Effects of Regular Networks Composed of Rigid and Flexible

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Materials and Interfaces

Effects of regular networks composed of rigid and flexible segments on the shape memory performance of epoxies Xiaocun Tan, Qi Zou, Yizhou Huang, Mengyu Ouyang, Yazhou Tian, Jue Cheng, and Junying Zhang Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b01312 • Publication Date (Web): 23 May 2018 Downloaded from http://pubs.acs.org on May 23, 2018

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Industrial & Engineering Chemistry Research

Effects of regular networks composed of rigid and flexible segments on the shape memory performance of epoxies

Xiaocun Tan†, Qi Zou †, Yizhou Huang †, Mengyu Ouyang †, Yazhou Tian †,Jue Cheng†,*, Junying Zhang†,* †Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, People’s Republic of China *Corresponding author. Tel.: +86 10 64425439; fax: +86 10 64425439 E-mail address: [email protected] (J. Cheng), [email protected] (J.Zhang)

ABSTRACT A series of regular rigid-flexible crosslinking epoxy networks were prepared from dithiol allyl glycidyl ethers (DTAGEs) and 4,4’-diaminodiphenylmethane (DDM). In these networks, the chemical structure of DTAGEs was tidily flexible and that of DDM was simply rigid, which ensured the flexible segments more distinguishable from the rigid units. The effects of regularity and rigid-flexible character of the networks on shape memory properties, especially shape recovery speed, were investigated detailly. It was found shape recovery speed was reversely proportional to the flexibility of the regular crosslinking networks. Compared with flexibility, regularity had a greater impact on the recovery speed. In addition, regularity had a significant influence on the recovery speed of the rigid units while had little influence on that of the flexible segments. The well-designed regular rigid-flexible crosslinking networks exhibited excellent shape memory performance with high shape memory fixity (≥ 98.4%) and shape memory recovery (≥ 99.4%).

KEY WORDS: Shape memory epoxy; rigid-flexible crosslinking network; thiol-ene click chemistry; regularity

1. INTRODUCTION Recently, shape memory polymers1,2 (SMPs) have become one of the most popular smart materials because of their unique advantages, such as potential high recoverable strain, light weight, low cost, and easy processability. SMPs could be deformed and fixed in a temporary shape and able to recover their original shape under certain stimulations (e.g., heat3,4, light5–7, pH8,9 or electron current10,11. Various types of thermal sensitive SMPs such as

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polyurethane12,13, polyester7,14, poly(ε-caprolactone)11,15,16 have been investigated in many fields including biomateria17–19, sensor20, aerospace21–23.The shape memory epoxy resins (SMEPs) have been attracting much interest and are promising candidate materials for space deployable structure materials and wing morphing materials, due to their easy tuning in thermal, thermomechanical properties and excellent shape memory properties, mechanical properties and environmental durability24,25. It’s well known that typical epoxy-based materials (extensively applied in adhesives, coatings, and matrix material for structural composites) are rigid with relatively low failure strains, being undesirable properties for SMEPs. To focus on this problem, two possible ways can be used for increasing the strain of SMEPs. One method is increasing their application temperature during deformation26. It was confirmed that the stain of SMEPs at the onset temperature of glass transition (TgE’) was about 3-5 times higher than that in the vicinity of Tg. As a consequence, selecting TgE’ as the switching temperature (short as Tsw) was beneficial to improve the stain of SMEPs. The other is based on material design containing ‘physical blending’ and ‘chemical structure design’, which attracted wide interests24,26–33. It is noticeable that epoxy crosslinking networks built by both methods of ‘Physical blending’ and ‘chemical structure design’ are ‘irregular’. The irregularity of crosslinking network originated in various molecular structures in physical blends and polydisperse chain lengths in epoxides and diamines, leading to internal stress and defect. Theoretically, compared to regular crosslinking network, irreversible transformation and deformation should be easy to occur in irregular ones under the applied stress, which probably limits the enhancement of shape memory properties (show in Scheme 1). However, the effect of regularity of crosslinking network on the shape memory properties were rarely reported, possibly due to the difficulty and challenge in preparing epoxides with regular structure. Essentially, regular structural epoxy should hold higher content of epoxy groups, close to theoretical number, and desirable chain structure. In our previous work34, we have prepared an eugenol-based epoxy followed by the UV light thiol-ene click reaction with aliphatic dithiol compounds to form a series of relatively regular epoxy resins with rigid-flexible chain. Owing to the thiol-ene click reaction features: simplicity, high selectivity and efficiency and mild reaction conditions35–38, the epoxide values of as-prepared rigid-flexible epoxy resins is close to 90% theoretical ones. After curing with 4,4’-Diaminodiphenylmethane (DDM) to form the rigid-flexible crosslinking networks, the as-prepared SMPs exhibited high shape memory fixity ratio (> 97%) and shape memory recovery ratio (> 99%). Importantly, it is found that the regularity of the epoxy resin network is the primary factor determining the


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shape recovery speed 34. Whereas, eugenol-based rigid-flexible epoxy contains aromatic units and an aliphatic chain, after further cured by DDM, it’s not clear to distinguish the rigid units from flexible segments in the network, making it impossible to investigate the contribution of rigid units and flexible segments to shape recovery speed. Actually, shape recovery speed relies on the two-phase microstructures: fixed phase and switching segments. The fixed phase refers to rigid units and functions as defining and memorizing the permanent shape; switching segments refers to flexible segments and recovers to the original shape by the change of segment conformation when they suffer from thermal stimulus (e.g., melting transition or glass transition). Therefore, it’s crucial to construct an epoxy network with clear rigid-flexible distinguishable architectures to study their effects on the shape recovery speed. In this work, a series of novel flexible dithiol allyl glycidyl ethers (DTAGEs, shown in Scheme 2) were designed via click reaction of allyl glycidyl ethers(AGE) and dithiols (1,2-Ethanedithiol, EDT; 1,6-Hexanedithiol allyl glycidyl ether (HDT); and 1,10-Decanedithiol allyl glycidyl ether (DDT), respectively.). Thanks to high purity of the commercial AGE (99%) and high efficiency of click reaction (close to 100%)36, the epoxy equivalent weights of as-prepared DTAGEs were basically consistent with the theoretical ones. These make the crosslinking network extraordinarily regular and clear after DTAGEs curing with DDM (see in Scheme 2). In addition, the distinguishable rigid units and flexible segment in the crosslinking network is highly valuable to further study their effects on the shape recovery speed. Furthermore, the effect of regularity on the shape memory properties was comparatively studied by employing an irregular crosslinking network of an equal mass mixture of the three asprepared DTAGEs (named as M-AGE) as a reference. This work provides a new insight on the structural design of high-performing SMPs.

2. EXPERIMENTAL SECTION 2.1. Materials. EDT (98%), HDT (97%), and DDT (96%) were purchased from Alfa Aesar Chemicals Co., Ltd. (Shanghai, China). AGE (99%), DDM (99%), and photo initiator 2-Hydroxy-2-methylpropiophenone (1173, 99%) were purchased from Aladdin Industrial Corporation (Shanghai, China). All chemicals were used as received.

2.2 Synthesis of DTAGEs



As we mentioned above, DTAGEs was a generic term referring as three kinds of flexible epoxy resins, 1,2ethanedithiol allyl glycidyl ether (EDT-AGE), 1,6-Hexanedithiol allyl glycidyl ether (HDT-AGE), and 1,10Decanedithiol allyl glycidyl ether (DDT-AGE), which were synthesized by a click reaction (catalyst 1173) of EDT/ HDT/ DDT and AGE under UV light. The reaction route was showed in Scheme 2 and the procedure was as follows: EDT/HDT/DDT and AGE were mixed stoichiometrically with a molar ratio of C=C to sulfydryl equal to 1:1. Then the reactants were stirred under UV light for 4 h. The epoxy equivalent weight of as-prepared DTAGEs (measured by hydrochloric acid-acetone titration) as well as the detailed formulations (mass ratio) for the synthesis of DTAGE was shown in Table 1.

2.3 Characterization of DTAGEs 2.3.1 Fourier transform infrared (FTIR) spectroscopy The FTIR spectra were recorded on a Nicolet Nexus 670 FTIR spectrometer in transmission mode. The wavenumber range was 4000-400 cm−1 with a resolution of 4 cm−1. 2.3.2 1H NMR spectroscopy 1

H NMR spectra were recorded on a Bruker Avance 400 spectrometer (400 MHz) with tetramethylsilane as an

external standard and deuterated CDCl3 as a solvent.

2.4 Preparation of DTAGEs/DDM and M-AGE/DDM samples DTAGEs and M-AGE (an equal mass mixture of the three as-prepared DTAGEs) were stoichiometrically mixed with DDM with a molar ratio of epoxy groups to amino hydrogen equal to 1:1 at 90ºC. Then, the reactants were degassed in a vacuum oven at 70 °C for 45 min to remove the trapped air bubbles. Afterward, the degassed reactants were poured into a preheated copper mold, and curing reaction was conducted thermally at the stepwise schedule: 100ºC for 1.5 h, 120 ºC for 2 h and 150ºC for 4 h. The detailed formulations (mass ratio) for the curing reaction were shown in supporting information (see Table S1).

2.5 Characterization of shape memory behavior 2.5.1 Dynamic mechanical analysis (DMA)


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The thermomechanical properties of DTAGEs/DDM and M-AGE/DDM were evaluated using a DMA Q800 (TA Instruments) in the film tension mode. Rectangular samples were width of 6 mm and thickness of 1 mm. And the samples were analyzed from -10 ºC to 100 ºC at 1 Hz and a heating rate of 3 ºC min-1. The storage modulus (E’), the onset of glass transition temperature (TgE’), and the glass transition temperature (Tg) were obtained on the DMA spectra. Tg was determined from the peak value in tanδ. TgE’ was determined as the onset in the storage modulus decrease during the glass transition drop. 2.5.2 Shape memory effect (SME) analysis The SME analysis of the SMEP was quantitatively evaluated in controlled-force mode on the Q800 DMA using rectangular samples with width of 3 mm and thickness of 1 mm. (a) Deformation: the sample was deformed till an appropriate strain at its TgE’; (b) Cooling: under the imposed deformation constraint, the sample was cooled from TgE’ to the setting temperature (TgE’ -30) ºC with a cooling rate of 3ºC min-1; (c) Unloading: at (TgE’ -30) ºC, the deformation constraint was released to 0.001N and the strain reached a value of εm, and the sample was equilibrated at (TgE’ -30) ºC for 5 min and the strain reached a value of εu; (d) Recovery: the temporarily deformed sample was heated up to (TgE’+30) at a heating rate of 3 °C min-1 and the strain adopts a value of εf. The shape fixity (Rf) and the shape recovery ratio (Rr) for the SME were calculated as follows: Shape fixity:R N = Shape recovery: R N =

× 100%

× 100%

(1) (2)

N represents the cycle number.

3. RESULTS AND DISCUSSION 3.1 Structural characterization of DTAGEs DTAGEs were synthesized by the reaction of AGE with EDT, HDT, and DDT. To confirm the structures of DTAGEs, DTAGEs and AGE were tested by FTIR and 1H NMR shown in Figure 1 and Figure 2, respectively. The assignment of characteristic absorption bands of DTAGEs in Figure 1 was as follows: the bands at 1096 cm-1 and 1647 cm-1 are assigned to the C-O-C stretching vibration and the C=C stretching vibration; the absorption bands of



C=C out-of-plane bending and epoxy ring stretching overlapped at vicinity of 920 cm-1. Noticeably, the intensity of the C-O-C stretching peak is identical for all the samples, while the absorbance of the C=C stretching at 1647cm-1 disappeared, and the absorbance of the epoxide rings in EDT-AGE, HDT-AGE, and DDT-AGE appeared at 913cm1

. It can be confirmed from Figure 1 that the C=C bonds were consumed completely after the UV light thiol-ene

click reaction. On the other hand, the absorbance of ethylene (-CH2-) stretching vibration at 2926 cm-1 increased significantly for EDT-AGE, HDT-AGE, and DDT-AGE, coming from the ethylene units in dithiols. Figure 2 showed the 1H NMR spectra of DTAGEs and AGE. For the spectrum of AGE, the chemical shifts at 5.24 and 5.91 ppm correspond to the unsaturated protons 8 and 7 attached to the double bonds respectively, and the peak at 4.05 ppm is derived from the proton 6 (CH2=CH-CH2-O-). The signals from unsaturated protons disappeared in the 1H NMR spectra of EDT-AGE, HDT-AGE, and DDT-AGE in Figure 2, indicating the completion of the UV light thiol-ene click reaction of AGE and dithiols. Correspondingly, the signals from protons 8, 7 and 6 shifted to 2.64, 1.86, and 3.58 ppm, respectively, after the UV light thiol-ene click reaction. Peaks of other protons in AGE and DTAGEs were also identified accordingly at the 1H NMR spectra, that is, the peaks at 2.80, 2.62, and 3.16 ppm in Figure 2 (AGE spectrum, EDT-AGE spectrum, HDT-AGE spectrum, DDTAGE spectrum) represented the protons 1, 2, 3 in the epoxide ring and the peaks at 3.40, 3.72 represent the protons 4, 5 in AGE and DTAGEs. For EDT-AGE spectrum, the peak at 2.72 ppm represented proton 9. For HDT-AGE, the peaks at 2.51, 1.59, and 1.40 ppm represent protons 9, 10 and 11 respectively. For DDT-AGE spectrum, the peaks at 2.50, 1.57, 1.36 and 1.28 ppm represent protons 9, 10, 11 and 12, respectively. These clarified that three kinds of DTAGEs were successfully synthesized. Besides, the integral values of peak 3 and peak 7 in Figure 2 were also selected to estimate the epoxy equivalent weight of EDT-AGE, HDT-AGE and DDT-AGE, and the results coincided with those showed in Table 1 very well, close to theoretical value respectively.

3.2 DMA TgE’s of SMEPs, chosen as Tsws, was the essential parameter to determine the temperature range of deformation, cooling, fixing, and recovery and was determined by DMA spectra (see Figure 3). And the values of TgE’, Tg, E’ (0ºC) were listed in Table 2. The TgE’, Tg, and E’ (0ºC) increased with increasing the crosslinking density and decreasing the flexibility. While, the values of TgE’, Tg, E’ (0ºC) of sample M-AGE/DDM were close to those of sample HDT-AGE/DDM, which was reasonable due to their almost the same epoxy equivalent weights.


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3.3 SME analysis of DTAGEs/DDM and M-AGE/DDM networks To evaluate the shape memory performance of SMEPs, three-dimensional (3D) shape memory cycle test was conducted（see Figure 4 and Figure S2）. Figure 4 presented the shape memory cycle diagram for the quantitative shape memory evaluation of EDT-AGE/DDM, and other DTAGEs/DDM and M-AGE/DDM were shown in Figure S2. And each sample was tested three cycles. It can be observed that DTAGEs/DDM networks all have robust cycle stability in cyclic tests. This suggests that the as-prepared SMEPs can be reused with a reliable accuracy. The shape memory cycle had four consecutive steps as described previously: ‘Deformation’, ‘Cooling’, ‘Fixing’, and ‘Recovery’. In the ‘Deformation’ step, all rectangular samples were stretched to basically the same strain about 22%, and the corresponding stress values were listed in Table 3. In the ‘Cooling’ step, DTAGEs/DDM and M-AGE/DDM networks all had less creep deformation because of their highly integrated crosslinking networks and limited defects. In the ‘Unloading’ step and ‘Recovery’ step, the shape memory fixity (Rf) and the shape memory recovery (Rr) were calculated by equation 1 and equation 2 respectively, and the results were listed in Table 3. DTAGEs/DDM networks had excellent recovery performance, because all the Rr values of DTAGEs/DDM networks are higher than 99.4% shown in Table 3. And, the Rr of M-AGE/DDM network, as a reference, is 98.4%, smaller than those of DTAGEs/DDM networks. On the other hand, M-AGE/DDM network presented larger deviation during the three cycles, which can be observed from Figure 5 that the final strain of M-AGE/DDM did not reach the initial strain in the shape memory cycle. This means that M-AGE/DDM network can’t recover to the initial state after the first cycle, because the network of M-AGE/DDM was irregular and three kinds of flexible chain length blocked each other, leading to more energy loss. Meanwhile, DTAGEs/DDM showed good shape fixity ( Rf ≥ 98.4 %). In a word, the as-prepared DTAGEs/DDM networks had excellent shape memory performance and robust cycle stability and less creep deformation. In order to characterize the thermo-responsibility of the shape recovery of SMEPs, the shape recovery speed against temperature diagrams in DTAGEs/DDM and M-AGE/DDM networks were obtained by differentiating the ‘recovery’ step curves (see Figure 6). In Figure 6, curves are not symmetrical and have visible shoulders, which may arise from two recovery processes, the rigid unit recovery process and the flexible segment recovery process. The rigid units recovered to its original state owing to the interaction between the groups of intra-chains, and the flexible



segments recovered to its original state due to the entropy elasticity. Consequently, two peaks were deconvoluted: rigid unit fitting peak and flexible segment fitting peak. The fitting peak sum of all crosslinking networks was basically overlapped by the experimental data. All the segments were in movable state38 because the ‘Recovery’ step was basically in glass transition zone. The recovery of the rigid units was based on the interaction of hard groups38, which can be easily and rapidly released. Therefore, the shape recovery speed fitting curve of rigid unit was narrow and sharp. On the other hand, the recovery of flexible segment was driven by the entropy elasticity, and entropy elasticity was reflected by conformation transitions of segment, which was positively correlated with temperature and negatively correlated with the length of flexible segments38. Thus, the recovery force of flexible segments was released relatively slow, and the shape recovery speed fitting curve of flexible segments was wide and short. The peak temperature of the rigid unit fitting curve was lower than that of the flexible segment fitting curve since the temperature has little influence on the interaction of rigid group and has positively relation with the entropy elasticity. The maximum fitting recovery speeds of networks, rigid units and flexible units were listed in Table 3. The maximum (fitting) recovery speed was the value of the peak of the shape recovery speed against temperature (fitting) diagram. The maximum recovery speed of networks decreases in the sequence: EDT-AGE/DDM > HDTAGE/DDM > DDT-AGE/DDM > M-AGE/DDM, which is influenced by the regularity and rigid-flexible property of the networks. As to DTAGEs/DDM networks, the regularities of the networks are similar. The decrease of recovery speed is led by the decrease of fitting max speeds of both rigid unit and the flexible segment. This result agrees with the fact that content of rigid units decreases and the length of flexible segment increases. As to MAGE/DDM network, the fitting maximum recovery speed of the rigid unit is the slowest, and that of flexible segment is a bit faster than the speed of HDT-AGE/DDM, although the rigid-flexible property of M-AGE/DDM network is similar to that of HDT-AGE/DDM network. This result is due to the irregularity of M-AGE/DDM network. It is considered that the network regularity mainly affects the uniformity of the distribution of rigid units in the crosslinking network. The distribution of rigid units is nonuniform if the crosslinking network is irregular, and the rigid units will constrain each other at various positions and can’t reinstate the original state synchronously in this case, so the rigid unit recovery speed becomes slow. The shape recovery speed of the flexible segment mainly relies on the entropy elasticity, which is a relatively smooth process depending on the conformation transitions of segments. The network regularity had little effect on conformation transitions of flexible segments, therefore, the


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network regularity has little effect on flexible segment recovery speed. M-AGE contains EDT-AGE with shorter flexible segments and entropy elasticity is negatively correlating with the length of flexible segments. Thus, its flexible segment maximum recovery speed is relatively faster. In fact, as shown in Table 3, the maximum recovery speed of M-AGE/DDM is the slowest, clarifying that the effect of crosslinking network regularity on the recovery speed is greater than that of flexibility. Therefore, the regularity of the crosslinking network is the first factor influencing shape recovery speed, and the flexibility is the second factor.

4. CONCLUSION A series of regular rigid-flexible crosslinking networks, with tidily distinguishable flexible segments and the rigid units, were prepared using DTAGEs and DDM. The regular networks showed excellent shape memory performance with high Rf (≥ 99.4%) and Rr (≥ 98.4%). The shape memory recovery process consisted of two parts: the rigid unit recovery and the flexible segment recovery. The regularity of the crosslinking network had a significant influence on the recovery speed of the rigid units while had little influence on that of the flexible segments. Moreover, the regularity of the crosslinking network was the first factor affecting the shape recovery speed, and the flexibility was the second factor.

SUPPORTING INFORMATION The Supporting Information is available free of charge on the ACS Publications website.

ACKNOWLEDGEMENTS The authors would like to acknowledge the financial support from the National Natural Science Foundation of China under Grant No.21476013.

REFERENCES (1)

Zhao, Q.; Qi, H. J.; Xie, T. Recent Progress in Shape Memory Polymer: New Behavior, Enabling Materials, and Mechanistic Understanding. Prog. Polym. Sci. 2014, 49–50, 79–120.

(2)

Hager, M. D.; Bode, S.; Weber, C.; Schubert, U. S. Shape Memory Polymers: Past, Present and Future Developments. Prog. Polym. Sci. 2015, 49, 3–33.



(3)

Xiao, X.; Kong, D.; Qiu, X.; Zhang, W.; Zhang, F.; Liu, L.; Liu, Y.; Zhang, S.; Hu, Y.; Leng, J. ShapeMemory Polymers with Adjustable High Glass Transition Temperatures. Macromolecules 2015, 48 (11), 3582–3589.

(4)

Shi, Y.; Yoonessi, M.; Weiss, R. A. High Temperature Shape Memory Polymers. Macromolecules 2013, 46 (10), 4160–4167.

(5)

Kumpfer, J. R.; Rowan, S. J. From Photo-Cross-Linked Metallo-Supramolecular Polymers. 2011, 12866– 12874.

(6)

Wang, K.; Jia, Y.-G.; Zhu, X. X. Biocompound-Based Multiple Shape Memory Polymers Reinforced by Photo-Cross-Linking. ACS Biomater. Sci. Eng. 2015, 1 (9), 855–863.

(7)

Rochette, J. M.; Ashby, V. S. Photoresponsive Polyesters for Tailorable Shape Memory Biomaterials. Macromolecules 2013, 46 (6), 2134–2140.

(8)

Song, Q.; Chen, H.; Zhou, S.; Zhao, K.; Wang, B.; Hu, P. Thermo- and pH-Sensitive Shape Memory Polyurethane Containing Carboxyl Groups. Polym. Chem. 2016, 1739–1746.

(9)

Lu, W.; Le, X.; Zhang, J.; Huang, Y.; Chen, T.; Yan, X. Z.; Wang, F.; Zheng, B.; Huang, F. H.; Miyata, T.; et al. Supramolecular Shape Memory Hydrogels: A New Bridge between Stimuli-Responsive Polymers and Supramolecular Chemistry. Chem. Soc. Rev. 2017, 46 (5), 1284-1294..

(10)

Liu, Y.; Lv, H.; Lan, X.; Leng, J.; Du, S. Review of Electro-Active Shape-Memory Polymer Composite. Compos. Sci. Technol. 2009, 69 (13), 2064–2068.

(11)

Xiao, Y.; Zhou, S.; Wang, L.; Gong, T. Electro-Active Shape Memory Properties of Poly(ε-Caprolactone)/ Functionalized Multiwalled Carbon Nanotube Nanocomposite. ACS Appl. Mater. Interfaces 2010, 2 (12), 3506–3514.

(12)

Ahmed, N.; Kausar, A.; Muhammad, B. Advances in Shape Memory Polyurethanes and Composites: A Review. Polym. Plast. Technol. Eng. 2015, 54 (13), 1410-1423.

(13)

Kausar, A. Review on Technological Significance of Photoactive, Electroactive, pH-sensitive, Water-active, and Thermoresponsive Polyurethane Materials. Polym. Plast. Technol. Eng. 2016, 56 (6), 606-616.

(14)

Coativy, G.; Misra, M.; Mohanty, A. K. Synthesis of Shape Memory Poly(glycerol Sebacate)-Stearate Polymer. Macromol. Mater. Eng. 2017, 302 (2), 201600294.


Page 10 of 23

Page 11 of 23 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(15)

Garle, A.; Kong, S.; Ojha, U.; Budhlall, B. M. Thermoresponsive Semicrystalline Poly(ε-Caprolactone) Networks: Exploiting Cross-Linking with Cinnamoyl Moieties to Design Polymers with Tunable Shape Memory. ACS Appl. Mater. Interfaces 2012, 4 (2), 645–657.

(16)

Lewis, C. L.; Meng, Y.; Anthamatten, M. Well-Defined Shape-Memory Networks with High Elastic Energy Capacity. Macromolecules 2015, 4918-4926.

(17)

Fan, J.; Li, G. High Performance and Tunable Artificial Muscle Based on Two-Way Shape Memory Polymer. RSC Adv. 2017, 7 (2), 1127–1136.

(18)

Ecker, M.; Danda, V.; Shoffstall, A. J.; Mahmood, S. F.; Joshi-Imre, A.; Frewin, C. L.; Ware, T. H.; Capadona, J. R.; Pancrazio, J. J.; Voit, W. E. Sterilization of Thiol-ene/Acrylate Based Shape Memory Polymers for Biomedical Applications. Macromol. Mater. 2016, 302 (2), 201600331.

(19)

Chan, B. Q. Y.; Low, Z. W. K.; Heng, S. J. W.; Chan, S. Y.; Owh, C.; Loh, X. J. Recent Advances in Shape Memory Soft Materials for Biomedical Applications. ACS Appl. Mater. Interfaces 2016, 8 (16), 10070– 10087.

(20)

Kunzelman, J.; Chung, T.; Mather, P. T.; Weder, C. Shape Memory Polymers with Built-in Threshold Temperature Sensors. J. Mater. Chem. 2008, 18 (10), 1082-1086.

(21)

Liu, Y.; Du, H.; Liu, L.; Leng, J. Shape Memory Polymers and Their Composites in Aerospace Applications: A Review. Smart Mater. Struct. 2014, 23 (2), 23001-23022.

(22)

Lee, T.; Leok, M.; McClamroch, N. H. Geometric numerical integration for complex dynamics of tethered spacecraft. Proc. 2011 Am. Control Conf. 2011, 1885–1891.

(23)

Santo, L. Shape Memory Polymer Foams. Prog. Aerosp. Sci. 2016, 81, 60–65.

(24)

Santhosh Kumar, K. S.; Biju, R.; Reghunadhan Nair, C. P. Progress in Shape Memory Epoxy Resins. React. Funct. Polym. 2013, 73 (2), 421–430.

(25)

Karger-Kocsis, J.; Kéki, S. Review of Progress in Shape Memory Epoxies and Their Composites. Polymers (Basel). 2017, 10 (1), 1–38.

(26)

Feldkamp, D. M.; Rousseau, I. A. Effect of the Deformation Temperature on the Shape-Memory Behavior of Epoxy Networks. Macromol. Mater. Eng. 2010, 295 (8), 726–734.



(27)

Yu, R.; Yang, X.; Zhang, Y.; Zhao, X.; Wu, X.; Zhao, T.; Zhao, Y.; Huang, W. 3D Printing of Shape Memory Composites with Epoxy-Acrylate Hybrid Photopolymer. ACS Appl. Mater. Interfaces 2017, 9 (2), 1820-1829.

(28)

Arnebold, A.; Hartwig, A. Fast Switchable, Epoxy Based Shape-Memory Polymers with High Strength and Toughness. Polym. (United Kingdom) 2016, 83, 40–49.

(29)

Rousseau, I. a.; Xie, T. Shape Memory Epoxy: Composition, Structure, Properties and Shape Memory Performances. J. Mater. Chem. 2010, 20 (17), 3431-3441.

(30)

Santiago, D.; Fabregat-Sanjuan, A.; Ferrando, F.; De La Flor, S. Recovery Stress and Work Output in Hyperbranched Poly(ethyleneimine)-Modified Shape-Memory Epoxy Polymers. J. Polym. Sci. Part B Polym. Phys. 2016, 54 (10), 1002–1013.

(31)

Liu, Y.; Zhao, J.; Zhao, L.; Li, W.; Zhang, H.; Yu, X.; Zhang, Z. High Performance Shape Memory Epoxy/Carbon Nanotube Nanocomposites. ACS Appl. Mater. Interfaces 2016, 8 (1), 311–320.

(32)

Zheng, N.; Fang, G.; Cao, Z.; Zhao, Q.; Xie, T. High Strain Epoxy Shape Memory Polymer. Polym. Chem. 2015, 6 (16), 3046–3053.

(33)

Fan, M.; Liu, J.; Li, X.; Zhang, J.; Cheng, J. Thermal, Mechanical and Shape Memory Properties of an Intrinsically Toughened Epoxy/anhydride System. J. Polym. Res. 2014, 21 (3), 1-8.

(34)

Zou, Q.; Ba, L.; Tan, X.; Tu, M.; Cheng, J.; Zhang, J. Tunable Shape Memory Properties of Rigid???flexible Epoxy Networks. J. Mater. Sci. 2016, 51 (23), 10596–10607.

(35)

Carioscia, J. A.; Stansbury, J. W.; Bowman, C. N. Evaluation and Control of Thiol-Ene/thiol-Epoxy Hybrid Networks. Polymer (Guildf). 2007, 48 (6), 1526–1532.

(36)

Hoyle, C. E.; Bowman, C. N. Thiol-Ene Click Chemistry. Angew. Chemie - Int. Ed. 2010, 49 (9), 1540– 1573.

(37)

Hoyle, C. E.; Lowe, A. B.; Bowman, C. N. Thiol-Click Chemistry: A Multifaceted Toolbox for Small Molecule and Polymer Synthesis. Chem. Soc. Rev. 2010, 39 (4), 1355–1387.

(38)

Dondoni, A.; Marra, A. Recent Applications of Thiol–ene Coupling as a Click Process for Glycoconjugation. Chem. Soc. Rev. 2012, 41 (2), 573-586.

(39) The Physics of Polymers. Springer Berlin Heidelberg: 1997.


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Figure Captions

Scheme 1. Schematic illustration of the different shape memory behavior between (a) irregular network and (b) regular network

Scheme 2. Diagram of preparation of regular rigid-flexible epoxy network

Figure 1. FTIR spectra of DTAGEs and AGE

Figure 2. 1H NMR spectra of DTAGEs and AGE

Figure 3. DMA spectra of EDT-AGE/DDM sample

Figure 4. 3D strain-stress-temperature diagram for EDT-AGE/DDM network

Figure 5. Strain-temperature diagrams for DTAGEs/DDM and M-AGE/DDM networks

Figure 6. Temperature dependence of shape recovery speed and fitting curves for DTAGEs/DDM and MAGE/DDM networks



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Table Captions and Tables

Table 1. Formulations (Mass Ratio) of DTAGEs Epoxy equivalent weight (g·mol-1)

Samples

AGE (g)

EDT (g)

HDT (g)

DDT (g)

1173 (g)

EDT-AGE

100

42.1

0

0

0.71

163.40

HDT-AGE

100

0

67.9

0

0.84

193.05

DDT-AGE

100

0

0

95.2

0.98

224.22

Table 2. Values of TgE’, Tg and E’ (0 ºC)

Samples

TgDMA (ºC)

TgE’ (ºC)

E’ (0ºC) (MPa)

EDT-AGE/DDM

42.9

33.7

1561

HDT-AGE/DDM

37.9

28.3

1198

DDT-AGE/DDM

25.2

16.3

927

M-AGE/DDM

34.7

25.1

1257

Table 3. Values of shape memory properties and fitting max recovery speeds for DTAGE/DDM and M-AGE/DDM networks

Samples EDTAGE/DDM HDTAGE/DDM DDTAGE/DDM MAGE/DDM

Fitting Max Recovery speed (%·min-1) Flexible Rigid unit segment

Shape fixity ratio (%)

Shape recovery ratio (%)

Max Stress (MPa)

Max Recovery speed (%·min-1)

99.49±0.02

99.83±0.13

2.19

-6.48

-4.75

-3.22

99.51±0.02

99.45±0.12

1.59

-5.56

-4.30

-2.44

98.44±0.06

99. 76±0.06

1.47

-5.26

-4.25

-2.23

97.48±0.04

98.56±0.09

1.65

-4.91

-3.91

-2.66


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Scheme 1. Schematic illustration of the different shape memory behavior between (a) irregular network and (b) regular network 283x124mm (150 x 150 DPI)

ACS Paragon Plus Environment


Scheme 2. Diagram of preparation of regular rigid-flexible epoxy network 143x83mm (150 x 150 DPI)


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Figure 1. FTIR spectra of DTAGEs and AGE 194x135mm (96 x 96 DPI)



Figure 2. 1H NMR spectra of DTAGEs and AGE 201x288mm (300 x 300 DPI)


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Figure 3. DMA spectra of EDT-AGE/DDM sample 287x201mm (300 x 300 DPI)



Figure 4. 3D strain-stress-temperature diagram for EDT-AGE/DDM network 287x201mm (300 x 300 DPI)


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Figure 5. Strain-temperature diagrams for DTAGEs/DDM and M-AGE/DDM networks 180x127mm (150 x 150 DPI)



Figure 6. Temperature dependence of shape recovery speed and fitting curves for DTAGEs/DDM and MAGE/DDM networks 201x141mm (300 x 300 DPI)


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For Table of Contents Only 47x26mm (300 x 300 DPI)


Effects of Regular Networks Composed of Rigid and Flexible

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