Sustainable Multiple- and Multistimulus-Shape-Memory and Self

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Sustainable Multiple and Multi-stimuli Shape Memory and Self-Healing Elastomers with Semi-interpenetrating network Derived from Biomass via Bulk Radical Polymerization Chuanwei Lu, Yupeng Liu, Xiaohuan Liu, Chunpeng Wang, Jifu Wang, and Fuxiang Chu ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.8b00329 • Publication Date (Web): 28 Mar 2018 Downloaded from http://pubs.acs.org on March 31, 2018

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ACS Sustainable Chemistry & Engineering

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Sustainable Multiple and Multi-stimuli Shape

2

Memory and Self-Healing Elastomers with Semi-

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interpenetrating network Derived from Biomass via

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Bulk Radical Polymerization

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Chuanwei Lua, Yupeng Liua,b, Xiaohuan Liua,c, Chunpeng Wanga,b, Jifu Wanga,b*, Fuxiang

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Chua,b*

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a

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Biomass Chemical Utilization; Key and Open Lab. of Forest Chemical Engineering, SFA; Key

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Lab. of Biomass Energy and Material, Jiangsu Province, No 16, Suojin Wucun, Nanjing 210042,

Institute of Chemical Industry of Forestry Products, CAF; National Engineering Lab. for

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China.

11

b

12

c

13

*

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ABSTRACT

Institute of Forest New Technology, CAF, No 1, Dongxiaofu Haidian, Beijing 100091, China.

School of Engineering, Zhejiang A & F University, 666 Wusu Street, Hangzhou 311300, China. CorrespondingAuthors: [email protected], [email protected]

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Sustainable shape memory and self-healing elastomers with semi-interpenetrating network were

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prepared by a simple, efficient and green bulk radical polymerization of ethyl cellulose, furfural

17

and fatty acids derived monomers. This approach could in situ one-pot form a semi-

18

interpenetrating network elastomer with the properties combining multiple-shape memory and

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self-healing under solvent-free conditions. These elastomers were found to possess excellent

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multiple-shape memory properties toward temperature, water, THF and methanol. Moreover, the

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multiple-shape memory properties could assist the self-healing of these elastomers, which was

22

triggered by heating. Self-healing behavior studies showed that the presence of linear polymers

23

in these elastomers could significantly improve the self-healing performance. This work provides

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a facile, efficient and green approach in solvent-free system to design the new-generation

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sustainable green and functional materials.

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KEYWORDS:

27

interpenetrating network.

28

INTROUDUCTION

Shape

memory

polymers,

Self-healing,

Elastomer,

Biomass,

semi-

29

The utilization of biomass resources has been commonly recognized to reduce the carbon

30

emission and enhance the sustainability of ecological environment. A great deal of biomass

31

products has been developed for commodity chemicals, polymers, and advanced materials1-3.

32

However, compared with the petroleum based counterparts, most biomass products have the

33

inferior performance, as well as the high cost mostly due to the inherent structural diversity and

2


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chemical heterogeneity of biomass. Thus, it is vital to explore robust and low cost approaches to

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fabricate biomass derived with high value4-5.

36

Shape memory polymers (SMPs) are a class of smart materials that have been widely served in

37

intelligent packaging, biomedical devices, sensors and actuators. SMPs can exchange between

38

temporary shape and permanent shape under specific stimuli6-8. Heat is the most commonly

39

stimulus for SMPs. As deeper research of SMPs, new stimulus including light, chemical and

40

magnetic, has been developed to trigger shape recovery9-13. Meanwhile, a few multishape-

41

memory polymers (multi-SMPs) and multiple stimuli-responsive SMPs also have been

42

developed14-17. In general, SMPs contain a cross-linking network which determines the

43

permanent shape, and a reversible segment that have a glass transition or crystalline melting

44

transition18-20. Self-healing polymers (SHPs) are another class of smart materials that possess the

45

ability of self-repair from a physical damage with the aid of external stimulus21-23. And the self-

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healing behavior of polymer could be achieved by the diffusion of polymer chains across the

47

break surface that followed by re-entangling to heal the fracture24-26.

48

During the last decades, a few works about utilizing cellulose to prepare SMPs, have been

49

reported27-29. Bai and co-workers developed a novel biological friendly shape memory polymer

50

(SMP) based on ethyl cellulose (EC) and polycaprolactone (PCL), which showed an excellent

51

mechanical strength and shape memory property, and had a potential application in biomedical

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suture30. Liu and co-workers developed a thermo-responsive and water-responsive cellulose

53

based shape-memory polymer by chemically cross-linking cellulose nanocrystals (CNCs) with

54

polycaprolactone (PCL) and polyethylene glycol (PEG)31. Wang and co-workers successfully

55

prepared a class of novel SMPs based on cellulose nanocrystals. These SMPs showed excellent

56

multiple shape-memory properties toward temperature, water, and organic solvents32. However, 3



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these cellulose-based shape memory polymers were purely chemical cross-linked network

58

structure, and only showed shape memory properties.

59

Most recently, it was found that shape memory polymer with semi-interpenetrating network

60

also can assist the self-healing. In a semi-interpenetrating network system, the chemical

61

crosslinking network is expected to play an important role in controlling the shape memory

62

performance, and the linear chain plays an important role in self-healing33-36. During the self-

63

healing process，the shape memory behavior could aid the crack surface achieving spatial

64

contact by releasing the stored strain under the stimulus, then the linear chain diffuses and

65

rearranges between the crack to achieve self-healing. Luo and co-workers developed a semi-

66

interpenetrating network shape memory and self-healing polymer which consisting of cross-

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linked poly(ε-caprolactone) network (n-PCL) with linear poly(ε-caprolactone) (l-PCL)

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interpenetrating the network37. Qi and coworkers developed a microfibrillated cellulose (MFC)

69

reinforced bio-based poly(propylene carbonate) that possessed shape memory and self-healing

70

properties. In this shape memory and self-healing polymer, the MFC acted as a physical cross-

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linkers to form “MFC network” structure in the PPC matrix which imparts the shape memory

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properties to polymers, and self-healing was achieved by the diffusion of the linear

73

poly(propylene carbonate) chain segments across the wounded interfaces38. However, the

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research on the full biomass shape memory and self-healing materials are rare.

75

In this study, we report an efficient, simple and green approach to prepare a class of semi-

76

interpenetrating network elastomers derived from biomass without any solvent, using ethyl

77

cellulose and biomass based monomers (lauryl methacrylate (LMA) derived from fatty acid and

78

tetrahydrofurfuryl methacrylate (THFMA) derived from furfural ) as feedstock. In this strategy,

79

we first converted ethyl cellulose (EC) into a macromonomer (ECM) that has multiple acrylate 4


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groups (Scheme S1). Then, one-step bulk copolymerization of ECM, LMA and THFMA was

81

performed to form the full biomass semi-interpenetrating network elastomers that consisted of

82

crosslinking copolymers and linear copolymers (Scheme 1). These elastomers exhibited

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excellent multiple shape-memory properties toward temperature, water, THF and methanol. And

84

the multiple-shape memory could be used to aid the self-healing of these elastomers. The linear

85

copolymers that formed in this approach could further aid the self-healing properties of these

86

elastomers.

87

88

EXPERIMENTAL SECTION

89

Materials

90

Ethyl cellulose (EC) (180-220 mpa.s), dimethylaminopyridine (DMAP, 99%), methacrylic

91

anhydride, 2,2-Azobis(2-methylpropionitrile) (AIBN), methanol and tetrahydrofuran (THF) were

92

purchased from Aladdin Industrial Inc. Lauryl methacrylate (LMA), tetrahydrofurfuryl

93

methacrylate (THFMA) were purchased from Aladdin Industrial Inc, and used after the remove

94

of inhibitor by aluminium oxide.

95

Characterization

96 97 98 99

FT-IR analysis was performed using a Nicolet iS10 FT-IR spectrometer by an attenuated total reflectance method; 1

H NMR analysis was carried out using a BrukerAVANCE3 400MHz NMR spectrometer, and

CDCl3 was used as a solvent;

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100

Gel permeation chromatography (GPC) was performed using a Malvern Viscotek 3580 System

101

equipped with Viscotek GPC2502 RI detector. The eluent was HPLC grade THF, and the flow

102

rate was 1 mL/min-1. Monodispersed polystyrene (PSt) was used as the standard to generate the

103

calibration curve.

104

The mechanical tests were performed at room temperature using CMT7504 universal testing

105

machine with the crosshead speed of 50 mm/min and the load cell was 250N. The samples were

106

prepared by hot-press and cut into dumbbell film with the thicknesses of 1.2-1.6 mm, width of 4

107

mm and length of 16 mm. The results were based on five independent measurements of each

108

sample performed at the same condition. The tensile cyclic processing was conducted as follows:

109

the sample was extended up to strain of 50, 100, 150, 200, 250 and 300% at the speed of 50

110

mm/min at each step. Once the sample reached the targeted maximum strain, the crosshead

111

direction was reversed and the sample strain was decreased at the same strain rate of 50 mm/min

112

until zero stress was achieved. After that, the crosshead was immediately reversed, and the

113

sample was then extended again at the same speed until it reached the next targeted maximum

114

strain. The cyclic tensile processing was continued until the maximum strain of 300% was

115

reached. The elastic recovery (ER) values of these thermoplastic elastomers were obtained from

116

these step cyclic tests. And the ER value was calculated from ER=100% (εmax-ε(0, εmax))/εmax,

117

where εmax is the maximum strain and ε(0, εmax) is the strain in the cycle at zero stress after the

118

maximum strain εmax.

119

To demonstrate the shape memory property, the spline was heated to 110 °C and bent or

120

stretched to give a temporary shape, and cooled to 0 °C to fix the temporary shape. Then the

121

spline was reheated to 110 °C to recover their permanent shape. The temperature for the shape

122

recovery occurs at 110 oC was chosen according to DMA tests, in which the highest termination 6


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123

temperature of Tg in all samples is about 110 oC. In order to maintain the same conditions for

124

comparison, the 110 oC was set as the shape recovery temperature.

125 126 127

Dynamic mechanical analysis (DMA) was carried out on Q800 DMA (TA Instruments). The DMA spectra were scanned with a frequency of 10 Hz and a heating rate of 3 oC /min. A DMM-880C microscope equipped with digital color camera was used to observe the self-

128

healing results at 50 times magnification.

129

Synthesis of EC macromonomer (ECM)

130

As illustrated in Scheme S1, EC 1g (4.55 mmol OH) and DMAP 0.278 g (2.27 mmol) were

131

dissolved in THF (20 mL) and placed into an oil bath preheated at 55 oC, methacrylic anhydride

132

0.701 g (4.55 mmol) was added drop-wise and then stirred for 6 h. The ECM was obtained by

133

the precipitation of the resulting solution in an excess amount of deionized water with 5 ‰

134

Na2CO3, followed by filtration and dry for 24 h at 40 °C under vacuum.

135

Synthesis of semi-interpenetrating network elastomers derived from cellulose, furfural and

136

fatty acid

137

Elastomers with semi-interpenetrating network were synthesized by one pot bulk

138

polymerization of ECM, LMA and THFMA. A typical procedure is as follows (Table 1, Entry 2).

139

A mixture of ECM 0.1933 g, LMA (5.79 g, 34.04 mmol), THFMA (3.86 g, 15.18 mmol) and

140

AIBN (19.33 mg, 0.1175 mmol) were charged into a round bottom flask, and the flask was

141

placed into water bath preheated at 25 oC and was continual stirring for 20 min. Then the mixture

142

was poured into a PTFE mold, and degassed under vacuum. Afterward, the mixture polymerized

143

at 110 °C for 4 h to obtain multiple-shape memory and self-healing elastomers. In order to

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144

remove the unreacted monomers, the elastomers were extracted two times by methanol for 1 h.

145

And then the elastomers were dried to constant weight.

146

RESULTS AND DISCUSSION

147

Synthesis of semi-interpenetrating network elastomers

148

As shown in Scheme 1 in the bulk radical polymerization, AIBN, an initiator well dispersed in

149

the mixture of LMA, THFMA and ECM, initiated the polymerization and formed the chemical

150

cross-linking network, which led to significant increase in the viscosity of the reaction system.

151

Therefore, LMA and THFMA could not move freely, resulting in the in situ formation of the

152

linear copolymers at the same time. These linear copolymers interspersed in the chemical cross-

153

linking network to form the semi-interpenetrating networks with the different contents of ECM,

154

THFMA and LMA. The data was summarized in Table 1. In this approach, ECM offered

155

elastomers with two types of cross-linking networks: permanent cross-linked junctions by the

156

multiple acrylate groups of ECM, and dynamic physical cross-linked network by hydrogen

157

bonds originated from free hydroxyl group of EC. Chemical cross-linking junctions afforded

158

elastomers with the permanent shape, whereas the physically cross-linked network endowed

159

them with the multi-responsive and multi-shape-memory properties. And the linear copolymers

160

P(LMA-co-THFMA) could achieve the self-healing properties of these elastomers.

161 8


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162 163

Scheme 1: Synthesis of semi-interpenetrating network elastomers.

164

The utilization of ECM in the preparation of elastomers was also accompanied with the

165

solubility change. As shown in Figure S4, the sample without ECM (Table 1, entry 7) was

166

dissolved in tetrahydrofuran (THF) after 20min, whereas ECM2%-LMA4-THFMA6 (Table 1,

167

Entry 2) was only swollen. This result indicated the presence of ECM could lead to the

168

formation of permanent cross-linked junctions in these elastomers.

169

In order to further investigate the composition of these semi-interpenetrating network

170

elastomers, THF was used to extract the linear polymers. And the contents of crosslinking

171

copolymer and linear copolymer were calculated and summarized in Table S1. It was found that

172

under the same content of LMA/THFMA, the content of linear copolymer was decreased with

173

the increasing of ECM content. So we can control the content of the linear copolymer by

174

adjusting the ECM content. In this context, the content of linear copolymer in those elastomers

175

was controlled to be less than 10 wt %. In addition, the molecular weight of linear copolymer

176

LMA4-THFMA6 was measured about 80000 g/mol by GPC. 9



177

The Tg of ECM2%-LMA4-THFMA6 was determined by DMA. As shown in Figure 1,

178

ECM2%-LMA4-THFMA6 exhibits a broad glass transition ranging from -40 oC to 75 oC, which

179

is probably resulted from the formation of semi-interpenetrating networks39-40. When the linear

180

copolymer was removed from elastomer, the Tg of ECM2%-LMA4-THFMA6 was shifted to the

181

range from -10 oC to 110 oC. The increase of Tg was also observed in other elastomers with

182

different compositions after the extraction (Figure S5), indicating that the linear copolymer

183

plays a role in plasticizing these elastomers.

184

3

After extraction Before extraction

1000 100

2

10

Tan δ

Storage Modulus (MPa)

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

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1

1

0.1 0.01 -60

-40

-20

0

20

40

60

80

0 100 120

Temperature (°C)

185 186

Figure 1: DMA curves of ECM2%-LMA4-THFMA6 before and after extraction of linear

187

copolymer.

188 189 190 191 192 10


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193

Mechanical properties of elastomers

194

Table 1: Reaction conditions and mechanical properties of elastomers.

Entry

Sample namea

ECM content (wt %)

THFMA content (wt %)

AIBN content (wt %)

LMA content (wt %)

Stress at Strain at break break (MPa) (%)

1

ECM1%-LMA4THFMA6

1

59.3

0.2

39.5

1.16

660

2

ECM2%-LMA4THFMA6

2

58.7

0.2

39.1

2.16

420

3

ECM3%-LMA4THFMA6

3

58.1

0.2

38.7

2.54

385

4

ECM4%-LMA4THFMA6

4

57.5

0.2

38.3

2.84

316

5

ECM3%-THFMA10

3

96.8

0.2

0

5.4

6

6

ECM3%-LMA3THFMA7

3

67.8

0.2

29

3.07

310

7

LMA4-THFMA6

0

59.9

0.2

39.9

-

-

195 196

a: Sample names are defined as follows: the numbers behind “LMA” and “THFMA” stand for the mass ratio of “LMA” and “THFMA”

197

The elaborately designed cross-linking network could endow polymers with elastomer

198

properties. Mechanical properties of these semi-interpenetrating network elastomers were

199

measured by monotonic tensile stress-strain and step cyclic tensile tests.

200

Figure 2a shows the monotonic tensile stress–strain curves for elastomers with the different

201

ECM content, and the results were summarized in Table 1. It shows that all the samples have

202

elastomeric behavior, and the composition of starting mixtures of ECM, LMA and THFMA has a

203

great influence on the mechanical properties. For the ECM content with the same mass ratio of

204

LMA/THFMA, the stress at break of elastomers was increased with the increasing of ECM

205

content, while the elongation at break was just the opposite. The reason for phenomenon can


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206

be explained by that as a cross-linker, the increase of the increasing of ECM content in the

207

starting mixtures could further increase the crosslink density (crosslinking component, Table S1)

208

of the elastomer and resulted in the increase of stress32, 38.

209

The effects of the mass ratios of LMA/THFMA in these elastomers with the fix ECM content

210

on the mechanical properties were also investigated. Figure 2b shows the monotonic tensile

211

stress-strain curves for these elastomers with the different mass ratio of LMA/THFMA, and the

212

mechanical properties of these elastomers were also summarized in Table 1. It was found that

213

the stress at break increased with the increase of THFMA content, while the elongation at break

214

increased with the increase of LMA content, which agreed with the previous reports32, 41-42. Note

215

that for the ECM3%-THFMA10 (Table1, entry 5), the stress at break and the elongation at

216

break are 5.4 MPa and 6 %, respectively (stress-strain curve not shown), which demonstrates that

217

this sample did not has elasticity probably due to the absence of flexible LMA content.

218

Figure S6 shows the monotonic tensile stress–strain curves for these elastomers before and

219

after the extraction of linear copolymer. It was found that the stress at break increased after the

220

extraction of linear copolymer, indicating that the presence of linear would decrease the stress of

221

elastomers and could play a role in plasticizing for these elastomers.

222

In brief, the mechanical properties of those elastomers can be easily tailored by adjusting the

223

content of LMA/THFMA and ECM, or by the composition of these semi-interpenetrating

224

networks.

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4.0

a

3.5 Stress / MPa

3.0

ECM1%-LMA4-THFMA6 ECM2%-LMA4-THFMA6 ECM3%-LMA4-THFMA6 ECM4%-LMA4-THFMA6

2.5 2.0 1.5 1.0 0.5 0.0 0

100 200 300 400 500 600 700 Strain / %

225 3.5

b

ECM3%-LMA4-THFMA6 ECM3%-LMA3-THFMA7

3.0 Stress / MPa

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


2.5 2.0 1.5 1.0 0.5 0.0 0

50 100 150 200 250 300 350 400 450 Strain / %

226 227

Figure 2: stress-strain curves for elastomers with different ECM contents (a) and different

228

LMA/THFMA ratios (b)

229

ECM1%-LMA4-THFMA6 was used as a representative example to perform the step cyclic

230

tensile tests. Figure 3a shows the typical nominal stress-strain curve during cyclic tensile

231

deformation with the maximum strain of 50, 100, 150, 200, 250, 300, 350, 400, 450, and 500%.

232

It can be clearly observed that the first loading curve and subsequent loading curves are

233

completely different in a given cycle, and the residual strain at zero stress is gradually 13



234

becoming larger due to the plastic deformation. The stress-strain curves of the other elastomers

235

were shown in Figure S8. It is worth noting that these elastomers exhibit excellent elastic

236

recovery (ER) behavior at higher strains. As shown in Figure 3b, all the ER values of these

237

elastomers are all above 90% at the strain of 250%, and the strain for approaching 90% of ER

238

values increased with the increase of THFMA content.

0.25

ECM1%-LMA4-THFMA6

a

Stress / MPa

0.20 0.15 0.10 0.05 0.00 0

100

200 300 Strain / %

400

500

239 100

b

90 Elastic recovery / %

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

Page 14 of 33

80 70

ECM1%-LMA4-THFMA6 ECM2%-LMA4-THFMA6 ECM3%-LMA4-THFMA6 ECM4%-LMA4-THFMA6

60 50 40 30 20 10 0

100

200 300 Strain / %

400

500

240 241

Figure 3: Cyclic stress-strain curves (a) and elastic recovery (b) of elastomers

242

Thermally responsive shape memory performance of elastomers 14


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243

Sample ECM2%-LMA4-THFMA6 was first used to perform the thermal-induced shape

244

memory experiment evaluated by stress-controlled dynamic mechanical analysis (DMA). Figure

245

4a shows the evolution of strain, stress and temperature during the dual shape-memory

246

programming steps. After the sample was heated to 110 ºC, 0.02 MPa stress is applied and a

247

strain of 25.5 % was reached within 20 min. When the sample was cooled to 0 ºC, the stretched

248

state was fixed, followed by the release of the stress. Subsequently, the sample was reheated to

249

110 ºC and beginning to recover. It was found that ECM2%-LMA4-THFMA6 stretched at 110

250

ºC, showing a high shape fixed ratio of 99% and a shape recovery ratio of 94.2% (For definition,

251

see Supporting Information). Figure 4b shows the representative pictures about one-way stretch

252

shape memory process of ECM2%-LMA4-THFMA6 corresponding to the DMA test. The spline

253

was hearted to 110 ºC and stretched, then spline was cooled to 0 ºC to fix a temporary shape.

254

Finally, the elongated shape sample was reheated to 110 ºC, and the film recovered to the

255

permanent shape within 150s. It is worth noting that no obvious damage was observed after three

256

times of the repeated shape recovery process. 30

a 120 0.04

100 80 60 40

20

0.02

15

0.01

20

10 5

0.00

0 0

257

0.03

Strain / %

25

Stress / MPa

Temperature / oC

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


20

40

60 80 Time / min

100

0 120

15



Page 16 of 33

258

259 260

Figure 4: DMA curve of dual-shape-memory programming (a), photo of shape recovery process

261

at 110 ºC (b) and photo of spiral shape recovery process at 110 ºC (c) of elastomers ECM2%-

262

LMA4-THFMA6.

263

Figure 4c shows the representative pictures about the evolution from a temporary spiral to

264

permanent shape of ECM2%-LMA4-THFMA6. The temporary spiral shape was made at 110 ºC

265

and cooled to 0 ºC to fix the temporary shape. Then the spiral shape sample was reheated to 110

266

ºC, and pictures of the sample were taken at different times. ECM2%-LMA4-THFMA6 shows

267

recovery completely within 200s. The shape recovery process of ECM2%-LMA4-THFMA6 was

268

repeated three times without obvious damage observed, and the shape from temporary spiral to 16


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269

permanent shape was achieved fully each time. Figure S9 shows the photos about the process

270

from a temporary bending to permanent shape of ECM1%-LMA4-THFMA6, ECM2%-LMA4-

271

THFMA6, ECM3%-LMA4-THFMA6, ECM4%-LMA4-THFMA6. All of these samples have

272

shape memory behavior. With the increasing of the ECM (role as cross-linker) content, the time

273

of shape recovery was decreased. This result indicated that the shape recovery time of these

274

elastomers could be tuned by changing the content of cross-linker.

275 276

Figure 5: Schematic illustration of heat-triggered shape memory behavior of elastomers.

277

The mechanism of the thermally induced shape memory effects of these elastomers is

278

generally explained by the dual-state mechanism, in which the entangled molecular long chains

279

were regarded as the reversible phase and the nodes of physical or chemical crosslinks were

280

regarded as the permanent phase. In the ECM-LMA-THFMA, ECM acts as cross-linker and

281

forms the chemical network with molecular long chains. The shape-memory cycle was

282

schematically illustrated in Figure 5. At room temperature, the elastomer was a rigid material.

283

Upon heating above the Tg, the elastomer became a soft rubber due to the increased mobility of

284

the molecular long chains and the breakage of hydrogen bonds. The entangled molecular long

285

chains extended easily when an external stress was applied. When cooled to a temperature below

286

Tg, the molecular chain in extension state was frozen and locked the deformation. At the same 17



Page 18 of 33

287

time, hydrogen bonds were regenerated to assist in locking the deformation. This temporary

288

shape was very stable unless when the sample was reheated above the Tg.

289 290

Figure 6: Triple-shape-memory effect for ECM2%-LMA4-THFMA6: (A)original shape1; (B)

291

shape 2, bended at 110 ºC and fixed at 0 ºC; (C) shape 3, bended at 50 ºC and cooled to 0 ºC; (D)

292

recovered to shape 2, after re-heating to 50 ºC; (E) recovered to shape 2, after re-heating to 100

293

ºC

294

It is well known that semi-interpenetrating polymer networks (IPNs) are an effective means to

295

produce the broadened glass transition, which could achieve multi-shape memory property. The

296

transition temperature of middle temporary shape is usually chosen within the range of broad

297

glass transition as long as the sectional energy during cooling is enough to fix a shape32, 40, 43-44.

298

We therefore expected that ECM2%-LMA4-THFMA6 with a broad glass transition ranging from

299

-40 oC to 75 oC (Figure 1) is supposed to be multi-shape-memory materials. In order to

300

distinguish the temperature of shape fixed and final temporary shape, 50 oC as another transition

301

temperature.

302

Figure 6 shows the multi-shape-memory properties of ECM2%-LMA4-THFMA6 at the

303

different stages of the recovery process. Firstly, the upper part of permanent elongated shape was

304

bended at 110 ºC and fixed at 0 ºC. Then the lower part was bended at 50 ºC and cooled to 0 18


Page 19 of 33 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


305

ºC to fix the temporary shape. When the sample was reheated to 50 ºC, the lower part recovered

306

fully and the upper part just has slightly recovery. When the temperature rose to 110 ºC, the

307

spline was recovery fully to the permanent shape.

308

The molecular mechanism for multi-shape memory behavior could be explained by that the

309

chemical cross-linking networks formed by covalent linkages and the entanglement between

310

linear copolymers and networks constrained the movement of polymer chains, led to the

311

relaxation of macromolecular chain segment when the samples were heated. This would give rise

312

to a widening of the glass transition temperature range, which is a key factor for the multi-shape

313

memory. Meanwhile, the whole energy, which stored in whole Tg range can be distributed into

314

several parts, is also an important factor for multi-shape memory programming40, 44-45. In the

315

process of triple shape memory, the elastomer would become flexible when it was heated to 110

316

o

317

partially frozen and partial energy in whole Tg range was stored, which could fix the middle

318

temporary shape. When the elastomer was cooled to 0 oC, the chain segment was completely

319

frozen and the stored energy fixed final temporary shape. Inversely, when the elastomer was

320

heated to 50 oC and 110 oC successively, the sectional energy stored in shape fixed process was

321

released step-by-step to recover its original shape through two-steps shape transformation.

C, and when it was cooled from 110 oC to 50 oC, the macromolecular chain segment was

322 323

Water and solvent-responsive shape memory performance of elastomers

324

For these elastomers ECM-LMA-THFMA, the hydrogen bonds from ECM also play a role in

325

the fixed temporary morphology, and will increase the Tg of the elastomers. Theoretically, the

326

shape-recovery properties of these elastomers could be induced by any chemicals, which can

327

break the hydrogen bonds or plasticize the samples (to decrease the Tg).


19


Page 20 of 33

328

Water, THF and methanol were selected to induce the shape memory properties of ECM2%-

329

LMA4-THFMA6. Figure 7a shows the effect of water at 38 ºC on the bent sample. It can be

330

clearly observed that the sample recovery near fully to the permanent shape within 360s. This

331

result indicated that when the sample was immersed in water, trace of water can diffuse into the

332

sample and form new hydrogen bonds with ECM segments, which weakened the hydrogen

333

bonds in ECM network and led to the shape recovery. Figure S10 shows the shape recovery of

334

ECM3%-LMA4-THFMA6 and ECM4%-LMA4-THFMA6 in water at 38 ºC. Compared with

335

ECM2%-LMA4-THFMA6, it can conclude that the more cross linker in the elastomers, the less

336

time was used to recover the permanent shape.

337

When the sample was exposed to tetrahydrofuran (THF) atmosphere at room temperature

338

(Figure 7b), a full recovery of ECM2%-LMA4-THFMA6 was also achieved within 25 min. It is

339

worth noting that THF could not form hydrogen bonds with ECM segments, the shape recovery

340

may be caused by the plasticization effect, which can decrease the Tg of sample and lead to shape

341

recovery.

342

The shape recovery property induced by methanol was also investigated. As shown in Figure

343

7c the sample could also fully recovery within 35 min. These results indicated these elastomers

344

did have multistimuli-responsive shape memory performance.

345

20


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346

347 348

Figure 7: Photo of a shape recovery process of elastomers (ECM2%-LMA4-THFMA6) in water

349

at 38 ºC (a), in THF (b) and in methanol (c)

350

Self-healing behavior of elastomers

351

Similar to Qi’s report38, the elastomers with semi-interpenetrating network in our cases are

352

supposed to have self-healing behavior with the aid of the shape memory effect. In the following,

353

typical optical images and tensile tests were utilized to investigate the self-healing performance

354

of these elastomers. Figure 8a shows the photo of self-healing process of the representative

355

elastomer. Firstly, ECM2%-LMA4-THFMA6 was cut into two sections by the sharp blade, and

356

then the two sections were close to each other so that the cut surface could achieve spatial

357

contact. Next, the cut ECM2%-LMA4-THFMA6 was heated to 110 oC for 30 min and has not

358

visible crack. It can be found that the damage has been healed and could be bent to spline shape.

359

In addition, the tensile test (Figure 8a) indicated that the mechanical properties were also

360

partially restored. 21



Page 22 of 33

361

Figure 8b shows the schematic illustration of self-healing mechanism of these semi-

362

interpenetrating network elastomers. The self-healing of elastomers was triggered by heating to a

363

temperature higher than Tg, and then the following two events could be used to explain the self-

364

healing properties. First, the elastomers release the stored strain by the shape memory effect to

365

close the crack, and making the cross-section of the crack in contact with each other. Second, the

366

linear polymer melted and flowed at the crack interfaces. The diffusion and rearrangement of the

367

polymer chain at the crack interfaces healed the damage or cracks. We noted that the presence of

368

linear polymers chain was a key factor to achieve self-healing performance.

369

370 371

Figure 8: Photo of self-healing process of elastomer ECM2%-LMA4-THFMA6 (a) and

372

schematic illustration of the shape memory assisted self-healing concept (b)

373

In order to verify the surmise that the presence of linear polymers can greatly improve the self-

374

healing performance, Figure 9a, b shows the self-healing results of ECM2%-LMA4-THFMA6

375

before and after extracting linear copolymer. It can be clearly observed that ECM2%-LMA4-

376

THFMA6 before extracting linear copolymer exhibited better self-healing performance. The 22


Page 23 of 33

377

crack width was obviously narrower than that of the counterparts without the linear polymers.

378

This phenomenon was also related to the relative higher Tg of elastomers after extracting linear

379

copolymer, which was confirmed by DMA as shown in Figure 1.

380

381

C Elastomers-neat Healed elastomers before extracting linear copolymer Healed elastomers after extracting linear copolymer

2.0

Stress / MPa

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


1.5 1.0 0.5 0.0 0

100

200

300

400

500

Strain / % 382 383

Figure 9: photo of the crack partial enlarged after healing of elastomers ECM2%-LMA4-

384

THFMA6. (a) before extracting linear copolymer; (b) after extracting linear copolymer; (c) 23



Page 24 of 33

385

stress-strain curve for elastomers and healed elastomers before and after extracting linear

386

copolymer.

387

In addition to the healing of shape, the recovery of mechanical properties was also an

388

important factor for evaluating the healing efficiency. Figure 9c shows the stress-strain curves of

389

elastomers-neat, Healed elastomers before extracting linear copolymer and healed elastomers

390

after extracting linear copolymer. The data of mechanical properties was summarized in Table

391

S2. It can be obviously observed that the elongation at break of the healed elastomers before

392

extracting linear copolymer was 352% which was recovered to 81.2%, while the elongation at

393

break of healed elastomers after extracting linear copolymer was 110% which was only

394

recovered to 25.4 %; As for the tensile strength, the stress at break of the healed elastomers

395

before extracting linear copolymer was recovered to 55.4 % which was obviously higher than

396

that of healed elastomers after extracting linear copolymer (14.6 %). Those results further

397

confirmed the linear polymers play an important role in enhancing self-healing ability of these

398

elastomers.

399 400

CONCLUSION

401

In summary, we demonstrated a simple, effective and green approach to design a sustainable

402

semi-interpenetrating network elastomers derived from biomass: cellulose, fatty acid and furfural

403

under solvent-free condition. These elastomers consisted of crosslinking copolymers and linear

404

copolymers, and have excellent multiple-shape-memory and self-healing properties. Specially,

405

these elastomers have both excellent elastomeric behavior and multiple shape memory

406

performance toward temperature, water, THF and methanol. Moreover, with the assistance of 24


Page 25 of 33 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


407

shape memory effect, the elastomers with semi-interpenetrating network also exhibited excellent

408

self-healing behavior, and the self-healing efficiency of strain could reach 81.2%. The presence

409

of linear polymers could great enhance the self-healing performance. These new-generation

410

sustainable elastomers could be valued as a class of sustainable smart materials and have great

411

potential to replace the corresponding petrochemical products.

412

ASSOCIATED CONTENT

413

Supporting Information

414

Scheme S1 of synthesis of EC macromonomer (ECM), FT-IR and 1H NMR spectra of ECM,

415

FT-IR spectrum of elastomers (ECM2%-LMA4-THFMA6, Table 1, entry 2), Photo of swelling

416

test of LMA4-THFMA6 and ECM3%-LMA4-THFMA6, Monotonic stress-strain curves of

417

elastomers (ECM3%-LMA4-THFMA6) before and after the extraction of linear copolymer,

418

Photo of shape recovery process, Cyclic stress-strain curves and elastic recovery for elastomers,

419

Table S1 and Table S2. The Supporting Information is available free of charge on the ACS

420

Publications website.

421 422 423

AUTHOR INFORMATION

424

Corresponding Author

425

Correspondence should be addressed to [email protected], [email protected].

426

Acknowledgements

25



Page 26 of 33

427

We would like to acknowledge support from Central Non-profit Research Institution of CAF

428

(CAFYBB2017ZF003), the National Natural Science Foundation of China (31570579), China

429

International Science and Technology Cooperation (2011DFA32440).

430

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567

complex

actively

moving

568

10.1039/C2SM27077C.

569

Abstract Graphic

polymers.

Soft

Matter

2013,

9

(6),

1744-1755.

DOI:

570 571 572

A kind of bio-based semi-interpenetrating network elastomer with multiple-shape memory and

573

self-healing performance was developed to use as a smart material.

33


Sustainable Multiple- and Multistimulus-Shape-Memory and Self

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