Controlling Short-Range Interactions by Tuning ... - ACS Publications

Article pubs.acs.org/JPCB

Controlling Short-Range Interactions by Tuning Surface Chemistry in HDPE/Graphene Nanoribbon Nanocomposites Soheil Sadeghi, Alireza Zehtab Yazdi, and Uttandaraman Sundararaj* Polymer Processing Group, Department of Chemical and Petroleum Engineering, University of Calgary, 2500 University Dr, NW Calgary, AB T2N1N4, Canada S Supporting Information *

ABSTRACT: Unique dispersion states of nanoparticles in polymeric matrices have the potential to create composites with enhanced mechanical, thermal, and electrical properties. The present work aims to determine the state of dispersion from the melt-state rheological behavior of nanocomposites based on carbon nanotube and graphene nanoribbon (GNR) nanomaterials. GNRs were synthesized from nitrogen-doped carbon nanotubes via a chemical route using potassium permanganate and some second acids. High-density polyethylene (HDPE)/GNR nanocomposite samples were then prepared through a solution mixing procedure. Different nanocomposite dispersion states were achieved using different GNR synthesis methods providing different surface chemistry, interparticle interactions, and internal compartments. Prolonged relaxation of flow induced molecular orientation was observed due to the presence of both carbon nanotubes and GNRs. Based on the results of this work, due to relatively weak interactions between the polymer and the nanofillers, it is expected that short-range interactions between nanofillers play the key role in the final dispersion state.

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INTRODUCTION The performance of nanofillers for improving physicomechanical properties of polymeric matrices can be tremendously impacted by the inherent properties of the nanofiller, state of dispersion, interfacial chemistry, and nanoscopic morphology. Polymer chains’ diffusive motion in the interfacial region is predicted to be significantly affected by the presence of welldispersed nanoparticles for distances up to several radii of gyration of the bulk unconstrained polymer chain.1,2 This can lead to the formation of a percolated network of near-surface regions with modified chain mobility which, presumably, can create composites with superior mechanical and thermal properties.3 Better dispersion states, providing enormous surface area per volume, are believed to be the main prerequisite for achieving such interconnected interphase regions. Among carbon-based nanofillers, carbon nanotubes (CNTs) have received extensive attention due to their inherent electrical4 and mechanical properties.5,6 Electrical percolation was achieved for single-walled carbon nanotube/epoxy nanocomposites at loadings as low as 0.005 wt %.7 The practicality of attaining the desired dispersion state, however, remained a major challenge for most polymeric matrices. Carbon nanotubes can be fully dispersed in viscous matrices under an external flow field.8,9 Due to very strong attractive interactions between neighboring tubes (U/kBT ∼ 3510), they will reaggregate upon discontinuing the external flow field. It would be useful to avoid and/or disable attractive interactions © 2015 American Chemical Society

to stabilize the state of dispersion attained during shearing stage. This was found to be possible through both experimental and theoretical procedures.10 Chemical doping,11,12 along with covalent13 and noncovalent14 functionalization of carbon nanotubes, are among the most widely used methods to stabilize the state of dispersion. Graphene nanoplatelets (GNPs)15−20 produced using different methods were also extensively examined as nanofiller for polymeric matrices. Chemical modification, solution exfoliation, and in situ reduction of graphite oxide are commonly used techniques to incorporate well-dispersed graphene-based sheets into a polymer matrix. Various research works reported electrical20 and physicomechanical21 properties comparable with carbon nanotubes, for these recently developed nanofillers. Oxygen functionalities will be introduced on the basal plane and edges of the graphene sheets during the preparation stage. The level of oxidation (C/O ratio) plays a major role in determining the affinity of GNPs with organic solvents and polymer matrices. It is found that the C/O ratio significantly impacts the dispersion state of graphene sheets in polar matrices like PMMA.19 Upon being dispersed in a viscous medium, nanoparticles form a self-similar fractal structure consisting of interconnected aggregates as their concentration increases. Elastic properties of Received: April 13, 2015 Revised: July 23, 2015 Published: August 12, 2015 11867

DOI: 10.1021/acs.jpcb.5b03558 J. Phys. Chem. B 2015, 119, 11867−11878

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The Journal of Physical Chemistry B

Figure 1. (a) XPS high resolution C 1s spectra of MWCNTs, GONRs, and RGNRs. (b) the deconvoluted C 1s spectra of GONRs synthesized via Method A (CNx-GONR-A), showing the hydroxyl, epoxy, carbonyl, and carboxyl groups. (c) the deconvoluted C 1s spectra of GONRs synthesized via Method B (CNx-GONR-B), showing only epoxy and carboxyl groups.

dispersion-state is investigated, and polymer/GNR nanocomposites are compared with the parent carbon nanotubes nanocomposite in a nonpolar polymeric matrix. Linear and nonlinear viscoelastic behavior of high density polyethylene (HDPE) nanocomposites containing undoped carbon nanotubes, nitrogen-doped carbon nanotubes and nitrogen-doped graphene oxide nanoribbons (CNx-GONRs) with different oxidation levels prepared via different synthesis methods are evaluated and used to determine the network structure. GNRs are synthesized from nitrogen-doped carbon nanotubes via a chemical route using potassium permanganate and some second acids. Chemically reduced nitrogen-doped graphene nanoribbons are also compared with their oxidized counterparts. Differences in superstructures, formed by different fillers, are correlated with their surface chemistry, mainly quantified by the C/O ratio. Considering the nonpolar nature of the matrix, it is expected that filler−filler interactions control the rheological response.

nondilute, non-Brownian CNT suspensions are controlled by contributions from short-range and long-range interparticle interactions.22 These interactions depend on nanotubes’ concentration, dispersion state, surface chemistry, spatial state of orientation, and the geometrical characteristics. In particular, the electrical conductivity of the final nanocomposite is strongly dependent on CNTs’ network superstructure. Alig et al.23,24 reported a huge decrease in conductive properties for CNT/ polymer nanocomposite upon applying an external flow field. The conductive properties partially recovered upon cessation of the flow. They have ascribed these observations to the flowinduced orientation of CNTs during shearing and randomization of the orientation state upon discontinuing the flow field. It is worth mentioning that arrested dynamics would significantly affect this behavior. Above the gel point, CNT suspensions that underwent different preshearing histories showed a minor change in the CNT network superstructure as observed by Khalkhal and Carreau, using rheological technique.25 In spite of a great deal of research devoted to structure−property relationships for carbon nanotube and graphene nanoplatelet-based polymer nanocomposites, no comparable results are available for polymer/graphene nanoribbon (GNR) nanocomposites. Graphene nanoribbons (GNRs),26−28 narrow elongated strips of graphene with ultrahigh aspect ratio and edge-dependent properties, have recently attracted much interest and are an excellent candidate to replace graphene nanosheets and CNTs, particularly if synthesized by unzipping multiwalled carbon nanotubes (MWCNTs).29−31 If made by the unzipping process, GNRs have more available surface areas for interaction with polymer chains than the parent CNTs. By controlling the unzipping conditions, GNRs may have only a few layers of graphene and, therefore, can be more easily exfoliated in the polymers than GNPs. An important side effect is surface functionalities introduced during GNRs’ synthesis process. In our previous work, it is demonstrated that oxygen functional groups dispersed throughout the surface can deleteriously interfere with cross-linking reaction of fluoroelastomer/GNR nanocomposite samples.32 In this study, the effect of nitrogen doping and oxygen surface functionalities of GNRs on

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MATERIALS AND METHODS Details of nanofiller synthesis procedures, nanocomposite preparation method, nonisothermal dynamic scanning calorimetry (DSC), rheology, and X-ray photoelectron spectroscopy (XPS) are elaborated in the Supporting Information.

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RESULTS AND DISCUSSION Surface Chemistry Analysis. To study the oxygen and nitrogen surface functionalities, all nanoparticles were analyzed by XPS. The high resolution C 1s spectra of original carbon nanotubes, undoped MWCNT (Un-MWCNTs) and CNxMWCNTs, graphene oxide nanoribbons synthesized via Methods A and B (CNx-GONRs-A, CNx-GONRs-B) and reduced graphene nanoribbons by hydrazine (CNx-RGNRs) are given in Figure 1. In Method A, CNx-MWCNTs were chemically oxidized/unzipped by a mixture of H2SO4 and KMnO4. In Method B, a second acid such as H3PO4 or TFA was also added to the mixture for better unzipping performance. A more detailed description of synthesis procedures is available in Supporting Information. It is evident that the oxidation level by Method A (see Figure 1a, C/O = 5.99) is 11868


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Figure 2. XPS determined nitrogen atomic concentration and functionalities of nanomaterials used in this study.

oxide nanoribbons, obtained by Method A in this study, are also reduced by hydrazine monohydrate. Figure 1a indicates the C 1s XPS spectra of oxidized samples, by Method A, that are then reduced by hydrazine. Reduction by hydrazine monohydrate slightly improves the C/O ratio from 5.99 to 7.80 however, the assigned shoulders to most of the oxygen functional groups disappear in the reduced samples (CNxRGNR). The nitrogen content of CNx-MWCNTs after oxidation/ unzipping and reduction in hydrazine is measured from the N 1s XPS spectra, with results shown in Figure 2. Based on the deconvoluted peaks of CNx-MWCNTs, nitrogen may incorporate into the hexagonal carbon structure in four main configurations with specific binding energies: pyridinic (398.3−399.8 eV), pyrrolic (400.1−400.5 eV), quaternary (401.0−401.4 eV), and intercalated nitrogen molecules or nitrogen oxide species (404.0−405.6 eV).26,35 The removal of nitrogen molecules trapped inside the nanotube structure after oxidation is an indication of successful unzipping, thus creating more edges in the structure. Apparently, bamboo compartments are partially affected by Method A oxidation as they have still high amounts of trapped intercalated nitrogen molecules in CNx-GONR-A (Figure 2). On the other hand, oxidation by Method B removes almost all of these trapped molecules, and no characteristic peak was observed for CNx-GONR-B. The XPS peaks of nitrogen molecules were also recently reported to have disappeared after successful unzipping of CNx-MWCNTs without bamboo structures.35 Comparing the nitrogen contents before (2.31 at. %) and after oxidation, however, shows that the total nitrogen that remained in the structure after oxidation by Method A (1.28 at. %) was significantly lower than after oxidation/unzipping by Method B (1.75 at. %). This might be due to the excessive removal of pyridinic functional groups, as nitrogen rich regions, by Method A. The nitrogen content of the reduced graphene nanoribbons are also shown in Figure 2. Reduction by hydrazine slightly improves the overall nitrogen content of the oxidized nanotubes, mostly in the form of quaternary and pyrrolic structures; very few pyridinic functional groups can be detected for CNx-RGNR samples.

significantly lower than Method B, where 4 mL of trifluoroacetic (TFA) acid was used (see Figure 1a, C/O = 1.93). The deconvolution of C 1s peaks, based on a Lorentz−Gauss algorithm, also indicates almost all oxygen functional species are dispersed into the nanoribbon surfaces obtained via oxidation by Method A (Figure 1b), while in the samples oxidized by Method B, they are predominantly in the form of epoxy and carboxyl groups (Figure 1c). The measured range of binding energies for the oxygen species include: 286.2−286.5 eV for hydroxyl (C−OH), 286.7−287.0 eV for epoxy (C−O), 287.6−287.8 eV for carbonyl (CO), and 288.8−289.1 eV for carboxyl (OC−OH) groups. Note that all spectra is calibrated with a binding energy of 284.8 eV for CC bond. According to the generally accepted Lerf−Klinowski model for graphene oxides, hydroxyl and epoxy groups attach predominately to the graphene basal plane, while carbonyl and carboxyl groups presumably located at the edges.26,33−35 In contrast, the pioneering works of unzipping pristine MWCNTs have showed only slight changes in the C/O ratio (1.5−1.8) both with and without use of a second acid successful unzipping was observed.26,28 Regarding the geometrical complexity of bamboo structures and chemical doping by nitrogen in CNx-MWCNTs, the significant C/O ratio difference between oxidation Methods A and B can thus be attributed to the different unzipping mechanisms of these nanotubes. When CNx-MWCNTs are oxidized using only sulfuric acid and potassium permanganate (Method A), bamboo compartments are preserved, and few internal breakages of the caps are observed.36,37 This incomplete unzipping process, also reported by Silva et al.,35 could prevent the attachment of more oxygen functional groups into the sp2 carbon network, and therefore, a higher C/O ratio is obtained. Alternatively, CNx-MWCNTs are fully unzipped by helical or dendritic mechanisms if a second acid (TFA or H3PO4) is added to the oxidation protocol (Method B).36,37 This provided good conditions for adding more oxygen species leading to further unzipping of the nanotubes, and thus a lower C/O ratio is achieved. To recover properties, hydrazine is extensively used to reduce graphene oxide derivatives and is found to be one of the best chemical reagents.26,28 Graphene 11869


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The Journal of Physical Chemistry B Table 1. Properties of the Synthesized Nanofillers sample aspect ratio (TEM) C/O (XPS) doping % (XPS) method of synthesis a

Un-MWCNT

CNx-MWCNT

CNx-GONR-A

CNx-GONR-B

CNx-RGNR

∼50

∼70

∼300

∼300

∼300

47.73 (1.60a)

41.29 (1.12) 2.31 (0.08) catalytic chemical vapor deposition

5.99 (0.72) 1.28 (0.17) chemical unzipping

1.93 (0.17) 1.75 (0.07) chemical unzipping (using second acids)

7.8 (1.03) 2.09 (0.21) chemical reduction (hydrazine)

catalytic chemical vapor deposition

Standard deviation of nitrogen-doping percent and C/O ratio.

Figure 3. TEM images of the nanofillers (a) CNx-MWCNT, (b) Un-MWCNT, (c) CNx-GONR-B, and (d) CNx-GONR-A high-resolution TEM image.36,37

sections had an average thickness of ∼30 μm. Sections were kept molten at 180 °C for 5 min to ensure complete removal of thermal history and then crystallized at a cooling rate of 5 K/ min. Different samples demonstrated hugely different structural heterogeneities in terms of size and aspect ratio. It is observable that GNRs, regardless of their percentage of doping and carbon to oxygen ratios, exhibited a better dispersion level and smaller cluster size. It is also possible to conclude that nitrogen doping improved the dispersion level in the CNx-MWCNT sample, as compared to the Un-MWCNT sample. For GNR samples, the CNx-GONR-A and CNx-RGNR samples exhibited relatively more elongated clusters with larger aspect ratios, leading to a greater chance for interlocking with the neighboring cluster. It is expected that the final microstructure of the nanocomposite is mainly controlled by interparticle interactions, interaction potential between the matrix polymer chains and nanoparticles, and composition. Hooper and Schweizer38,39 and Hall et al.,40,41 through considering a wide range of interfacial chemistry, proposed a phase separation theory induced by spinodal demixing. They predicted the presence of two distinct phase separation processes, separated by a miscibility region. At relatively lower filler−polymer attraction strength, a depletion−

Table 1 summarizes the structural properties associated with the nanofillers. The nitrogen atomic percent and C/O ratios were calculated in each sample at three different spots. Reported values are the arithmetic averages accompanied by standard deviation. Averages of aspect ratios reported in Table 1 were calculated based on the measurements of >70 nanotubes per TEM sample. Figure 3 also shows low-magnification and high-magnification TEM images of selected nanofillers. The bamboo-shaped structure for nitrogen-doped carbon nanotubes and relatively thicker walls of undoped carbon nanotube are observable in these images. Additionally, a fully unzipped structure of oxidized graphene nanoribbon-B with partly folded edges is notable in Figure 3c. CNx-MWCNTs oxidized using method B have been mainly unzipped via helical cleavage around the tub showing a multifaceted structure along the edges as shown in high-resolution TEM image in the inset in Figure 3c.36,37 However, oxidation using method A showed that bamboo compartments inside the nanotubes are initially attached by oxidants, but unzipping was unsuccessful (see high-resolution TEM image in Figure 3d).36,37 Nanocomposites Microstructural Observations. Figure 4 depicts optical micrographs of prepared composites. Prepared 11870


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Figure 4. Microstructure observed by optical microscope for thin sections (thickness ∼30 μm) of nanocomposite samples. Sections were kept molten at 180 °C for 5 min, crystallized at a cooling rate of 5 K/min, and viewed at 25 °C (dimension of each image: 600 μm × 400 μm).

Figure 5. TEM micrographs representative of individually dispersed nanofiller for (a) CNx-GONR-A, (b) CNx-RGNR, and (c) CNx-GONR-B nanocomposite samples (scale bar is 100 nm).

attraction induced phase separated state is expected. This will result in a nonergodic microstructure mainly induced by contact aggregation. By increasing the filler−polymer attraction strength, they demonstrated an abrupt transition to a phase mixed enthalpically stabilized state. Figure 5 shows TEM micrographs of ultratomed sections (thickness ∼100 nm) of prepared nanocomposites containing 0.5 wt % of nanofiller. These images are representative of individually dispersed CNx-GNRs in the HDPE matrix. The unsuccessful and/or partial unzipping of nitrogen-doped MWCNTs is observable in CNx-GONR-A and CNx-RGNR nanocomposite samples. It is also observed that CNx-GONR-B (Figure 5c) is fully unraveled at on end, while it is folded onto itself in the middle. To achieve a phase mixed state, comprised of individual particles dispersed throughout the space, the formation of a thin, thermodynamically stable polymer bound layer around filler particles is necessary. At a relatively high filler−polymer attractive interaction, a second transition was predicted by Hooper and Schweizer.38,39 It is proposed that local polymer bridges and telebridges will form filler−polymer complexes, constituting a physical network phase.

For relatively weak polymer matrix−filler interactions, which are expected for HDPE carbon-based nanocomposites, it is anticipated that structural heterogeneities, as observed in Figure 4, would correspond to phase separated states mainly induced by entropic depletion attraction.38,39 comprised of polymer-rich and particle-rich phases. The characteristic size and shape of the particle clusters in the filler collective structure would be dictated mainly by functional groups present on the surface of the nanofillers. Nucleating Ability. Carbon nanomaterials are reported to induce crystallization effectively in a wide range of semicrystalline polymers. This effect can be determined via a notable increase in the onset crystallization temperature and peak crystallization temperature during nonisothermal crystallization. Figure 6 shows the plot of log β (log of cooling rate) as a function of log 1/ΔTp2 (ΔTp = Tcrys − Tmelt) for different nanofillers used in this study, according to Dobreva’s42 approach. Detailed differential scanning calorimetry data are available in Supporting Information (see Figure S1). The ratio of the slopes of the linear function of log β, as a function of log 1/ΔTp2 for the nanocomposites and the neat HDPE, can be considered as a measure of the nucleation activity of the filler. 11871


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Figure 6. Nucleating ability of the nanofillers in the HDPE matrix according to Dobreva’s approach42 (all samples contain 0.8 wt % of the nanofiller). The inset shows the nucleation activity (ψ) as a function of doping percent and C/O ratio.

The ratio of the slopes is referred to as ψ. In fact, the ψ function, varies in limits 0 < ψ < 1, is the factor by which the thermodynamic barrier for nucleus formation is decreased in the heterogeneous case compared to homogeneous nucleation. The more active a substrate is, the closer ψ is to 0. Based on the results presented in Figure 6, it can be inferred that as the carbon to oxygen ratio (C/O) increases, the filler becomes more active, and the ψ-value becomes smaller and closer to zero as it is shown in the inset of Figure 6. In this context, undoped MWCNT had the highest nucleating activity, while the CNx-GONR-B can be considered totally inert in terms of nucleating ability. Interestingly, CNx-RGNR samples has demonstrated a better nucleating activity, lower ψ-value, compared to CNx-MWCNT sample which can be considered as a result of additional surface area created by the unzipping process.43 It is suggested that heterogeneous nucleation in the crystallization of polyolefin is mainly based on the low surface energy of the substrate and its ability to accommodate polymer chains on its surface by providing “ditches” and “steps” causing polymer chains to prealign and to facilitate crystallization.44,45 Rheological Behavior. Early work on the rheology of nanocomposites, using small amplitude oscillatory shear experiments, demonstrated a pseudosolid-like behavior marked by the formation of a plateau in complex moduli, at lower frequencies, with dominant elasticity, known as nonterminal behavior.9,17,46−51 There is an ongoing debate to determine if this behavior stems from the prolonged molecular relaxation associated with chains located in the interfacial region or from the mesoscale percolated network of the nanofiller. Randomizing events, like particle−particle hydrodynamic interaction and Brownian motion, are also thought to contribute to the observed elasticity.52−54 Additionally, the bending/stretching of a single one-dimensional nanoparticle was also proposed by some authors as a possible origin for this behavior.52 In spite of these postulates, based on observing the nonterminal behavior for weakly interacting nanocomposites,55 in which chain dynamics are slightly altered, the hypothesis that the filler network is the main contributor to the elasticity at lower frequency seems to be plausible. This behavior was further envisioned in the frame of fractal scaling theories which were already found to be successful in describing structural properties of colloidal gels.25,56 Linear Rheology. The frequency dependence of G′ and G″ at small strain amplitude (γ = 0.1%) are shown in Figure 7 for a

Figure 7. Oscillatory shear response in linear regime (γ = 0.1%) for neat HDPE and nanocomposite samples containing 0.8 wt % of the nanofiller at 160 °C.

frequency range from 0.01 rad/s to 625 rad/s. Measured G′, for all nanocomposite samples, was frequency-independent at small frequencies. For most of the frequency range, G′ is smaller than G″, and only at very low frequencies does it get slightly larger than G″. It is reported that interparticle interactions, polymer matrix molecular weight, molecular weight distribution, and chain architecture are crucial parameters in determining the linear viscoelastic response in the dynamic mode. Stronger interparticle attraction, lower polymer matrix Mw and narrower distribution will result in stronger solid-like behavior in carbonbased polymer nanocomposites.57 All nanocomposite samples showed a crossover between G′ and G″, at very low frequencies, indicating the dominance of elastic response within the investigated region which is a common feature in soft materials corresponding to an ultraslow “β-relaxation” mechanism.58 The concentration dependences of small amplitude oscillatory shear response of prepared nanocomposites are presented in Supporting Information (see Figure S2). Stress Relaxation. Figure 8 depicts the time evolution of relaxation modulus (G(t,γ0) = τ/γ0) as determined by the stepstrain test for neat HDPE and nanocomposite samples containing 0.8 wt % of the corresponding nanofiller. In the step-strain test, a finite strain (γ0 = 0.1%, 1%, and 10%) was applied to the sample at 160 °C, and the process of stress relaxation was followed. The observed trend for neat HDPE is reminiscent of the relaxation behavior of an entangled polymer melt. The relaxation scenario for such a system is a complex combination of mechanisms like local Rouse dynamics, reptation, contour length fluctuation, and constraint release.59 While Rouse dynamics dominate for short time response, the gradual formation of a plateau in the long time response of neat HDPE is linked to the presence of entanglements. The intermediate and terminal responses clearly show a prolonged stress relaxation for samples containing carbon nanotubes for 11872


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If the δ-value calculated for γ0 = 1% is plotted as a function of percent of nitrogen doping for different C/O ratios, it exhibits a minimum; this minimum corresponds to the CNx-GONR-B sample (see Figure 9). As mentioned above, this verifies the fact

Figure 9. Power-law exponent (δ) for intermediate stress relaxation response as a function of doping at different C/O ratios at γ0 = 1%. A minimum in δ is seen at C/O = 1.93 and N-doping % = 1.75, corressponding to CNx-GONR-B sample.

that short-range attractive interactions are strongly suppressed for graphene oxide nanoribbon samples, as compared to nanotube samples. Suppression of attractive tube−tube interactions and interruption in formation of flocculated network superstructure in multiwalled carbon nanotube nanocomposites due to covalent functionalization was previously reported by other researchers.60 This resulted in a rheological response comparable to that of semiflexible fibers under an external shearing field. Comparable results were reported for effect of oxygen content of graphene sheets on network formation and linear melt rheology of graphene/ polymer nanocomposites.19 Thixotropic Behavior. The melt-state rheology of nanocomposites, like gel forming colloidal suspensions, is strongly dependent on the deformation history imposed on the sample. Shear flow sensitivity and augmentation of elasticity, under quiescence, are features associated with this characteristic referred to as thixotropy.62 This phenomenon necessitates designing a well-controlled deformation protocol to obtain repeatable results. Figure 10 shows the time evolution of elastic modulus of nanocomposite samples that underwent preshearing history at 1 s−1 for 300 s (see Supporting Information, Figure S3). A two-stage recovery process is distinguishable for samples containing nitrogen-doped carbon nanotubes, especially for more concentrated samples. A similar behavior is also observable for CNx-RGNR samples at all concentrations. The only distinct difference is the relatively larger recovery rate (dG′/dt) observed for CNx-RGNR nanocomposite samples. Nitrogen-doped graphene oxide nanoribbons exhibited extremely different behavior, especially for dilute samples. As can be seen in Figure 10, CNx-GONR (both type A and B) dilute nanocomposite samples show a negative recovery rate initially, which changed to positive values at longer times. This initial decreasing trend, in storage modulus versus time plot, was completely suppressed for samples containing 0.8 wt % CNxGONR-A and CNx-GONR-B. Additionally, the rate of increase in elasticity (dG′/dt) is relatively higher for the CNx-GONR-B 0.8 wt % sample compared to the corresponding CNx-GONRA sample. It should be noted that the structural recovery kinetics observed for the early stages of the aging process are most probably controlled by Brownian forces trying to randomize the state of orientation gained during the shearing stage. This Brownian motion scenario by its own, however, is

Figure 8. Evolution of relaxation modulus for (a) neat HDPE, (b) 0.8 wt % Un-MWCNT, (c) 0.8 wt % CNx-MWCNT, (d) 0.8 wt % CNxGONR-A, (e) 0.8 wt % CNx-GONR-B, and (f) 0.8 wt % CNx-RGNR nanocomposite samples.

all strains. There is a noticeably higher strain dependence of CNx-MWCNT sample stress dissipation, compared to the UnMWCNT sample. CNx-MWCNT sample at γ = 0.1% had a relatively larger long-time modulus value which can be due to its relatively higher aspect ratio compared to Un-MWCNT sample. However, at larger strains (γ = 1%, 10%), CNxMWCNT sample had much lower long-time modulus and faster stress dissipation compared to Un-MWCNT which is an indication of hindered short-range attractive interactions as result of nitrogen doping. On the other hand, for GNR samples, the stress dissipation behavior is comparable with the neat HDPE sample. This implies that GNRs move with the matrix rather than forming a sluggish phase hindering the stress dissipation process. This may be explained by lower attractive interactions and/or the presence of repulsive forces (if any) between neighboring nanoparticles caused by nitrogen doping and the presence of surface oxygen groups.60 The other noticeable feature in the stress relaxation behavior of GNR samples was observed for CNx-GONR-B (see Figure 8e) which, interestingly for lower strains (γ0 = 0.1% and 1%), showed an incomplete stress relaxation (up to t ∼ 100 s) followed by an increase at longer times. It is well-understood that, in melts with a gel-like structure and thixotropic behavior, the recovery of percolated gelled structure prevents complete stress relaxation.47 This phenomenon is known as the “effect of frozen memory”. The observed increase in stress at longer times, however, would indicate that rearrangements in the nanofiller network structure occurred for the CNx-GONR-B sample, while the longer time mobility of nanoparticles in other nanocomposite samples are highly hindered due to physical jamming.61 The intermediate response (0.1 (s) < t < 10 (s)), where smaller scale motions play major role, can be essentially described as a power-law-like decay (G(t) ∼ tδ) for all samples. 11873


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Figure 10. Time evolution of elastic modulus at frequency of 1 (Hz) and strain of 1% for CNx-MWCNT with fully bamboo structure, CNx-GONRB, CNx-RGNR and CNx-GONR-A nanocomposites at different concentrations. The top curve shows the most concentrated sample, and the bottom curve shows the least concentrated sample.

recovery rate becomes positive. Sufficiently concentrated CNxGONR (both type A and B) nanocomposite samples demonstrated a positive and relatively large recovery rate from the very beginning of the aging process. Step Stress Response: Creep Behavior. Strong, shortrange interactions can lead to aggregation of colloidal particles into fractal-like clusters, forming a space-filling network. As mentioned earlier, such gelled, nonergodic systems exhibit features including solid-like behavior, thixotropy, ultraslow relaxation process, heterogeneities in the dynamics of the system,71 and other complex rheological behaviors. The presence of strong, short-range attractive interactions can dramatically affect the nonergodic features of colloidal systems. It is suggested that an ultraslow relaxation process exists which corresponds to the transition from solid-like behavior to ultimately liquid-like behavior of the gel at very low frequencies.58 The ultraslow relaxation process of gelled structures of colloidal dispersions necessitates experiments performed at very low frequencies, which are essentially inaccessible to oscillatory rheology. Fortunately, creep measurement at low applied shear stress can readily distinguish structural differences under nearly at-rest conditions.72 Figure 11 displays the differences between different HDPE nanocomposites containing 0.8 wt % of the nanofillers in creep experiments performed for σc = 1 Pa, σc = 10 Pa, and σc = 50 Pa. At low stress, σc = 1 Pa, the initial response is purely elastic, and strain increases linearly with time. This behavior is accompanied by inertial ringing73 for CNx-RGNR and UnMWCNT samples. The strain γ gradually loses its time dependence, and dγ/dt tends to very small values, reminiscent of the characteristics of a stable solid. At intermediate stress, σc = 10 Pa, the immediate response remains the same, with no inertial ringing observed. Nitrogen-doped graphene oxide nanoribbon nanocomposite samples (both type A and type B), though, do not show time-independent creep behavior at longer times and gap-wise shear rate reaches nonzero plateau values. At higher stress, σc = 50 Pa, none of the nanocomposite samples show time-independence and the gap-wise shear rate

not able to fully explain such a prolonged, two-stage aging process.63−66 The recovery of the low-frequency elastic response, upon cessation of the flow, is also reported for nanoclay/polymer nanocomposites,63−66 carbon nanotube/polymer nanocomposites,23,52,67 graphene-based polymer nanocomposites,68 and attractive colloidal suspensions.69 In early stages, this intensification of solid-like behavior, as annealing time elapses, can be considered as a collective response, which is comprised of Brownian randomization and short-range van der Waals interparticle interaction. Elastic recovery of deformed aggregates could also have some effects on the short-term response. At longer aging times, this process is continued by the formation of a fractal-like network of aggregates which appreciably promotes the elastic response. In another words, the second stage corresponds to the jamming dynamics of interactive particles in a crowded medium.61 The nature of this process is multiscale and far from equilibrium. Considering the above-mentioned controlling mechanisms for the thixotropic behavior of nanocomposites, it is possible to explain our observations in the following manner. The disappearance of negative recovery rate for CNx-RGNR sample confirms that chemical reduction procedure used in this study has effectively removed oxygen functional groups and thereby eliminated their effect on hindering short-range interparticle interactions. The aging process that occurred for CNx-MWCNT and CNxRGNR samples is mainly due to Brownian and short-range attractive van der Waals forces, regardless of the relative orientation of the particles. Furthermore, as the concentration increases, the overall recovery rate will increase due to shorter interparticle distances. The higher probability for repulsive forces generated between neighboring nanoparticles for systems with higher oxidation level (lower C/O ratio), would be an impediment to structural recovery,70 as evidenced by the negative recovery rate for dilute CNx-GONR-A and CNxGONR-B nanocomposite samples. Additionally, after a certain elapsed time, particles are able to reaccommodate a relative orientation-state in which repulsive forces are minimal and the 11874


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Figure 12. Recovery after removal of step stress (a) σc = 1 Pa, (b) σc = 10 Pa, and (c) σc = 50 Pa.

nanotube sample had a linear, slow recovery process and reached no time-independent state up to 1000 s. Nitrogendoped graphene oxide samples have shown a slow recovery behavior, and type B demonstrated a relatively larger maximum percentage of recovery, as compared to type A. For σc = 10 Pa, the immediately recovered strain is significantly larger for the CNx-RGNR sample, and in the first 20 s, 50% of γmax was recovered. At longer times (t > 400 s), a reversion in recovery process was observable for the CNx-RGNR sample. The CNxGONR-A sample showed no immediate recovery of strainl however, at longer times, a slow recovery process was observed. The CNx-GONR-B displayed no significant strain recovery in the time window of the experiment. The nitrogen-doped, multiwalled carbon nanotube sample exhibited a fast recovery process followed by a slight time dependence at longer times. In contrast, undoped multiwalled carbon nanotube sample showed slower recovery rate with a relatively larger maximum percentage of recovery, as compared to the nitrogen-doped multiwalled carbon nanotube sample. For σc = 50 Pa, all samples displayed a slight recovery of strain accumulated over the creep experiment. Minor differences in recovery behavior among samples are distinguishable. The CNx-RGNR sample still showed the largest percentage of strain recovery. Next to the chemically reduced graphene nanoribbon sample, the nitrogen-doped, multiwalled carbon nanotube sample exhibited the highest amount of recovery. The remainder of the samples showed similar extents of recovery. The underlying microscopic mechanism proposed for the recovery of colloidal gels is the relaxation of stretched, but unbroken, inter- and intracluster bonds back to isotropy, upon removal of the external stress.53,72 It is suggested that cluster size, strength, and range of interparticle attractive interactions, elasticity of clusters, and elasticity of network bonds play major roles in determining the extent of recovery. For σc = 1 Pa, Figure 11a and b, the applied stress could disrupt the elastic network of the filler for all measured samples, along with a maximum strain reached at the end of the creep stage. The gapwise shear rate, however, had very small values, indicating that no simple flow has happened. The huge extent of strain recovery observed for CNx-RGNR at σc = 1 Pa indicates that the structural heterogeneities are minimally impacted by the

Figure 11. Creep response of prepared nanocomposites at (a, b) σc = 1 Pa, (c, d) σc = 10 Pa, and (e, f) σc = 50 Pa.

reaches a nonzero plateau value, which is due to a catastrophic failure of the network structure. Therefore, at high stress, no difference in creep behavior of nanocomposites is identifiable. The failure of the highly heterogeneous, mesoscopic network of colloidal gels is assumed to take place catastrophically, under a strong enough external stress field, by a simultaneous dissociation of all bonds in the network strands cross-section. A structural breakdown under lower stresses, however, is slow and has been described as “stochastic erosion”.72 Based on the results presented in Figure 11, it is possible to infer that nitrogendoped graphene oxide nanoribbon nanocomposite samples (both type A and B) formed a weakly linked network which is much less resilient to yielding. In contrast, the nitrogen-doped and chemically reduced graphene nanoribbon sample (CNxRGNR), up to an intermediate stress loading, displayed a timeindependent plateau in the creep experiment, verifying the high elasticity of this sample. Samples containing undoped and nitrogen-doped multiwalled carbon nanotubes showed similar behavior for both low and intermediate stress loadings, corresponding to characteristics of a stable solid. These findings support the following hypothesis: oxygen functional groups, on the surface of nitrogen-doped graphene oxide nanoribbon to have a major impact on short-range attractive interactions between neighboring particles. Step Stress Response: Recovery. Figure 12 depicts the recovery behavior of HDPE nanocomposites containing 0.8 wt % of the nanofillers. Samples were subjected to an applied stress of σc = 1, 10, and 50 Pa for 2000s. After this time, the sample accumulated a maximum strain of γmax. Recovered strain (γmax − γ(t)), normalized with respect to γmax, was plotted as a function of time. At applied stress of σc = 1 Pa, the CNx-RGNR sample showed fast strain recovery at initial times, leading to full recovery in less than 1 s. Furthermore, the nitrogen-doped multiwalled carbon nanotube sample recovered 50% of the maximum strain in ∼70 s. The undoped multiwalled carbon 11875


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Figure 13. Conceptual schematics of GNR nanoparticles.

stress field during the creep stage. In contrast, nitrogen-doped graphene oxide nanoribbon samples were largely affected and showed a tremendously slow recovery process. It is also noticeable that nitrogen doping led to more elasticity for the CNx-MWCNT sample as compared to the Un-MWCNT. At intermediate applied stress, σc = 10 Pa, the external stress field could considerably break the filler network, leading to the formation of independent clusters and individual nanoparticles. The elastic structure formed by the filler remained partially intact and was able to the recover accumulated deformation to some extent. Again, the CNx-RGNR sample demonstrated significant ability for strain recovery, indicating the survival of the elastic structure in this sample. CNx-GONR sample type A recovered ∼9% of the accumulated strain in 1000 s, and the CNx-GONRB sample was unable to recover the maximum strain reached in the creep stage. These samples also showed a transition from creep to flow (see Figure 11c and d). The observed recovery behavior, by step stress test, provides conclusive evidence for the effect of the oxygen functional groups on the surface of graphene nanoribbons on weakening short-range attractive interactions. A slight recovery, observed after application of σc = 50 Pa, indicates that some structure was still present at the end at creep stage, as is consistent with our observations in Figure 8 for large amplitude. Presence of surface functional groups and doped atoms can dramatically alter the electronic structure of MWCNT and graphene nanoribbons.74−78 This strongly affects the interparticle attractive interactions due to steric hindrance and/or creation of repulsive interactions. As a consequence, interparticle distances are increased, and particle−particle interactions are dependent on the relative orientation state. As verified by linear and nonlinear rheological response of nanocomposite samples, surface functional groups and nitrogen-doping appreciably lowered structural stability, delayed structural recovery, and hindered relaxation of flow-induced anisotropy. The schematics in Figure 13 depict the structure of the different GNR nanoparticles and show how nitrogen atoms and oxygen functional groups are introduced on the basal plane and edges of nanoparticles. According to the generally accepted Lerf−Klinowski model for graphene oxides, hydroxyl and epoxy groups are attached predominately to the graphene basal plane, while carbonyl and carboxyl groups are presumably located at the edges.26,33−35 As discussed above, the presence of these

functionalities will result in a highly uneven charge density distribution which substantially impacts short-range interactions between neighboring nanoparticles. Using the XPS determined C/O ratio, it is expected that CNx-GONR-B should demonstrate highly weakened short-range attractive interactions.

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CONCLUSION Herein, we investigated the effect of surface chemistry of nitrogen-doped graphene nanoribbons on the dispersion state and rheological behavior of their nanocomposites with HDPE. Nitrogen-doped graphene oxide nanoribbons were synthesized by chemical unzipping of nitrogen-doped multiwalled carbon nanotubes, using different procedures, resulting in different surface chemistry and percentage of nitrogen doping. Chemical reduction was also applied to remove oxygen functional groups present on the surface of graphene oxide nanoribbons. It was found that increasing the nitrogen-doping percent and oxidation level either increased steric hindrance or created repulsive forces, thus avoiding short-range attractive interactions between neighboring nanoparticles. These resulted in the formation of smaller and possibly more shear-sensitive networks, in graphene nanoribbon-based nanocomposite samples. Huge changes in thixotropic behavior and stress relaxation behavior were also observed. Chemical reduction efficiently removed oxygen functional groups and thereby eliminated their effect on network formation; chemically reduced nitrogen-doped graphene nanoribbons formed a collective network with significant structural elasticity, which was able to immediately relax anisotropy upon application of an external stress field. The structural stability observed for CNxRGNR based nanocomposites is beneficial for some crucial material properties, such as electrical conductivity, particularly in applications where nanocomposites are under stress.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.5b03558. Details of nanofillers synthesis procedures, nanocomposites preparation method, nonisothermal dynamic scanning calorimetry (DSC), rheology and X-ray photoelectron spectroscopy (XPS) (PDF) 11876


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AUTHOR INFORMATION

Corresponding Author

*Phone: +1-(403) 210-6549. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research is financially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Alberta Innovates Technology Futures (AITF).

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