and Weak Polyelectrolyte Brushes at Varying pH and Salt Concentration. Langmuir 2010, 26, 6400−6410.

H


Article

Macromolecules (7) Drechsler, A.; Synytska, A.; Uhlmann, P.; Stamm, M.; Kremer, F. Tuning the Adhesion of Silica Microparticles to a Poly(2-vinyl pyridine) Brush: an AFM Force Measurement Study. Langmuir 2012, 28, 15555−15565. (8) Kost, J.; Langer, R. Responsive polymeric delivery systems. Adv. Drug Delivery Rev. 2001, 46, 125−148. (9) Bajpai, A.; Shukla, S.; Bhanu, S.; Kankane, S. Responsive Polymers in Controlled Drug Delivery. Prog. Polym. Sci. 2008, 33, 1088−1118. (10) Pillai, O.; Panchagnula, R. Polymers in drug delivery. Curr. Opin. Chem. Biol. 2001, 5, 447−451. (11) Reineke, T. Stimuli-Responsive Polymers for Biological Detection and Delivery. ACS Macro Lett. 2015, 5, 14−18. (12) Currie, E.; Sieval, A.; Fleer, G.; Cohen Stuart, M. A. Polyacrylic Acid Brushes: Surface Pressure and Salt-Induced Swelling. Langmuir 2000, 16, 8324−8333. (13) Cunliffe, D.; de las Heras Alarcón, C.; Alarco, H.; Peters, V.; Smith, J.; Alexander, C. Poly(N-isopropylacrylamide) copolymers: Effect of phase transitions on protein and bacterial attachment. Langmuir 2003, 19, 2888−2899. (14) Hayashi, H.; Kono, K.; Takagishi, T. Temperature-Controlled Release Property of Phospholipid Vesicles Bearing a Thermo-Sensitive Polymer. Biochim. Biophys. Acta, Biomembr. 1996, 1280, 127−134. (15) Ista, L.; Pérez-luna, V.; López, G. Surface-Grafted, Environmentally Sensitive Polymers for Biofilm Release. Appl. Environ. Microbiol. 1999, 65, 1603−1609. (16) Stayton, P.; Shimoboji, T.; Long, C.; Chilkoti, A.; Chen, G.; Harris, J.; Hoffmann, A. Control of Protein Ligand Recognition Using a Stimuli Responsive Polymer. Nature 1995, 378, 472−474. (17) Du, H.; Chandaroy, P.; Hui, S. Grafted poly-(ethylene glycol) on lipid surfaces inhibits protein adsorption and cell adhesion. Biochim. Biophys. Acta, Biomembr. 1997, 1326, 236−248. (18) Alswieleh, A. M.; Cheng, N.; Canton, I.; Ustbas, B.; Xue, X.; Ladmiral, V.; Xia, S.; Ducker, R.; El Zubir, O.; Cartron, M.; Hunter, C.; Leggett, G.; Armes, S. Zwitterionic Poly(amino acid methacrylate) Brushes. J. Am. Chem. Soc. 2014, 136, 9404−9413. (19) de Vos, W. M.; Biesheuvel, P.; de Keizer, A.; Kleijn, J.; Cohen Stuart, M. Adsorption of the Protein Bovine Serum Albumin in a Planar Poly(acrylic acid) Brush Layer As Measured by Optical Reflectometry. Langmuir 2008, 24, 6575−6584. (20) Qiu, Y.; Park, K. Environment-Sensitive Hydrogels for Drug Delivery. Adv. Drug Delivery Rev. 2001, 53, 321−339. (21) De Las Heras Alarcon, C.; Pennadam, S.; Alexander, C. Stimuli responsive polymers for biomedical applications. Chem. Soc. Rev. 2005, 34, 276−285. (22) Delcroix, M.; Huet, G.; Conard, T.; Demoustier-Champagne, S.; Du Prez, F.; Landoulsi, J.; Dupont-Gillain, C. Design of Mixed PEO/ PAA Brushes with Switchable Properties Toward Protein Adsorption. Biomacromolecules 2013, 14, 215−225. (23) Delcroix, M.; Demoustier-Champagne, S.; Dupont-Gillain, C. Quartz Crystal Microbalance Study of Ionic Strength and pHDependent Polymer Conformation and Protein Adsorption/ Desorption on PAA, PEO, and Mixed PEO/PAA Brushes. Langmuir 2014, 30, 268−277. (24) Yu, Q.; Zhang, Y.; Chen, H.; Zhou, F.; Wu, Z.; Huang, H.; Brash, J. Protein Adsorption and Cell Adhesion/Detachment Behavior on Dual-Responsive Silicon Surfaces Modified with Poly(Nisopropylacrylamide)-block-polystyrene Copolymer. Langmuir 2010, 26, 8582−8588. (25) Bittrich, E. Design of New Responsive Materials Based on Functional Polymer Brushes. Ph.D. Thesis, Leibniz-Institüt für Polymerforschung, Dresden, Germany, 2010. (26) Psarra, E.; König, U.; Ueda, Y.; Bellmann, C.; Janke, A.; Bittrich, E.; Eichhorn, K.-J.; Uhlmann, P. Nanostructured Biointerfaces: Nanoarchitectonics of Thermoresponsive Polymer Brushes Impact Protein Adsorption and Cell Adhesion. ACS Appl. Mater. Interfaces 2015, 7, 12516−12529. (27) Schmaljohann, D. Thermo- and pH-responsive polymers in drug delivery. Adv. Drug Delivery Rev. 2006, 58, 1655−1670.

(28) Heskins, M.; Guillet, J. Solution Properties of Poly(Nisopropylacrylamide). J. Macromol. Sci., Chem. 1968, 2, 1441−1455. (29) Taylor, L.; Cerankowski, L. Preparation of Films Exhibiting a Balanced Temperature Dependence to Permeation by Aqueous Solutions  a Study of Lower Consolute Behavior. J. Polym. Sci., Polym. Chem. Ed. 1975, 13, 2551−2570. (30) Cheng, H.; Shen, L.; Wu, C. LLS and FTIR Studies on the Hysteresis in Association and Dissociation of Poly (N-isopropylacrylamide) Chains in Water. Macromolecules 2006, 39, 2325−2329. (31) Bittrich, E.; Burkert, S.; Müller, M.; Eichhorn, K.-J.; Stamm, M.; Uhlmann, P. Temperature-Sensitive Swelling of Poly(N-isopropylacrylamide) Brushes with Low Molecular Weight and Grafting Density. Langmuir 2012, 28, 3439−3448. (32) Christau, S.; Thurandt, S.; Yenice, Z.; von Klitzing, R. StimuliResponsive Polyelectrolyte Brushes As a Matrix for the Attachment of Gold Nanoparticles: The Effect of Brush Thickness on Particle Distribution. Polymers 2014, 6, 1877−1896. (33) Christau, S.; Möller, T.; Yenice, Z.; Genzer, J.; von Klitzing, R. Brush/Gold Nanoparticle Hybrids: Effect of Grafting Density on the Particle Uptake and Distribution within Weak Polyelectrolyte Brushes. Langmuir 2014, 30, 13033−13041. (34) Yenice, Z.; Schön, S.; Bildirir, H.; Genzer, J.; von Klitzing, R. Thermoresponsive PDMAEMA Brushes: Effect of Gold Nanoparticle Deposition. J. Phys. Chem. B 2015, 119, 10348−10358. (35) Sinha, S.; Das, S. Under-water adhesion of rigid spheres on soft, charged surfaces. J. Appl. Phys. 2015, 118, 195306. (36) Diamanti, S.; Arifuzzaman, S.; Genzer, J.; Vaia, R. Tuning Gold Nanoparticle-Poly(2- hydroxyethyl methacrylate) Brush Interactions: From Reversible Swelling to Capture and Release. ACS Nano 2009, 3, 807−818. (37) Krishnamoorthy, M.; Hakobyan, S.; Ramstedt, M.; Gautrot, J. Surface-Initiated Polymer Brushes in the Biomedical Field: Applications in Membrane Science, Biosensing, Cell Culture, Regenerative Medicine and Antibacterial Coatings. Chem. Rev. 2014, 114, 10976− 11026. (38) Tokareva, I.; Minko, S.; Fendler, J.; Hutter, E. Nanosensors Based on Responsive Polymer Brushes and Gold Nanoparticle Enhanced Transmission Surface Plasmon Resonance Spectroscopy. J. Am. Chem. Soc. 2004, 126, 15950−15951. (39) Gupta, S.; Agrawal, M.; Uhlmann, P.; Simon, F.; Oertel, U.; Stamm, M. Gold Nanoparticles Immobilized on Stimuli Responsive Polymer Brushes as Nanosensors. Macromolecules 2008, 41, 8152− 8158. (40) Gupta, S.; Uhlmann, P.; Agrawal, M.; Chapuis, S.; Oertel, U.; Stamm, M. Immobilization of Silver Nanoparticles on Responsive Polymer Brushes. Macromolecules 2008, 41, 2874−2879. (41) Wang, T.; Wang, S.; Zhang, X.; Song, G.; Yu, Y.; Chen, X.; Fu, Y.; Zhang, J.; Yang, B. Responsive etalon based on PNIPAM@SiO2 composite spacer with rapid response rate and excellent repeatability for sensing application. Nanotechnology 2015, 26, 285501. (42) Ferhan, A.; Guo, L.; Zhou, X.; Chen, P.; Hong, S.; Kim, D.-H. Solid-Phase Colorimetric Sensor Based on Gold Nanoparticle-Loaded Polymer Brushes: Lead Detection as a Case Study. Anal. Chem. 2013, 85, 4094−4099. (43) Welch, M.; Rastogi, A.; Ober, C. Polymer Brushes for Electrochemical Biosensors. Soft Matter 2011, 7, 297−302. (44) Chen, Y.; Gai, P.; Xue, J.; Zhang, J.-R.; Zhu, J.-J. An“ON-OFF” Switchable Power Output of Enzymatic Biofuel Cell Controlled by Thermal-Sensitive Polymer. Biosens. Bioelectron. 2015, 74, 142−149. (45) Ashaduzzaman, M.; Anto Antony, A.; Arul Murugan, N.; Deshpande, S.; Turner, A.; Tiwari, A. Studies on an on/off-switchable immunosensor for troponin T. Biosens. Bioelectron. 2015, 73, 100−107. (46) Welch, M.; Doublet, T.; Bernard, C.; Malliaras, G.; Ober, C. A Glucose Sensor Via Stable Immobilization of the GOx Enzyme on an Organic Transistor Using a Polymer Brush. J. Polym. Sci., Part A: Polym. Chem. 2015, 53, 372−377. (47) Mitsuishi, M.; Koishikawa, Y.; Tanaka, H.; Sato, E.; Mikayama, T.; Matsui, J.; Miyashita, T. Nanoscale Actuation of Thermoreversible I


Article

Macromolecules Polymer Brushes Coupled with Localized Surface Plasmon Resonance of Gold Nanoparticles. Langmuir 2007, 23, 7472−7474. (48) Shi, A.-C.; Noolandi, J. Theory of Inhomogeneous Weakly Charged Polyelectrolytes. Macromol. Theory Simul. 1999, 8, 214−229. (49) Wang, Q.; Taniguchi, T.; Fredrickson, G. Self-Consistent Field Theory of Polyelectrolyte Systems. J. Phys. Chem. B 2004, 108, 6733− 6744. (50) Feng, E.; Lee, W.; Fredrickson, G. Supramolecular Diblock Copolymers: a Field-Theoretic Model and Mean-Field Solution. Macromolecules 2007, 40, 693−702. (51) Witte, K.; Kim, S.; Won, Y.-Y. Self-Consistent Field Theory Study of the Effect of Grafting Density on the Height of a Weak Polyelectrolyte Brush. J. Phys. Chem. B 2009, 113, 11076−11084. (52) Witte, K.; Won, Y.-Y. Self-Consistent-Field Analysis of Mixed Polyelectrolyte and Neutral Polymer Brushes. Macromolecules 2006, 39, 7757−7768. (53) Nakamura, I.; Balsara, N.; Wang, Z.-G. Thermodynamics of IonContaining Polymer Blends and Block Copolymers. Phys. Rev. Lett. 2011, 107, 198301. (54) Nakamura, I.; Wang, Z.-G. Salt-doped Block Copolymers: Ion Distribution, Domain Spacing and Effective χ Parameter. Soft Matter 2012, 8, 9356−9367. (55) Nakamura, I.; Wang, Z.-G. Thermodynamics of Salt-Doped Block Copolymers. ACS Macro Lett. 2014, 3, 708−711. (56) Nap, R.; Gong, P.; Szleifer, I. Weak Polyelectrolytes Tethered to Surfaces: Effect of Geometry, Acid-base Equilibrium and Electrical Permittivity. J. Polym. Sci., Part B: Polym. Phys. 2006, 44, 2638−2662. (57) Gong, P.; Genzer, J.; Szleifer, I. Phase Behavior and Charge Regulation of Weak Polyelectrolyte Grafted Layers. Phys. Rev. Lett. 2007, 98, 018302. (58) Tagliazucchi, M.; Calvo, E.; Szleifer, I. Molecular Theory of Chemically Modified Electrodes by Redox Polyelectrolytes under Equilibrium Conditions: Comparison with Experiment. J. Phys. Chem. C 2008, 112, 458−471. (59) Nap, R.; Tagliazucchi, M.; Szleifer, I. Born Energy, Acid-base Equilibrium, Structure and Interactions of End-grafted Weak Polyelectrolyte Layers. J. Chem. Phys. 2014, 140, 024910. (60) Sing, C.; Zwanikken, J.; de la Cruz, M. Interfacial Behavior in Polyelectrolyte Blends: Hybrid Liquid-State Integral Equation and Self-Consistent Field Theory Study. Phys. Rev. Lett. 2013, 111, 168203. (61) Sing, C.; Olvera de la Cruz, M. Polyelectrolyte Blends and Nontrivial Behavior in Effective Flory-Huggins Parameters. ACS Macro Lett. 2014, 3, 698−702. (62) Sing, C.; Zwanikken, J.; Olvera de la Cruz, M. Electrostatic Control of Block Copolymer Morphology. Nat. Mater. 2014, 13, 694− 698. (63) Léonforte, F.; Mü ller, M. Morphology Modulation of Multicomponent Polymer Brushes in Selective Solvent by Patterned Surfaces. Macromolecules 2015, 48, 213−228. (64) Léonforte, F.; Müller, M. Poly(N-isopropylacrylamide)-Based Mixed Brushes: A Computer Simulation Study. ACS Appl. Mater. Interfaces 2015, 7, 12450−12462. (65) Wang, J.; Müller, M. Microphase Separation of Mixed Polymer Brushes: Dependence of the Morphology on Grafting Density, Composition, Chain-Length Asymmetry, Solvent Quality, and Selectivity. J. Phys. Chem. B 2009, 113, 11384−11402. (66) Bittrich, E.; Uhlmann, P. Private communication. (67) Bittrich, E.; Rodenhausen, K.; Eichhorn, K.-J.; Hofmann, T.; Schubert, M.; Stamm, M.; Uhlmann, P. Protein adsorption on and swelling of polyelectrolyte brushes: A simultaneous ellipsometryquartz crystal microbalance study. Biointerphases 2010, 5, 159−167. (68) Afroze, F.; Nies, E.; Berghmans, H. Phase Transitions in the System Poly(Nisopropylacrylamide)/water and Swelling Behaviour of the Corresponding Networks. J. Mol. Struct. 2000, 554, 55−68. (69) Shin, B.; Jhon, M.; Lee, H.; Yuk, S. pH/Temperature Dependent Phase Transition of an Interpenetrating Polymer Network: Anomalous Swelling Behavior Above Lower Critical Solution Temperature. Eur. Polym. J. 1998, 34, 1675−1681.

(70) Houbenov, N.; Minko, S.; Stamm, M. Mixed Polyelectrolyte Brush from Oppositely Charged Polymers for Switching of Surface Charge and Composition in Aqueous Environment. Macromolecules 2003, 36, 5897−5901. (71) Khutoryanskiy, V.; Mun, G.; Nurkeeva, Z.; Dubolazov, A. pH and Salt Effects on Interpolymer Complexation via Hydrogen Bonding in Aqueous Solutions. Polym. Int. 2004, 53, 1382−1387. (72) Mikhaylova, Y.; Ionov, L.; Rappich, J.; Gensch, M.; Esser, N.; Minko, S.; Eichhorn, K.-J.; Stamm, M.; Hinrichs, K. In Situ Infrared Ellipsometric Study of Stimuli-Responsive Mixed Polyelectrolyte Brushes. Anal. Chem. 2007, 79, 7676−7682. (73) Hinrichs, K.; Aulich, D.; Ionov, L.; Esser, N.; Eichhorn, K.-J.; Motornov, M.; Stamm, M.; Minko, S. Chemical and Structural Changes in a pH-Responsive Mixed Polyelectrolyte Brush Studied by Infrared Ellipsometry. Langmuir 2009, 25, 10987−10991. (74) Ayres, N.; Cyrus, C.; Brittain, W. Stimuli-Responsive Surfaces Using Polyampholyte Polymer Brushes Prepared via Atom Transfer Radical Polymerization. Langmuir 2007, 23, 3744−3749. (75) Yu, K.; Han, Y. Effect of block sequence and block length on the stimuli-responsive behavior of polyampholyte brushes: hydrogen bonding and electrostatic interaction as the driving force for surface rearrangement. Soft Matter 2009, 5, 759−768. (76) Lu, Y.; Zhuk, A.; Xu, L.; Liang, X.; Kharlampieva, E.; Sukhishvili, S. Tunable pH and Temperature Response of Weak Polyelectrolyte Brushes: Role of Hydrogen Bonding and Monomer Hydrophobicity. Soft Matter 2013, 9, 5464−5472. (77) Lesch, H.; Kaikkonen, M.; Pikkarainen, J.; Yla-Herttuala, S. Avidin-biotin technology in targeted therapy. Expert Opin. Drug Delivery 2010, 7, 551−564. (78) Kim, M.; Lee, J.; Jones, C.; Revzin, A.; Tae, G. Heparin-based hydrogel as a matrix for encapsulation and cultivation of primary hepatocytes. Biomaterials 2010, 31, 3596−3603. (79) Sadurní, P.; Alagón, A.; Aliev, R.; Burillo, G.; Hoffman, A. Immobilization of streptavidinhorseradish peroxidase onto a biotinylated poly(acrylic acid) backbone that had been radiation-grafted to a PTFE film. J. Biomater. Sci., Polym. Ed. 2005, 16, 181−187. (80) Detcheverry, F.; Kang, H.; Daoulas, K.; Müller, M.; Nealey, P.; de Pablo, J. Monte Carlo Simulations of a Coarse Grain Model for Block Copolymers and Nanocomposites. Macromolecules 2008, 41, 4989−5001. (81) Silbert, L.; Ertas, D.; Grest, G.; Halsey, T.; Levine, D.; Plimpton, S. Granular flow down an inclined plane: Bagnold scaling and rheology. Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 2001, 64, 051302. (82) Currie, E.; van der Gucht, O.; Borisov, J.; Cohen Stuart, M. EndGrafted Polymers with Surfactants: A Theoretical Model. Langmuir 1998, 14, 5740−5750. (83) Currie, E.; Fleer, G.; Cohen Stuart, M.; Borisov, O. Grafted Polymers with Annealed Excluded Volume: A Model for Surfactant Association in Brushes. Eur. Phys. J. E: Soft Matter Biol. Phys. 2000, 1, 27−40. (84) Kim, J.; O’Shaughnessy, B. Nanoinclusions in Dry Polymer Brushes. Macromolecules 2006, 39, 413−425. (85) Chen, Y.; Chen, J. Absorption and Engulfing Transitions in Nanoparticle Infiltration into a Polymer Brush: A Monte Carlo Simulation. J. Polym. Sci., Part B: Polym. Phys. 2012, 50, 21−26. (86) Halperin, A.; Kröger, M.; Zhulina, E. Colloid-Brush Interactions: The Effect of Solvent Quality. Macromolecules 2011, 44, 3622−3638. (87) Opferman, M.; Coalson, R.; Jasnow, D.; Zilman, A. Morphological Control of Grafted Polymer Films via Attraction to Small Nanoparticle Inclusions. Phys. Rev. E 2012, 86, 031806. (88) Akkilic, N.; Leermakers, F.; de Vos, W. Responsive Polymer Brushes for Controlled Nanoparticle Exposure. Nanoscale 2015, 7, 17871−17878. (89) Chin, H.-Y.; Wang, D.; Schwartz, D. Dynamic Molecular Behavior on Thermoresponsive Polymer Brushes. Macromolecules 2015, 48, 4562−4571.

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