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Oct 4, 2016 - Xiaodong Qi, Yilan Guo, Yuan Wei, Peng Dong, and Qiang Fu*. College of Polymer Science and Engineering, State Key Laboratory of Polymer ...
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Multi-Shape and Temperature Memory Effects via Strong Physical Confinement in Poly(Propylene Carbonate)/Graphene Oxide Nanocomposites Xiaodong Qi, Yilan Guo, Yuan Wei, Peng Dong, and Qiang Fu J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.6b08536 • Publication Date (Web): 04 Oct 2016 Downloaded from http://pubs.acs.org on October 12, 2016

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Multi-Shape and Temperature Memory Effects via Strong Physical Confinement in Poly(Propylene Carbonate)/Graphene Oxide Nanocomposites

Xiaodong Qi, Yilan Guo, Yuan Wei, Peng Dong, Qiang Fu* College of Polymer Science and Engineering, State Key Laboratory of Polymer Materials Engineering, Sichuan University, Chengdu 610065, China.

Abstract: The importance of filler-matrix interactions is generally recognized for mechanical property enhancement, their direct impact via physical confinement on diverse functional properties has remained poorly explored. We report here our effort in achieving versatile shape memory performances for a biodegradable poly(propylene carbonate) (PPC) matrix containing high contents of graphene oxide (GO). The excellent dispersion in the entire filler range (up to 20 wt%) allows precise morphological tuning, along with the physical filler-matrix interactions, contributing overall to a strong nano-confinement effect that positively affects the thermo-mechanical properties of nanocomposites. Only one glass transition temperature (Tg) of PPC is detected as GO content is below 10 wt%, corresponding to a slightly confined system, whereas two distinct Tgs are observed with GO content over 10 wt%, corresponding to a highly confined system. As such, tunable multi-shape memory effect can be achieved simply by tuning the filler contents. Dual shape memory effect (SME) is observed for slightly confined system, while a triple SME can be achieved via deformation at two distinct Tgs for highly confined system. More importantly, it is interesting to find that the switch temperature (Tsw) evolves linearly with the programing temperature (Tprog) for both slightly and highly confined system, with Tsw ≈ Tprog for highly confined system, but Tsw < Tprog for slightly confined system. Our work suggests a highly flexible approach to take advantage of strong nano-confinement effect via tuning the content of GO within a single polymer to access versatile SME, such as dual, triple shape memory and temperature memory effect.

*

Corresponding author: Tel: +86 28 8546 1795, Email: [email protected] (Q. Fu)

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1. Introduction Shape memory polymers (SMPs) are a class of functional polymers that can fix deformed temporary shapes and recover to their original shapes upon exposure to external stimuli.1-8 Such an intelligent ability gives SMPs great opportunity to be used as actuators, biomedical and aerospace devices. Most SMPs are dual-shape memory polymers (DSMPs) that can store temporary shape and permanent shape.9,10 However, the applications of DSMPs are limited when they comes to the use of smart devices with some specific and complex requirements, which can be attributed to the fact that they can only store one temporary shape. Triple-shape memory polymers (TSMPs), which are able to recover to their original shapes from two previously deformed temporary shapes, are proposed in recent years.11 Given that such materials could fix two different temporary shapes and memorize shapes at two different temperatures, TSMPs are regarded to be of great significance in industrial applications. The strategy for preparing TSMPs is to incorporate two distinct transitions into a polymer.12 The methods are mainly included chemical block or graft copolymerization, physically cross-linked crystalline polymer blends and macroscopic epoxy bilayers.13-18 Instead of multiple discrete thermal transitions, a highly flexible strategy based on a single broad thermal transition is also reported.19-21 Xie et al. discovered that Nafion, a commercial polymer with a broad glass transition, could exhibit triple and quadruple shape memory behavior.19,22 The broad thermal transition could be regarded as a consecutive distribution with a large amount of sharp transitions, which is the fundamental basis for the multi-shape memory effect (MSME). Furthermore, it was found that Nafion could remember the temperature at which the deformation was programmed, referring to the temperature memory effect (TME).23 Temperature memory polymers (TMPs) are capable to memorize the programmed temperatures, thus providing a flexible approach to tailor the shape memory behaviors without changing the chemical composition of polymers.24,25 Lendlein et al. reported that the copolyesterurethanes with a broad melting transition from 32 to 65 °C could memorize the programmed temperature under stress-free and constant strain recovery.26 Besides neat polymers with broad thermal transitions, Poulin et al. reported that the polyvinyl alcohol (PVA)/carbon nanotubes (CNTs) nanocomposites showed a TME because of the confined structure in the polymer nanocomposites.27,28 Although the PVA/CNTs nanocomposites exhibit the TME and

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extremely high recovery stress, their recovery ratio (Rr) are lower than 60 %. The low Rr indicates that the PVA chains are only partially crosslinked by CNTs owing to the weak OH-π interactions.29 Previous studies imply that the key point for acquiring complete recovery is to ensure the uniform distribution of crosslinkings.30 It is logical to ask if other filler-matrix combinations can be explored to confine polymer chains more effectively to form more robust physical crosslinking, thus increasing Rr. In particular, the effect of physical confinement structure on the shape memory behavior should be carried out by using different filler contents to truly understand the mechanism, yet such critical information is missing in previously reported work. 27 The first step towards our goals is the preparation of polymer nanocomposites with stronger interfacial interactions and high filler contents, which itself is a typical challenge because of the difficulty in maintaining fine dispersion. Until now, only a few reports are available to help guide the preparation of polymer nanocomposites with high content of nanofillers.31,32 Our previous work shows that the incorporation of graphene oxide (GO) can significantly influence the Tg of poly(propylene carbonate) (PPC) via physical confinement of the polymer chains.32 While not directly related to the focus of the current study, it is worth noting that PPC has attracted considerable attention due to its efficient CO2 sequestration capability, its less reliance on petroleum sources as well as its biodegradability.33 Graphene oxide (GO), a two-dimensional nanomaterial with abundant oxygenic functional groups, is usually obtained through oxidation and exfoliation of graphite powders.34 Of relevance here is that PPC contains carbonyl groups (C=O) and hydroxyl groups (-OH) or carboxylic groups (-COOH), which make it possible to form strong non-covalent interactions with GO. Particularly, the two-dimensional plate-like structure of GO is well suited for acting as chemical or physical cross-linker to anchor polymers.30,35,36 For this reason, PPC/GO nanocomposites could serve as an ideal system to explore the strong nano-confinement effect on the versatile shape memory effects, such as dual, triple shape memory and temperature memory effect. More importantly, by changing the content of GO in PPC matrix, the effect of different confined structure on the shape memory behavior can be investigated and a better understanding of the shape memory mechanism can be achieved.

2. Materials and methods 2.1 Materials

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Poly(propylene carbonate) (PPC) was kindly provided by the Changchun Institute of Applied Chemistry (Jilin, China). Its average molecular weight (Mw) was 2.48 × 105 g mol-1 and polydispersity index (Mw/Mn) was 3.2. Graphite powders were purchased from Black Dragon Graphite Company (Qingdao, China). Sulfuric acid (H2SO4), sodium nitrate (NaNO3), potassium permanganate (KMnO4), hydrogen peroxide (H2O2) and dimethyl sulfoxide (DMSO) were purchased from Kermel Chemical Reagent Company (Tianjin, China) and used as received. 2.2 Preparation of PPC/GO nanocomposites Graphene oxide (GO) sheets were obtained via the oxidation of artificial graphite powders according to the Hummers method.37 GO/DMSO solution was prepared through a solvent-exchange process. DMSO was mixed with the GO/H2O solution, and then H2O was gradually distilled out at 100 oC by using a rotary evaporator. Then, the homogeneous PPC/GO/DMSO solution was prepared through adding PPC powders into the resulting GO/DMSO solution at 60 °C. The PPC/GO precipitates were obtained via the following solution co-precipitation process. The PPC/GO/DMSO solution was gradually dripped into ethanol with stirring. The PPC/GO precipitates were washed repeatedly with ethanol and dried in oven at 60 °C until their weight were unchanged. After that, the PPC/GO nanocomposites (containing 0, 1, 5, 10, 15 and 20 wt% GO, respectively) were compression molded into plates at 150 oC for 6 min under 10 MPa. The maximum decomposition temperature of PPC in the air is 214 oC (see Figure. S1). Therefore, PPC would not decompose at 150 oC. 2.3 Characterization The cryo-fractured morphologies of PPC/GO nanocomposites were inspected by using an FEI Inspect F scanning electron microscope (SEM) under an acceleration voltage of 5 kV. The X-ray diffraction patterns of PPC/GO nanocomposites were attained on an X’Pert PRO x-ray diffractometer (XRD). The interactions between GO and PPC matrix were analyzed via Kratos Axis Ultra DLD X-ray photoelectron spectroscopy (XPS). Dynamic mechanical analyzer (DMA Q800, TA Company) was used to investigate the impacts of GO on the dynamic mechanical behavior of PPC. The range of temperature was from -10 oC to 100 oC and the heating rate was 3 o

C min-1. For the dual shape memory tests, a four-step procedure was performed on DMA. (1) The

sample was firstly heated to 60 °C and stretched to a strain (ε) using a constant force. (2) The

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deformed sample was then rapidly cooled to low temperature (20 °C) with keeping the force. (3) The force was released and the strain (εload) was recorded. (4) The sample was reheated to 60 °C to observe the free strain recovery process and the strain (εrec) was recorded. The heating and cooling rates were 5 oC min-1. Shape recovery ratio (Rr) and shape fixing ratio (Rf) were calculated by the two equations (1) and (2) below:  =



(1)

 

(2)



 =



where ε was the deformed strain after loading, εload was the fixed strain after cooling and unloading, and εrec was the final strain after recovery. To investigate the triple shape memory behavior, take PPC15 as an example, the original shape εA was deformed at 80 oC, cooled to 20 oC, and then heated to 50 oC under the zero force mode to yield the first temporary shape εB. This temporary shape was further deformed at 50 oC and cooled to 20 oC to yield the second temporary shape εC. During the recovery process, the deformed PPC15 were reheated from 20 oC to 50 oC under a stress free condition and the recovered first temporary shape was recorded as εB,rec. After that, further heating sample from 50 o

C to 80 oC, the permanent shape (εA, rec) was finally obtained. The heating and cooling rates were

5 oC min-1. Equations (3) and (4) were used to evaluate Rf and Rr for the triple-shape memory effects.  

 × 100%

(3)

  ,

 × 100%

(4)

  →  = 

,  

  →  = 



where x and y represented the different shapes A, B or C, εy,load was the deformed strain after loading, εy and εx were fixed strains after cooling and unloading, and εx,rec was the recovery strain, respectively. To confirm the temperature memory effect, the samples were first deformed to a targeted strain at different temperatures and cooled down to 20 oC to fix the temporary shape. The samples were then heated at 2 oC min-1 under a stress free condition, and the recovery strain was recorded.

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3. Results and discussion 3.1 Dispersion and microstructures of GO in PPC matrix Fig. 1a schematically depicts the sample fabrication procedure. A solvent-exchange method was carried out to get full exfoliation of GO in dimethyl sulfoxide (DMSO), which was necessary for the preparation of PPC/GO nanocomposites through the following solution co-precipitation process. Hereinafter, the PPC/GO nanocomposites containing 0, 1, 5, 10, 15 and 20 wt% GO are termed as PPC, PPC1, PPC5, PPC10, PPC15 and PPC20, respectively. X-ray diffraction (XRD) is an effective tool for verifying the exfoliation of GO sheets in the polymer nanocomposites.38 Therefore, XRD was adopted to detect whether GO sheets are present as individual sheet in the PPC matrix. The XRD patterns of GO, pure PPC and PPC/GO nanocomposites with various GO content are presented in Fig. 1b. The typical diffraction peak of GO is observed at around 2θ = 9.97° and a broad peak at about 22.5° represents the totally amorphous PPC. After GO is incorporated into PPC, the XRD patterns of the PPC/GO nanocomposites only show the diffraction peak from PPC. The absence of the diffraction peak from GO suggests that GO is well dispersed as individual sheet in the PPC matrix. Notably, when GO content is over 10%, PPC/GO nanocomposites possess a second order peak at about 2θ = 7.5°, indicating another regularly layered structures.39 Owing to its good dispersion, GO can exhibit different filler architectures depending on its concentration. SEM was performed to further investigate the microstructures of GO in the PPC matrix. GO could be viewed as a two-dimensional macromolecule, thus making it show bending and folding behaviors, and these GO sheets can be assembled into different nanostructures when GO content changes from low to high. 32 As shown in Fig. 1c, For PPC1, GO sheets are discretely dispersed in the manner of ‘dots’ and are mostly segregated from each other because of the low GO content. When the GO content increases to 5 wt% or 10 wt%, a ‘GO network’ structure is formed in the PPC matrix, which is a common phenomenon for many polymer/GO nanocomposites. As the GO content reaches a higher value of 15 wt% or 20 wt%, a highly compact layered structure was ultimately obtained. Based on the observation from SEM, the distributed architecture of GO changes gradually from ‘GO dotted structure’ and ‘GO network’ to ‘GO highly compact layered structure’ with increasing GO content.

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Figure 1. (a) Preparation of PPC/GO nanocomposites; (b) XRD patterns of GO and PPC/GO nanocomposites; (c) SEM images of cryo-fractured morphologies for pure PPC and PPC/GO nanocomposites.

3.2 Analysis of filler-polymer interactions The strong interactions between GO and PPC matrix allow good dispersion of GO in PPC matrix at high filler content. X-ray photoelectron spectroscopy (XPS) is useful to analyze the filler-matrix interactions in polymer composites due to its excellent sensitivity.

40,41

Thus, XPS

was performed to detect the interfacial adhesions between GO and PPC. As shown in Fig. 2, it is clear that with increasing GO content, the absorption peaks corresponding to higher binding energy become more dominant, implying stronger interactions between PPC and GO. In PPC/GO system, the oxygen-containing groups of GO play the role of the proton donors, and the carbonyl groups of PPC serve as proton acceptors.31,32 The hydroxyl and carboxylic groups of GO can take part in several interactions (C=O---O=C, H-O---C=O, O-C---C=O) with the carbonyl groups of PPC chains. A scheme is given for illustrating the hydrogen bonding interactions generated in the PPC/GO nanocomposites, as shown in Fig. 2d. Despite these interactions are individually weak, their collective contribution can be very tremendous. For this reason, GO combines with PPC via sufficient hydrogen bonding interactions, leading to the excellent dispersion of GO in PPC matrix.

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Figure 2. XPS spectra of (a) pure PPC, (b) PPC5 and (c) PPC20; (d) Proposed hydrogen bonding interactions between GO sheet and PPC chains.

3.3 Dynamic mechanical analysis of the nano-confinement effect As reported earlier, the chain mobility and glass transition temperature (Tg) of polymers under nanoscale confinement are quite different from the bulk polymers. Thus, we are interested in probing and ultimately understanding the confinement effect specific to our systems. DMA was used to investigate the chain mobility for pure PPC and PPC/GO nanocomposites. Fig. 3a shows that the storage modulus of PPC increases greatly with the addition of GO. Moreover, the curves of storage modulus are right shifted with more GO content in the nanocomposites, suggesting an increase of Tg. The synergistic effects derived from the rigid GO sheets and the strong interactions between PPC and GO give rise to the augment of storage modulus and Tg. It’s worth noting that the storage modulus of all the nanocomposites suddenly decreases as the temperature goes above the Tg of PPC, an additional rubbery plateau was reached when the GO content reaches beyond 10 wt%. For example, the storage modulus of pure PPC drops down to near zero at 70 oC, it can still maintain at around 300 MPa for PPC15 and PPC20, which indicates that there exists a stiff

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network structure. With PPC and GO deeply interpenetrating with each other, the ‘GO highly compacted structure’ forms a framework that is strong enough to confine the PPC chains, which is similar to the configuration of the stiff steel structure in reinforced concrete. As shown in Fig. 3c and d, the Tg of polymer matrix is increased from 30 oC (pure PPC) to 38 o

C (PPC5), 40 oC (PPC10), 45 oC (PPC15) and 52 oC (PPC20), respectively. More interesting than

that is the appearance of another higher Tg lied on about 85 oC (PPC15) and 95 oC (PPC20). The storage modulus and Tg of pure PPC and PPC/GO nanocomposites is summarized in Table. 1. This second Tg indicates some PPC chains in nanocomposites can only be activated at a higher temperature, leading to the additional modulus plateau. The results imply an additional mechanism responsible for stronger PPC chains confinement. PPC5 and PPC10 correspond to the ‘slightly confined system’, while nanocomposites with GO content above 10 wt% represent the ‘highly confined system’. For the latter, some PPC chains probably transfer their arrangement from ‘standing up’ to ‘lying down’ on the surface of GO. Consequently, these ‘lying down’ PPC chains form more and denser interaction points with GO, thus showing a second Tg. The coexistence of ‘low-temperature Tg’ (Tg,low) and ‘high-temperature Tg’ (Tg,high) in PPC15 and PPC20 makes them interesting candidates to exhibit triple-shape memory effect (TSME).11 Moreover, the broadness of the tan δ peak (the half-maximum width of the tan δ peak) is remarkably increased with the addition of GO, together with a reduced height. That is, the two Tgs of PPC15 and PPC20 have significant overlap, can thus be regarded as one single broad transition (from 40 to 100 °C, Fig. 3c and d). This thermomechanical characteristic is regarded as a necessary basis for triggering the temperature memory effect (TME).23 Next, we shift our focus to investigate the nano-confinement effect on the versatile shape memory effects, including dual, triple shape memory and temperature memory effect.

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Figure 3. DMA curves of pure PPC and PPC/GO nanocomposites. (a) Storage modulus as a function of temperature; (b) the magnification of storage modulus curves from 55 oC to 110 oC; (c) Tan δ as a function of temperature; (d) the magnification of tan δ curves from 30 oC to 110 oC.

3.4 Dual-shape memory effect of PPC/GO nanocomposites The dual shape memory performances of PPC/GO nanocomposites with various GO content were measured on DMA, and the results were shown in Fig. 4. The shape-fixing ratio (Rf) and shape-recovery ratio (Rr) are two key parameters in quantitatively evaluation of the shape memory properties of SMPs, which can be calculated from the thermo-mechanical tensile curves. Pure PPC exhibits low Rf and Rr, which is ascribed to the relatively low modulus at ambient temperature and the fast relaxation of PPC chains during the programming process. With the addition of 5 wt% or 10 wt% GO, the Rf and Rr of nanocomposites increase remarkably to about 90 %. Further increase GO content to 15 wt% or 20 wt%, the Rf and Rr of nanocomposites both remain constant, suggesting that they reach a saturation phenomenon. For both slightly and highly confined PPC/GO nanocomposites, they all show excellent dual-shape memory properties. The enhancement of shape memory property is mainly attributed to the uniform dispersion of GO in PPC matrix, with the strong filler-matrix interactions serving as the physical cross-linking points necessary for good shape memory behaviors.

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Stress relaxation experiments of pure PPC and PPC/GO nanocomposites are measured by using DMA (see Figure. S2). The stress relaxation times of PPC, PPC5, and PPC10 are about 120 s, 210 s, and 500 s, respectively. For physically crosslinked shape memory polymers, the effective prohibition of polymer chain relaxation is essential for good shape memory behavior. Therefore, the shape recovery property of PPC/GO nanocomposites is superior to that of PPC owing to the longer relaxation time of PPC/GO nanocomposites.

Figure 4. The dual-shape memory behavior of pure PPC and PPC/GO nanocomposites, (a)PPC, (b)PPC5, (c)PPC10, (d)PPC15, (e)PPC20.

3.5 Triple-shape memory effect of highly confined PPC/GO nanocomposites The coexistence of ‘low-temperature Tg’ (Tg,low) and ‘high-temperature Tg’ (Tg,high) in PPC15 and PPC20 serve as an ideal candidates for exploring the triple-shape memory effect (TSME). The triple-shape memory effect (TSME) of PPC15, taking advantage of its two Tgs at about 45 oC and 85 oC, is presented in Fig. 5a. The procedure includes two deformations at two different temperatures with a tensile force controlled mode, which is similar to that of conventional TSMPs. The original shape εA was stretched at 80 oC, cooled to 20 oC, and then heated to 50 oC under a

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stress free condition to get the first temporary shape εB (26.1 %). This temporary shape was further stretched at 50 oC and cooled to 20 oC to get the second temporary shape εC (82 %). After that, upon reheating to 50 oC yielded the first recovered shape εB,rec (30 %). Further heating to 80 oC, the permanent recovered shape εC,rec (9.8 %) was finally attained. PPC15 clearly exhibited two different recovery states at Tg,low and Tg,high, respectively. Triple-shape memory behavior of PPC20 is illustrated in Fig. 5b (with two deformation temperatures set at 60 oC and 90 oC). In terms of shape recovery, all Rr are above 80%, demonstrating the excellent TSME of PPC15 and PPC20. The shape fix ratio (Rf) and shape recovery ratio (Rr) of pure PPC and PPC/GO nanocomposites measured from the dual and triple shape memory experiments are summarized in Table. 2. A notable difference between PPC15 and PPC20 is that higher deformation temperatures are used to deform shape for PPC20, which is attributed to the higher Tgs of PPC20. Thus, the TSME can be realized through two distinct Tgs of the PPC15 and PPC20, and the temperatures at each recovery state can be well controlled by varying the GO content.

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Figure 5. Triple-shape memory behavior of PPC15 (a) and PPC20 (b).

The tunable shape memory behavior of PPC/GO nanocomposites can be further visually demonstrated. Typical shape recovery behavior of PPC10 (corresponding to slightly confined system) and PPC20 (corresponding to highly confined system) is shown in Fig. 6. When the GO content is below 10 wt%, there is only one Tg for slightly confined system, thus they show dual-SME (DSME). As shown in Fig. 6a, the curled strip recovered to its original straight shape in 60 s at 70 oC. When the GO content is higher than 10 wt%, there is coexistence of Tg,low and Tg,high in PPC15 and PPC20. The dual Tgs of PPC15 and PPC20 are capable for deforming two different temporary shapes and memorizing shapes at two different temperatures. The visual triple-shape memory behavior of PPC20 is shown in Fig. 6b. The original shape was deformed at 100 °C and 70 °C to yield two different temporary shapes. The recoveries indicated that the intermediate and

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the original shape could well recover when reheating to 70 °C and 100 °C. Therefore, excellent TSME could be obtained. The different recovery phenomena between PPC10 and PPC20 derive from the different confined behavior of PPC with varying GO content, indicating the strong nano-confinement allows great flexibility in tuning the Tg of the PPC/GO nanocomposites, and the tunable SME can be achieved.

Figure 6. Illustration of the visual (a) DSME of PPC10 and (b) TSME of PPC20: A) original shape, B) first temporary shape, and C) second temporary shape.

3.6 Temperature memory effect of PPC/GO nanocomposites Moreover, for highly confined system, the two separated tan δ peaks of PPC15 and PPC20 become much broad and overlap together to construct a broad peak (from 40 °C to 100 °C). Thus PPC15 and PPC20 possess a broad glass transition region, which makes them suitable systems to explore the temperature memory effect (TME). To demonstrate the strain based TME, PPC15 and PPC20 were deformed at four different programing temperatures (Tprog) respectively. As shown in Fig. 7a and c, the free-strain recovery curves of PPC15 and PPC20 are remarkably shift to higher temperature by increasing the Tprog. The results from Fig. 7b and d indicates that there exists a prominent linear correlation between the Tprog and the switch temperature Tsw (the temperature corresponding to half values of Rr). The Tsw of PPC15 could be fairly well controlled by varying Tprog, with Tsw ≈ Tprog between ca. 40 °C and 70 °C. Only slight deviation by about 3 °C between Tprog and Tsw is observed, illustrating the excellent TME. For PPC20, the Tsw could be adjusted between 51 °C and 79 °C with Tprog increasing from 50 °C to 80 °C, combined with an increase of Rr to 80%. The data obtained in our work are superior to the values reported for PVA/CNTs

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nanocomposites where Rr is lower than 60 %.27 This is ascribed to the large aspect ratio of GO and strong PPC-GO interactions, form more robust physical crosslinkings to effectively confine polymer chains, thus increasing Rr. It is worth noting that the Rr is lower in the case of the temperature memory effect than the dual shape memory programming. This is due to the lower heating rate in the TME experiments (2 oC min-1), which may allow for stress relaxation.

Figure 7. Shape recovery ratio plots in continuous heating process (heating rate: 2 ºC min-1) for PPC15 (a) and PPC20 (c) deformed at four different programing temperatures (Tprog). In both two cases (b, d), the switch temperature Tsw (the temperature corresponding to half values of Rr) shows linear correlation with the applied Tprog.

According to previous studies, it’s widely accepted that a broad thermal transition is necessary for exhibiting TME.4,19,42 The broad transition can be regarded as a consecutive distribution with plenty of independent memory components. During the programing process, only the independent memory components with their transition temperatures below the Tprog are capable of movement. Upon reheating to the Tprog, these memory components are all re-activated, resulting in a maximum shape recovery rate at the corresponding Tsw. For highly confined PPC/GO nanocomposites, PPC15 and PPC20 possess a broad glass transition, and thus are able to memorize more than one programing temperature. This phenomenon is also in agreement with a

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theoretical mechanical analysis presented by Huang et al., who proposes that the broad thermal transition is the fundamental basis for both MSME and TME.43 Strain recovery experiments for slightly confined PPC/GO nanocomposites (PPC5, PPC10) were also performed at 40 oC, 50 °C and 60 °C, respectively. As shown in Fig 8.a, b, c, the strain recovery plots for PPC5 and PPC10 shift to lower temperatures than those of PPC15. Fig 8.d reveals the relationships between the Tsw and the Tprog of PPC/GO nanocomposites with various GO contents. For highly confined PPC/GO nanocomposites (PPC15, PPC20), the Tsw evolves linear correlation with the applied Tprog. While for slightly confined PPC/GO nanocomposites (PPC5, PPC10), the Tsw also exhibits linearly with the Tprog, but are all lower than the Tprog. The deviation of PPC5 and PPC10 may be attributed to their relatively low confined behavior. When the GO content is relatively low (below 10 wt%), the PPC chains are slightly confined. Some PPC chains are activated before reaching the Tprog, resulting in the Tsw below the Tprog. As the GO content increases above 10 wt%, a high fraction of interfacial area where the PPC chain mobility is significantly restricted by the sufficient hydrogen bonding interactions between PPC and GO. At the shape recovery process, the highly confined PPC chains are mostly activated around the Tprog, giving rise to the maximum shape recovery rate at the Tsw, which approximately equals to the Tprog. It can be concluded that the Tsw shows linear correlation with the Tprog for both slightly and highly confined PPC/GO nanocomposites over a wide temperature range, with the Tsw identical to the Tprog for highly confined system, but Tsw below Tprog for slightly confined system. So far, TME has been investigated for highly confined composites or materials with a broad transition temperature. The observation of linear relationship between Tsw and Tprog (Tsw < Tprog) for slightly confined composites is very interesting, and further research is needed to explore the microscopic mechanism and potential applications.

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Figure 8. Shape recovery ratio plots in continuous heating process (heating rate: 2 ºC min-1) for PPC5, PPC10 and PPC15 deformed at (a) 40 °C, (b) 50 oC and (c) 60 °C, respectively. (d) Relationships between the Tsw and the applied Tprog of PPC/GO nanocomposites with various GO contents.

4. Conclusions A new strategy for preparing tunable SMPs has been reported in this work, which utilizes the different confined polymer behavior by tuning the filler content. PPC/GO nanocomposites with high GO content are successfully fabricated via a combination of solvent-exchange and solution co-precipitation approach. It is found that GO sheet act as physical cross-linker and significantly change the thermomechanical behavior of PPC. The nano-confinement allows great flexibility in tuning the Tg of PPC/GO nanocomposites. As such, highly versatile shape memory behaviors including multi-shape memory and temperature memory effect can be achieved simply by tuning the filler contents. Our approach differs drastically from typical approaches that rely on tuning the compositions of polymer matrices via chemical synthesis to achieve diverse shape memory performances. Given that nanocomposites can be easily prepared, we believe that our method will allow easy access to polymers with tunable shape memory properties for applications in thermal actuators and multiple-stage shape memory devices. In addition, the use of a new biodegradable

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matrix (PPC) may open up new opportunities in biomedical device applications.

Supporting Information Available Figure S1, TGA and corresponding DTG curves of pure PPC and PPC/GO nanocomposites. Figure S2, Stress relaxation of PPC, PPC5 and PPC10 as a function of time. AUTHOR INFORMATION Corresponding Author E-mail: [email protected] (Q. Fu), Tel./Fax: +86 28 8546 1795. Notes The authors declare no competing financial interest.

Acknowledgements We would like to express our sincere thanks to the National Natural Science Foundation of China for financial support (Grant No. 51421061 and 51210005).

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117, 1467-1474. (11) Zhao, Q.; Behl, M.; Lendlein, A. Shape-Memory Polymers with Multiple Transitions: Complex Actively Moving Polymers. Soft Matter 2013, 9, 1744-1755. (12) Luo, X.; Mather, P. T. Triple-Shape Polymeric Composites (TSPCs). Adv. Funct. Mater. 2010, 20, 2649-2656. (13) Bellin, I.; Kelch, S.; Langer, R.; Lendlein, A. Polymeric Triple-Shape Materials. Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 18043-18047. (14) Cuevas, J. M.; Rubio, R.; Germán, L.; Laza, J. M.; Vilas, J. L.; Rodriguez, M.; León, L. M. Triple-Shape Memory Effect of Covalently Crosslinked Polyalkenamer based Semicrystalline Polymer Blends. Soft Matter 2012, 8, 4928-4935. (15) Zhao, J.; Chen, M.; Wang, X.; Zhao, X.; Wang, Z.; Dang, Z. M.; Ma, L.; Hu, G. H.; Chen, F. Triple Shape Memory Effects of Cross-linked Polyethylene/Polypropylene Blends with Cocontinuous Architecture. ACS. Appl. Mater. Interfaces 2013, 5, 5550-5556. (16) Kolesov, I. S. Multiple Shape-Memory Behavior and Thermal-Mechanical Properties of Peroxide Cross-linked Blends of Linear and Short-Chain Branched Polyethylenes. Express Polym. Lett. 2008, 2, 461-473. (17) Xie, T.; Xiao, X.; Cheng, Y. T. Revealing Triple-Shape Memory Effect by Polymer Bilayers. Macromol. Rapid Commun. 2009, 30, 1823-1827. (18) Bae, C. Y.; Park, J. H.; Kim, E. Y.; Kang, Y. S.; Kim, B. K. Organic-Inorganic Nanocomposite Bilayers with Triple Shape Memory Effect. J. Mater. Chem. 2011, 21, 11288-11295. (19) Xie, T. Tunable Polymer Multi-Shape Memory Effect. Nature 2010, 464, 267-270. (20) Dolog, R.; Weiss, R. A. Shape Memory Behavior of a Polyethylene-Based Carboxylate Ionomer. Macromolecules 2013, 46, 7845-7852. (21) Zhang, Q.; Song, S.; Feng, J.; Wu, P. A New Strategy to Prepare Polymer Composites with Versatile Shape Memory Properties. J. Mater. Chem. 2012, 22, 24776-24782. (22) Li, J.; Xie, T. Significant Impact of Thermo-Mechanical Conditions on Polymer Triple-Shape Memory Effect. Macromolecules 2011, 44, 175-180. (23) Xie, T.; Page, K. A.; Eastman, S. A. Strain-Based Temperature Memory Effect for Nafion and Its Molecular Origins. Adv. Funct. Mater. 2011, 21, 2057-2066. (24) Wang, L.; Di, S.; Wang, W.; Chen, H.; Yang, X.; Gong, T.; Zhou, S. Tunable Temperature Memory Effect of Photo-Cross-Linked Star PCL-PEG Networks. Macromolecules 2014, 47, 1828-1836. (25) Samuel, C.; Barrau, S.; Lefebvre, J.-M.; Raquez, J.-M.; Dubois, P. Designing Multiple-Shape Memory Polymers with Miscible Polymer Blends: Evidence and Origins of a Triple-Shape Memory Effect for Miscible PLLA/PMMA Blends. Macromolecules 2014, 47, 6791-6803. (26) Kratz, K.; Voigt, U.; Lendlein, A. Temperature-Memory Effect of Copolyesterurethanes and Their Application Potential in Minimally Invasive Medical Technologies. Adv. Funct. Mater. 2012, 22, 3057-3065. (27) Miaudet, P.; Derre, A.; Maugey, M.; Zakri, C.; Piccione, P. M.; Inoubli, R.; Poulin, P. Shape and Temperature Memory of Nanocomposites with Broadened Glass Transition. Science 2007, 318, 1294-1296. (28) Viry, L.; Mercader, C.; Miaudet, P.; Zakri, C.; Derré, A.; Kuhn, A.; Maugey, M.; Poulin, P. Nanotube Fibers for Electromechanical and Shape Memory Actuators. J. Mater. Chem. 2010, 20, 3487-3495.

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(29) Xie, T. Recent Advances in Polymer Shape Memory. Polymer 2011, 52, 4985-5000. (30) Qi, X.; Yao, X.; Deng, S.; Zhou, T.; Fu, Q. Water-induced Shape Memory Effect of Graphene Oxide Reinforced Polyvinyl Alcohol Nanocomposites. J. Mater. Chem. A 2014, 2, 2240-2249. (31) Qi, X. D.; Yang, G. H.; Jing, M. F.; Fu, Q.; Chiu, F. C. Microfibrillated Cellulose-Reinforced Bio-based Poly(propylene carbonate) with Dual Shape Memory and Self-Healing Properties. J. Mater. Chem. A 2014, 2, 20393-20401. (32) Gao, J.; Bai, H.; Zhou, X.; Yang, G.; Xu, C.; Zhang, Q.; Chen, F.; Fu, Q. Observation of Strong Nano-effect via Tuning Distributed Architecture of Graphene Oxide in Poly(propylene carbonate). Nanotechnology 2014, 25, 025702-025712. (33) Qi, X.; Dong, P.; Liu, Z.; Liu, T.; Fu, Q. Selective Localization of Multi-walled Carbon Nanotubes in Bi-component Biodegradable Polyester Blend for Rapid Electroactive Shape Memory Performance. Compos. Sci. Technol. 2016, 125, 38-46. (34) Bai, H.; Li, C.; Wang, X.; Shi, G. On the Gelation of Graphene Oxide. J. Phys. Chem. C 2011, 115, 5545-5551. (35) Dong, J.; Ding, J.; Weng, J.; Dai, L. Graphene Enhances the Shape Memory of Poly (acrylamide-co-acrylic acid) Grafted on Graphene. Macromol. Rapid Commun. 2013, 34, 659-664. (36) Wang, X.; Shi, G. An Introduction to the Chemistry of Graphene. Phys. Chem. Chem. Phys. 2015, 17, 28484-28504. (37) Hummers, W. S.; Offeman, R. E. Preparation of Graphitic Oxide. J. Am. Chem. Soc. 1958, 80, 1339-1339. (38) Liang, J.; Huang, Y.; Zhang, L.; Wang, Y.; Ma, Y.; Guo, T.; Chen, Y. Molecular-Level Dispersion of Graphene into Poly(vinyl alcohol) and Effective Reinforcement of their Nanocomposites. Adv. Funct. Mater. 2009, 19, 2297-2302. (39) Kou, L.; Gao, C. Bioinspired Design and Macroscopic Assembly of Poly(vinyl alcohol)-Coated Graphene into Kilometers-long Fibers. Nanoscale 2013, 5, 4370-4378. (40) Gunes, I. S.; Pérez-Bolivar, C.; Cao, F.; Jimenez, G. A.; Anzenbacher, P.; Jana, S. C. Analysis of Non-Covalent Interactions between the Nanoparticulate Fillers and the Matrix Polymer as Applied to Shape Memory Performance. J. Mater. Chem. 2010, 20, 3467-3474. (41) Zhou, S. B.; Zheng, X. T.; Yu, X. J.; Wang, J. X.; Weng, J.; Li, X. H.; Feng, B.; Yin, M. Hydrogen Bonding Interaction of Poly(D,L-lactide)/Hydroxyapatite Nanocomposites. Chem. Mater. 2007, 19, 247-253. (42) Kratz, K.; Madbouly, S. A.; Wagermaier, W.; Lendlein, A. Temperature-Memory Polymer Networks with Crystallizable Controlling Units. Adv. Mater. 2011, 23, 4058-4062. (43) Sun, L.; Huang, W. M. Mechanisms of the Multi-Shape Memory Effect and Temperature Memory Effect in Shape Memory Polymers. Soft Matter 2010, 6, 4403-4406.

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Table 1. Storage modulus and Tg of pure PPC and PPC/GO nanocomposites. Storage modulus at 0 oC

Storage modulus at 60 oC

(MPa)

(MPa)

Tg (oC)

Sample

PPC

2846

1

30

PPC5

4143

30

38

PPC10

5008

76

40

PPC15

5571

373

45; 85

PPC20

6550

519

52; 95

Table 2. Summary of the shape fix ratio (Rf) and shape recovery ratio (Rr) of pure PPC and PPC/GO nanocomposites measured from the dual and triple shape memory experiments. Dual SMP

Triple SMP

Sample

Rf (%)

Rr (%)

Rf (A-B) (%)

Rf (B-C) (%)

PPC

72.6

68.9

-

-

-

-

PPC5

92.9

85.3

-

-

-

-

PPC10

91.0

89.9

-

-

-

-

PPC15

94.9

88.2

95.6

98.9

87.2

87.7

PPC20

93.1

82.8

94.9

94.3

81.5

80.3

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TOC Graphic

Temperature memory effect 80

PPC5 PPC10 PPC15 PPC20

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40

50 60 Tprog (°°C)

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70

80