Coupled carbon nanotube network and acoustic emission monitoring for sensing of damage development in composites

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Coupled carbon nanotube network and acoustic emission monitoring for sensing of damage development in composites Limin Gaoa,b, Erik T. Thostensona, Zuoguang Zhangb, Tsu-Wei Choua,* a

Department of Mechanical Engineering, Center for Composite Materials, University of Delaware, 126 Spencer Laboratory, Newark, DE 19716, USA b School of Materials Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China

A R T I C L E I N F O

A B S T R A C T

Article history:

Material and structural reliability is crucial for the potential use of composite materials in a

Received 14 November 2008

variety of structural applications. As a result, damage detection and health monitoring of

Accepted 20 January 2009

fiber-reinforced composites are attracting progressively more attention in the field of mate-

Available online 29 January 2009

rials research. In this work, small amounts of carbon nanotubes are added into traditional fiber composites to form electrically conductive networks throughout the polymer matrix. The electrical response of the carbon nanotube network to accumulated damage combined with the acoustic emission (AE) technique is utilized to sense damage initiation and evolution in laminated composites. The parameters which correspond to the resistance change of the specimen due to damage in quasi-static and cyclic tests are used to evaluate the damage state in the material. There exists a bi-linear relationship between the resistance change and AE signal cumulative counts which gives insight toward the damage state of the material during quasi-static and cyclic tests. Ó 2009 Elsevier Ltd. All rights reserved.

1.

Introduction

Fiber-reinforced polymer composites are now widely used in aircraft and other industries due to their high specific strength and modulus [1]. During their service life, many structural components require inspection and evaluation to detect damage that may lead to failure, and the development of techniques for damage detection and structural health monitoring of composites is crucial to expanding their applications. In composite materials, damage initiates in the polymer matrix in the form of microcracks or delaminations. Because of the micro-scale nature of damage in composites, many non-destructive techniques are unable to detect the initiation and accumulation of microcracks. Improved understanding of the damage mechanisms in composite materials is essential for enhanced methodologies for life prediction and also the development of in-service damage monitoring techniques.

For carbon–fiber-reinforced composites, electrical resistance measurements have been investigated as a nondestructive means of damage monitoring. Due to their inherent electrical conductivity, breakage of the load-carrying carbon fibers results in changes in the composite electrical conductivity [2–9]. The electrical response of carbon–fiberreinforced composites is dominated by fiber breakage and is less sensitive to the onset of matrix damage, where damage is first initiated. With the development of carbon nanotubes, which have dimensions that are three orders of magnitude smaller than traditional advanced fibers, the electrical resistance measurements can be extended to sense damage in the nonconductive polymer matrix. Carbon nanotubes, which have exceptionally high current carrying capacity [10–12], are able to form electrically conductive networks in polymers at very low volume contents [13]. Because of the small scale of carbon nanotubes relative to that of the reinforcing fibers,

* Corresponding author: Fax: +1 302 831 3619. E-mail address: [email protected] (T.-W. Chou). 0008-6223/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.carbon.2009.01.030

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carbon nanotubes are able to form electrically conductive networks surrounding the fibers and penetrating into the matrixrich interlaminar regions. This conductive network enables monitoring of matrix-dominated damage initiation and accumulation [13–17]. Thostenson and Chou [14] subsequently established that the damaged resistance parameter DRD/L (X/cm) can be utilized as a quantitative measure of damage and accounts for the re-opening of existing cracks and is defined as the damaged resistance change per length; it is obtained from a curve fit of the resistance–strain curve corresponding to elastic deformation without additional damage. Furthermore, crack opening and closing during cyclic testing provides insight on the extent of damage [17]. Acoustic emission (AE) is an efficient and non-destructive testing (NDT) technique to detect damage in materials and it has been widely utilized in materials research and application for decades. A unique characteristic of the AE technique is that it detects acoustic activity within the material in realtime; while many other NDT methods attempt to image the internal damage after it occurs [18]. When materials experience damage-related structural changes, such as the formation of cracks, the release of energy generates transient elastic waves that can be detected with surface-mounted sensors [19]. The AE technique has been utilized to monitor defect formation and development in composite materials [20– 22]. Recently new AE parameters and analysis methodologies have been introduced to explain the events within the material. AE frequency-based methodologies were investigated for damage evolution analysis where frequency bands correspond to distinct damage modes [23]. Some researchers have analyzed the wave propagating modes of acoustic emission [24] and associated the AE wave signal with specific damage mechanisms. While there have been many efforts to develop AE methodologies that are able to elucidate failure modes based on specific acoustic emissions, interpretation of the AE response is still largely qualitative. We have established in our earlier research that damaged resistance change can be used as a quantitative parameter to assess the accumulated damage since the damaged resistance change per unit specimen length increases linearly with increasing crack density [17]. In this work, we utilize both carbon nanotubes as an in situ electrical sensing network and AE for real-time detection of damage in glass–fiber-reinforced composites. Multi-walled carbon nanotubes were dispersed in a vinyl ester resin at a concentration of 0.5 wt% and cross-ply composites were fabricated using a vacuum-assisted resin transfer molding (VARTM) technique. Static and cyclic tests were performed to monitor the damage initiation and accumulation in the laminates. Damaged resistance change and AE counts are correlated to improve the understanding of damage mechanisms by comparing resistance change and AE signal in the composites.

2.

Experimental

Cross-ply E-glass/vinyl ester [0/90]2 composite laminates with nanotubes dispersed throughout the polymer matrix were produced by first dispersing the carbon nanotubes in vinyl ester followed by drawing the mixture through the preform

using a vacuum-assisted resin transfer molding (VARTM) technique. After processing the composites were machined into tensile test specimens for electrical and acoustic emission sensing.

2.1. Processing compo-sites

of

carbon

nanotube/fiber

hybrid

Vinyl ester monomer was synthesized by reacting stoichiometric amounts of a commercially available bisphenol-f epichlorohydrin epoxy resin (EPON 862, Hexion Specialty Chemicals, Inc.) with methacrylic acid (99% purity, Sigma–Aldrich), as described in Ref. [25]. The catalysts are triphenyl phosphine (99% purity, Sigma–Aldrich) and triphenyl antimony (99% purity, Sigma–Aldrich). Following synthesis of the vinyl ester monomer, CVD-grown multiwall carbon nanotubes (ILJIN Nanotech, Korea), with nanotube diameters in the range of 15–25 nm and purity higher than 95% were dispersed into vinyl ester monomer using a three-roll-mill calendering technique described previously [26]. Then, 40 wt% styrene (Fina Oil and Chemical Co.) was added to the vinyl ester monomer and mixed thoroughly. After processing in the three roll mill and the addition of styrene, the dispersion was de-gassed under vacuum at room temperature. Cross-ply [0/90]2 composite laminates were manufactured using VARTM technique. The nanotube/fiber hybrid composites were fabricated by first adding cobalt naphthenate accelerator (0.2%; Aldrich) and cumene hydroperoxide initiator (1%; Trigonox 239a, Akzo-Nobel) to the nanotube dispersed resin and then drawing the vinyl ester/nanotube dispersion through unidirectional sheets of E-glass fibers under vacuum. After infusion, the composite was cured at room temperature and then post-cured at 165 °C for two hours. As demonstrated in our previous research [14], electron microscopy shows that nanotubes fully penetrate the fiber bundles and form an electrically conductive network throughout the polymer matrix.

2.2. Coupled mechanical/electrical/acoustic characterization Non-conductive end tabs were bonded to the cured composite laminates and specimens were obtained by cutting the laminate into strips with a width of 12.7 mm (0.5 in.). Electrodes were placed directly on the ends of specimens by anchoring a copper lead-wire to the end tab and then applying conductive silver paint (Structure Probe, Inc.) across the cross-section of the specimen. One edge of each specimen was polished for conducting edge replication and microscopy examination. Mechanical tests were performed using a screw-driven load frame (Instron 5567) at a fixed displacement rate of 1.27 mm/min (0.05 in./min). For quasi-static tests, the specimens were loaded until failure. For cyclic loading, the specimens were loaded and unloaded at the same rate with progressively increasing peak values of cyclic load with step value of 444 N (100 lbs) until failure. During each cycle the specimens was held under load for 6 min in order to take a replica of the specimen edge for later microscopic imaging. The replica was obtained by applying acetone to the side of the specimen and then applying acetate replica tape (Ted Pel-

3.1.

Results and discussion Quasi-static test

Fig. 1 shows the resistance–strain and cumulative acoustic emission-strain graphs for a specimen loaded in tension to approximately 1.4% strain. During initial loading of the undamaged specimen it can be seen that the trends in the resistance response and cumulative acoustic emission are very similar, where changes in specimen resistance correspond directly with the accumulation of acoustic events. Both techniques provide real-time information on the accumulation of damage within the specimen. Upon unloading some cracks in the 90° plies are closed and create electrical contact since the stiff 0° plies continue to behave elastically, as described in Ref. [17]. During subsequent re-loading of a damaged specimen, the resistance–strain and acoustic emission-strain behavior are substantially different. In addition to a permanent resistance change due to damage in the specimen, there is nonlinearity in the resistance–strain curve. The increase in slope during re-loading of the specimen is a consequence of cracks re-opening at small strains and is followed by a linear region corresponding to elastic deformation without further damage accumulation. Both the permanent resistance change and the nonlinearity of the resistance–strain curve indicate the presence of permanent damage in the specimen. Thostenson and Chou [14] utilized the nonlinear re-loading curve to define the ‘‘damaged resistance’’ parameter, DRD/L, which is obtained from the yintercept of a linear curve fit of the elastic portion of the reloading curve. It has been demonstrated recently that the damaged resistance is a quantitative measure of the accumulated damage and can be utilized to detect transitions between transverse cracking and delamination [17]. While acoustic emission is a valuable tool for monitoring the occurrence of damage, the acoustic emission data is acquired only when new damage is accumulated upon re-load-

a

ΔR/L (Ω/cm)

la, Inc.) along the side of the specimen. After drying, the replica tape was removed from the specimen and mounted on a glass slide. A Keithley 6430 voltage–current meter was used to measure the resistance of the specimens by sourcing a constant voltage of 20 V and measuring the resulting current. Resistive strain gages (Vishay Micro-Measurements) were mounted on the surface of the specimens for strain measurement. Simultaneous resistance, strain and load measurements were integrated in a data acquisition program written in LabView. A two-channel acoustic emission system (Physical Acoustics, Princeton Junction, NJ) was used to record acoustic events throughout the test. A transducer (35–100 KHz, Physical Acoustic Corporation) with 100 KHz–1 MHz analog filter was mounted on the surface of the specimens using a hotmelt adhesive. Because extraneous background noise can be recorded by the acoustic sensors, a threshold of 45 dB was utilized to filter-out noise that is not related to the formation of damage in the specimen. The pencil lead break test was performed [27] prior to applying load in order to confirm the reproducibility of the AE system.

3.

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Elastic Deformation Crack Reopening

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Loading 5000

ΔRE/L 0 0

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Fig. 1 – (a) Resistance–strain loading and re-loading behavior highlighting the resistance change is a state function and (b) AE (cumulative counts)–strain loading and re-loading behavior showing the process-dependence of AE.

ing. The electrical resistance change of the carbon nanotube network provides information on both existing damage and the accumulation of new damage. This is because the mechanisms of resistance change and AE for damage detection in materials are different. The resistance change with the applied load is due to structural changes of the electrical network. In addition to changes in resistance due to straining of the network, the presence of cracks causes portions of the electrical network to open and close with the applied load. The resistance change, DR/L, depends on the damage state of the material and not on the loading process or history. For AE, the energy release and the associated generation of elastic wave due to the damage during tests give rise to the AE signal. Only if there is enough energy released in the material and AE is recorded during the loading period can AE signal is detected. There is almost no detectable signal of AE at the beginning of re-loading, known as the Kaiser effect [28]. This is because no new damage is generated during the crack reopening and elastic deformation stage. Thus, the key result

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350

1.6x10 Stress (MPa) ΔR/L- Δ R /L ( Ω/cm)

300

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150 100

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250

4

2000 50

2x10

0.5

1

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0

0 2.5

0 0

4

2

Strain (%) Fig. 2 – Stress, AE (counts) and resistance change response to strain showing damage initiation, accumulation and delamination until failure during a quasi-static test.

1.2x10

1x10

E

ΔR/L-ΔR /L (Ω/cm)

is that the electrical resistance measurement provides information about the state of damage in the specimen that is independent of prior measurements other than the initial resistance. For AE to be utilized to detect the accumulation of damage continuous monitoring and data acquisition is required. From Fig. 1, we also can see the resistance change per unit length due to elastic deformation (DRE/L), which is obtained from the slope of the initial linear portion of the resistance–strain curve upon re-loading. Fig. 2 shows the typical resistance change and acoustic emission response with applied deformation for the crossply composite specimens during a quasi-static test until failure. Carbon nanotube-based composites are known to be piezoresistive [14] and at small strains the resistance–strain behavior, presented in terms of resistance change per unit length in the gage area of the specimen and shown in Fig. 1, is linear. The resistance response in Fig. 2 is expressed as the resistance change per unit length (DR/L) of specimen during testing minus the resistance change per unit length due to elastic deformation (DRE/L). The resistance change due to elastic deformation is reversible with applied strain and DR/L DRE/L corresponds to the resistance change of the specimen due to damage. Therefore, DR/L DRE/L  DRD/L in Figs. 2 and 3. In these initial stages of loading, there are very few AE signals which may correspond to the formation of incipient damage. As damage is accumulated in the polymer matrix conducting paths in the composite are severed, resulting in increased specimen resistance and deviation from the initial linear resistance–strain response. With increasing load, transverse cracks form in the 90° plies and are responsible for jumps in the resistance change curve and the deviation from the linear piezoresistive behavior. In this stage there is also substantial AE activity, where the magnitude and frequency of AE signals are increased over the previous stage. The linear increase of DR/L DRE/L exhibits the stable transverse crack accumulation and the number of transverse cracks increases progressively with increasing deformation until saturation.

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AE (Cumulative Counts)

Fig. 3 – The relationship between resistance change and AE (cumulative counts).

The transverse cracks terminate at the interface between the 90° and 0° plies. With the increasing load, the stress concentrations at the crack tips initiate delamination between 0° and 90° ply interfaces and fiber breakage in 0° plies. Delamination and fiber breakage which generate both transient elastic waves (AE signals) and further breaks-up the percolating electrical network of nanotubes are responsible for the large number of AE signals and large jumps in specimen resistance. The relation between resistance response and AE cumulative counts can be seen in Fig. 3. At the beginning of the test, the flaws and microcracks begin to cut the electrical network so the resistance increases, but released energy from these flaws and microcracks are small and less detectable. As the applied load increases, the transverse cracks are formed progressively. These transverse cracks which are related to higher energy released AE signals break the path of electrical

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current. The following linear relationship of resistance change and AE counts indicates that damaged resistance can identify the material damage state quantitatively. At the end of the test, delamination and fiber breakage occur, both of which generate strong transient elastic waves. There is more cumulative AE count increase than resistance change and the slope of the curve changes during this time. That is because resistance change is more sensitive to early stage matrix-dominated cracks which introduce breaks to electrical network and AE is more sensitive to energy release in terms of fiber breakage and delamination. Real-time monitoring of both accumulated acoustic emission and resistance data may provide information on the transition of damage from matrix cracking to delamination and fiber breakage.

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Incremental cyclic loading

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Time (min) It has been demonstrated that cyclic loading and the subsequent opening and closing of cracks can provide insight on material behavior and result of measurement of damage accumulation. Fig. 4 shows the typical transient resistance change and accumulated acoustic emission counts of a cross-ply composite undergoing cyclic loading with progressively increasing peak load, and the inset of Fig. 4 shows the stress–strain behavior under cyclic loading. It is clear that in each subsequent cycle after damage is initiated there is a permanent resistance change in the unloaded state and also a larger resistance change upon re-loading due to cracks reopening. When the applied load is increased beyond the previous maximum the AE counts corresponding to damage accumulation are measured. Fig. 5 shows the transient AE counts, AE cumulative counts and DR/L behavior in a typical load/unload cycle. The resistance increases and decreases with applied load instantaneously. As observed previously in the resistance–strain data (Fig. 1a), at the beginning of the loading cycle the re-opening of previously closed cracks accompanied by elastic straining of the network accounts for the initial increased slope of the resistance response and the following liner portion of the curve is due only to elastic

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deformation of the material and straining of the carbon nanotube network. Subsequently, there are large resistance increases due to the formation of new cracks accompanied by a sudden jump of cumulative AE counts when new damage occurs in the material. The utilization of both techniques simultaneously provides valuable information on the damage state as well as the accumulation of new damage. Crack reopening, elastic deformation and new damage accumulation can easily be observed from the resistance curve; however, AE is only sensitive to the new damage in the material. Fig. 6 shows (a) accumulated AE counts and (b) electrical resistance change as a function of strain for the [0/90]s laminates during the incremental cyclic loading. From the third cycle onward permanent resistance changes of the specimen appear at low strain and cracks re-opening and closing during the load/unload cycle are observed, resulting in nonlinearity.

AE (Cumulative Counts)

2x10

Fig. 4 – AE (cumulative counts) and resistance response showing permanent damage increase and damage accumulation during a cyclic loading test. Inset: corresponding stress–strain behavior of [0/90]2 specimen.

500

0

Time (min) Fig. 5 – AE (counts and cumulative counts) and resistance behavior showing crack re-opening, elastic deformation and new damage accumulation in a typical cycle.

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Fig. 7 – The relationship of AE (cumulative counts) and damage resistance change per length. Inset: damaged resistance change per length-strain behavior for a cyclic test showing microcracking, transverse crack and delamination stage.

Δ R/L (Ω/cm)

4x104

3x104

2x104

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0 0

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Strain (%)

Fig. 6 – (a) AE (cumulative counts) behavior for cyclic test of [0/90]2 specimen and (b) corresponding resistance change per length behavior.

Elastic deformation and new damage propagation can be observed in the resistance response, as described in Fig. 1a. In the region of the loading curve corresponding to elastic deformation without crack re-opening or additional damage accumulation the slope of the resistance–strain curve is nearly the same for each cycle. There is no detectable AE signal during the re-opening and closing of cracks. When the applied load is increased beyond the previous peak load, there is an obvious increase in AE counts. There is a strong correlation between the AE counts and resistance at the peak strain of each cycle. As established in our earlier research, DRD/L (X/cm) can be utilized a quantitative measure of the extent of damage in specimens. The relationship between DRD/L (X/cm) and strain is shown in Fig. 7 (inset). The resistance–strain graph can be clearly divided into the three damage stages [17] and these damage states are verified from microscopy of edge replicas taken from the specimen. From the third cycle, the damaged resistance increases linearly with strain indicating the accumulation of transverse cracks with increased strain. At the point where delamination is initiated there is a significant increase in specimen resistance with additional strain. The

relationship of DRD/L and acoustic emission of [0/90]s during cyclic test is given in Fig. 7 which shows a bi-linear relationship between damaged resistance and accumulated acoustic emission, similar to that observed in Fig. 3. There exists an initial linear increase in resistance with the progressive accumulation of transverse microcracks followed by a second stage of liner relationship due to sharp increase in AE which is the initiation and progression of delamination at the ply interfaces. The linear increase in damaged resistance with accumulated acoustic emission counts at the initial stage of the test reflects the sensitivity of electrical resistance measurements to matrix related damage and accumulation of transverse cracks. Electrical resistance measurements and AE both can detect the stable accumulation of transverse cracks in material and thus the DRD/L increases with cumulative AE counts linearly. The second stage of AE counts near the end of the test is a consequence of fiber breakage and delamination. Micrographs of edge replicas taken at points (A) and (B) labeled in Fig. 7 are shown in Fig. 8a and b, respectively. In Fig. 8a the micrograph clearly shows the formation of transverse cracks in the 90° plies and is near the point at which the cracks are uniformly spaced, indicating saturation. Fig. 8b clearly shows the presence of delamination at the ply interfaces and corresponds directly with the transitions observed in Fig. 7.

Fig. 8 – Micrograph shows (a) the transverse crack saturation and (b) delamination.

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Conclusions

Sensing and monitoring of damage initiation and accumulation in composite materials has attracted recent interest since fiber reinforced composites are being used more commonly in primary structural applications. Adding a small account of carbon nanotubes to form an electrically percolating network in non-conductive fiber reinforced polymer composites is an effective way to sense damage development. By measuring the electrical resistance changes in the carbon nanotube network it is possible to identify damage in situ during quasi-static and cyclic testing in composite materials. The parameters DR/L DRE/L and DRD/L, which correspond to the resistance change of the specimen due to damage in quasistatic and cyclic tests, are used to evaluate the damage state in the material. By comparing resistance and AE it is possible to monitor the onset and propagation of damage in composite material. The carbon nanotube network is sensitive to matrix-dominated damage mechanisms such as microcracking and transverse cracking in fiber composite while AE is more sensitive to energy release as delamination and fiber breaking. The resistance change and AE counts show a bi-linear relation in detecting damage in quasi-static and cyclic tests which give additional insight toward the damage evolution. Resistance change is a function of damage extent and state in the material and non loading history dependence. Thus, carbon nanotube networks show potential to determine the damage state and extent without knowing the loading history of the material.

Acknowledgements This work is funded by the US Air Force Office of Scientific Research (FA9550-06-1-0489) Dr. Byung-Lip Lee, Program Director and the US Office of Naval Research (N00014-07-1-0345) Dr. Yapa Rajapakse, Program Director. Limin Gao’s study abroad at the University of Delaware is supported by the State Scholarship Fund of the China Scholarship Council.

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