FULL PAPER
Soft Robotics

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Low-Cost, Facile, and Scalable Manufacturing of Capacitive
Sensors for Soft Systems
Edward L. White, Michelle C. Yuen, Jennifer C. Case, and Rebecca K. Kramer*
there is a need to develop highly deformable, electrically conductive materials
with moduli similar to nontraditional soft
materials such as elastomers or biologicaltissues.[7] In addition, soft systems often
lack defined joints and exhibit continuousand distributed deformation, complicatingstate measurements. One solution for
tracking these large continuous deformations is to distribute large numbers ofstrain sensors across the surface of a soft
structure.
Our focus is on the development ofsensory skins, which are planar substrates
embedded or affixed with distributed sensors that can be wrapped and secured tothe surface of a host structure.[8] In orderto achieve this goal, we require scalable androbust methods to create many sensors ofarbitrary geometry and configuration on asingle substrate at low cost. One approachis to directly fabricate elastomer-based sensors onto a fabric substrate. Our sensors
are made from a composite material which
relies on expanded intercalated graphite(EIG) to achieve electrical conductivity.
Conductive elastomer composites are awell-developed field[9–13] and EIG specifically has a long history.[10,14–19] We describe three approaches to making strain sensors using the same materials: (1) direct writing and (2) screen
printing of finished-shape sensors directly onto a substrate and(3) a film-based process to produce free-standing sensors which
can be affixed to a substrate as a subsequent step. We havechosen to focus on fabric as the substrate because of its conformability and tear-resistance. The fabric-based approaches reduce
the number of manufacturing steps required to produce a sensory skin and utilize methods compatible with roll-to-roll systems for scalable, in situ manufacture of strain sensors. Throughcharacterization of the sensors, we found that the performanceand functionality of the sensors is robust to process variance,from graphite exfoliation to material deposition, and the sensors
manufactured by different methods exhibit similar performance.
These devices could be used to provide sensor data to soft robotic
systems[20–26] or to measure human motion or pose.[2,27,28]

In the field of soft robotics there is a need for robust and reliable large-deformation strain sensing. Further, the field needs a way to produce such sensors
in large quantities and at low cost. Toward these goals, the fabrication of highly
stretchable capacitive strain sensors made from conductive elastomer composites is described here. Two novel methods of manufacturing these sensors
directly onto a fabric substrate are developed: direct writing of elastomer using
an extrusion process and screen printing of elastomer patterns. The effect ofmaterial processing parameters on the parameters of the finished composite
films is studied and it is determined that the process is robust to a wide rangeof variations. The performance of sensors produced on fabric substrates isshown to be similar between the two fabrication processes. Further, the sensors are highly deformable with consistent performance up to 250% strain,
and are reliable, with no changes in performance observed at 1000 cycles.
It is also demonstrated that the sensors continue to perform with reduced
gauge factors up to 100 000 cycles. For comparison, free-standing capacitive
sensors are also produced with the same materials and it is shown that thesedevices are equally stable and robust. In conclusion, the fabrication processdemonstrated here is robust to process variations and is capable of producing
sensors directly on fabric substrates, which facilitates the production of large
arrays of sensors without the need for an additional assembly step.

1. Introduction
The field of soft robotics presents the opportunity to create
devices with capabilities totally unlike traditional rigid devices.
From mobile robots[1] to wearable systems[2,3] to fabric-based
sensory skins,[4] highly stretchable devices allow us to address
challenges in new ways. Soft robots, wearable devices, and biological systems have lower elastic moduli than are found in traditional engineering materials,[5] such as metals,[6] which leads
to incompatibilities and interface mismatches. Because soft
systems often undergo strains on the order of 100%, commercially available strain gauges are not a compatible solution, as
they typically measure strains on the order of 10%. Therefore,

Dr. E. L. White, M. C. Yuen, J. C. Case, Prof. R. K. Kramer
School of Mechanical Engineering
Purdue University
585 Purdue Mall, West Lafayette, IN 47907-2088, USA
E-mail: rebecca.kramer@yale.edu
The ORCID identification number(s) for the author(s) of this article
can be found under https://doi.org/10.1002/admt.201700072.

DOI: 10.1002/admt.201700072

Adv. Mater. Technol. 2017, 2, 1700072

2. Graphite Exfoliation
The first step in fabricating our sensors is the preparation of
the conductive phase. There are many methods of exfoliating

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www.advmattechnol.degraphite into few-layer graphene, including mechanical, electrochemical, and thermal schemes.[15,18,19] Previously reported
work has either considered how variations in processing affectmaterial parameters, or has demonstrated how a single setof processing parameters can be used to produce a device.
Our approach is different in that it focuses on componentlevel parameters rather than material parameters. As such,
we connect variations in processing all the way through the
manufacturing sequence to the performance of finished conductive composite films, focusing on the sheet resistance ofthe films. Using the general consensus of the methods previously reported, the process we have used is as follows (see additional details in the Experimental Section). First, graphite flakes(Figure 1, 1st row) are soaked in an acid mixture, intercalating
the sheets of graphene comprising the graphite with sulfuric
acid. The acid-intercalated graphite is then roasted in an ovento vaporize the sulfuric acid in between the graphene sheets,
causing expansion of the graphite (Figure 1, 2nd row). To further separate the multi-layer graphene sheets from one another,
the expanded intercalated graphite is sonicated in a solvent(Figure 1, 3rd row). Finally, the EIG-solvent mixture is mixed
with silicone elastomer at 10 wt% EIG, and then cast into conductive composite films (Figure 1, 4th and 5th rows).

2.1. Screening Study
To study the graphite exfoliation process, we identified nine
critical process parameters with practical ranges based on theavailable literature, shown in Table 1, and constructed a study
to measure main effects of these parameters (Figure 2) (seeSupporting Information for treatments and measurements(Section S1)). The null hypothesis for this test was that there isno difference between different parameter levels for the sheet
resistance of the composite films. The significance, p, represents the probability that the two treatments are drawn fromthe same population. From Table 1, all of the p-values wereabove a chosen Type I threshold of 0.05, indicating that the
we failed to reject the null hypothesis on any parameter. However, the effect sizes, η2, were all below a chosen effect strength
threshold of 0.2, indicating that none of the parameters had apractical impact on the sheet resistance.
Based on this initial screening, we determined that sonication parameters were convolved. We accounted for this effectby combining the sonication-related parameters together into
specific sonication energy (sonication energy per unit massof graphite). The resulting relationship, plotted in Figure 2b,
shows that increased specific sonication energy results insmaller particles and higher sheet resistance. We fit an exponential model to the data and obtained−5

Rsheet = 69.10 e 1.007×10 E(1)where Rsheet is the sheet resistance in Ω and E is the specificsonication energy in J g−1. Specific sonication energy accounts
for 74.9% of the variation in the Rsheet measurements (R2 value),
which is a significant part of the overall variation in sheet resistance, as expected. In order to quantify the effects of the otherparameters, we computed the expected sheet resistance based

Adv. Mater. Technol. 2017, 2, 1700072

on this exponential model to account for the specific sonicationenergy, and then computed the deviation between the observation and the model. We then determined the significance of theremaining parameters, p′, based on this deviation. The resultsof this analysis are shown in Table 1 and Figure 2c. From thissecond step, we tentatively concluded that roasting temperature and acid ratio have a more significant impact on material
parameters, while roasting time, acid soak time, and solvent
have insignificant contributions.

2.2. Response Surface Model
Based on the tentative results of the screening study, we conducted a second detailed study using a space-filling centralcomposite experimental design to create a response surface
model based on the significant parameters: specific sonicationenergy, roasting temperature and acid ratio (see Supporting
Information for treatments (Section S2)). The goal of the
response surface model was to further confirm the significanceand determine the magnitude of the effect of the significant
parameters on the sheet resistance of the resulting film. However, when we limited the number of parameters in the study,
we found that the sheet resistance was largely unaffected byaltering the values of those parameters (Figure 2d and Table 2).
This was not unexpected, as the effect sizes of all the parameters in both the screening study and the detailed study showthat none of the parameters have a practical impact on the
resulting film’s sheet resistance. This finding further demonstrates the robustness of the overall graphite processing procedure; nearly any combination of values chosen within the range
shown in Table 1 will yield conductive composite films withrelatively similar properties.
Our conclusion from this study is that specific sonicationenergy is the most effective way to adjust sheet resistance.
As specific sonication energy increases, the EIG particle size
decreases, resulting in smaller conductive filler particles in the
conductive elastomer composite. Films with larger expandedgraphite particles had very low resistance at the expense of poor
mechanical parameters, such as a low yield strain. Conversely,
films with smaller particles had superior mechanical strength
but exhibited much higher resistance. Conductive composites
at either of these extremes are unsuitable for high deformation
sensing. By performing this study, we identified and verified
the range of significant processing parameters for producing
expanded graphite with the appropriate morphology for capacitive sensors. In addition to this effect, we also experimentally
verified the percolation threshold of 3 wt% for this system[29]and demonstrated that increasing particle loading above 15 wt%
does not significantly improve conductivity (see Supporting
Information for experimental responses (Section S3)). The
bolded parameters listed in Table 1 indicate those used to makethe sensors for the following section of the paper.

3. Highly Deformable Strain Sensors
In order to make use of the conductive elastomer films as
a sensing element, we must consider their performance as a

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Figure 1. SEM images and photographs of the graphite exfoliation process, in order from graphite flakes (1st row), expanded graphite (2nd row),
sonicated graphite (3rd row), and finally, the conductive composite (4th and 5th rows). The columns show increasing zoom from left to right.

transducer. One of the challenges of directly measuring theresistance of conductive composites in highly deformable sensors is the tendency of material properties to change over time.

Adv. Mater. Technol. 2017, 2, 1700072

The change in Young’s modulus and conductivity in an EIG
and silicone system over many cycles was clearly illustrated
by Kujawski, et al.[29] For this reason, we have elected to use

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Table 1. Processing parameters evaluated in initial screening study and pro-forma study.
The solvent category is not a metric scale, therefore “min” and “max” are merely labels inthat case. The bolded values indicate the parameter values later used for manufacturing all
sensors. The p-values (significance) and effect sizes (η2) (measure of correlation) of thescreening study and pro-forma screening study were found using ANOVA. Values associatedwith the pro-forma study are labeled with a′. For a parameter to be significant, we have chosena threshold of 0.05 such that parameters with p < 0.05 are deemed significant. For a parameter to have sufficient effect strength, we have chosen a threshold of 0.2 such that η2 > 0.2 aredeemed significantly correlated.
Min

Max

p

η2

p′

η′2

50 mL g−1

100 mL g−1

0.215

0.107

–

–

Sonication Volume

100 mL

500 mL

0.253

0.0899−−Solvent

TolueneCyclohexane

0.302

0.07210.904

0.000820

30

70

0.351

0.0582

−

−

3:1

4:1

0.374

0.0523

0.199

0.100

30 min

120 min

0.487

0.0316−−

Parameter
Sonication Concentration[29]Sonication Amplitude
Acid Ratio[15]Sonication Time
Acid Soak Time

1h

24 h

0.492

0.0308

Roast Time

5 min

10 min0.505

0.0289

Roasting Temperature[15,18]

500 °C

800 °C

0.764

0.00574

capacitive sensing, which we demonstrate is more stable. Many
examples of capacitive sensors appear in the soft electronics
literature, including those for sensing strain, pressure, andproximity. These sensors have been madefrom metal electrodes,[20,30–33] carbon nanotubes,[34] liquid metals,[35–38] printed conductive inks,[39] conductive elastomers,[40,41]
graphene-filled
sponges,[42]conductive
fibers,[43] silver nanowires,[44] and salt solutions.[45] Although these examples utilize different fabrication methods and materials, thediversity of approaches illustrates the underlying utility of capacitive sensing in many
applications.

3.1. Materials and Manufacture

We fabricated our sensors from two typesof elastomer: nonconductive pure silicone
elastomer, which we used as a dielectric
0.949
0.000231
layer and support layer, and EIG-loaded elas0.722
0.00718
tomer, which we used as electrode layers (see0.08930.185
Supporting Information for more details(Section S4)). For the film-based manufacturing process, we fabricated films on a sacrificial PET substrate and then folded them in half to form a three-layer
structure (Figure 3a). In the screen-printing method, liquid

Figure 2. Results of graphite processing studies. a–c) For the box plots, the thick bar indicates the mean, the shaded rectangle is the 95% confidence
about the mean, the thinner lines show the maximum and minimum sheet resistance values measured. a) Box plot comparing the sheet resistance
between the min and max values of all parameters tested in the screening study. b) Sheet resistance as a function of specific sonication energy. All 18
trials of the screening study are included in this plot. 95% confidence intervals are shown based on three samples, each with three measurements.
Solid line represents best exponential fit of the data. Note the logarithmic scale. c) Box plot comparing the sheet resistance between the min and max
values of the pro-forma screening study. d) Box plot comparing the statistics of the response surface modeling study.

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Table 2. ANOVA results of treatments evaluated in response surface
model. The p-values indicate the statistical significance of the parameter,and η2 indicates the effect size of the parameter. For a parameter to besignificant, we have chosen a threshold of 0.05 such that parameterswith p < 0.05 are deemed significant. For a parameter to have sufficienteffect strength, we have chosen a threshold of 0.5 such that η2 > 0.5 aredeemed significantly correlated.
pη2

Roast temperature

0.261

0.109

Acid ratio

0.708

0.0264

Sonication amplitude

0.229

0.120

Sonication time

0.319

0.0913

Parameter

elastomers were rod-coated, layer-by-layer, through stencils onto
Spandex fabric (Figure 3b). For the direct-writing approach, we
extruded the elastomers, layer-by-layer, onto a fabric substrateusing a modified commercial filament-type 3D printer (Figure3c). The film-based manufacturing process is most similar topreviously developed highly deformable sensors as it results infree-standing sensors. The screen-printing and direct-writing
methods allow us to construct sensors in situ, directly patterning them onto a substrate. Once the sensor bodies arecompleted, each of the EIG-elastomer electrodes was electrically interfaced via copper-clad polyimide film (Figure 3d) (seeSupporting Information for more details (Section S5)). Wires
soldered to the copper were then run to a signal conditioning
board to measure capacitance and convert it to an analog voltage
output (see Supporting Information for more details (SectionS6)). Following fabrication, we measured the thickness of eachof the layers comprising the sensors (Figure 3e) and foundthat the variance in thickness across all three manufacturingmethods is similar, indicating that all methods are relatively
consistent. The variances of all electrode layers are very similar
and the mean thicknesses are all within 40 µm of one another.
The dielectric and base layers had larger variance. We believethat this is because the pure silicone elastomer has higher viscosity and will not reflow to the same extent as the EIG-loaded

Figure 3. Sensor manufacture, assembly, and physical characterization. Schematics and photos illustrate the a) film-based, b) screen-printed, andc) direct-writing manufacturing approaches. d) Photos of the interface for the film-based and screen-printed sensors. e) Thicknesses of each layer
comprising the sensors. The notch shows the mean, the bar indicates the 95% confidence bounds about the mean. The film-based sensors lack afabric backing and thus no data are plotted.

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Figure 4. An assortment of sensors. At the top, a set of screen-printed sensors lay across foam block. The stretched sensor and the group of sensors
on the bottom right are manufactured using the film-based method. The group of sensors on the bottom left is manufactured using direct writing.

elastomer, resulting in a less smooth film. The dielectric layeron the film-based sensors is much thicker because the film isfolded over onto itself to form the devices. Despite the differences in layer thicknesses, all sensors performed similarly as
shown through the following characterization tests. Sensors
fabricated using all three approaches are shown in Figure 4.

3.2. Sensor Characterization
We first demonstrated the stability of the sensors’ capacitance.
We measured the resistance of the conductive composite electrodes and the unstrained sensor output (i.e., capacitance)
before and after subjecting the sensors to 50 cycles of strain
from 0% to 50% strain (Figure 5a,b). The resistance of theelectrodes clearly increased as a result of the strain cycling(Figure 5a). However, the sensor output is unaffected by the
50 cycles of strain (Figure 5b). This result confirms our choiceof capacitive sensing over resistive strain sensing, and additionally speaks to the robustness of the sensor functionality inoperation.
We then subjected sensors to degradation testing to determine the maximum operating strain. In these tests, we cycled
the sensors to a specific strain value for 10 cycles, and thenincremented to the next strain value. To identify the strain
at which the sensors failed, we extracted the sensor signal atits unstrained length at the end of the 10th cycle to a specificstrain value, which we call dV10 (Figure 5c). A still-functioning
sensor should show a dV10 = 0 V, i.e., the sensor returns to its
initial value. We see that the dV10 of the fabric-based sensors
begins to deviate from the ideal early on in this test. This is partially due to plastic deformation of the Spandex fabric backing,which causes the sensors to be permanently strained relative totheir starting length. At strains of approximately 250%, both of
the fabric-based sensors have strained to the point of failure,

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as indicated by the large change in the confidence bounds ofthe dV10 values. However, the film-based sensors can withstandstrains to 375% until they no longer function. This test demonstrates the sensors’ ability to withstand extremely large strains,such as those that may occur during installation of these sensors or during stowage and transport.
Further characterization tests showed that the sensors display similar device functionality independent of fabrication
method. We first applied a low number of cycles (50) on eachsensor to 50% strain to characterize the mechanical (force)and electrical (sensor signal) responses during the break-in
period (Figure 5d,e). The electrical responses across all manufacturing approaches are approximately linear (Figure 5d). The
linearity of the sensor response to strain simplifies the calibration process of these sensors in robotic systems. There was no
noticeable transient phase in the sensor signal during the low
cycle count test. The mechanical response, which displays the
typical non-linear response of polymers, shows no decrease inload as the number of cycles increase (Figure 5e). The loads
in the screen-printed and direct-written sensors are consistently much larger than that of the film-based sensors due tothe additional fabric backing and the elastomer base layers inthese sensors. We further subjected sensors to an additional
1000 cycles from 0% to 50% strain to determine behavior overrepeated cycling (Figure 5f,g). The magnitude of the confidence
intervals is similar between the 50 cycle and 1000 cycle tests,
demonstrating that neither initial transients nor long-term degradation is present in the system. A more detailed explorationof the hysteresis and transient response of the sensors can befound in Supporting Information (Section S7). The number ofcycles tested in this study is of the same order of magnitude asreported in characterization other highly deformable sensors.[46]This is an important consideration as we move from laboratory
prototypes to sensors integrated into more complex devices
where sensor replacement is not an option.

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Figure 5. Sensor characterization plots. Where applicable, the data are presented as means with 95% confidence bounds. a) Comparison between theinitial and final (after 50 cycles) resistances of the sensor electrodes. b) Comparison between the initial and final unstrained sensor responses. c) Plotillustrating degradation of the sensors due to strain. Three sensors from each manufacturing method were subjected to incrementally increasing strains
with 10 cycles applied at each strain increment. The 95% confidence bounds of the sensor response at its unstrained length are plotted at each strain
increment. Ideally, the sensors should show a dV value of 0V when unstrained; larger bars indicate degradation of sensor functionality. d–g) Plots ofthe electrical sensor signal (left) and mechanical (right) responses as functions of strain. dV is calculated as V −V0, and is a linearly scaled measure ofchange in capacitance. d,e) Data from testing six sensors from each manufacturing method for the first 50 cycles. In (d), the dashed line indicates themean response and the solid line indicates the curve fit. f,g) Data from three sensors from each manufacturing method for 1000 cycles. For details of
mechanical testing, see the Experimental Section. h) Comparison of the sensor gauge factor after subjecting three sensors from each manufacturingmethod to 0, 25 000, 50 000, 75 000, and 100 000 cycles of strain to 50%. i) Comparison of the sensor gauge factor during testing of three sensors
from each manufacturing method at ambient (22 °C) and elevated (50 °C) temperatures.

The gauge factors of the screen-printed and direct-written
sensors are larger than that of the film-based sensors, as
observed in the larger slopes in Figure 5d,f and as listed inTable 3. Because the sensors are constructed on fabric, theboundary conditions of the bottom electrode and the dielectric layer are altered. In the film-based sensors, both electrodes
freely contract in the transverse direction simultaneously withthe applied longitudinal stretch. In contrast, the fabric backing
for the screen-printed and direct-written sensors does notcontract transversely under longitudinal strain. It instead has
a tendency to curl inward, maintaining its width and solely
increasing in length. Under strain, the contracting transverse
stress across the interface between the dielectric layer and theAdv. Mater. Technol. 2017, 2, 1700072

free top electrode is not sufficient to overcome the opposing
transverse stress from the bond between the bottom electrodeand the fabric/base layer. To examine this, the change in capacitance of the sensors can be modeled asC=

ε 0εr Lw ε 0εr L0 (1 + ε)w 0 (1 + ε)−ν=tt0 (1 + ε)ν −1

C = C0 (1 + ε )2(1−ν )

(2)

(3)

where C is the capacitance, L and w are the length and width of
the active region of the sensor, t is the thickness of the dielectric

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Table 3. Gauge factors of the strain sensors during the break-in periodof 50 cycles and the longer term response over 1000 cycles. The values
represent the mean ± 95% confidence interval. The gauge factors correspond to the slopes of the electrical response curves shown in
Figure 5d,f.
Gauge factor

Film-based

50 cycles

1000 cycles

0.538 ± 0.010

0.546 ± 0.008

Screen-printed

1.13 ± 0.079

1.17 ± 0.039

Direct-written

0.983 ± 0.029

0.999 ± 0.016

layer, ε0 is the permittivity of free space, εr is the relative permittivity, ε is the strain, and ν is the Poisson ratio of the sensor.
The model assumes the sensor maintained constant volume
and experienced inhomogeneous deformation, namely therates of change in width (−ν) and thickness (ν − 1) as a function of longitudinal strain were not equal. The initial length, L0,
was 80 mm, the initial width, w0, was 10 mm, and the average
initial thicknesses of the dielectric layers, t0, were 607, 339, and319 µm for the film-based, screen-printed, and direct-written
sensors, respectively (Figure 3e). The difference in boundary
conditions is observed in a Poisson ratio, ν, of 0.350 for thefilm-based sensors, compared to 0.696 and 0.817 for the screenprinted and direct-written sensors, respectively. The fabricbacked sensors exhibit a planar dilation (ν > 0.5) as the sensors
are stretched. In addition to differences in gauge factor, at small
strains, we found that the electrical responses of fabric-backed
sensors (screen-printed and direct-written) are flat. This is due
to plastic deformation of the relatively stiffer Spandex fabric,
resulting in the sensor being slack at these small displacements
after the first cycle. In implementation, these fabric-backed sensors can be precycled and prestrained to remove initial plastic
effects and operate purely in the elastic region.
In addition to the 1000 cycle tests described previously, we
also subjected the sensors to extended cyclic tests to determine their long-term performance. In these tests, we applied
100 000 cycles of 50% strain and measured the response after
every 25 000 cycles, resulting in five total data sets per sensor.
The measured gauge factors show several trends (Figure 5h).
First, all three types of sensors experience decreases in gauge
factor at high cycle counts. We attribute this to degradationin the conductivity of the electrode layer, which results in theelectric field becoming more concentrated in the region of theinterface electrodes, where the deformation is smaller than
the active middle region due to the presence of the reinforcing
fabric layer. Second, in the case of film-based and direct-written
sensors, the confidence interval in the gauge factor decreases.
We attribute this to a “break-in” effect, where variations in electrical interface conditions are removed over multiple cycles.
The third result is that, although the gauge factor changes, theperformance of the sensors in terms of noise and linearity isotherwise unchanged. The noise and electrical responses of all
types of sensors at all cycle counts are similar to the data shownin Figure 5f, indicating that the sensors continue to function
over at least a 100 000 cycle lifetime. Therefore, with appropriate recalibration processes, the sensors could continue toserve as state observers in highly deformable systems.

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In order to determine the sensor response to variations intemperature, we compared sensor response at 50 °C to thatat room temperature (22 °C). The resulting gauge factors areshown in Figure 5i. Although the mean gauge factors decrease
for all of the sensor types, this change in mean is well within
the 95% confidence intervals, indicating that it is not a statistically significant effect. Anecdotal tests at −40 °C likewise show
an insignificant change in gauge factor. In summary, we conclude that effects of temperature are insignificant on the performance of the sensors, within the temperature bounds of thesilicone elastomers.
The underlying theme through all of these sensor characterization tests is consistency in response. Despite large changes
in the resistance of the conductive composite electrodes, thesensor signals remain stable. All of the sensors, independent of
manufacturing method, display similar behavior in terms of anearly linear electrical sensor output and a consistent mechanical response. Additionally, each sensor’s performance stays
self-consistent throughout operation over a large number ofcycles. At larger numbers of cycles, we observe that all types of
sensors experience a similar change of behavior. Of particularnote, the characterization tests show that the direct-written
and screen-printed sensors behave nearly identically despite
differences in fabrication approach. These characterization
tests indicate the suitability of these capacitive strain sensors
for integration into high-deformation systems because of theirinsensitivity to variations in fabrication processing and theirreliability during operation.

4. Conclusion
In conclusion, we have demonstrated an end-to-end process foreasily realizing robust and highly deformable capacitive strain
sensors using low-cost materials. We have investigated preparation of an EIG-based conductive composite material, construction of strain sensors using three fabrication methods, andresponse of the finished strain sensors. The conductive elastomer composite was shown to be highly robust to variationsin processing conditions, with only specific sonication energy
found to affect the sheet resistance and mechanical parameters of the resulting composite. We further characterized the
response of sensors comprised of the EIG composite to strainover 100 000 cycles and identified their degradation behaviors.
Across three distinct fabrication methods, the sensors exhibitedno significant degradation in performance during cyclic testingon the order of 103 cycles and showed similar changes in gauge
factor at the 25 000 cycle observation and beyond. Further, allsensors failed in a repeatable and consistent manner due toincreasing strain during degradation testing. These studies
show that expanded graphite-elastomer composites are a promising material for sensing large deformations in soft systems via
capacitance. The gauge factor, ultimate strain, and cyclic performance of the sensors are comparable to other state-of-the-art
soft strain sensors that are frequently used in soft robotic applications, with conductive composites demonstrating favorable
robustness, ease of manufacturing, and lower cost. The threefabrication methods demonstrated herein enable simple sensor
integration in a range of applications, from directly printing

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strain sensors on soft robotic components to manufacturing
strain-sensitive wearable garments.

5. Experimental Section
Graphite Exfoliation: The exfoliated graphite was prepared using athree step chemo-thermo-physical process. First, 5g of graphite flakes(Sigma-Aldrich) were soaked in 80 mL of sulfuric acid (Fisher Chemical)
and 20 mL of nitric acid (Macron Fine Chemicals) for at least 1 h. This
processed material was filtered over glass microfiber filters (934-AH,
Whatman) in a Buchner filter (Z247332, Sigma-Aldrich). The filteredmaterial was then washed with 200 mL of distilled water. After washing,
the material was roasted by loading a small scoop of the material(≈3 mL) into a stainless steel cap (4981T63, McMaster-Carr) and placing
it in an oven (Lindberg Blue M) set at 800 °C for 5 min. The resulting
graphite exhibited a radical increase in volume over the starting
material. The expanded material was further exfoliated by adding 500 mL
cyclohexane (BDH1111, VWR) followed by ultrasonication at 20 kHz with
an amplitude of 36 µm (30% setting) for 120 min (Q700 sonicator fittedwith 1/2” tip, QSonica). After sonication, the cyclohexane and graphite
mixture was more homogeneous and the large majority of the volume
was a well-suspended mixture of the graphite in cyclohexane. The slurry
was allowed to settle and excess solvent was decanted. Further solvent
was removed by heating the slurry until a paste-like consistency wasachieved, with ≈150 mL of the mixture remaining. Samples of the slurry
were extracted and massed before and after drying to determine theexpanded graphite concentration in each batch.
Conductive Polymer Composite: The conductive elastomer material
was prepared by dispersing expanded graphite into silicone elastomer(DragonSkin 10 Slow, Smooth-On Inc.). To prepare the composite,
equal parts by mass of parts A and B of the elastomer were mixed, thenthe required mass of expanded graphite slurry was added to achieve
10 wt% loading in the final composite. To maintain consistent material
properties between batches, which had slightly different concentrations,pure cyclohexane was added to the mixture to achieve a graphitein-slurry loading of 0.03g g−1. The sheet resistance of these films wasmeasured with a digital multimeter (5492B, BK Precision) using fourterminal resistance sensing.
Film-Based Capacitive Sensors: As a basis for comparison, stand-alone
capacitive sensors were manufactured from three layers of elastomer.
To do so, first a film of the conductive composite was rod-coated onto
a sacrificial substrate, using the approach described in ref. [47], andthis layer was allowed to cure for ≈2 h. Then a film of native silicone
elastomer was rod-coated on top of the cured composite layer using thesame approach to create the dielectric layer and strips of fabrics werelaid onto the silicone layer to reinforce the ends of the sensors. Afterletting the silicone cure to a “tacky” stage, which took between 45 and60 min, the film was folded over onto itself. After curing for ≈4 h, thisstack formed the final electrode–dielectric–electrode structure. The
sensors were then cut out of the film using a laser patterning system(VLS 2.30, Universal Laser Systems). Finally, water and dish soap wereused to clean the soot off the sensors.
Screen-Printed Capacitive Sensors: The screen-printing process wasvery similar to the film-based sensor manufacturing process describedabove. However, instead of creating large films onto a sacrificial
substrate, they were patterned directly onto a Spandex fabric substrate.
Thus, these devices consisted of five layers: a fabric substrate, a baselayer of insulating elastomer, a conductive bottom electrode, a dielectric
layer, and a conductive top electrode. Each layer was patterned by rodcoating through a laser-cut PET mask, allowing each layer to cure in
between. After all layers were patterned and cured, the sensors were cut
out and cleaned with the same process as for the film-based sensors.
Direct Writing of Capacitive Sensors: Direct writing of sensors onto
fabric substrates was accomplished using a modified commercial
3D printer (Simple Metal, Printrbot). The filament extruder had been
removed from this device and replaced with a syringe pump. The pump

Adv. Mater. Technol. 2017, 2, 1700072

was controlled using the same components as the filament drive motor.
The printer was controlled with commercial software (Repetier-Host). A.stl file of the selected sensor layer was loaded into the software, and theintegrated slicing algorithm (Slic3r) was used to generate a tool path in
G-code. With this, the liquid elastomer could be directly extruded onto
the substrate. As in the screen-printing case, one layer at a time wasprinted, with sufficient time between layers to achieve complete curing.
After all layers were patterned and cured, the sensors were cut out usinga laser patterning system.
Sensor Interface: After the sensor bodies were laser-cut and cleaned,copper interface electrodes (copper-clad polyimide film, Pyralux,
DuPont) and polystyrene tabs were sewn onto the ends of the sensors.
Sewing holes were laser cut through the polystyrene, copper, and sensor
for alignment of layers and increased ease of assembly. Holes were laser
cut through the ends of the sensor to prevent the electrode layers fromshorting with each other due to sewing. Ample tension was applied
during sewing to ensure that the copper electrodes had good contact
against the conductive composite electrodes with polystyrene tabs.
Sensor Signal Conditioning Board: The signal conditioning boards were
designed in house. A microcontroller (PIC16F1825, Microchip) was thecore of this board. A charging signal was sent every 8.4 ms to charge
the sensor to 2.262 V. The time it took to discharge to 0.238 V wasmeasured. This was converted to an analog voltage signal, which wasreported as the sensor response.
Mechanical and Electrical Response Testing: All sensor specimens were
tested using a materials tester (Instron 4435). A 50 N load cell was used
to measure the load and a voltage transducer was used to measure theanalog voltage output from sensor signal conditioning board. All tests
applied strain at a rate of 100% min−1 = 80 mm min−1. The sensors
were secured to the materials tester via polystyrene plates that had
been sewn onto the ends of the sensor. The sensors were installed ina slack position and the crosshead of the materials tester was raised
until the sensors were not slack; no further pretension was applied tothe sensors.
For the cyclic fatigue testing, sensors were placed in a slider crankmechanism driven by a drill press running at 1000 rpm. After every 25 000
cycles, the sensors were removed from the slider crank mechanism andreturned to the Instron to perform the same mechanical and electricalresponse testing as described previously. For the thermal testing, theInstron was fitted with a temperature-controlled heated environmental
chamber. Samples were initially tested at room temperature in thechamber. After the initial test was completed, the chamber was activatedand brought to a stable temperature at 50 °C, and the sensors werere-tested using the same method.

Supporting Information
Supporting Information is available from the Wiley Online Library orfrom the author.

Acknowledgements
E.L.W. and M.C.Y. contributed equally to this work. The authors would
like to thank R. Adam Bilodeau for his assistance obtaining SEM
images of the graphite materials and Dr. Mohammed G. Mohammed
for assistance preparing the images for the manuscript. This work
was supported by the National Aeronautics and Space Administration
through the Early Career Faculty Program (Space Technology Research
Grants Program, Grant NNX14AO52G). E.L.W. and M.C.Y. are supportedby the National Science Foundation Graduate Research Fellowship(Grant DGE-1333468). J.C.C. is supported by the National Aeronautics
and Space Administration’s Space Technology Research Fellowship
program (Grant NNX15AQ75H). The opinions and findings expressedin this paper are those of the authors, and do not necessarily reflect
those of the National Aeronautics and Space Administration nor the
National Science Foundation.

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www.advancedsciencenews.com

www.advmattechnol.de

Conflict of Interest
The authors declare no conflict of interest.

Keywords
additive manufacturing, conductive composite, large-deformation strain
sensing, soft robotics
Received: March 20, 2017
Revised: May 17, 2017
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