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Smart piezoresistive tunnelling composite for flexible robotic sensing skin

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2013 Smart Mater. Struct. 22 125039

(http://iopscience.iop.org/0964-1726/22/12/125039)

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Smart Mater. Struct. 22 (2013) 125039 (9pp) doi:10.1088/0964-1726/22/12/125039

Smart piezoresistive tunnelling compositefor flexible robotic sensing skin

S Stassi1,2, G Canavese2, F Cosiansi3, R Gazia2, C Fallauto3,S Corbellini3, M Pirola3 and M Cocuzza2,4

1 Dipartimento di Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli Abruzzi 24,I-10129 Torino, Italy2 Center for Space Human Robotics@PoliTo, Istituto Italiano di Tecnologia, Corso Trento 21, I-10129Torino, Italy3 Dipartimento di Elettronica, Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Torino, Italy4 CNR-IMEN, Parco Area delle Scienze 37, I-43124 Parma, Italy

E-mail: stefano.stassi@polito.it

Received 22 July 2013, in final form 18 October 2013Published 22 November 2013Online at stacks.iop.org/SMS/22/125039

AbstractA highly mechanically flexible tactile device based on a metal–elastomer composite materialwas prepared by an efficient and simple process. The microcasting fabrication technique, usedfor the preparation of a selfstanding sheet of functional material, gives the possibility of easilyfabricating complex-shaped structures suitable for integration on robot surfaces for tactilesensing applications. Under the action of a compressive stress the composite material exhibitsa giant piezoresistive effect, varying its electrical resistance by several orders of magnitude.This phenomenon can be tuned by changing the material composition parameters, whichdirectly modify the sensitivity of the sensor. After a comprehensive characterization of thefunctional properties of the material, an 8× 8 pressure sensor matrix with dedicatedelectronics was fabricated and tested.

(Some figures may appear in colour only in the online journal)

1. Introduction

The challenge to transfer robots from the confinedenvironment of a production line to complex humanenvironments, where smart tasks and increasingly difficultoperations are required, has pushed towards the improvementof not only in-hand manipulation and exploration tasks butalso of safe interactions. In order to satisfy these requirements,there is an increased interest, in particular for humanoidrobots, in the development of large-area or whole-bodytactile sensing structures [1]. Moreover, the increase ofenvironmental complexity implies, as a consequence, adifferentiation of the sensing modalities [2].

Depending on the location of a sensor on a robot body, thesensing capability can be classified as extrinsic and intrinsicsensing. Intrinsic sensors, aimed at the replication of thekinaesthetic sensing in humans, are usually placed within themechanical structure of the system and collect data such as themagnitude of force and torque [3]. Extrinsic or tactile sensor

arrays are mounted at the contact interface and, similarly tocutaneous sensing in humans, they collect data from localizedregions [4, 5].

Another approach to classify tactile sensors is based onthe working principle. There are literature reports on tactilesensors exploiting resistive, capacitive, inductive, optical,magnetic, piezoelectric, ultrasonic and magneto-electricprinciples [6–8].

Concerning the coupling between tactile sensing devicesand the robot structure, two methods are generally adopted.One consists of the integration, with the robot surface, ofarrays of separate sensing devices [9], while the other consistsof the application of a continuous sensitive film across thewhole robot surface [10]. The second method increasinglyinvolves piezoresistive materials. The transduction method ofpiezoresistive materials is based on the variation, under anapplied mechanical stress, of the electric resistance.

Tactile sensor devices combining both piezoresistivesilicon components and polymers have been proved to provide

10964-1726/13/125039+09$33.00 c© 2013 IOP Publishing Ltd Printed in the UK & the USA

Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

high sensitivity, high spatial resolution and ease of integrationinto electronic devices [11, 12]. Nevertheless, since silicon isa brittle material, the application of such devices is limitedin terms of flexibility or stretchability, particularly when thesensors need to be packaged onto the curved surfaces ofsurgical probes or robotic manipulators [13]. Furthermore,the finite size of silicon wafers imposes size-related designconstraints on the dimensions of the tactile sensors.

Among the different materials used in piezoresistivedevices, composites based on polymers have severaladvantages, such as flexibility, mechanical robustness, andinsensitivity to overload, and can be synthesized by simpleand low-cost techniques [8].

Properties such as flexibility, conformability and stretch-ability are necessary for easy integration of the sensingstructures with the bodies of robots and for the effective usageof the touch sense modality in any robotic tactile system [14].

This work presents the design and fabrication ofan extrinsic, continuous sensitive film based on a newpiezoresistive material composed of microstructured copperparticles dispersed into a silicone rubber matrix.

Recently, electrodes made by winding copper wiresaround an elastic nylon line have been proposed to electricallyconnect discrete piezoresistive tactile elements based on met-als (copper and silver), carbon and polymer composite [15].The authors claim that their approach could decrease the crosstalk problem and at the same time increase the flexibility,but neither functional characterizations nor the thicknessof the nodes have been reported. While the evaluation ofconductivity of composites with pure copper powder asa conductive filler has been previously reported [16, 17],to the best of our knowledge the present work is the firsttime that microstructured copper particles in a PDMS matrixcomposite have been successfully employed as a functionalmaterial in tactile devices.

The advantages with respect to sensors fabricatedwith nickel based composites reside in the much loweramount of metal particles required to obtain a comparablefunctional response, thus also increasing the flexibility of thecomposite [18]. In addition, copper based composites show anabsence of toxicity problems (mainly related to the presenceof nickel oxide), whereas with respect to the synthesized goldnanostars [17, 19] the use of commercial powders, such as thecopper ones, introduces no further issues related to cost of thechemical precursors and synthesis control, time and yield.

The electrical conduction in the developedcopper–elastomer composite occurs mainly by tunnellingmechanisms, as already reported for other metal–polymerhybrid systems with nickel [19, 20] and gold spikyparticle fillers [17]. In the prepared composite samples,copper particles are intimately coated by the polymer, thusavoiding any physical contact between them. This resultsin an insulating electrical behaviour when no mechanicaldeformation is applied to the specimens, even above theexpected percolation threshold [21]. When the samples aresubjected to a compressive strain, the gap represented bythe insulating layer between the metal particles is reduced,thus causing an exponential increase of the probability for

the electrons to tunnel between neighbouring particles. Asa consequence, the electrical conduction of the specimensincreases by several orders of magnitude.

A dedicated read-out circuit was designed for real-timeanalysis and connected to an 8 × 8 tactile sensor array basedon the synthesized composite. A trans-impedance logarithmicamplifier was used to manage the large variability of theresistance on the whole resistance range and software fortactile imaging was developed for the data elaboration and 3Dvisualization of the applied pressure.

2. Experimental methods

Selfstanding thin sheets of copper–PDMS composite wereobtained with a microcasting technique that allows alarge degree of freedom in the shape and size of thefinal sample [20]. Different functional materials wereprepared by dispersing 150, 200 and 250 parts perhundred resin (phr) by weight of commercial copperpowder (POMETON Ltd—LT10) into the elastomer baseof a bi-component polydimethylsiloxane (Dow CorningCorporation—SYLGARD 184). The blend was gently handmixed, in order to avoid disruption of the tips on the particlesurface that would reduce their field enhancement effect,for 10–15 min to obtain a uniform paste. No solvents wereused to improve the particle dispersion because, as observedby FESEM analysis, the fillers were adequately dispersedby hand mixing to avoid a conductive path in the curedcomposite. Then the PDMS curing agent was added to theblend in a ratio of 1:10 by weight with respect to thePDMS base. The obtained paste was then mixed manuallyagain to obtain a homogeneous distribution, poured intopoly(methyl methacrylate) (PMMA) moulds, fabricated by amilling technique, and outgassed under vacuum for 1 h atroom temperature. After all the air bubbles were eliminated,the mould was clamped between two PMMA plates in order toobtain flat surfaces. Then the composite was thermally curedat 75 ◦C for three hours and later removed from the moulds.A graphical representation of the process flow is presented infigure 1.

The quantity of metal filler was varied between 150and 250 phr by weight, because they are the minimumand maximum value for which it is possible to obtain apiezoresistive composite. In fact, by adding less than 150 phrthe variation of electrical resistance under an applied pressure(in the range 0–2 MPa) is not appreciable. On the other hand,on increasing the copper content above the maximum valuethe composites become too rigid and fragile and showed areticulation problem during the curing step [18].

Morphological and dispersion characterization wereperformed both on the copper powder and the composite witha field emission scanning electron microscopy (FESEM, ZeissSupraTM 40) with an acceleration voltage of 3 kV.

Piezoresistive characterizations of the functional com-posites were carried out by applying a compressive pressurewith a universal mechanical testing machine (MTS Qtest 10),that controls the force values by means of a load cell andmeasuring the electrical resistance with a Keithley 2635A

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Figure 1. Process flow of the realization of the composite material: (a) PDMS base weighing, copper particles weighing, (b) mixing,(c) curing agent weighing, (d) mixing, mixture outgassing, (e) pouring in the mould, (f) closing with PMMA plates and (g) demolding.

sourcemeter coupled with a home-made sample holder. Thecomposite samples were placed between two stiff copperplates, fixed to the grips of the testing machine, used aselectrodes, and thus connected with the sourcemeter. Theplates were previously cleaned with HCl–water solution toremove any residue of a copper oxide layer.

Piezoresistive composites were characterized in thepressure range from 0 to 2 MPa, corresponding to forcevalues up to 200 N. The application of a compressive loadto the samples was controlled in strain and applied with adisplacement speed of 0.1 mm min−1.

3. Functional composite materials

3.1. Tunnelling conduction model

The electrical conduction inside the composite sample isattributed to a quantum tunnelling mechanism and is enhancedby the characteristic morphology of the particles, presentingvery sharp spikes on the surface [17, 21]. The presence ofthese particular protuberances on the copper powder helpsthe polymer to intimately coat the filler, avoiding physicalcontact between neighbouring particles. In the absence of anyapplied pressure, the composite presents an insulating electricbehaviour (hundreds of M� up to some G�). In contrast,when the composite is compressed and therefore deformed,the insulating layer between the particles is reduced, causingan increase of the tunnelling probability of the electronsand consequently an exponential decrease of the electricalresistance of the sample.

This tunnelling behaviour is promoted by the char-acteristic shape of the particles, presenting multi-branchedmicrostructures covered by very sharp nanometric spikes onthe surface. The role of the tips in the functional materialis well-rendered by comparing the piezoresistive response

of the microstructured copper–PDMS with other tunnellingcomposites with rounded fillers. Actually a considerablylower variation of the electrical resistance at the same appliedpressure was obtained in composites using zinc, nickel andalso smoother copper particles [22, 23].

Tunnelling conduction is the dominant mechanismin these composites, but is not the only one present.Electrical field induced emission [24], Richardson–Schottkytransmission types and Pole–Frenkel conduction [25] aresecondary order conduction mechanisms and thereforenegligible. In contrast, the percolation mechanism isnegligible in the pressure range of interest for this study,while for elevated pressures it becomes predominant becausethe insulating layer can no longer avoid contact betweenconductive particles strictly close to each other.

The piezoresistive behaviour of the copper–PDMScomposite could be simulated with a complex mathematicalmodel, proposed by Lantada et al [26] and successivelysimplified through the elimination of the temperature andtime dependence [18]. The model can be applied to anycomposite with a tunnelling conductive mechanism and canpredict the functional response of the material depending onthe composition and applied pressure. These simulated dataare fundamental for the fabrication of the composite andits implementation and calibration in the tactile sensor. Theresponse of the material was modelled by investigating theeffect of a compressive pressure on the quantum model of thepotential barrier represented by the insulating polymeric layerbetween two spiky particles. In fact in quantum mechanicsthere is a non-zero probability that an electron can crossa potential barrier even if its energy is lower than theheight of the barrier. This tunnelling probability correspondsto the square root of the barrier transmission coefficientT , describing the percentage of the incident electron wavecrossing the potential barrier [27], computed starting from

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Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

Figure 2. FESEM images of (a) the copper powder and (b) the copper–PDMS composite.

Schrodinger equation as:

T =

(1+

ϕ2(sinh(2πd√

2m(ϕ − E)/h2))2

4E(ϕ − E)

)−1

(1)

where d and ϕ are the width and the height of thepotential barrier constituted by the PDMS film, E and mare the electron energy and mass respectively, and h is thePlanck constant. Therefore the tunnelling current between twometallic conductive particles through the polymeric insulatinggap is proportional to the probability of one electron to crossit. The probability varies under an external perturbation thatdirectly modifies the dimensions of the barrier. Since in thiswork the measurements were performed at room temperatureand with a compression velocity high enough to neglect thecreep effect, the potential barrier was considered subjectedonly to mechanical deformation according to the followingequation:

ϕ = ϕ0

(1−

p

G

), d = d0

(1−

p

G

)(2)

where d0 and ϕ0 are the width and the height of thepotential barrier without any mechanical deformation, andG the polymer compressive modulus. In this analysis thecompressive modulus of the metal (orders of magnitudehigher with respect to the PDMS value) is not takeninto account since the particle deformation is negligible ifcompared with those of the elastomeric matrix.

From the above consideration, it is possible to evaluatethe resistance R of the whole composite sample under amechanical compressive pressure as a variation from theresistance value in the undeformed state R0, proportional tothe ratio of the tunnelling probability, and thus to the twobarrier transmission coefficients, T0 and T , in the absence andin the presence of an external perturbation, respectively:

R(p) = R0(T0/T)1/2

= R0

1+ ϕ2(sinh(2πd√

2m(ϕ−E)/h2))2

4E(ϕ−E)

1+ϕ2

0 (sinh(2πd0

√2m(ϕ0−E)/h2))2

4E(ϕ0−E)

1/2

. (3)

The material properties and parameters used for the fitting ofthe curves in this work were measured or obtained from the

Table 1. Parameters of the theoretical calculation.

Symbol Parameter Values and units

m Electron mass 9.1× 10−31

h Planck constant 6.63× 10−34

ϕ Potential barrier height 0.73 eVd0 Interparticle gap 25–80 nma

R0 Electrical resistance at 0 Pa 0.3–1 G�a

G Compressive modulus E0+ E1 ∗ p+ E2 ∗ p2b

a Depending on the filler amount.b Fitting of the stress–strain curve with a parameter depending onthe filler amount.

data sheet and manufacturer. R0 and G depend on the type ofsample. In particular to improve the precision of the fitting, Gwas not used as a constant value, but as a quadratic functioncomputed by fitting the stress–strain curves of each compositesample. The interparticle gap d0 was evaluated by consideringall the particles as spherical and of the same size, as alreadyreported in [18], a strong assumption that anyway resultedin an excellent fit to the experimental curves. The value ofthe height of the potential barrier was obtained by Lantada’swork [26] and modified according to copper instead of nickel.A summary of the main parameters used in the theoreticalcalculation are reported in table 1.

3.2. Material characterizations

Field emission scanning electron microscopy (FESEM)micrographs acquired on the as-received copper powdershowed particles in the range 10–20 µm, having a highlyirregular surface. The particles present multi-branchedmicrostructures covered by very sharp spikes (up to a fewmicrometres in length), as shown in figure 2(a). FurtherFESEM observations were collected on the cured compositeshowing that the mechanical mixing step ensures a uniformdistribution of the metal particles inside the polymer matrix,avoiding the formation of large aggregates and damage on theparticle surface (figure 2(b)).

The piezoresistive composite material was tested between0 and 2 MPa because this working range includes theboundary of extrinsic tactile sensing applications, aimed toreproduce the cutaneous sense of touch, which are limited

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Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

to some hundreds of kPa [2, 8]. Additionally it is possibleto use these functional materials not only for tactile sensors,requiring higher pressure value limits, such as joint sensors,but also for other devices not necessarily related to the roboticfield.

The mobility of the copper particles inside the elastomermatrix directly affects the piezoresistive behaviour of thecomposite. In fact the probability of tunnelling of the electronsincreases when the insulating polymeric layer placed betweentwo neighbouring particles is deformed and thinned bythe external load. Since the PDMS used in this workis a bi-component, the Young’s modulus of the obtainedcomposite can be tuned by varying the copolymer–curingagent ratio [28]. Then the sensitivity of the final material tothe applied pressure would be lower for compositions witha higher content of PDMS curing agent with respect to thebase, since more cross-linked polymer with higher stiffnesswould be obtained [29]. This effect is further enhanced in acomposite with a lower content of copper particles, becausethe thickness of the polymeric layer between metal particlesincreases. On the basis of the observation reported in ourprevious work on nickel–silicone composites [30], a 10:1base–curing agent ratio was selected for the copper–PDMScomposite, thus guaranteeing the optimal stiffness in orderto achieve the sensitivities requested in tactile sensingapplications.

Furthermore, since the functional material is composedof a metal part and a polymer part, the variation of theirmutual concentrations tunes the composite piezoresistiveresponse, modifying, as a consequence, the sensitivity ofthe final sensor. A higher metallic filler quantity means ahigher pressure sensitivity since the tunnelling gap betweenclose particles in the undeformed state is smaller than incomposites with a lower metallic content. This gap is furtherreduced when the sample is compressed. An example of thefunctional response of the copper–PDMS is shown in figure 3for samples with a thickness of 1 mm. All the compositionsexhibit an insulating behaviour without any applied pressure.The electrical resistance of the undeformed sample is higherthan 100 M�, confirming that the copper particles arecompletely covered by the polymer, as already observedby the FESEM analysis, and there are no conductive pathsinside the composite. Under the application of a compressivepressure, the resistance of the samples decreases by severalorders of magnitude. At 2 MPa the sample of 250 phrsuffers a variation of around eight orders of magnitude,whereas the 200 phr composition varies by seven orders,and the 150 phr by just three orders. The comparison ofthe functional response of the different composites withthe behaviour computed with equation (3) reveals that thetheoretical model predicts the piezoresistive response of thematerial well for all the ranges of applied pressure, taking intoaccount the experimental error obtained over an average of tenmeasurements, thus confirming that the prevalent conductionmechanism in the composite is quantum tunnelling.

Piezoresistive materials can be analysed and comparedby evaluating their piezosensitivity and strain sensitivity. The

Figure 3. Comparison between the experimental and theoreticalpiezoresistive response of the copper–PDMS composite as afunction of the copper to PDMS weight ratio.

piezosensitivity is defined as the fractional change in electricalresistance due to an applied pressure [31]:

Sp =dR

R

1dP=

d ln R

dP(4)

where R is the resistance and P the pressure. Forour composites the piezosensitivity was calculated to be0.0109 kPa−1 for the 250 phr sample, 0.0061 kPa−1 for the200 phr sample and 0.0037 kPa−1 for the 150 phr sample.These values are in line with the piezoresistive compositemade with PDMS or epoxy resin using nickel particles asfiller [31, 32].

The strain sensitivity of a material is indicated by thegauge factor (GF), which is the ratio of relative change inelectrical resistance to the applied strain ε [22]:

GF =1R

dR

dε. (5)

The gauge factor values calculated for the 250 phr, the 200 phrand the 150 phr samples are 48, 42 and 27, respectively.These gauge factors are higher than the values found forpolymer composites prepared with zinc particles or othercopper particles (∼30 or lower) [22, 23], but lower thanthose found for nickel based composites (∼200) [23, 31],where the metal content is higher. Obviously the correlationbetween piezosensitivity and GF is the elastic modulus of thefunctional material, hence a composite with a low gauge factorcould have a high piezosensitivity, which is more interestingfor fabricating a tactile sensor array.

The shape and size of the copper–PDMS compositesheet are other fundamental parameters able to affect thepiezosensitivity of the sensor. Figure 4 reports the functionalresponses of 10 mm × 10 mm copper–PDMS compositesamples fabricated with 200 and 250 phr compositionswith different thicknesses (0.5, 1 and 2 mm). A highlynonlinear relationship between the electrical resistance andthickness can be noticed. The value of resistance in theundeformed state is again very high for all the specimens,

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Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

Figure 4. Piezoresistive response of copper–PDMS as a function of the thickness for composites with (a) 200 phr and (b) 250 phrcomposition.

while under compression the pressure sensitivity is muchhigher for thinner samples, especially in the 250 phr, 0.5 mmthick sample, where the electrical resistance of the materialbecomes lower than the contact value before reaching 2 MPaof applied pressure.

A fatigue characterization was also performed on the250 phr sample, the stiffer among the various composites. Thepiezoresistive sample was subjected to 104 bending cycleswith a 2 mm of radius of curvature of the fold. No significantvariations of the piezoresistive response were observed afterthe test, thus revealing a high fatigue performance.

4. Matrix tactile sensor

4.1. Sensor design and fabrication

For the fabrication of the pressure sensor, metal electrodeswere deposited by the radio frequency magnetron sputteringtechnique on both the sides of a composite sample withan area of 40 mm × 40 mm and a thickness of 1 mm.Electrodes were patterned in the shape of 2 mm-wideparallel strips, eight on each side, in such a way that theyideally perpendicularly crossed the strips deposited on theopposite sample side, thus creating an 8 × 8 matrix ofnodes. Each strip consisted of a first layer of titanium(∼20 nm), working as adhesion layer, and a film of gold(∼200 nm). The electrodes were characterized by a goodadhesion to the surface of the composite, and preserved theirconductivity even after several stretching and compressivedeformations. Each electrode was connected to an equivalentpattern, fabricated on Cu-metallized polyimide, by means ofa conductive silver paste. Finally the sensor was passivatedwith a few micrometres thick layer of pure PDMS (10:1base–curing agent ratio by weight) by the spinning technique.

A customized electronic circuit was fabricated on aprinted circuit board (PCB) to monitor the resistance valueof each node of the sensor matrix (figure 5) and the acquireddata for the processing step were sent to a PC, thus providingthe intensity and spatial distribution of the pressure througha graphical software. The main parameters of the wholeread-out circuit are summarized in table 2.

Figure 5. Image of the sensor connected to the dedicated electronicboard.

Table 2. Parameters of the read-out system.

Parameter Value

Number of nodes 8 × 8 = 64Node scan rate 2 kHzMatrix scan rate 31.25 HzNumber of bits of the ADC 12Voltage input to the node 1 VCurrent range of the trans-impedancelogarithmic amplifier

100 pA to10 mA

Nodes of the software grid 34× 34 = 1156

The system evaluates the resistance of each node byapplying a fixed voltage to the element and measuringthe value of the current flowing through it. Each nodeinvestigation is performed at a frequency of 2 kHz, so thatthe whole matrix, composed of 64 elements is measured at afrequency of around 30 Hz, providing a real-time responseand visualization. Each of the 64 nodes is investigated byapplying a fixed voltage of 1 V to the corresponding rowand by measuring the flowing current which is collectedfrom its corresponding column; two analog multiplexers(controlled by the microcontroller) are employed to connectthe measuring circuit to the desired row and column of

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Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

Figure 6. Basic schematic of the sensor dedicated electronic board.

the matrix. The multiplexers were chosen to ensure thattheir leakage current remains negligible with respect to theminimum current expected when no pressure is applied on thesensing material.

One of the most challenging requirements of thecircuit is represented by the combination of the rather highmeasurement rate and the tremendously wide range of thematerial resistance, which can easily span from 100 � to10 G�. In the designed circuit, this issue is tackled bymeans of a trans-impedance logarithmic amplifier whichconverts the flowing current back into a voltage that can bedirectly acquired by a low-cost microcontroller without loss insensitivity. The converter can handle a current range of eightdecades, from 100 pA to 10 mA. This strategy, resorting to apreliminary log compression, permits one to sweep the wholerange without gain control and adjustment of the transducerstage.

Then the resulting voltage is sampled by a 12 bit analogto digital converter (ADC), embedded in the microcontrollerand sent to the PC for conversion into pressure values andvisualization. A basic schematic of the whole system ispresented in figure 6.

A specifically designed computer program was preparedto permit the real-time analysis of the applied pressure. Theprogram receives the voltage signal, converts it into pressurevalues, using a calibration law experimentally determined,and saves the measurements of the 8 × 8 matrix. A 3Drepresentation depicts the spatial planar distribution of theapplied pressure, by changing the heights of the nodes, placedon a horizontal grid, corresponding to the sensor matrixelements. The grid size is increased to 34 × 34 to returna visually clear representation of the sensor matrix, withsmooth transactions between adjacent nodes. The larger gridis constructed by inserting new empty elements into themeasurement matrix and by convolving the result with theinterpolating matrix shown in table 3. Some of the elementsof the new grid are in common between two sensing elements.

4.2. Sensor characterization

The flexibility and quality of the electrodes of the sensor weretested by bending the sensing composite sheet at different

Figure 7. Images of the sensing composite sheet with sputteredelectrodes bent at different radii of curvature.

Table 3. Interpolating matrix for the enlargement of the softwaregrid.

0.1 0.1 0.2 0.2 0.1 0.10.1 0.7 0.8 0.8 0.7 0.10.2 0.8 1 1 0.8 0.20.2 0.8 1 1 0.8 0.20.1 0.7 0.8 0.8 0.7 0.10.1 0.1 0.2 0.2 0.1 0.1

radii of curvature between 6 mm and 1 mm, as shown infigure 7. The tested composite was the 250 phr sample, thestiffer among the three compositions, because of the highermetal content. The samples were bent 100 times and everytime they returned to their original shape without showing anydefects induced by the test. After the test, the conductivity ofthe electrodes was measured to be the same as before bendingand FESEM images confirm that no important structuralcracks were created.

The resistance to overload of the sensor matrix wasevaluated by submitting the sensing device up to 10 MPa.The test was carried out by the set-up described in theexperimental methods. After the release of compressive loadthe sample show no permanent deformation and an unvariedpiezoresistive response.

The repeatability of the sensor was tested by measuringthe voltage output of the electronic board during twentyapplications of compressive pressure up to 2 MPa withthe mechanical testing machine. The average sensor noderesponse with the measurement error is reported in figure 8. Itis noteworthy that the percentage measurement error is alwaysbelow 5%, and even below 2% after 0.9 MPa of appliedpressure. The sensitivity of the sensor is not constant in theentire 2 MPa range, but decreases with increasing appliedpressure. In order to express a sensitivity value S, the whole

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Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

Figure 8. Sensor output voltage under the application of acompressive pressure profile up to 2 MPa. The sensor response andthe error bars were calculated with an evaluation over 20 differentmeasurements on the same matrix node. On the graph are reportedthe sensor sensitivity in the three different pressure ranges.

pressure range was divided into three different sections andan average value was computed for each section using thefollowing formula:

Sx =dVout

Vout

1dP

(6)

where Vout is the sensor output voltage. Between 0 and0.25 MPa the sensor sensitivity is 8.77 MPa−1, whileit decreases considerably between 0.25 and 0.85 MPa to2.21 MPa−1, and even more in the range up to 2 MPa,reaching a value of 0.63 MPa−1.

Similarly the reproducibility of the sensor matrix wastested by applying the same compressive pressure profile (upto 2 MPa) to all the 64 nodes of the matrix separately. Theresponse of the functional nodes is highly reproducible, with apercentage error below 7.5%, and even below 5% after 1 MPaof applied pressure.

The sensor output is later sent to the tactile imagingsoftware which elaborates the data, converting it in a pressurevalue and graphically showing the pressure distribution on thematrix. An example is reported in figure 9 with a screenshotof the software during a measurement session showing, with achange in colour and shape, the pressure applied to the nodesof the matrix.

5. Conclusion

We have reported a simple, fast and economic route forthe preparation of a mechanical flexible piezoresistive sensorbased on an innovative metal filler–polymer matrix compositefor robotic tactile applications. The electrical resistance ofthe composite is found to be highly sensitive to compressivepressure, with variations by up to eight orders of magnitude.Moreover, the developed sensor shows an extraordinaryresistance to overload and a high endurance limit to flexuralcyclic tests. A tactile sensor device, including read-out

Figure 9. Screenshot of the computer program during ameasurement session showing the applied pressure distribution.

electronics and software for 3D representations of pressuredistribution, was indeed prepared and tested, showing thatspiky copper particles can be used, here for the first time, forsuch purposes. Moreover, the possibility to tailor the pressuresensitivity, by controlling the composition and thickness of thefunctional material, makes these composites good candidatesas sensitive elements for a wide range of applications, notonly as robotic tactile sensors. Since the composite is basedon a viscoelastic polymer, future works for tactile sensorimprovements will be focused on compensation and reductionof the hysteretic behaviour of the functional material.

References

[1] Lumelsky V J, Shur M S and Wagner S 2001 Sensitive skinIEEE Sensors J. 1 41–50

[2] Dahiya R S and Valle M 2013 Robotic Tactile Sensing(Netherlands: Springer)

[3] Galvez J A, De Santos P G and Pfeiffer F 2001 Intrinsic tactilesensing for the optimization of force distribution in a pipecrawling robot IEEE/ASME Trans. Mechatronics 6 26–35

[4] De Maria G, Natale C and Pirozzi S 2012 Force/tactile sensorfor robotic applications Sensors Actuators A 175 60–72

[5] Mittendorfer P and Cheng G 2011 Humanoid multimodaltactile-sensing modules IEEE Trans. Robot. 27 401–10

[6] Najarian S, Dargahi J and Mehrizi A A 2009 Artificial TactileSensing in Biomedical Engineering (New York:McGraw-Hill Biophotonics)

[7] Schmitz A, Maiolino P, Maggiali M, Natale L, Cannata G andMetta G 2011 Methods and technologies for theimplementation of large-scale robot tactile sensors IEEETrans. Robot. 27 389–400

[8] Yousef H, Boukallel M and Althoefer K 2011 Tactile sensingfor dexterous in-hand manipulation in robotics—a reviewSensors Actuators A 167 171–87

[9] Kim K, Lee K R, Lee D S, Cho N K, Kim W H, Park K B,Park H D, Kim Y K, Park Y K and Kim J H 2006A silicon-based flexible tactile sensor for ubiquitous robotcompanion applications J. Phys.: Conf. Ser. 34 399–403

[10] Harsaanyi G 2000 Polymer films in sensor applications:a review of present uses and future possibilities Sensor Rev.20 98–105

[11] Jonathan E, Jack C and Chang L 2003 Development ofpolyimide flexible tactile sensor skin J. Micromech.Microeng. 13 359

8

Smart Mater. Struct. 22 (2013) 125039 S Stassi et al

[12] Yang Y J, Cheng M Y, Chang W Y, Tsao L C, Yang S A,Shih W P, Chang F Y, Chang S H and Fan K C 2008 Anintegrated flexible temperature and tactile sensing arrayusing PI-copper films Sensors Actuators A 143 143–53

[13] Nambiar S and Yeow J T W 2011 Conductive polymer-basedsensors for biomedical applications Biosens. Bioelectron.26 1825–32

[14] Someya T and Sekitani T 2009 Printed skin-like large-areaflexible sensors and actuators Procedia Chem. 1 9–12

[15] Ming-Yuan C, Chan-Mo T and Yao-Joe Y 2010An anthropomorphic robotic skin using highly twistabletactile sensing array The 5th IEEE Conf. on IndustrialElectronics and Applications (ICIEA) 2010 pp 650–5

[16] Mamunya Y P, Zois H, Apekis L and Lebedev E V 2004Influence of pressure on the electrical conductivity of metalpowders used as fillers in polymer composites PowderTechnol. 140 49–55

[17] Stassi S, Cauda V, Canavese G, Manfredi D and Pirri C F2012 Synthesis and characterization of gold nanostars asfiller of tunneling conductive polymer composites Eur. J.Inorg. Chem. 16 2669–73

[18] Stassi S and Canavese G 2012 Spiky nanostructured metalparticles as filler of polymeric composites showing tunableelectrical conductivity J. Polym. Sci. B 50 984–92

[19] Bloor D, Donnelly K, Hands P J, Laughlin P and Lussey D2005 A metal–polymer composite with unusual propertiesJ. Phys. D: Appl. Phys. 38 2851–60

[20] Canavese G, Stassi S, Stralla M, Bignardi C and Pirri C F 2012Stretchable and conformable metal–polymer piezoresistivehybrid system Sensors Actuators A 186 191–7

[21] Bloor D, Graham A, Williams E J, Laughlin P J and Lussey D2006 Metal–polymer composite with nanostructured fillerparticles and amplified physical properties Appl. Phys. Lett.88 102103

[22] Abyaneh M K and Kulkarni S K 2008 Giant piezoresistiveresponse in zinc–polydimethylsiloxane composites underuniaxial pressure J. Phys. D: Appl. Phys. 41 135405

[23] Abyaneh M K, Ekar S and Kulkarni S K 2012 Piezoresistivityand mechanical behavior of metal–polymer compositesunder uniaxial pressure J. Mater. Sci. Res. 1 50–8

[24] Beek L K H and Van Pul B I C F 1962 Internal field emissionin carbon black-loaded natural rubber vulcanizates J. Appl.Polym. Sci. 6 651–5

[25] Strumpler R and Glatz-Reichenbach J 1999 Conductingpolymer composites J. Electroceram. 3 329–46

[26] Lantada A D, Lafont P, Sanz J L M, Munoz-Guijosa J M andOtero J E 2010 Quantum tunnelling composites:characterisation and modelling to promote theirapplications as sensors Sensors Actuators A 164 46–57

[27] Eisberg R and Resnick R 1985 Quantum Physics of Atoms,Molecules, Solids, Nuclei and Particles 2nd edn (New York:Wiley)

[28] Quaglio M, Canavese G, Giuri E, Marasso S L, Perrone D,Cocuzza M and Pirri C F 2008 Evaluation of differentPDMS interconnection solutions for silicon, Pyrex andCOC microfluidic chips J. Micromech. Microeng.18 055012

[29] Fu S-Y, Feng X-Q, Lauke B and Mai Y-W 2008 Effects ofparticle size, particle/matrix interface adhesion and particleloading on mechanical properties of particulate–polymercomposites Composites B 39 933–61

[30] Canavese G, Lombardi M, Stassi S and Pirri C F 2012Comprehensive characterization of large piezoresistivevariation of Ni–PDMS composites Appl. Mech. Mater.110–116 1336–44

[31] Chang F G, Yang F, Wang S X, Zhang N and Song G L 2009Enhanced piezoresistivity in Ni–silicone rubber compositesChin. Phys. B 18 652–7

[32] Martin J E, Anderson R A, Odinek J, Adolf D andWilliamson J 2003 Controlling percolation infield-structured particle composites: observations of giantthermoresistance, piezoresistance, and chemiresistancePhys. Rev. B 67 942071

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