Dominance of Chain Entanglement over Transient Sticking on Chain

Apr 3, 2018 - The chain dynamics in supramolecular polymer networks is determined by the interplay of the kinetics of transient interchain association...
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Article Cite This: Macromolecules XXXX, XXX, XXX−XXX

Dominance of Chain Entanglement over Transient Sticking on Chain Dynamics in Hydrogen-Bonded Supramolecular Polymer Networks in the Melt Amir Jangizehi,†,‡ S. Reza Ghaffarian,*,† Willi Schmolke,‡ and Sebastian Seiffert*,‡ †

Department of Polymer Engineering and Color Technology, Amirkabir University of Technology, No. 424, Hafez Avenue, Tehran 15875-4413, Iran ‡ Institute of Physical Chemistry, Johannes Gutenberg-University of Mainz, Duesbergweg 10-14, Mainz D-55128, Germany ABSTRACT: The chain dynamics in supramolecular polymer networks is determined by the interplay of the kinetics of transient interchain association and relaxation of the network chains themselves. This interplay can be addressed by studying model supramolecular polymer networks in which the number of associative side groups and the molar mass of the covalently jointed backbone polymers are both varied systematically. To realize this idea, we use precursor chains with three different molar masses, which comes along with different extents of entanglement in the melt state. For each molar mass, the precursor polymers are functionalized with three different relative contents of associative side groups, giving rise to transient network formation in the melt state. We evaluate the chain dynamics in these transient networks by probing the diffusivity of fluorescently labeled tracer chains by fluorescence recovery after photobleaching (FRAP). In these studies, we find that the presence of entanglements markedly outweighs the influence of transient associative interactions. breaking and fusing.32 This model predicts scaling laws for the reptation time, the viscosity, and the translational polymerchain diffusion coefficient as a function of the polymer volume fraction.33 For the other case of side-chain associative supramolecular polymers, a dynamical model has been given by Rubinstein, Leibler, and Colby:34 they extended the classical reptation model such as to describe the relaxation time and the diffusion coefficient of entangled sticky polymers, further translating to the frequency-independent storage modulus of the resulting transient polymer networks. In this model, two distinct storage-modulus plateaus are predicted. The first plateau relates to experimental time scales shorter than that of the dissociation of the noncovalent bonds and therefore reflects contributions from both the transient cross-links and the chain-backbone entanglements. The second plateau is related to time scales longer than that of the dissociation of the noncovalent bonds, which are similar to those of linear chains without stickers. Later on, Rubinstein and Semenov refined and extended this concept and developed two models based on Rouse-type motion and reptation to describe the dynamics of nonentangled and entangled side-chain supramolecular polymer solutions.35−37 Similar as the Cates model, these theories predict scaling laws for system parameters like the terminal relaxation time and the viscosity as a function of the polymer volume fraction as well as the number of side-chain stickers.

1. INTRODUCTION Supramolecular polymers are macromolecular materials based on noncovalent interactions, in which permanent covalent bonds are partially or fully replaced by transient binding interactions.1 These polymers offer outstanding promise for designing scaffolds, coatings, and matrixes to serve in selfhealing,2−4 shape-memory,5 optoelectronic,6 and biomedical materials.7,8 There are two general types of supramolecular polymers:9 main-chain telechelics, which have associative motifs at the ends of their oligomeric or polymeric building blocks, and side-chain associates, which have pendant associative “sticky” groups along a linear or branched macromolecular backbone. In either of these supramolecular polymers, highly directional noncovalent bonds such as metal−ligand complexes,10−15 hydrogen bonds,16−19 ionic interactions,20−22 π−π stacking,23 and/or host−guest interactions4,24−26 are in a dynamic equilibrium between associated and dissociated states,9 thereby providing transient association of the building blocks to form a dynamic and stimuli-sensitive material.27 To rationally design such a material for a specific application, it is necessary to understand its dynamics at two levels;28,29 these are set by (i) the lifetime of the sticker association and (ii) the relaxation of the transient or permanent polymer chain segments. In some cases, it is also necessary to consider further effects such as nano- or microphase segregation, which adds another level of supramacromolecular dynamics.30,31 To provide a basis for a quantitative assessment of telechelic supramolecular polymer dynamics, Cates developed a model based on reptation of linear chains abetted by reversible chain © XXXX American Chemical Society

Received: October 10, 2017 Revised: January 30, 2018

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DOI: 10.1021/acs.macromol.7b02180 Macromolecules XXXX, XXX, XXX−XXX

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Scheme 1. (A) Synthesis of a Poly(n-butyl acrylate-ran-hydroxyethyl acrylate) Precursor Copolymer 1 by Reversible Addition− Fragmentation Chain Transfer (RAFT) Polymerization Using Azobisisobutyronitrile (AIBN) as Initiator and tert-Butyl Dithiobenzoate (t-BDB) as Chain Transfer Agent; (B) Functionalization of the Precursor Copolymer 1 with 2-(6Isocyanatohexylaminocarbonylamino)-6-methyl-4[1H]pyrimidinone (UPy-Hexyl-Isocyanate) To Obtain Copolymer 2 Capable of Forming Supramolecular Network Structures by Transient Interchain Linking via Quadruple Hydrogen Bonding; (C) Typical 1H NMR Spectrum of a Supramolecular Polymer Network of Type 2a

a The inset zoom shows the peaks of the UPy group (δ > 10 ppm). Labels a and b at δ = 4.06−4.2 and label c at δ = 3.8 ppm denote the signal of the CH2 protons in the vicinity of the acrylate group and the OH group, respectively, in the polymer backbone (see panel A), whereas labels d, e, and f at δ = 10.2, 11.8, and 13.1 ppm denote the signal of the amine protons of the UPy group (see panel B).

exponent of 0.5 for the frequency dependence of the relaxation moduli, 38 but it cannot predict the presence of the aforementioned second low-frequency elastic plateau. In another related theoretical work, Hawke et al. predicted both the intermediate-frequency Rouse regime and the second plateau of the storage modulus at low frequencies.40 In an earlier experimental work, Anthamatten et al. investigated the influence of both the number and the association strength of sticky side groups on the dynamics of side-chain supramolecular polymers by also using pBA functionalized with different hydrogen-bonding groups.41 In rheological measurements, supramolecular polymers of this kind bearing only weak hydrogen-bonding groups were shown to display liquid-like properties very similar to the nonsticky precursors, with just a slight downshift of the crossover point of their storage and loss moduli to lower frequencies for higher contents of sticky groups. By contrast, polymers with strong hydrogen-bonding groups exhibited network-like mechanics. Concluding from these and other studies,42 the dynamics of supramolecular polymer networks appear to depend on at least six variables: (i) the associative group strength, (ii) the number and (iii) the distribution of associative groups along the polymer chain, (iv) the molar mass of the precursor polymer and the relative number of entanglements that it can form, (v) the supramolecular polymer state (melt or solution), and (vi), if

To challenge these conceptual pictures and the quantitative modeling based upon them, several experimental studies have been conducted during the past decade. Recently, Alvarez et al. studied the dynamics of a series of supramolecular polymer networks based on randomly hydrolyzed poly(n-butyl acrylate) (pBA) with different levels of hydrolysis to introduce carboxylic acid moieties as sticky hydrogen-bonding side groups.38 The presence of these weak hydrogen bonds impacts the viscoelastic dynamics of these polymers by (i) rising the plateau of the storage modulus, (ii) reducing the low-frequency crossover of the storage and loss moduli, G′ and G″, (iii) shallowing the power-law exponent of the frequency dependence of both these moduli to 0.5, and (iv) elevating their absolute values at low frequencies. At high acrylic acid contents, a second plateau of the storage modulus was observed at low frequencies. This was attributed to phase separation of mutually associated polar stickers into clusters with lifetimes longer than that of simple pairwise assemblies. On the theoretical side, in close relation to this experimental work, Ahmadi, van Ruymbeke, and coworkers developed a time marching algorithm based on the classical reptation model to describe the dynamics of side-chain supramolecular polymer systems, with special emphasis on the effect of hindered fluctuations besides sticky Rouse and sticky reptation mechanisms.39 Comparison of the model with experimental results showed that it can predict a power-law B

DOI: 10.1021/acs.macromol.7b02180 Macromolecules XXXX, XXX, XXX−XXX

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oxide. All other chemicals are obtained from Sigma-Aldrich and used without further purification. Synthesis of P(BA-ran-HEA) Copolymers. p(BA-ran-HEA) copolymers are prepared by RAFT polymerization. Azobis(isobutyronitrile) (AIBN) and tert-butyldithiobenzoate (t-BDB) are used as initiator and RAFT agent, respectively. For each polymerization, the molar ratio of AIBN:t-BDB is 1:10. All polymers are synthesized by the same general procedure, during which only the molar ratio of AIBN:(BA + HEA) is varied according to the targeted number-average molar mass of the random copolymer. Samples are designated as 1.M, where 1 refers to the precursor copolymers shown in Scheme 1A, whereas M denotes the number-average molar mass, Mn, in units of kg mol−1. In a typical polymerization (1.05), BA (11.11 mL, 78.02 mmol), HEA (1.80 mL, 17.22 mmol), AIBN (14.33 mg, 0.087 mmol), and t-BDB (0.17 mL, 0.87 mmol) are added to a 50 mL Schlenk flask. The mixture is degassed by three freeze−pump−thaw cycles. The flask is placed in a preheated oil bath at 90 °C. After 16 h, the reaction mixture is frozen with liquid nitrogen to stop the polymerization and diluted with 10 mL of chloroform. The copolymer is precipitated twice in cold hexane, isolated by filtration, and then dried under vacuum. The relative (polystyrene analogue) numberaverage molar masses, Mn, and the polydispersity indexes are determined by size exclusion chromatography (SEC) (PSS-SDV 5 μL 1E3, 1E5, and 1E6 columns, 25 °C, tetrahydrofuran eluent, molar mass calibration with polystyrene standards). 1H NMR (CDCl3): δ = 4.06−4.2 (qq, J = 12.2, 6.1, 1 Hz, OCH2CH2) 3.8 (m, CH2CH2OH), 2.29 (m, CH2CH in polymer backbone), 1.92 (m, CH2CH in polymer backbone), 1.60 (m, OCH2CH2CH2), 1.38 (m, CH2CH2CH3), 0.94 (m, CH2CH2CH3) ppm. Synthesis of Matrix Polymers. Matrix polymers are obtained by functionalization of the p(BA-ran-HEA) copolymers from the previous step with UPy groups. Samples are designated as 2.MUf, where 2 refers to the matrix polymers shown in Scheme 1B and M denotes their number-average molar mass, Mn, in units of kg mol−1. In a typical functionalization (2.05U0.5), 1.05 (1.7 g) is dissolved in 15 mL of anhydrous toluene at 80 °C. UPy-hexyl-isocyanate, which is only partially soluble in toluene (5.38 mg, 0.18 mmol), is added to the polymer solution. After 16 h, unreacted UPy-hexyl-isocyanate is removed by filtration. The product is precipitated in cold hexane, isolated by filtration, and then dried under vacuum. The quantity of UPy-hexyl-isocyanate used in each reaction is adjusted such to match the targeted mole percentage in the matrix polymer. 1H NMR (CDCl3): δ = 13.1 (s, CH3CNH), 11.8 (s, CH2NHCONH), 10.2 (s, CH2NHCONH), 4.6 (s, NHCOO), 4.06−4.2 (qq, J = 12.2, 6.1, 1 Hz, OCH2CH2), 3.8 (m, CH2CH2OH), 3.2 (m, CH2NHCOO, CH2NHCONH), 2.29 (m, CH2CH in polymer backbone), 2.2 (s, CH3CCH), 1.92 (m, CH2CH in polymer backbone), 1.60 (m, OCH2CH2CH2), 1.38 (m, CH2CH2CH3), 0.94 (m, CH2CH2CH3) ppm. The mole percentage of UPy groups relative to the number of repeating units per polymer chain (C) is calculated from the integral of the 1H NMR signal of the amine protons of the UPy group (δ = 13.1, 11.8, 10.2 ppm, labeled as d, e, and f in Scheme 1B) in relation to that of the CH2 protons in the vicinity of the acrylate group in the polymer backbone (δ = 4.06−4.2 ppm, labeled as a and b inScheme 1A). The average number of UPy groups per polymer chain ( f) is then calculated from C as f = C × N/100, where N is the average number of monomer repeating units per polymer chain. Note that this method of estimation does not determine the actual number of UPy groups per single chain but, instead, the average of that number over all chains in the polymer sample. Preparation of Fluorescently Labeled Tracers. Fluorescencently labeled tracer polymers are prepared in two steps. In a typical example procedure, 2.05U0.5 (140 mg) is dissolved in 5 mL of anhydrous dichloromethane under an argon atmosphere. Anhydrous pyridine (4.69 μL, 0.06 mmol) and p-nitrophenyl chloroformate (5.84 mg, 0.03 mmol) are added to the polymer solution, and the mixture is stirred at room temperature for 12 h. For purification, the mixture is added to a separating funnel containing dichloromethane (50 mL) and brine (10 mL). The organic layer is washed three times with brine, dried over MgSO4, and concentrated in vacuo. The product is

the polymer is in solution, the concentration of the supramolecular associated polymer. With regard to the latter two points, it must be stated that many experimental studies probe dynamics of supramolecular polymer networks in a dissolved or gelled state, but there is only little work on solvent-free systems,43−51 especially with a focus on systematically studying the influence of the molar mass of the precursor polymer and the number of associative groups on the resulting melt dynamics.52−56 To contribute to filling this gap, this paper presents such a systematic study on a set of supramolecular polymer networks in the melt state, focusing on comparing different molar masses and associative-group contents. This comparison serves to derive a consistent picture of the interplay of chain relaxation, as assessed by polymer physics, and chain association, as assessed by supramolecular chemistry. As a further point of focus, this study is conducted from a microscopic perspective, which is rare in the literature so far.53,57−64 In this work, we study the diffusive dynamics of linear “sticky” polymers in the melt state and investigate the impact of their molar mass and degree of functionalization with associative groups. We do this from a microscopic point of view by probing the polymers with a confocal microscope. The material basis of our study is random copolymers of n-butyl acrylate (BA) and hydroxyethyl acrylate (HEA), named poly(nbutyl acrylate-ran-hydroxyethyl acrylate), p(BA-ran-HEA), which we synthesize by reversible addition−fragmentation chain transfer polymerization (RAFT). By this means, we exert control on the precursor polymer molar masses and limit their polydispersities.65,66 We prepare copolymers with three different average molar masses in such a fashion that they (i) cannot entangle, (ii) undergo a single entanglement per chain, or (iii) are able to multiply entangle with one another. In addition, for each molar mass, the copolymers are divided into three substocks to which different amounts of strongly selfassociating ureidopyrimidinone moieties, UPy,67 are attached as stickers. A small portion of these copolymers is further functionalized such to carry a fluorescent label, (S)-(+)-4-(3aminopyrrolidino)-7-nitrobenzofurazan (NBD). For comparison, we also prepare labeled tracer chains that carry no sticky side groups and embed them into the UPy-modified unlabeled matrixes. The translational diffusion coefficients of the sticky and nonsticky tracers in these supramolecular-associated polymer matrixes in the melt state are measured by fluorescence recovery after photobleaching (FRAP) carried out on a confocal laser scanning microscope, as also employed in several earlier works.60,68−70 The point of using this method for our study is twofold. First, use of a sensitive fluorescencebased method allows us to probe a low mole percentage fraction of tracer chains in a background matrix that is chemically largely similar to them, with just minor modification of the tracers by attachment of just single fluorophore units. Second, the FRAP technique covers micrometer scales and a second-to-minute range, perfectly complementing macroscopic rheology on similar time scales.

2. EXPERIMENTAL SECTION Materials. 2-(6-Isocyanatohexylaminocarbonylamino)-6-methyl-4[1H]pyrimidinone, in short, UPy-hexyl-isocyanate, is synthesized as reported by Folmer et al.17 tert-Butyl-dithiobenzoate (t-BDB) is prepared as reported by Charleux et al.71 n-Butyl acrylate and hydroxylethyl acrylate are purified by passing through basic aluminum C

DOI: 10.1021/acs.macromol.7b02180 Macromolecules XXXX, XXX, XXX−XXX

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Table 1. Macromolecular Characteristics of the Poly(n-butyl acrylate-ran-hydroxyethyl acrylate) Precursor Copolymers 1 Obtained by Reversible Addition−Fragmentation Chain Transfer (RAFT) Copolymerization As Shown in Scheme 1A copolymera

Mnb (kg mol−1)

av no. of monomer repeating units per chain (N)

radius of gyration, Rgc (nm)

Mw/Mnb

OHd (mol %)

glass transition temp, Tg (°C)

1.05 1.28 1.69

5.2 28.0 69.0

40 230 550

1.92 4.46 6.99

1.1 1.6 1.7

15 12 10

−56.25 −55.42 −54.02

a

Sample designation 1.M, where 1 refers to the precursor copolymers shown in Scheme 1A and M denotes their number-average molar mass, Mn, in kg mol−1. bEstimated by size exclusion chromatography (SEC) calibrated with polystyrene standards. cRg is estimated according to ⟨Rg2⟩ = ⟨R02⟩/6, where ⟨R02⟩ is the mean-square end-to-end distance of the polymer chain, calculated from ⟨R02⟩ = Nl2C∞, with N the average number of repeating units, l the average bond length of the repeating units, and C∞ the characteristic ratio.75 dAverage mole percentage of OH groups relative to the number of monomeric repeating units per polymer chain, calculated from the integral of the 1H NMR signal of the CH2 protons close to the OH group of HEA (δ = 3.8 ppm, labeled as c in Scheme 1A) in relation to the signal of the CH2 protons in the vicinity of the acrylate group (δ = 4.06− 4.2 ppm, labeled as a and b in Scheme 1A). precipitated in cold hexane, isolated by filtration, and then dried under vacuum. In a second step, the substance (100 mg) is dissolved in 5 mL of dimethylformamide, and triethylamine (25.97 μL, 0.19 mmol) and NBD (30.92 mg, 0.12 mmol) are added to the solution. The reaction proceeds overnight, and the product is purified by the same procedure described for the first step. Preparation of Supramolecular-Network Matrixes Containing Embedded Fluorescencently Labeled Tracers. To prepare samples to be probed in FRAP, each matrix and tracer polymer is dissolved in chloroform, and the matrix−polymer solutions are mixed with the respective sticky or nonsticky tracer-polymer solutions with a molar ratio of tracer:matrix = 1:99. Then, 0.4 mL of each sample is poured into a chamber slide and left for 24 h at 20 °C (760 mmHg) for solvent evaporation. All samples are then further dried at room temperature under reduced pressure and annealed at 55 °C for 12 h. Fluorescence Recovery after Photobleaching (FRAP). The diffusive mobilities of the tracer chains within the supramolecularnetwork matrixes are studied by recording temporally and spatially resolved fluorescence photobleaching profiles at 25 °C. For this purpose, the samples are placed on the stage of a Leica TCS SP8 confocal laser scanning microscope with a 5× dry objective of low numerical aperture, NA = 0.15. The low NA ensures that photobleaching creates no appreciable gradient in the z-direction; as a result, two-dimensional lateral diffusion needs to be considered only. The fluorophores are excited with the 488 nm line of an Ar-ion laser. A stack of six images is taken to record the prebleach situation. To bleach a spot pattern into the confocal plane, a micrometer-sized region of each sample containing the fluorescently labeled chains is illuminated by a brief, 3 s laser light pulse of high intensity (14 mW at the object level), thereby bleaching the fluorophores and creating a nonfluorescent 4−5 μm wide dark spot within the sample. The likelihood of bleaching is proportional to the light intensity, and because the laser has a Gaussian radial intensity profile, the bleached spot has a Gaussian intensity profile as well. The initial bleach depth in the center of the dark spot is approximately 50% of the original fluorescence intensity. After bleaching, this Gaussian pattern smears into the environment due to the diffusive exchange of bleached and unbleached fluorophores between the nonfluorescent region and its surroundings. The following evolution of the bleaching profile is monitored by postbleach imaging. In most of our experiments, the postbleach images are recorded in three series of 30 images each. Temporal spacing between single images is 0.29 s for the first series, 1 s for the second series, and 5 s for the third series. With that the total experimental time is ∼3 min. To check for the long-term sample dynamics, in some selected experiments, two additional time series are recorded, with intervals of 1 and 20 min between the images. This expands the experimental time frame to more than 10 h. Through analysis of the postbleach images, we determine a set of spatially (r) and temporally (t) resolved fluorescence intensity profiles, I(r,t), that are attenuated by a Gaussian sink in the bleached region around r = 0. The temporal evolution of this pattern is connected to the ensemble of translational diffusion coefficients Di in respective amounts Mi in the sample, with one D;Mpair for each differently diffusing species i in the sample. Quantitative

analysis of these D;M-pairs with a MATLAB script based on a multicomponent diffusion model yields the sample’s distribution of diffusion coefficients.72 Rheology. Linear viscoelastic responses of the random copolymers and supramolecular networks are measured using a stress-controlled Anton Paar MCR301 rheometer equipped with a parallel plate−plate geometry (gap size 100−400 μm, plate diameter 8 mm). In all experiments, the sample is monitored for 30 min at a constant shearing amplitude and frequency (γ = 1%, ω = 1 rad s−1) to ensure sample equilibration; no change of the dynamic moduli is observed during this time-sweep experiment in any sample of this study. Then, an amplitude-sweep measurement is recorded at a constant frequency (γ = 0.1−100%, ω = 1 rad s−1) to determine the linear viscoelastic regime for each sample, followed by a frequency-sweep experiment at a constant strain amplitude (γ = 1%, ω = 0.01−100 rad s−1). This is done in a temperature range between −10 and 40 °C to create time− temperature superposition mastercurves at 25 °C.

3. RESULTS AND DISCUSSION Supramolecular Polymer-Network Matrixes. Three p(BA-ran-HEA) precursor copolymers are synthesized by RAFT polymerization, as shown in Scheme 1A. The reactivity ratios of the monomers BA and HEA are 0.91, and 0.95, respectively.73 These values indicate the monomers to be distributed randomly along the p(BA-rand-HEA) copolymer chains. Based on the entanglement molar mass of pBA, Me = 16.8 kg mol−1,74 the precursor copolymers are targeted to have different extents of interchain entanglement. In view of this goal, we prepare three different precursors with macromolecular characteristics as detailed in Table 1. One of them exhibits a low molar mass, therefore consisting of nonentangled chains only. The second precursor exhibits a medium molar mass, which corresponds to an average of one entanglement point per chain. The third precursor has a high molar mass well above Me. Each of these copolymers is further functionalized with UPy stickers at three different contents, following the reaction shown in Scheme 1B. The mole percentage and the number of UPy groups are estimated by 1H NMR spectroscopy as detailed in the Experimental Section (Scheme 1C). With that we have a total of nine precursor polymers to build supramolecular networks with different building-block molar mass and associative-group contents, as summarized in Table 2. All glass transition temperatures, Tg, of these functionalized copolymers are in a narrow window between −60 and −50 °C, thereby ensuring that all these copolymers are well in a melt state at the temperature of observation, which is room temperature. Moreover, the difference between Tg of each precursor polymer and its corresponding supramolecular associable network-forming polymer is 3 °C at maximum. D

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Macromolecules Table 2. Sticker Content of the Supramolecular-Network Matrixes 2 Formed from the Poly(n-butyl acrylate-ranhydroxyethyl acrylate) Precursor Copolymers 1

supramolecular matrix polymera

precursor copolymer

UPy mol % (C)b

2.05U0.5 2.05U1.0 2.05U2.0 2.28U3.0 2.28U5.0 2.28U8.0 2.69U7.0 2.69U13.0 2.69U20.0

1.05 1.05 1.05 1.28 1.28 1.28 1.69 1.69 1.69

1.2 2.6 4.1 1.4 2.5 3.8 1.3 2.4 3.7

av no. of UPy groups per chain ( f)c

av no. of repeating units between two UPy groups (LUPy)

glass transition temp, Tg (°C)

0.5 1 2 3 5 8 7 13 20

80 40 20 76 46 28 78 42 27

−56.01 −55.45 −54.83 −55.11 −54.42 −53.52 −53.62 −52.42 −51.32

Figure 1. Storage (closed symbols) and loss (open symbols) moduli of precursor copolymers 1 with molar masses of 5.2, 28.0, and 69.0 kg mol−1. The numbers next to the curves indicate their log−log slope in the terminal low-ω regime. On the other side of the frequency range (ω = 102.8−103.8 rad s−1), a part of the Rouse region of the samples with molar masses of 28.0 and 69.0 kg mol−1 is observed; in this region, the rheological data of these samples superimpose.

a Sample designation 2.MUf, where 2 refers to the precursor copolymers shown in Scheme 1B, M denotes their number-average molar mass, M n , and f denotes their average number of ureidopyrimidinone groups per polymer chain. bMole percentage of UPy groups relative to the number of repeating units per polymer chain; calculated from the integral of the 1H NMR signal of the amine protons of the UPy group (δ > 10 ppm, labeled as d, e, and f in Scheme 1B) in relation to the CH2 protons in the vicinity of the acrylate group (4.06−4.2 ppm, labeled as a and b in Scheme 1A). c Average number of UPy groups per polymer chain calculated by C × N/100. dAverage number of repeating units between two UPy groups calculated by N/f.

Therefore, whereas all the precursor polymers flow like Maxwellian fluids when given enough time in the low-frequency range, they more and more display viscoelastic signatures at high and intermediate frequencies if their molar mass is higher. This is because at high enough molar mass, the chains start to entangle with one another, thereby delaying their onset of a terminal regime with Maxwell-type scaling of G′(ω) and G″(ω) to lower frequencies, whereas viscoelastic ranges with G′ ≈ G″ or even G′ > G″ are observed at intermediate frequencies. In our set of polymers, the low-molar-mass sample exhibits Maxwell-type scaling of G′(ω) and G″(ω) with G′ < G″ over the whole frequency range probed, leading us to conclude that these chains are not entangled. The intermediate molar-mass sample displays G′ ≈ G″ at mid-frequencies, which is the border of transition to G′ > G″, such that we conclude these polymers to just have one entanglement per chain. The highmolar-mass sample exhibits a region with G′ > G″, leading us to conclude that these chains exhibit multiple interchain entanglement that allows elastic energy to be stored on short time scales. These results are in agreement with the intended average number of interchain entanglements for the precursor copolymers based on their molar masses, as determined by SEC, in view of the literature-known74 entanglement molar mass of pBA. Functionalization of the copolymers with UPy side groups postpones the terminal relaxation for all three samples, as seen in Figure 2A−C; it also significantly shallows the scaling of the frequency dependence of the moduli of the nonentangled polymer, as seen in Figure 2A. These observations can be related to the presence of UPy associations with the lifetimes greater than the relaxation time of the precursor copolymers.42 However, the influence of the UPy side groups on the rheological properties of these copolymers does not lead to (i) creation of a rubbery plateau in the storage modulus of the nonentangled sample and (ii) significant raise of this plateau for the entangled samples, as may both be expectable in view of earlier studies.41,49 The lack of these effects can be attributed to the polarity of the residual free hydroxyl groups in our samples, which may weaken the strength of UPy associations. This assumption can be checked by studying the shift factors, aT, obtained from the construction of T−t superimposed mastercurves, as compiled in Figure 2D−F. From these, the energy of activation for the relaxation of the supramolecular polymer

Therefore, we regard the influence of this difference on the network-chain viscoelastic and diffusive properties to be negligible. Oscillatory Shear Rheology. To study the macroscopic viscoelastic characteristics of our samples in their nonsticky melt and sticky transient-network states, we probe the precursor copolymers and the supramolecular networks with ∼4 mol % of UPy groups by oscillatory shear rheology. The values of the dynamic moduli depend on temperature in view of their position along the frequency axis only, but not in view of their position along the moduli axis. Accordingly, we can treat these samples to be thermorheologically simple and use the time−temperature superposition principle to construct mastercurves. This approximation is in agreement with previous findings on similar supramolecular polymer networks.41,49 In the frequency range covered with this method, G′ is smaller than G″ for the shortest precursor polymer chains (1.05), with a terminal regime displaying a frequency dependence of the moduli closely matching the Maxwell-type scaling of G′ ∼ ω2 and G″ ∼ ω1, as seen in Figure 1 (black curves). For the medium molar mass precursor polymer (1.28), the values of G′ are equal to G″ at intermediate frequencies (ω = 102.5−103 rad s−1), as also seen in Figure 1 (red curves). The precursor copolymer with the highest molar mass (1.69) exhibits G′ values greater than those of G″ in the frequency range of ω = 100.85−103.1 rad s−1, also shown in Figure 1 (blue curves). For the latter two precursor polymers, the dynamic moduli are partly superimposed in the high-frequency Rouse regime (ω = 103.1−103.4 rad s−1), which must be the case, as they represent the same polymer type. At the other end of the frequency range covered, these samples display a terminal regime with a frequency dependence of the moduli close to Maxwell-type scaling of G′ ∼ ω2 and G″ ∼ ω1, as also seen in Figure 1. E

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Figure 2. (A−C) Dynamic moduli of precursor random copolymers 1 and supramolecular networks 2 derived from them with ∼4 mol % of UPy groups, with polymer molar masses of 5.2 (A), 28.0 (B), and 69.0 kg mol−1 (C). All data sets are mastercurves constructed by time−temperature superposition referenced to 25 °C. The inset zoom in panel B shows the dynamic moduli of the supramolecular network with the molar mass of 28.0 kg mol−1 in the frequency range of ω = 101.6−103.0 rad s−1, in which G′ > G″. The numbers next to the curves indicate their log−log slope in the terminal low-ω regime. (D−F) Horizontal shift factors obtained from the mastercurve construction.

In each supramolecular associative polymer, τrelax depends on τflow and on the dissociation time of the associative groups, τdiss. If τflow ≫ τdiss, then the relaxation of the supramolecular associating polymer is dominated by the relaxation of the precursor chains, whereas the contribution of the supramolecular motifs is negligible. As a result, τrelax ≈ τflow in that case, and according to eq 2, this corresponds to exp(Ea,relax/RT) ≈ exp(Ea,flow/RT), such that Ea,relax ≈ Ea,flow. Vice versa, if τdiss ≫ τflow, then the dissociation time of the transient bonds determines the relaxation of the supramolecular associative polymer, whereas the contribution of the relaxation of the precursor chains can be ignored. In this case, τrelax ≈ τdiss, such that according to eq 2, exp(Ea,relax/RT) ≈ exp(Ea,diss/RT), and thus, Ea,relax ≈ Ea,diss. When τflow and τdiss are of the same order of magnitude, the relaxation of the precursor chains, captured by τflow, and the dissociation of the transient bonds between them,

networks, Ea,relax, and the energy of activation for the relaxation of the corresponding precursor-polymer chains, Ea,flow, can be determined:49 aT = A exp(Ea /RT )

(1)

where Ea is the energy of activation and A is a constant. From eq 1, we calculate Ea,relax ≈ Ea,flow ≈ 50 kJ mol−1 in our work. Alternativley, Ea,relax and Ea,flow can also be estimated by the relaxation time of the supramolecular associative polymers, τrelax, and the relaxation time of the precursor polymer chains, τflow, respectively:76 τ = B exp(Ea /RT )

(2)

where Ea is the energy of activation and B is a constant. Annable et al. showed that the energies of activation calculated by eqs 1 and 2 are identical.77 F

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Scheme 2. Activation of One Hydroxyl Group per Chain of Poly(n-butyl acrylate-ran-hydroxyethyl acrylate) 1 (p = 0) and Ureidopyrimidinone (UPy)-Modified Poly(n-butyl acrylate-ran-hydroxyethyl acrylate) 2 by Reaction with 4-Nitrophenyl Chloroformate (p-NO2PhOC(O)Cl) and Subsequent Reaction with (S)-(+)-4-(3-Aminopyrrolidino)-7-nitrobenzofurazan (NBD) Yields the Fluorescently Labeled Copolymer 3

Scheme 3. Sketch Showing Fluorescently Labeled Tracer Chains Embedded within Supramolecular Networks Transiently Cross-Linked by Quadruple Hydrogen-Bonding between Pendant UPy Groups: (A) Nonsticky Tracers Can Diffuse within the Surrounding Supramolecular Network Matrixes Only Hampered by Topological Constraint Such as Entanglement, Whereas (B) Sticky Tracers Also Temporarily Bind (“Stick”) to the Surrounding Supramolecular Network Matrixes via Quadruple Hydrogen Bonding of Their UPy Motifs, Which Exerts Extra Drag on Their Diffusion

captured by τdiss, contribute equally to the final relaxation of the supramolecular associative polymer (τrelax). Therefore, τrelax can be considered as an average of τflow and τdiss, which has been described in the Cates model32 as τrelax ≈ (τflowτdiss)0.5

considerably, and the frequency dependence of the storage modulus changes from G′ ∼ ω1.84 for the nonsticky precursor chains 1.05 to G′ ∼ ω0.81 for the UPy-functionalized sticky derivative, as seen in Figure 2A. Both these effects are in agreement with similar earlier findings.38 For the single entangled, medium-mass polymer chains, both moduli rise at frequencies lower than 101.5 rad s−1. In addition, we can observe a region in which G′ > G″ in a frequency range of ω = 101.6− 103.0 rad s−1. However, in this region, the difference between G′ and G″ is very low (inset in Figure 2B). Such an effect is observed even more strongly upon functionalization of the high-molar-mass, entangled polymer chains, which extends the region where G′ is greater than G″ to ω = 100.16−103.5 rad s−1 (Figure 2C). In summary, we conclude from these rheological findings that the influence of transient association on the viscoelastic dynamics is less significant in entangled systems than it is in nonentangled ones. To further investigate this notion and to add a deeper, microscopic perspective, we study our samples with microscopic FRAP experiments.

(3)

According to eqs 2 and 3, exp(Ea,relax/RT) ≈ [exp(Ea,flow/RT) exp(Ea,diss/RT)]0.5, and thus, exp(Ea,relax/RT) ≈ 0.5 exp[(Ea,flow + Ea,diss)/RT]. Therefore, Ea,relax is the arithmetic average of Ea,flow and Ea,diss: Ea,relax ≈ (Ea,flow + Ea,diss)/2. As Ea,relax ≈ Ea,flow ≈ 50 kJ mol−1 in our work, Ea,diss is estimated to be ≈50 kJ mol−1 as well. This value is in a good agreement with the energy of activation of a UPy−UPy dissociation in a polar matrix estimated elsewhere.78 The change of the viscoelastic properties of the precursor copolymers after functionalization with UPy groups is markedly dependent on the polymer molar masses and on the extent of chain entanglement related to that. For a nonentangled system, the absolute values of the storage and loss moduli rise G

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Figure 3. (A) Translational diffusion coefficient, D, of the nonsticky tracers as a function of the average number of ureidopyrimidinone (UPy) groups per sticky matrix chain, f. In each case, the tracers have the same molar mass, Mn, as the matrix chains, values of them given in the data set legend. Dashed lines represent scaling-law fits according to phenomenological scaling D ∼ ( f)α, with the apparent power-law exponents α given as the log−log slopes. The values of r-square are greater than 0.95 in all these fits. (B) Translational diffusion coefficient, D, of the nonsticky tracers within plain, nonsticky precursor polymers with molar masses of 5.2, 28.0, and 69.0 kg mol−1. In each case, the tracers have the same molar mass, Mn, as the matrix chains. Each experiment was repeated 5-fold, and the values of D given are the arithmetic mean of this data. Error bars denote the standard deviation.

10−1−102 μm2 s−1, which can be well probed on the time scale of usual short-term (3 min) FRAP experiments. The second fraction shows a significantly slower diffusion speed with very low D values in the order of 10−4−10−2 μm2 s−1, requiring additional long-term (10 h) FRAP experiments to correctly quantify it. We proceed our discussion by first considering only the fastdiffusing fraction. We find that the diffusion coefficients of the nonsticky tracers of this fraction exhibit very little to no dependence on the sticker content of the network matrix, f. This aspect is visualized by the power-law exponent α in the phenomenological scaling of D ∼ (f)α, which is very close to 0, as plotted in Figure 3A. This finding indicates that the matrix UPy association is not a sensitive parameter for the tracer motion. One may interpret this finding from two different, contrary viewpoints. In one view, one may conclude that even at the lowest content of UPy stickers in the matrix, the matrix−polymer association is strong, such that it markedly prolongs the matrix− polymer relaxation time over that of the tracer polymer. This view can be checked with a simple estimate: the lifetime of a binary UPy association in a polar matrix is ∼60 ms.78 By contrast, the average time that a tracer chain with radius of gyration Rg needs to diffuse a distance equal to its own size is τ ≈ Rg2/D,79 which is ∼0.05 ms even for our slowest sample. As a result, on the time scale of motion of their own sizes, all our tracers explore matrixes that are virtually permanently crosslinked, thereby rendering further addition of UPy stickers, and, with that increase of f, unimportant for the diffusion of the tracers. This view can further be elucidated by considering that the diffusion of the nonsticky tracers within the supramolecular polymer−network matrixes (Figure 3A) is much slower than their diffusion inside the plain, nonsticky precursor polymers (Figure 3B), whereas it is not significantly decelerated by further addition of UPy groups (Figure 3A). This observation indicates that once UPy associations are created inside the polymer matrixes, the speed of diffusion of the nonsticky tracers is decelerated, but further addition of UPy content does not have further considerable effect on their diffusion. In a second, contrary view, the sticking of the matrix chains to one another may be concluded to be weak, such that it does not hinder the tracer motion, especially if the tracer is nonsticky

Tracer Polymers. To allow FRAP experiments to be conducted, two different types of tracers are prepared: one tracer type is made by functionalization of 1 mol % of the UPymodified p(BA-ran-HEA) polymers with NBD as a fluorescent dye. These tracers have the same degree of polymerization as the network-matrix chains from which they are derived and can stick to them via the same number of UPy groups; we refer to these as “sticky tracers”. A second tracer type is obtained by tagging the p(BA-ran-HEA) precursor copolymers with NBD without additional functionalization with UPy. These tracers cannot stick to the supramolecular-network matrixes wherein they are embedded. Instead, they are able to diffuse freely within them; we refer to these as “nonsticky tracers”. Both types of tracers are prepared with different molar masses to match those of the unlabeled UPy-modified polymers 2 that form the network matrixes. To bind the fluorescent NBD dye to the copolymers, an average of two hydroxyl groups per chain are activated by reaction with p-nitrophenyl chloroformate and then subjected to further reaction with the amine-functional NBD, as shown in Scheme 2. With these tracers, we perform FRAP experiments on two sets of samples. The first set consists of supramolecular networks hosting the sticky tracers, whereas the second set consists of supramolecular networks hosting the nonsticky tracers. The tracers have the same Mn and, for the sticky tracers, f as the unlabeled matrix chains. By monitoring the diffusion of the sticky tracers that bind to the network matrixes via transient UPy hydrogen bonding, the sticky chain self-diffusion coefficients are determined. In contrast, the nonsticky tracers diffuse through the network without transiently sticking to them and therefore establish a reference system, as illustrated in Scheme 3. Tracer Chain Dynamics in the Supramolecular-Network Matrixes. The diffusive dynamics of both types of linear tracer chains in the transiently cross-linked networks is studied by fluorescence recovery after photobleaching (FRAP). In our study, no perceptibly broad distribution is obtained in any case; instead, each sample shows just two distinct and well-defined diffusion coefficients differing from one another by 2−4 orders of magnitude. From this finding, we conclude that the samples contain two fractions that show markedly different independent mobilities. The first fraction has values of D in the order of H

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precursor polymers is postponed to lower frequencies after functionalization with UPy groups (Figure 2A−C). This finding suggests that also the sticky-tracer diffusion is further decelerated by formation of transient bonds to the matrix chains at higher f. This effect, however, is more pronounced for nonentangled chains that carry less ( f = 0.5−2) associative groups than their highly entangled counterparts with more associative groups (f = 7−20). This is reflected by a power-law exponent α = −0.86 at low Mn, denoting a scaling that is about 3 times steeper than that for entangled tracers (α = −0.29). This difference indicates that entanglements markedly reduce the influence of transient associative interactions on the dynamics of our supramolecular polymer networks. That is in agreement with the results of our macroscopic oscillatory shear study, where we found that the change of the viscoelastic properties of our copolymers upon functionalization with UPy groups is more marked for a nonentangled system. Very recently, Scherman et al. also observed such an effect in semidilute solutions of supramolecular polymers transiently cross-linked by host−guest interacting side groups.80 Also, van Ruymbeke et al. found something similar in the linear viscoelastic properties of telechelic star-shaped pBA and monofunctional linear pBA associated by metal−ligand complexes:81 for both these polymer architectures, the impact of the transient-bond dynamics on the polymer relaxation times is less prominent for high molar masses than for low molar masses. These results and conclusions tie in to and extend previous findings by Hawker, Kramer, and co-workers.49 These colleagues used oscillatory shear rheology to study the relaxation times, τ, of a series of supramolecular polymer networks based on mostly nonentangled p(n-butyl acrylate-ranhexyl acrylate) (Mn = 9.6−32.5 kg mol−1) functionalized with UPy side groups. Their results show that the network dynamics is strongly influenced by the content of UPy groups when it is composed of chains with a molar mass of 24 kg mol−1; in this case, addition of UPy groups to raise f from 7 to 19 prolongs the relaxation time by more than 2 orders of magnitude and makes it exceed 104 s.49 For our samples with a broader range of molar masses (Mn = 5.2−69.0 kg mol−1), we expect a similar reduction of the diffusivity of the tracer chains at high UPy contents, corresponding to extended relaxation times (D ≈ Rg2/ τ).79 While we indeed observe this effect, we also find an even stronger dependence on the extent of entanglement of the polymer matrix. Our highest-molar-mass sample, which has about four entanglement points per chain, is in fact largely unaffected by a change of f. We conclude from this finding that the drag introduced by transient UPy−UPy hydrogen bonds seems to be the prime barrier for the tracer motion in a nonentangled system. Once entanglements form, however, they dominate on the diffusion of the tracers, rendering the contribution from transient associations less significant. This argument is supported by yet another study performed by Creton and co-workers.82,83 They investigated a series of pBA chains with molar masses of 5−100 kg mol−1, each chain functionalized with just a single hydrogen-bonding group at its center. When probing the terminal relaxation time of these polymers, the authors could distinguish two different viscoelastic regimes based on the polymer molar masses. The transition from one to the other occurs around the entanglement molar mass, Me, of pBA. Below Me, the relaxation time drops from ∼100 to ∼10−4 s when the molar mass is raised from 5.2 to 20 kg mol−1. In sharp contrast, above Me, the time

itself and does not participate in any matrix interaction. In our system of study, such a supposedly weak sticker association could be due to the polarity of the OH groups in the polymer samples, which may substantially weaken the UPy binding strength. The lack of a rubbery plateau in the storage modulus of the nonentangled supramolecular sample as well as the just slight raise of this plateau for entangled supramolecular network could be related to this viewpoint. We consider the first viewpoint to be more relevant in this work than the second. We get to this conclusion due to (i) the significantly slower diffusion of the nonsticky tracers in the sticky than in the nonsticky matrixes and (ii) the postponing the terminal relaxation process for all the three polymer samples; both confirm that the lifetime of UPy associations is longer than the time scale of the precursor−polymer relaxation. It should be noted that in both these alternative views, however, the only relevant experimentally variable obstruction of the tracer polymer motion appears to be topological constraints such as chain entanglements. These become more relevant at higher tracer molar masses, whereas matrix-polymer associations add upon that a f ixed additional constraint, with more or less extent depending on whether weak or strong sticker association is present. We further focus on the motion of the sticky tracers, which all have the same f and Mn as the respective unlabeled supramolecular-network matrix chains hosting them. As was true for the nonsticky tracers, the diffusion speed of the sticky tracers is markedly related to the molar mass of the chains: tracers with a high molar mass diffuse much slower than lighter ones do. In regard to f, we observe that the tracer motion is slowed down upon functionalization of the matrix and tracer polymers with a low amount (∼1 mol %) of UPy groups (Figures 3B and 4). This motion is further moderately

Figure 4. Translational diffusion coefficient, D, of the sticky tracers as a function of the average number of ureidopyrimidinone (UPy) groups per sticky matrix and tracer chain, f. The sticky tracers have the same content of associative groups, f, and molar mass, Mn, as the hosting supramolecular-network chains, values of the latter given in the data set legend. The dashed lines represent scaling-law fits of D ∼ ( f)α, with the power-law exponents α given as the slope of the data sets in the log−log plots. The values of r-square are greater than 0.95 in all these fits. Each experiment was repeated 5-fold, and the values of D given are the arithmetic mean. Error bars denote the standard deviation.

decelerated at higher sticker contents. While the apparent scaling exponents α are almost 0 for our nonsticky tracers, their values are between −0.3 and −0.9 for the sticky tracers, as illustrated in Figure 4. This deceleration of the tracer motion is in agreement with the results of our rheological measurements, which show that the terminal relaxation process of the I

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Macromolecules scale of polymer relaxation is extended from ∼10−2 to ∼100 s by raising the molar mass from 40 to 100 kg mol−1. Because Creton’s and co-workers’ samples had only a single associative group, high molar masses of the polymer chains translate to low mole percentages of associative groups in them, which reduces the contribution of the associative bonds significantly. Probing a chemically equivalent but nonassociative reference system revealed no such split viscoelastic regimes: the relaxation times of these chains increase regularly with the chain molar mass. These results support our hypothesis stated above: as soon as entanglements are present in the system, the influence of supramolecular associations on the chain dynamics is less prominent. Unlike as in the work by Creton and co-workers, this is true even when the entangled supramolecular network contains more transient bonds than the nonentangled one. A comparison of the diffusivities of our sticky and nonsticky tracers with the same chain length shows that the ratio of their diffusion coefficients strongly depends on the average chain length between the associating groups of the matrixes into which they are embedded. This is however, found in a counterintuitive order, as illustrated in Figure 5: When LUPy >

two UPy groups within the matrix is high (LUPy > 76), resulting in a change of RD < 1 to RD > 1 as this distance gets smaller, as shown in Figure 5. A more thorough investigation of this hypothesis will be subject to future investigations by our group as well as other groups as we hope. For theoretical assessment, we compare the results of this work with the Rubinstein−Semenov theories of sticky Rouse dynamics and sticky reptation.36,37 In these theories, the concept of a renormalized bond lifetime, τ*b, is introduced. This is the time it takes for a sticker to bind to a new partner after dissociating from an old one, which may encompass multiple events of recombination with the old partner first. It can be assumed that there is a mutual interplay between τ*b and Mn in the entangled regime: chains with a higher number of entanglements have less possibility to diffuse away from one another, which extends τ*b. According to the theories by Rubinstein and Semenov, the relaxation time, τ, of a side-sticky polymer is high at high Mn and associative group content, f, obeying power-law relationships. The values of the diffusion coefficients determined in our study are in line with this assumption: tracers with a high f and Mn have low D values, as seen in Figure 4. Rubinstein’s and Semenov’s theories define a τ( f)-scaling exponent, which is connected to our D(f)-scaling exponent by the relation D ≈ Rg2/τ.79 This parameter is found to be constant and independent of Mn within each concentration regime of the Rubinstein−Semenov polymer-solution-based assessment. In stark contrast, we find that in the melt state, the D(f)-scaling exponent varies systematically with the molar mass of the chains. Since the extent of entanglement in a polymer solution depends not only on the polymer molar mass but also on the polymer concentration, an interdependency of transient binding and entanglement, noticeable by a change of the τ(f)-scaling exponent with concentration, might be anticipated in the Rubinstein−Semenov theories as well. Nevertheless, in these theories, this interdependency is only assessed as a function of the polymer concentration, but not as a function of the polymer molar mass. We interpret this discrepancy to be due to different influences of Mn on τ*b in the melt vs solution states. While these effects are present in solution, they are not as pronounced as in the melt because in the latter, the segmental density is much higher. This means that the effects of τ*b and Mn on the polymer chain diffusion are generally much stronger in the melt than in solution, which is recognizable from the variation of the parameter α as a function of Mn. Aside from the diffusion processes discussed allover above, a second, much less mobile fraction could be detected in our samples, exhibiting diffusivities in the range of only 10−2−10−1 μm2 s−1, as quantified in a set of additional 10 h FRAP experiments. This very marked deceleration of the chain diffusion can be related to nanophase separation of UPy dimers into collective assemblies by π−π stacking.89−91 Polymer segments that enter more than one of these assemblies are trapped and cannot relax by fluctuation and reptation, but instead, only by Rouse-type motion and later, when their entanglements with other chains are relaxed, by an activated constraint-release Rouse process.92 On basis of these arguments, we assume that some such trapped chain segments show a much slower mobility in our FRAP experiments. This second, slower type of chain dynamics, nevertheless, is well separated from and independent of the first, faster one. This is justified by the well-separated values of the diffusion coefficients of the trapped chains, as quantified in 10 h FRAP experiments, which

Figure 5. Ratio of the translational diffusion coefficient of our sticky tracers to that of our nonsticky tracers, RD, as a function of the average number of repeating units between two ureidopyrimidinone (UPy) groups, LUPy, in the supramolecular polymer-network matrixes hosting the tracers. All tracers have the same molar mass, Mn, as the sticky matrix chains, which are 5.2, 28, and 69 kg mol−1, allocated to the data sets as indicated by the legend in the figure. The sticky tracers also have the same LUPy as their hosting-supramolecular matrixes.

76, the sticky tracers explore the supramolecular networks faster than the nonsticky tracers, with a ratio RD = Dsticky‑tracer/ Dnonsticky‑tracer greater than unity for each molar mass. As LUPy is reduced, Dsticky‑tracer approaches Dnonsticky‑tracer for all samples. It is visible in Figure 5 that when 40 < LUPy > 46, the value of RD is ≈1. At LUPy < 28, the sticky tracers diffuse slower than the nonsticky tracers; in this case, we find values of RD of less than 1. These counterintuitive findings suggest that additional effects play a role on the tracer-chain diffusion, counteracting their intuitive obstruction due to chain entanglement and transient binding. In this context, we hypothesize the difference of polarity between the nonsticky tracers and their surrounding UPy-modified matrixes to be a relevant parameter. The diffusivity of polymer chains within a polymer matrix of different molecular structure depends on their miscibility within this matrix.84−86 It was shown that for two tracers with different molecular structures, the tracer with the better miscibility within the matrix shows faster diffusion than the other.87,88 In our present study, such better miscibility of the sticky and nonsticky tracers can be found when the average distance of J

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“Material Science in Mainz” (MAINZ), allowing A.J. to visit the Seiffert group in Berlin (2015−2016) and Mainz (2017−2018) to conduct the studies. We thank Axel Habicht for initial assistance with FRAP experiments. We express our special gratitude to the reviewers of this paper, who gave rich criticism plus suggestions for improvement of the work.

occur as an independent fraction about 3 orders of magnitude slower than the values of the diffusion coefficients of the nontrapped chains, as quantified in regular 3 min FRAP experiments. On the basis of this separation, we treat these two kinds of dynamics independent of one another and discuss the fast dynamics on the grounds of an idealizing model, as done in all our preceding discussion above. Note that in recent literature, such trapped chains have also been attributed to a second plateau of the storage-moduli curves at low frequencies.40,93,94 We do not see such a second plateau in any of our rheology data though, which leads us to conclude that the detected collective assemblies detected in the FRAP experiments are too weak to stand the shear stress applied in rheological tests.

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4. CONCLUSION The presence of chain entanglement markedly outweighs the influence of transient associative interactions on the dynamics of ureidopyrimidinone (UPy) side-group associating polymers in the melt state. The diffusion of nonsticky tracer chains in such transiently side-group associating network matrixes is independent of the associative group content of the matrix chains, f. The diffusion of sticky tracers is decelerated by formation of transient bonds to the matrix at raising f, but this deceleration gets weaker at stronger chain entanglement. In a semiquantitative assessment, the exponent α in a phenomenological scaling law of D ∼ ( f)α is almost 0 for the nonsticky tracers, whereas its values are between −0.3 and −0.9 for the sticky tracers, being systematically weaker at larger extent of entanglement. Thus, the contribution of transient associations on the chain diffusion is less significant in a network with highmolar-mass matrix chains. This conclusion could explain the observation of Alvarez et al. about the relatively low influence of hydrogen bindings on dynamics of highly entangled randomly hydrolyzed pBA chains.38 This conclusion has also been reported for other supramolecular associative pBA systems that have either different architectures (linear telechelic or starshape) or different sticker content (one sticker per linear chains or star arm).81 Further massive deceleration of the chain diffusion is exerted by trapping of polymer chains between UPy stacks. Our findings provide a systematic assessment of the interplay of chain relaxation, as assessed by polymer physics, and chain-supramolecular association, as assessed by supramolecular chemistry, on the dynamics of supramolecular polymer networks, which may provide a basis for further systematic assessment of their favorable properties such as adaptiveness and self-healing.

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REFERENCES

(1) Brunsveld, L.; Folmer, B. J.; Meijer, E. W.; Sijbesma, R. P. Supramolecular Polymers. Chem. Rev. 2001, 101, 4071−4098. (2) van Gemert, G. M.; Peeters, J. W.; Söntjens, S. H.; Janssen, H. M.; Bosman, A. W. Self-Healing Supramolecular Polymers in Action. Macromol. Chem. Phys. 2012, 213, 234−242. (3) Herbst, F.; Seiffert, S.; Binder, W. H. Dynamic Supramolecular Poly (Isobutylene) for Self-Healing Materials. Polym. Chem. 2012, 3, 3084−3092. (4) Takashima, Y.; Yonekura, K.; Koyanagi, K.; Iwaso, K.; Nakahata, M.; Yamaguchi, H.; Harada, A. Multifunctional Stimuli-Responsive Supramolecular Materials with Stretching, Coloring, and Self-Healing Properties Functionalized via Host−Guest Interactions. Macromolecules 2017, 50, 4144−4150. (5) Kumpfer, J. R.; Rowan, S. J. Thermo-, Photo-, and ChemoResponsive Shape-Memory Properties from Photo-Cross-Linked Metallo-Supramolecular Polymers. J. Am. Chem. Soc. 2011, 133, 12866−12874. (6) Schott, M.; Lorrmann, H.; Szczerba, W.; Beck, M.; Kurth, D. G. State-of-the-art Electrochromic Materials Based on Metallo-Supramolecular Polymers. Sol. Energy Mater. Sol. Cells 2014, 126, 68−73. (7) Bastings, M. M.; Koudstaal, S.; Kieltyka, R. E.; Nakano, Y.; Pape, A. C.; Feyen, D. A.; van Slochteren, F. J.; Doevendans, P. A.; Sluijter, J. P.; Meijer, E. W.; Chamuleau, S. A.; Dankers, P. Y. A Fast pHSwitchable and Self-Healing Supramolecular Hydrogel Carrier for Guided, Local Catheter Injection in the Infarcted Myocardium. Adv. Healthcare Mater. 2014, 3, 70−78. (8) Dankers, P. Y.; van Luyn, M. J.; Huizinga-van der Vlag, A.; van Gemert, G. M.; Petersen, A. H.; Meijer, E. W.; Janssen, H. M.; Bosman, A. W.; Popa, E. R. Development and In-vivo Characterization of Supramolecular Hydrogels for Intrarenal Drug Delivery. Biomaterials 2012, 33, 5144−5155. (9) Lehn, J. M. Dynamers: Dynamic Molecular and Supramolecular Polymers. Prog. Polym. Sci. 2005, 30, 814−831. (10) Beck, J. B.; Rowan, S. J. Multistimuli, Multiresponsive MetalloSupramolecular Polymers. J. Am. Chem. Soc. 2003, 125, 13922−13923. (11) Wang, P.; Xing, H.; Xia, D.; Ji, X. A Novel Supramolecular Polymer Gel Constructed by Crosslinking Pillar [5] Arene-based Supramolecular Polymers Through Metal−ligand Interactions. Chem. Commun. 2015, 51, 17431−17434. (12) Holder, E.; Langeveld, B. M.; Schubert, U. S. New Trends in the Use of Transition Metal−Ligand Complexes for Applications in Electroluminescent Devices. Adv. Mater. 2005, 17, 1109−1121. (13) Whittell, G. R.; Hager, M. D.; Schubert, U. S.; Manners, I. Functional Soft Materials from Metallopolymers and Metallosupramolecular Polymers. Nat. Mater. 2011, 10, 176−188. (14) Rowan, S. J.; Beck, J. B. Metal-Ligand Induced Supramolecular Polymerization: a Route to Responsive Materials. Faraday Discuss. 2005, 128, 43−53. (15) Liang, B.; Tong, R.; Wang, Z.; Guo, S.; Xia, H. High Intensity Focused Ultrasound Responsive Metallo-Sbupramolecular Block Copolymer Micelles. Langmuir 2014, 30, 9524−9532. (16) Gu, R.; Yao, J.; Fu, X.; Zhou, W.; Qu, D. H. A Hyperbranched Supramolecular Polymer Constructed by Orthogonal Triple Hydrogen Bonding and Host−Guest Interactions. Chem. Commun. 2015, 51, 5429−5431. (17) Folmer, B. J.; Sijbesma, R.; Versteegen, R.; Van der Rijt, J.; Meijer, E. Supramolecular Polymer Materials: Chain Extension of Telechelic Polymers Using a Reactive Hydrogen-Bonding Synthon. Adv. Mater. 2000, 12, 874−878.

AUTHOR INFORMATION

Corresponding Authors

*(S.S.) E-mail sebastain.seiff[email protected]; Tel +49 6131 39 23887. *(S.R.G.) E-mail: sr_ghaff[email protected]; Tel +98 21 64542402. ORCID

Sebastian Seiffert: 0000-0002-5152-1207 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work has been supported by a travel grant of the Iranian Ministry of Science and by the Graduate School of Excellence K

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Macromolecules (18) Chen, S.; Lechner, B. D.; Meister, A.; Binder, W. H. Hierarchical Micelles via Polyphilic Interactions: Hydrogen-Bonded Supramolecular Dendrons and Double Immiscible Polymers. Nano Lett. 2016, 16, 1491−1496. (19) Farnik, D.; Kluger, C.; Kunz, M. J.; Machl, D.; Petraru, L.; Binder, W. H. Synthesis and Self Assembly of Hydrogen-Bonded Supramolecular Polymers. Macromol. Symp. 2004, 217, 247−266. (20) Faul, C. F. Ionic Self-Assembly for Functional Hierarchical Nanostructured Materials. Acc. Chem. Res. 2014, 47, 3428−3438. (21) Bose, R. K.; Hohlbein, N.; Garcia, S. J.; Schmidt, A. M.; van der Zwaag, S. Relationship Between the Network Dynamics, Supramolecular Relaxation Time and Healing Kinetics of Cobalt Poly (Butyl Acrylate) Ionomers. Polymer 2015, 69, 228−232. (22) Bose, R. K.; Hohlbein, N.; Garcia, S. J.; Schmidt, A. M.; van der Zwaag, S. Connecting Supramolecular Bond Lifetime and Network Mobility for Scratch Healing in Poly(Butyl Acrylate) Ionomers Containing Sodium, Zinc and Cobalt. Phys. Chem. Chem. Phys. 2015, 17, 1697−1704. (23) Burattini, S.; Greenland, B. W.; Merino, D. H.; Weng, W.; Seppala, J.; Colquhoun, H. M.; Hayes, W. C.; Mackay, M. E.; Hamley, I. W.; Rowan, S. J. A Healable Supramolecular Polymer Blend Based on Aromatic π−π Stacking and Hydrogen-Bonding Interactions. J. Am. Chem. Soc. 2010, 132, 12051−12058. (24) Appel, E. A.; Biedermann, F.; Rauwald, U.; Jones, S. T.; Zayed, J. M.; Scherman, O. A. Supramolecular Cross-Linked Networks via Host−Guest Complexation with Cucurbit[8]uril. J. Am. Chem. Soc. 2010, 132, 14251−14260. (25) Yang, H.; Yuan, B.; Zhang, X.; Scherman, O. A. Supramolecular Chemistry at Interfaces: Host−Guest Interactions forFabricating Multifunctional Biointerfaces. Acc. Chem. Res. 2014, 47, 2106−2115. (26) Zhang, M.; Xu, D.; Yan, X.; Chen, J.; Dong, S.; Zheng, B.; Huang, F. Self-Healing Supramolecular Gels Formed by Crown Ether Based Host-Guest Interactions. Angew. Chem. 2012, 124, 7117−7121. (27) Yan, X.; Wang, F.; Zheng, B.; Huang, F. Stimuli-Responsive Supramolecular Polymeric Materials. Chem. Soc. Rev. 2012, 41, 6042− 6065. (28) Hackelbusch, S.; Rossow, T.; van Assenbergh, P.; Seiffert, S. Chain Dynamics in Supramolecular Polymer Networks. Macromolecules 2013, 46, 6273−6286. (29) Seiffert, S.; Sprakel, J. Physical Chemistry of Supramolecular Polymer Networks. Chem. Soc. Rev. 2012, 41, 909−930. (30) Sivakova, S.; Bohnsack, D. A.; Mackay, M. E.; Suwanmala, P.; Rowan, S. J. Utilization of a Combination of Weak Hydrogen-Bonding Interactions and Phase Segregation to Yield Highly Thermosensitive Supramolecular Polymers. J. Am. Chem. Soc. 2005, 127, 18202−18211. (31) Goldansaz, H.; van Ruymbeke, E.; Gohy, J. F.; Fustin, C. A.; Ries, M. E.; Bailly, C. Local Molecular Dynamics and Heterogeneity in PEO-NiCl2 Supramolecular Networks. Macromolecules 2015, 48, 2290−2298. (32) Cates, M. Reptation of Living Polymers: Dynamics of Entangled Polymers in the Presence of Reversible Chain-Scission Reactions. Macromolecules 1987, 20, 2289−2296. (33) Cates, M.; Candau, S. Statics and Dynamics of Worm-Like Surfactant Micelles. J. Phys.: Condens. Matter 1990, 2, 6869−6892. (34) Leibler, L.; Rubinstein, M.; Colby, R. H. Dynamics of Reversible Networks. Macromolecules 1991, 24, 4701−4707. (35) Semenov, A. N.; Rubinstein, M. Thermoreversible Gelation in Solutions of Associative Polymers. 1. Statics. Macromolecules 1998, 31, 1373−1385. (36) Rubinstein, M.; Semenov, A. N. Thermoreversible Gelation in Solutions of Associating Polymers. 2. Linear Dynamics. Macromolecules 1998, 31, 1386−1397. (37) Rubinstein, M.; Semenov, A. N. Dynamics of Entangled Solutions of Associating Polymers. Macromolecules 2001, 34, 1058− 1068. (38) Shabbir, A.; Goldansaz, H.; Hassager, O.; van Ruymbeke, E.; Alvarez, N. J. Effect of Hydrogen Bonding on Linear and Nonlinear Rheology of Entangled Polymer Melts. Macromolecules 2015, 48, 5988−5996.

(39) Ahmadi, M.; Hawke, L. G.; Goldansaz, H.; van Ruymbeke, E. Dynamics of Entangled Linear Supramolecular Chains with Sticky Side Groups: Influence of Hindered Fluctuations. Macromolecules 2015, 48, 7300−7310. (40) Hawke, L.; Ahmadi, M.; Goldansaz, H.; Van Ruymbeke, E. Viscoelastic Properties of Linear Associating Poly (n-butyl acrylate) Chains. J. Rheol. 2016, 60, 297−310. (41) Lewis, C. L.; Stewart, K.; Anthamatten, M. The Influence of Hydrogen Bonding Side-Groups on Viscoelastic Behavior of Linear and Network Polymers. Macromolecules 2014, 47, 729−740. (42) Shabbir, A.; Javakhishvili, I.; Cerveny, S.; Hvilsted, S.; Skov, A. L.; Hassager, O.; Alvarez, N. J. Linear Viscoelastic and Dielectric Relaxation Response of Unentangled UPy-Based Supramolecular Networks. Macromolecules 2016, 49, 3899−3910. (43) Yamauchi, K.; Lizotte, J. R.; Hercules, D. M.; Vergne, M. J.; Long, T. E. Combinations of Microphase Separation and Terminal Multiple Hydrogen Bonding in Novel Macromolecules. J. Am. Chem. Soc. 2002, 124, 8599−8604. (44) Yamauchi, K.; Kanomata, A.; Inoue, T.; Long, T. E. Thermoreversible Polyesters Consisting of Multiple Hydrogen Bonding (MHB). Macromolecules 2004, 37, 3519−3522. (45) Mather, B. D.; Lizotte, J. R.; Long, T. E. Synthesis of Chain End Functionalized Multiple Hydrogen Bonded Polystyrenes and Poly (Alkyl Acrylates) Using Controlled Radical Polymerization. Macromolecules 2004, 37, 9331−9337. (46) McKee, M. G.; Elkins, C. L.; Park, T.; Long, T. E. Influence of Random Branching on Multiple Hydrogen Bonding in Poly (Alkyl Methacrylate)s. Macromolecules 2005, 38, 6015−6023. (47) Elkins, C. L.; Park, T.; McKee, M. G.; Long, T. E. Synthesis and Characterization of Poly (2-Ethylhexyl Methacrylate) Copolymers Containing Pendant, Self-Complementary Multiple-Hydrogen-Bonding Sites. J. Polym. Sci., Part A: Polym. Chem. 2005, 43, 4618−4631. (48) Mather, B. D.; Elkins, C. L.; Beyer, F. L.; Long, T. E. Morphological Analysis of Telechelic Ureidopyrimidone Functional Hydrogen Bonding Linear and Star-Shaped Poly (ethylene-copropylene)s. Macromol. Rapid Commun. 2007, 28, 1601−1606. (49) Feldman, K. E.; Kade, M. J.; Meijer, E.; Hawker, C. J.; Kramer, E. J. Model Transient Networks From Strongly Hydrogen-Bonded Polymers. Macromolecules 2009, 42, 9072. (50) Goldansaz, H.; Voleppe, Q.; Pioge, S.; Fustin, C. A.; Gohy, J. F.; Brassinne, J.; Auhl, D.; Van Ruymbeke, E. Controlling The Melt Rheology of Linear Entangled Metallo-Supramolecular Polymers. Soft Matter 2015, 11, 762−774. (51) Goldansaz, H.; Auhl, D.; Goderis, B.; Voleppe, Q.; Fustin, C. A.; Gohy, J. F.; Bailly, C.; van Ruymbeke, E. Transient Metallosupramolecular Networks Built from Entangled Melts of Poly (Ethylene Oxide). Macromolecules 2015, 48, 3746−3755. (52) Hirschberg, J. K.; Beijer, F. H.; van Aert, H. A.; Magusin, P. C.; Sijbesma, R. P.; Meijer, E. Supramolecular Polymers from Linear Telechelic Siloxanes with Quadruple-Hydrogen-Bonded Units. Macromolecules 1999, 32, 2696−2705. (53) Knoben, W.; Besseling, N.; Bouteiller, L.; Cohen Stuart, M. Dynamics of Reversible Supramolecular Polymers: Independent Determination of the Dependence of Linear Viscoelasticity on Concentration and Chain Length by Using Chain Stoppers. Phys. Chem. Chem. Phys. 2005, 7, 2390−2398. (54) Hayashi, M.; Noro, A.; Matsushita, Y. Viscoelastic properties of supramolecular soft materials with transient polymer network. J. Polym. Sci., Part B: Polym. Phys. 2014, 52, 755−764. (55) Yan, T.; Schröter, K.; Herbst, F.; Binder, W. H.; ThurnAlbrecht, T. Nanostructure and Rheology of Hydrogen-Bonding Telechelic Polymers in the Melt: From Micellar Liquids and Solids to Supramolecular Gels. Macromolecules 2014, 47, 2122−2130. (56) Yan, T.; Schröter, K.; Herbst, F.; Binder, W. H.; ThurnAlbrecht, T. What Controls the Structure and the Linear and Nonlinear Rheological Properties of Dense, Dynamic Supramolecular Polymer Networks? Macromolecules 2017, 50, 2973−2985. L

DOI: 10.1021/acs.macromol.7b02180 Macromolecules XXXX, XXX, XXX−XXX

Article

Macromolecules

(75) Colby, R.; Rubinstein, M. Polymer Physics; Oxford University Press: Oxford, 2003; pp 274−281. (76) Vermonden, T.; van Steenbergen, M. J.; Besseling, N. A.; Marcelis, A. T.; Hennink, W. E.; Sudholter, E. J.; Cohen Stuart, M. A. Linear Rheology of Water-Soluble Reversible Neodymium (III) Coordination Polymers. J. Am. Chem. Soc. 2004, 126, 15802−15808. (77) Annable, T.; Buscall, R.; Ettelaie, R.; Whittlestone, D. The rheology of solutions of associating polymers: Comparison of experimental behavior with transient network theory. J. Rheol. 1993, 37, 695−726. (78) Söntjens, S. H.; Sijbesma, R. P.; van Genderen, M. H.; Meijer, E. Stability and Lifetime of Quadruply Hydrogen Bonded 2-Ureido-4 [1 H]-Pyrimidinone Dimers. J. Am. Chem. Soc. 2000, 122, 7487−7493. (79) De Gennes, P. Dynamics of Entangled Polymer Solutions. I. The Rouse model. Macromolecules 1976, 9, 587−593. (80) Tan, C. S. Y.; Agmon, G.; Liu, J.; Hoogland, D.; Janecek, E.-R.; Appel, E.; Scherman, O. A. Distinguishing Relaxation Dynamics in Transiently Crosslinked Polymeric Networks. Polym. Chem. 2017, 8, 5336−5343. (81) Zhuge, F.; Hawke, L. G.; Fustin, C. A.; Gohy, G. F.; Van Ruymbeke, E. Decoding the linear viscoelastic properties of model telechelic metallo-supramolecular polymers. J. Rheol. 2017, 61, 1245. (82) Callies, X.; Fonteneau, C.; Véchambre, C.; Pensec, S.; Chenal, J. M.; Chazeau, L.; Bouteiller, L.; Ducouret, G.; Creton, C. Linear Rheology of Bis-Urea Functionalized Supramolecular Poly (Butylacrylate): Part I−Weak Stickers. Polymer 2015, 69, 233−240. (83) Callies, X.; Véchambre, C.; Fonteneau, C.; Pensec, S.; Chenal, J. M.; Chazeau, L.; Bouteiller, L.; Ducouret, G.; Creton, C. Linear Rheology of Supramolecular Polymers Center-Functionalized with Strong Stickers. Macromolecules 2015, 48, 7320−7326. (84) Brochard, F.; Jouffroy, J.; Levinson, P. Polymer-Polymer Diffusion in Melts. Macromolecules 1983, 16, 1638−1641. (85) Klein, J. Interdiffusion of Polymers. Science 1990, 250, 640−646. (86) De Gennes, P. Dynamics of Fluctuations and Spinodal Decomposition in Polymer Blends. J. Chem. Phys. 1980, 72, 4756− 4763. (87) Composto, R. J.; Mayer, J. W.; Kramer, E. J.; White, D. M. Fast Mutual Diffusion in Polymer Blends. Phys. Rev. Lett. 1986, 57, 1312− 1315. (88) Kanetakis, J.; Fytas, G. Mutual Diffusion in Compatible Polymer Blends. Macromolecules 1989, 22, 3452−3458. (89) Appel, W. P.; Portale, G.; Wisse, E.; Dankers, P. Y.; Meijer, E. Aggregation of Ureido-pyrimidinone Supramolecular Thermoplastic Elastomers into Nanofibers: a Kinetic Analysis. Macromolecules 2011, 44, 6776−6784. (90) Nieuwenhuizen, M. M.; de Greef, T. F.; van der Bruggen, R. L.; Paulusse, J. M.; Appel, W. P.; Smulders, M. M.; Sijbesma, R. P.; Meijer, E. Self-Assembly of Ureido-Pyrimidinone Dimers into One-Dimensional Stacks by Lateral Hydrogen Bonding. Chem. - Eur. J. 2010, 16, 1601−1612. (91) Van Beek, D.; Spiering, A.; Peters, G. W.; Te Nijenhuis, K.; Sijbesma, R. P. Unidirectional Dimerization and Stacking of Ureidopyrimidinone End Groups in Polycaprolactone Supramolecular Polymers. Macromolecules 2007, 40, 8464−8475. (92) Goldansaz, H.; Fustin, C. A.; Wubbenhorst, M.; van Ruymbeke, E. How Supramolecular Assemblies Control Dynamics of Associative Polymers: Toward a General Picture. Macromolecules 2016, 49, 1890− 1902. (93) Jangizehi, A.; Ghaffarian, S. R.; Ahmadi, M. Dynamics of Entangled Supramolecular Polymer Networks in Presence of HighOrder Associations of Strong Hydrogen Bonding Groups. Polym. Adv. Technol. 2018, 29, 726−735. (94) Jangizehi, A.; Ghaffarian, S. R.; Nikravan, G.; Jamalpour, S. Thermal and viscoelastic properties of entangled supramolecular polymer networks as a powerful tool for prediction of their microstructure. Thermochim. Acta 2018, 661, 34−40.

(57) Lu, Q.; Solomon, M. J. Probe Size Effects on the Microrheology of Associating Polymer Solutions. Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 2002, 66, 061504. (58) van der Gucht, J.; Besseling, N. A.; Knoben, W.; Bouteiller, L.; Cohen Stuart, M. A. Brownian Particles in Supramolecular Polymer Solutions. Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 2003, 67, 051106. (59) Sprakel, J.; van der Gucht, J.; Cohen Stuart, M. A.; Besseling, N. A. Brownian Particles in Transient Polymer Networks. Phys. Rev. E 2008, 77, 061502. (60) Li, J.; Sullivan, K. D.; Brown, E. B.; Anthamatten, M. Thermally Activated Diffusion in Reversibly Associating Polymers. Soft Matter 2010, 6, 235−238. (61) Zhang, Z.; Luo, Y.; Chen, J.; Dong, S.; Yu, Y.; Ma, Z.; Huang, F. Formation of Linear Supramolecular Polymers That Is Driven by CH··· π Interactions in Solution and in the Solid State. Angew. Chem., Int. Ed. 2011, 50, 1397−1401. (62) Yan, X.; Li, S.; Pollock, J. B.; Cook, T. R.; Chen, J.; Zhang, Y.; Ji, X.; Yu, Y.; Huang, F.; Stang, P. J. Supramolecular Polymers with Tunable Topologies via Hierarchical Coordination-Driven SelfAssembly and Hydrogen Bonding Interfaces. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 15585−15590. (63) Schulze, B. M.; Watkins, D. L.; Zhang, J.; Ghiviriga, I.; Castellano, R. K. Estimating the Shape and Size of Supramolecular Assemblies by Variable Temperature Diffusion Ordered Spectroscopy. Org. Biomol. Chem. 2014, 12, 7932−7936. (64) Tang, S.; Habicht, A.; Li, S.; Seiffert, S.; Olsen, B. D. SelfDiffusion of Associating Star-Shaped Polymers. Macromolecules 2016, 49, 5599−5608. (65) Chiefari, J.; Chong, Y. K.; Ercole, F.; Krstina, J.; Jeffery, J.; Le, T. P. T.; Mayadunne, R. T. A.; Meijs, G. F.; Moad, C. L.; Moad, G.; Rizzardo, E.; Thang, S. H. Living Free-Radical Polymerization by Reversible Addition−Fragmentation Chain Transfer: The RAFT Process. Macromolecules 1998, 31, 5559−5562. (66) Moad, G.; Rizzardo, E.; Thang, S. H. Radical Addition− Fragmentation Chemistry in Polymer Synthesis. Polymer 2008, 49, 1079−1131. (67) Sijbesma, R. P.; Beijer, F. H.; Brunsveld, L.; Folmer, B. J.; Hirschberg, J. K.; Lange, R. F.; Lowe, J. K.; Meijer, E. Reversible Polymers Formed From Self-Complementary Monomers Using Quadruple Hydrogen Bonding. Science 1997, 278, 1601−1604. (68) Meng, Y.; Fenoli, C. R.; Aguirre-Soto, A.; Bowman, C. N.; Anthamatten, M. Photoinduced Diffusion Through Polymer Networks. Adv. Mater. 2014, 26, 6497−6502. (69) Rapp, P. B.; Omar, A. K.; Shen, J. J.; Buck, M. E.; Wang, Z.-G.; Tirrell, D. A. Analysis and Control of Chain Mobility in Protein Hydrogels. J. Am. Chem. Soc. 2017, 139, 3796−3804. (70) Cinar, G.; Ozdemir, A.; Hamsici, S.; Gunay, G.; Dana, A.; Tekinay, A. B.; Guler, M. O. Local Delivery of Doxorubicin Through Supramolecular Peptide Amphiphile Nanofiber Gels. Biomater. Sci. 2017, 5, 67−76. (71) Chernikova, E.; Morozov, A.; Leonova, E.; Garina, E.; Golubev, V.; Bui, C.; Charleux, B. Controlled Free-Radical Polymerization of nButyl Acrylate by Reversible Addition− Fragmentation Chain Transfer in the Presence of tert-Butyl Dithiobenzoate. A Kinetic Study. Macromolecules 2004, 37, 6329−6339. (72) Hauser, G.; Seiffert, S.; Oppermann, W. Systematic Evaluation of FRAP Experiments Performed in a Confocal Laser Scanning Microscope−Part II: Multiple Diffusion Processes. J. Microsc. 2008, 230, 353−362. (73) Mun, G. A.; Nurkeeva, Z. S.; Beissegul, A. B.; Dubolazov, A. V.; Urkimbaeva, P. I.; Park, K.; Khutoryanskiy, V. V. TemperatureResponsive Water-Soluble Copolymers Based on 2-Hydroxyethyl Acrylate and Butyl Acrylate. Macromol. Chem. Phys. 2007, 208, 979− 987. (74) Jullian, N.; Leonardi, F.; Grassl, B.; Peyrelasse, J.; Derail, C. Rheological Characterization and Molecular Modeling of Poly (nButyl Acrylate). Appl. Rheol. 2010, 20, 33685−33696. M

DOI: 10.1021/acs.macromol.7b02180 Macromolecules XXXX, XXX, XXX−XXX