Supplementary Material
Simple Triple-State Polymer Actuators with Controllable Folding
Characteristics
Shuyang Chen,1,2,a) Jing Li,1,2,3,a) Lichen Fang,1,2 Zeyu Zhu1,2,4 and Sung
Hoon Kang 1,2,b)
1Department
2Hopkins
3Hubei
of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
Extreme Materials Institute, Johns Hopkins University, Baltimore, MD 21218, USA
Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of
Technology, Wuhan, Hubei, 430070, China
4Institute
of Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China
Contents
1. Thermal response of shape memory polymer
2. Fabrication process of the actuators
3. Glass transition temperature (Tg) as a function of polymer composition
4. Derivation of the in-plane deformation strains (αi, i=1, 2)
5. Curvature measurement
6. Recovery force measurement
7. Stress-strain curves of top and bottom SMP layers at Tg1
8. Fabrication process of the two-dimensional robot base
9. Physical parameters of the robot after assembly
10. Robot obstacle avoidance
11. References
a)
These authors contributed equally to this work.
b)
Author to whom correspondence should be addressed. Electronic mail: [email protected].
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1. Thermal response of shape memory polymer
During glass transition process, the storage and the loss moduli of the polymer reduce, as
shown in Figure S1. Loss tangent (tan𝛿) of the bottom (up) and top (down) layers of shape
memory polymer (SMP), also shown in Figure S1, describes the viscoelastic dissipation
characteristic of the polymer. The peak of the tan𝛿 curve represents the key temperature, Tg.
Data are collected by using Q800 Dynamic Mechanical Analyzer (DMA) from TA Inc.
Figure S1. Storage modulus, loss modulus, and tan𝛿 of acrylate-based SMP with different glass transition
temperatures (bottom layer, Tg1, top layer, Tg2) as a function of the temperature.
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2. Fabrication process of the actuators
The fabrication process of an actuator is described as follows (Figure S2):
1) Purchase tert-Butyl acrylate (tBA), poly(ethylene glycol) dimethacrylate (PEGDMA)
with
molecular
weight
of
Mn
=
550,
and
photoinitiator
2,2-dimethoxy-2-phenylacetophenone (DMPA) from Aldrich and use as-received
conditions.
2) Mix tBA and PEGDMA with a 4:1 mass ratio (20 wt.% PEGDMA) with a magnetic
stirrer (Hanna Instruments, HI190M), then add 0.5 wt.% DMPA into the tBA-PEGDMA
mixture. Inject the mixture into a mold and polymerize the mixture in a UV oven (UVP,
CL1000 with power density of 100 μJ/cm2) for 10 minutes.
3) Mix tBA and PEGDMA with a 19:1 mass ratio (5 wt.% PEGDMA) with a magnetic
stirrer, then add 0.5 wt.% DMPA into the tBA-PEGDMA mixture. Add specific weight
(depends on the thickness ratio we need) of the mixture onto the top of the previously
cured layer. Place the mold into the UV oven for another 10 minutes to polymerize the
top layer.
4) Following UV curing, peel off the bilayer polymer specimen from the mold and use a
bending mold to program an expected angled permanent shape of the specimen as shown
in Figure S2.
5) Place the specimen in an oven at 70 °C for one-hour post curing. By using this method,
we can synthesize a bilayer polymer specimen with an angled permanent shape as shown
in Figure S2.
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Figure S2. The fabrication process of the actuator.
We also come up with a more robust method by using two bent molds with different
diameters instead of the flat PDMS mold used above to fix the angled permanent shape
during the polymerization of UV curing instead of the post curing in the oven. The
fabrication process is described as the follow example (Figure S3):
1) Use a laser cutter (Universal Laser System) to cut the acrylic bar (purchased from
McMaster-Carr) into specimens with inside diameter (I.D.) of 46/48 mm and height of 15
mm. Rinse specimens with DI water and dry. Place one specimen into the Karter
Scientific 206D2 Plastic Petri Dish (I.D.: 60 mm).
2) Mix 60 g Sylgard 184 base with 6 g Sylgard 184 curing agent (available from Dow
Chemical) with Mazerustar planetary mixer for 90 seconds.
3) Pour the resin mixture into the petri dish. Place the petri dish into a vacuum desiccator
for 1 hour to eliminate air bubbles.
4) Place the petri dish in the 60 °C oven for 90 minutes or room temperature for 24 hours to
cure PDMS completely.
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5) After curing, gently take out the solid PDMS blocks from the petri dish, and remove the
smaller PDMS block embedded inside the acrylic specimen. The block is then cleaned
extensively with ethanol, acetone and isopropanol sequentially, and dried.
6) Place the block obtained from the previous step into the Kimble Chase 23064 6015 Petri
Dish (I.D.: 52mm).
7) Fill the gap with 20 wt.% PEGDMA mixture and then place the mold in the UV oven
(UVP, CL1000 with power density of 100 μJ/cm2) for 10 minutes so that we can get four
arc-shape pieces with a thickness of 2 mm.
8) Put a smaller PDMS block (fabrication method similar to step 5 but obtained by using the
acrylic specimen with 46 mm I.D.) inside the petri dish and fill the gap with 5 wt.%
PEDGMA mixture, then place the mold in the UV oven for another 10 minutes curing, as
shown in Figure S3.
9) Now we can get four arc-shape bilayer polymer specimens with thickness 2 mm and 1
mm of each layer.
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Figure S3. The fabrication process of the actuator by using an angled mold during UV curing. The red dashed
lines in the top left figure denote the contour of the chambers in which resin mixtures will be injected, whereas
the lines in the bottom right figure denote the gaps where a resin mixture will be added.
3. Glass transition temperature (Tg) as a function of polymer composition
The Tg of the polymer can be adjusted by changing the mass ratio of PEGDMA to tBA1.
The glass transition temperatures are measured by TA Instruments Q800 dynamic mechanical
analyzer. The Tg of cured polymer decreases with the increasing weight percent of PEGDMA
in tBA-PEGDMA mixture, as shown in Figure S4.
Figure S4. Tg as a function of wt.% of PEGDMA in tBA-PEGDMA mixture (N=5, error bars represent the
standard deviation).
4. Derivation of the in-plane deformation strains (αi, i=1, 2)
Here, we use a partial recovery factor (λi, where i indicates the layer number, 1 for the
bottom layer and 2 for the top layer) to define the degree of partial recovery of each layer:
𝐿𝑟
𝜆𝑖 = 𝐿
0 𝜀0
(S1)
where L0 is the initial length of the polymer, 𝜀0 is the prestrain and Lr is the recovered
length.
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We define the in-plane deformation strain (αi, i=1, 2) of each layer as
𝐿
𝛼𝑖 = 𝐿 𝑟
(S2)
𝑃
LP is the length of the polymer after prestretch, where 𝐿𝑃 = 𝐿0 (1 + 𝜀0 ) and 𝐿𝑟 =
𝜆𝑖 𝐿0 𝜀0 . Then, the Equation S2 can be written as
𝐿
𝛼𝑖 = 𝐿 𝑟 = 𝐿
𝑃
𝜆𝑖 𝐿0 𝜀0
0 (1+𝜀0 )
𝜆𝜀
𝑖 0
= 1+𝜀
0
(S3)
5. Curvature measurement
To measure the maximum non-predetermined bending curvature that an actuator with
specific thickness ratio and prestrain can reach, we construct the apparatus shown in Figure
S5 (a). The apparatus includes a platform with a clamped polymer actuator, a camera (Canon
EOS 70D) to record videos of the bending process, and an angle-division paper as the
background (as a scale reference). We fix a 5Ω resistor to the bottom of the actuator and use
the Arduino (5V output pin) as a power source to activate the bending process. The bending
behavior is obtained from the snapshots of the video recorded by the camera. To quantify the
bending characteristics precisely, we align the camera, actuator, and the angle-division paper
collinearly, as illustrated in Figure S5 (b).
Then, we calculate the mean curvature of the bent configuration to express the bending
extent. First, we obtain the snapshot as shown in Figure S5 (b), and then, we rotate and
transfer it into a binary image by GIMP, illustrated in Figure S5 (c). Next, we conduct curve
fitting (polynomial regression) and calculate the corresponding mean curvature k of the
points on the curve (implemented in MATLAB), curvature of each point with coordinate (x, y)
is expressed as2:
𝑦 ′′
k = (1+𝑦 ′2 )3/2
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(S4)
Figure S5. (a) The apparatus used for measuring the bending curvature of an actuator and (b) the image of the
actuator in camera. (c) The binary image used to calculate the mean curvature.
6. Recovery force measurement
The maximum recovery force is one of the most important performance measures of the
actuator. We constructed the apparatus shown in Figure S6 (a) to explore the influence of
thickness ratio and prestrain on the maximum recovery force of the actuator during its
bending process. The apparatus is composed of a platform with a clamped actuator and a load
cell (LSB-200, 250g, Futek). The actuator is clamped on the platform and put close but not in
contact with the probe of the load cell (Figure S6 (b)). To activate the actuator, we use one 5Ω
resistor as a heating element and the Arduino (5V output pin) as a power source. Once
connected to the Arduino, the resistor can quickly increase the temperature of the actuator to
around 100 °C in 30 seconds and provide a stable temperature around 145 °C in 120 seconds,
which are above the Tgs of both polymer layers. In order not to interfere the action of the
actuator, we hold the resistor close to the actuator to provide heat but does not touch it.
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Figure S6. (a) The apparatus used for measuring the recovery force of an actuator and (b) the zoom-in image
that the actuator is clamped close but not contact with the probe of the load cell.
The result of the recorded force during the heating process by using the apparatus above
(data collected by the Futek load cell) of one actuator sample is illustrated in Figure S7.
Figure S7. An example of the measured recovery force of an actuator as a function of heating time recorded by
the Futek load cell.
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7. Stress-strain curves of top and bottom polymer layers at Tg1
The Young’s modulus of each layer is measured as 𝐸1 = 2.9 ± 0.15 MPa and 𝐸2 =
2.3 ± 0.18 MPa at Tg1 (48 °C) by MTS Insight 5 electromechanical test system with an
environment chamber (MTS Systems Corp., Eden Prairie, MN) from the measurements
shown in Figure S8. Here, n value is the Young’s modulus ratio (=E1/E2), so n≈1.26 at Tg1.
(a)
(b)
Figure S8. Stress-strain curves of bottom (a) and top (b) polymer layers at Tg1, respectively.
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8. Fabrication process of the two-dimensional robot base
We fabricate a two-dimensional robot base by cutting the cured PDMS with embedded
hard copy paper into four parts: one foundation, two wings and one tail as shown in Figure S9.
The pattern is designed to achieve our aiming 3D shapes (boat and car) accordingly. The
separated parts will be connected by actuators, and the gaps between different parts can
provide space for the contraction of the actuator.
Figure S9. Fabrication process of the robot base.
9. Physical parameters of the robot after assembly
The physical parameters of the robot after assembly is summarized in Table S1 as below.
Table S1. Physical characteristics of the robot after assembly
Dimension (WL)
Left Wing
Right Wing
Tail
Foundation
(cm)
(g)
(g)
(g)
(g)
1817
21.2
22.4
17.5
143.7
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10. Robot obstacle avoidance
After achieving the car state, we demonstrate obstacle avoidance as one of the
applications of the car (see supplementary material S10). The sonar (HC-SR04 Ultrasonic
Sensor) mounted on the car detects the distance between itself and the obstacles in front of
the car, and the microcontroller guides it to choose a better way based on the distance data
collected by the sonar. The results show that it can move around autonomously without
collision.
The sonar (HC-SR04 Ultrasonic Sensor) mounted on the robot detects the distance
between itself and the obstacles in front of the robot. If the distance is less than 15
centimeters, the microcontroller will control the robot as follows:
• First move backward for 0.5 s.
• Turn left for 0.5 s and measure distance of the nearest obstacle in front of it.
• Turn right for 1 s and measure distance of the nearest obstacle in front of it.
• Choose the better way to move forward (the direction with a larger free distance).
Figure S10 illustrates one cycle of the obstacle avoidance process described above. Three
obstacles are involved in this environment: obstacle A (the air tap), obstacle B (the wall) and
obstacle C (on the right side but not shown in the figure). At t = 0.5 s, the robot detects
obstacle B within 15 centimeters distance to itself and will move backward for 0.5 s. Then, at
t = 1 s, it turns left for 0.5 s and right for 1 s sequentially and measures the corresponding
distances from obstacles A and C to itself (dA and dC), and it turns left back at t = 3.5 s and
moves forward to start another cycle because dA is larger than dC.
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Figure S10. The obstacle avoidance performance of the robot. (a) The robot moves forward. (b) The robot starts
to move backward after detecting the wall (obstacle B). (c) The robot turns left for 0.5 s and measures the
distance from obstacle A to itself (dA). (d) The robot turns right for 1 s and measures the distance from obstacle
C to itself (dC). (e) The robot turns left back since dA > dC. (f) The robot moves forward to enter another
obstacle avoidance cycle.
11. References
1. D. L. Safranski, K. Gall K, Polymer 2008, 49, 4446.
2. W. Riley, L. Sturges, and D. Morris, “Mechanics of Materials,” John Wiley Sons, 2007.
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