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1. Introduction
Novel materials and processing routes provide opportunities for the production of advanced high performance structures for different applications. Ceramic matrix composites are one of these promising materials. Engineering ceramics such as Al2O3, Si3N4, SiC and ZrO2 produced by conventional manufacturing technology have high stiffness, excellent thermostability and relatively low density, but extreme brittle nature restricted them from many structural applications (Mukerji, 1993). Considerable attention has been adopted to improve the fracture toughness. An approach has been paid to the development of nanocrystalline ceramics with improved fracture properties. Decreasing the grain size of ceramics to the sub- and nano-meter scale leads to a marked increase in fracture strength (Miyahara et al., 1994). However, fracture toughness of nanocrystalline ceramics generally displays modest improvement or even deterioration (Miyahara et al., 1994; Rice, 1996; Yao et al., 2011). As one possible approach, incorporation of particulates, flakes and short/long fibers into ceramics matrix, as a second phase, to produce tougher ceramic materials is an eminent practice for decades (Evans, 1990). Recently, researchers have focused on the carbon nanomaterials, in particular carbon nanotubes (CNTs), which are nanometer-sized tubes of single- (SWCNTs) or multi- layer graphene (MWCNTs) with outstanding mechanical, chemical and electrical properties (Dai et al., 1996; Ebbesen et al., 1996; Treacy et al., 1996; Huang et al., 2006; Peng et al., 2008), motivating their use in ceramic composite materials as a fibrous reinforcing agent.
It is well recognized that some difficulties appear to be the major cause for the limited improvement in CNT/ceramic composites prepared to date. The first is the inhomogeneous dispersion of CNTs in the ceramic matrix. Pristine CNTs are well known for poor solubilization, which leads to phase segregation in the composite owing to the van der Waals attractive force (Chen et al., 1998). Such clustering produces a negative effect on the physical and mechanical properties of the resultant composites (Yamamoto et al., 2008). The second is the difficulty in controlling connectivity between CNTs and the ceramics matrix, which leads to a limited stress transfer capability from the matrix to the CNTs (Peigney, 2003; Sheldon & Curtin, 2004; Chen et al., 2011). The strengthening and toughening mechanisms of composites by fibers are now well established (Evans, 1990; Hull & Clyne, 1996); central to an understanding is the concept of interaction between the matrix and reinforcing phase during the fracture of the composite. The fracture properties of such composites are dominated by the fiber bridging force resulting from debonding and sliding resistance, which dictates the major contribution to the strength and toughness. Thus, the adequate connectivity with the matrix, and uniform distribution within the matrix are essential structural requirements for the stronger and tougher CNT/ceramic composites. To overcome these obstacles, various efforts, such as surface modification (De Andrade et al., 2008; Yamamoto et al., 2008; Kita et al., 2010; Gonzalez-Julian et al., 2011), heterocoagulation (Fan et al., 2006a, 2006b), extrusion (Peigney et al., 2002), and their combination, have been made to effectively achieve good dispersion of CNTs in ceramic matrix. Until now, however, most results for strengthening and toughening have been disappointing, and only little or no improvement have been reported in CNT/ceramic composite materials, presumably owing to the difficulties in homogeneous dispersion of CNTs in the matrix and in formation of adequate interfacial connectivity between two phases.
This chapter presents that novel processing approach based on the precursor method. The MWCNTs used in this study are modified with an acid treatment. Combined with a mechanical interlock induced by the chemically modified MWCNTs, this approach leads to improved mechanical properties. Mechanical measurements on the composites revealed that only 0.9 vol.% acid-treated MWCNT addition results in 37% and 36% simultaneous increases in bending strength (689.6 ± 29.1 MPa) and fracture toughness (5.90 ± 0.27 MPa m1/2), respectively, compared with a MWCNT-free alumina sample prepared under similar processing conditions. Structure-property relationship of present composites will be explained on the basis of the detailed nano/microstructure and fractographic analysis. We also explain why previous reports indicated only modest improvements in the fracture properties of MWCNT based ceramic composites. Here, the failure mechanism of the MWCNTs during crack opening in a MWCNT/alumina composite is investigated through transmission electron microscope (TEM) observations and single nanotube pullout tests. Achieving tougher ceramic composites with MWCNTs is discussed based on these results.
2. A novel approach for preparation of MWCNT/alumina composites
To disperse the MWCNTs homogeneously in the matrix and improve the connectivity between MWCNTs and matrix, we developed a novel approach with combination of a precursor method for synthesis of an alumina matrix, an acid treatment of MWCNTs and a spark plasma sintering method. The improvement on the bending strength and fracture toughness was confirmed by the fracture tests.
2.1. Materials and specimen preparation
2.1.1. Starting materials
The MWCNT material (Nano Carbon Technologies) used in this research was synthesized by a catalytic chemical vapor deposition method followed by high temperature annealing at 2600˚C. The purity was claimed to be 99.5% by the producer. Fig. 1 shows scanning electron microscope (SEM, Hitachi S-4300) and TEM (Hitachi HF-2000) images of the pristine MWCNTs. It can be seen from Fig. 1b that the pristine MWCNTs have a highly crystalline multi-walled structure with a narrow central channel. The corresponding geometrical and mechanical properties of the pristine MWCNT are listed in Table 1. The estimated diameter and length of the pristine MWCNTs from SEM and TEM measurements ranged from 33 to 124 nm (average: 70 nm) and 1.1 to 22.5 μm (average: 8.7 μm), respectively. Tensile-loading experiments with individual MWCNTs using a nanomanipulator tool operated inside SEM revealed that the tensile strengths of 10 pristine MWCNTs ranged from ∼2 to ∼48 GPa (average: 20 GPa) and the Young\'s modulus ranged from ∼50 to ∼1360 GPa (average: 790 GPa) (Yamamoto et al., 2010). It seems that the average tensile strength of the pristine MWCNT used in this research were somewhat lower than that of the arc-discharge grown MWCNTs (Yu et al., 2000).
Figure 1.
a) SEM and (b) TEM image of pristine MWCNTs used in this research.
ID (nm)
OD (nm)
l (μm)
ρ (Mg/m3)
σ f (GPa)
E (GPa)
I (nm4)
EI (N·nm2)
7 (3~12)
70 (33~124)
8.7 (1.1~22.5)
2.1
20 (2~48)
790 (50~1360)
1.2×106
9310×10-4
Table 1.
Measured geometrical and mechanical properties of pristine MWCNTs. Shown are the nanotube inner diameter (ID), outer diameter (OD), length (l), density (ρ), tensile strength (σ f), Young’s modulus (E), moment of inertia of cross sectional area (I) and flexural rigidity (EI), respectively.
2.1.2. Acid treatment of MWCNTs
The rationale behind the acid treatment is to introduce nanoscale defects and adsorb negatively charged functional groups at the MWCNT ends and along their lengths. The pristine MWCNTs were refluxed in 3:1 (volume ratio) concentrated H2SO4:HNO3 mixture at a temperature of 70˚C for 1 hour, 2 hours and 4 hours, washed thoroughly with distilled water to be acid-free, and then finally dried in an air oven at 60˚C. Fig. 2 shows the typical TEM images of a series of the acid-treated MWCNTs and the corresponding distribution of nanodefect depths treated with the various conditions. It is demonstrated that with the acid treatment of the pristine MWCNTs, we have deliberately introduced nanoscale defects on the surface of the MWCNTs. The depth of the nanodefects is on the nanoscale and the average size is in the range of 4.4~7.0 nm for the acid treatment used in this study. We can see that the nanodefects density, i.e., the number of nanodefects per unit of a MWCNT surface area increases with the increasing treatment time. Hereafter, the number of the nanodefects per unit of the MWCNT surface area is referred to as the nanodefect density.
In addition to the nanodefects density, the average size of the nanodefect depths appears to vary with respect to the treatment time. When the treatment time increases from 1 hour to 2 hours, the average size of nanodefect depths increases from 4.4 nm to 6.5 nm. Furthermore, when the treatment time further increases to 4 hours, it increases to 7.0 nm. The aspect ratio (α) of the nanodefects on the MWCNT surface were estimated using the equation α = Lwidth/Ldepth, where Lwidth is the average size of nanodefect widths on the MWCNT surface, and Ldepth is the average size of nanodefect depths. For the acid treated products with treatment time of 1 hour, 2 hours and 4 hours was 4.4, 4.9 and 3.9, respectively. The experimental results demonstrate that the present method, which uses the acid treatment, may provide an effective route for preparation of the nanodefects on the MWCNT surface, and it may be possible to adjust and control the average size and nanodefect density by varying the treatment time. According to the current TEM observations, peel-off of a few layers in the MWCNT structure was frequently observed for the MWCNT powders acid-treated for 4 hours. Thus, reduction of α may be due to the decrease in the MWCNT diameter by the peel-off of a few layers in the MWCNT structure and imply that the excessive acid treatment of the MWCNT resulted in degradation of the quality and mechanical properties of MWCNTs (Yamamoto et al., 2010). As previously reported (Liu et al., 1998), SWCNTs can be cut into shorter segments by acid treatment of 3:1 (volume ratio) concentrated H2SO4:HNO3 mixture. In this study, however, when the acid treatment times are 1 hour and 2 hours, no such change in the length has been found in the acid-treated MWCNTs. The average lengths of the acid-treated MWCNTs were 8.7 μm and 8.3 μm, respectively. In contrast, average length was decreased slightly with a further increase in the treatment time up to 4 hours, and reached about 7.2 μm.
The zeta potential values of the pristine MWCNTs and the acid-treated MWCNTs at different pH values are shown in Fig. 3a. Here, the changes in zeta potentials were measured in 1.0 mM KCl aqueous solution of varying pH using a zeta potential analyzer (ZEECOM ZC2000, Microtec). The pH value of the aqueous solution was adjusted with HCl and NaOH. Zeta potential values were calculated using the Smoluchowski equation. The isoelectric point (pHiep) for the pristine MWCNTs is located at about 3.0, whereas the acid treatment process makes the surface more negatively charged at tested pH values. The change in the zeta potential may be mainly due to the introduction of more functional groups after the acid treatment (Esumi et al., 1996; Liu et al., 1998). These functional groups make them easily dispersed in polar solvents, such as water and ethanol. Fig. 3b shows a photograph of the pristine MWCNTs and acid-treated MWCNTs suspensions at pH 6, respectively. It is clear that the pristine MWCNTs are not dispersed at pH 6. In contrast, the dispersion of the acid-treated MWCNTs is seen to improve dramatically. Furthermore, it can be expected that the larger electrical repulsive force between the acid-treated MWCNTs will facilitate their dispersion and prevent them from tangling and agglomeration. The zeta potential of the aluminum hydroxide, which is used as the starting material for synthesis of the alumina matrix, exhibited positive values over a wide pH range (pH = 3~9), while that of the acid-treated MWCNTs was negative in this pH range. On these two colloidal suspensions are mixed, particles of the aluminum hydroxide will bind onto the acid-treated MWCNTs because of the strong electrostatic attractive force between them, and this results in a homogeneous MWCNTs and aluminum hydroxide solution.
2.2. Preparation of MWCNT/alumina composites
A typical synthesis procedure for the composite preparation is as follows. The 50 mg MWCNTs acid-treated for 2 hours or pristine MWCNTs were dispersed in 400 ml ethanol with aid of ultrasonic agitation. 15.2 g aluminum hydroxide (Wako Pure Chemical Industries) was added to this solution and ultrasonically agitated. 73 mg magnesium hydroxide (Wako Pure Chemical Industries) was added to prevent excessive crystal growth. Here, the weight loss of the hydroxides caused by the dehydration process was accounted for in the calculation of the composite composition. The weight loss of the aluminum hydroxide and the magnesium hydroxide was 34.7% and 31.9%, respectively. The resultant suspension was filtered and dried in an air oven at 60˚C. Finally, the product obtained in the previous step was put into a half-quartz tube and was dehydrated at 600˚C for 15 min in argon atmosphere. The composites were prepared by spark plasma sintering (SPS, SPS-1050 Sumitomo Coal Mining) (Omori, 2000) in a graphite die with an inner diameter of 30 mm at a temperature of 1500˚C under a pressure of 20 MPa in vacuum for 10 min. For comparison, similar preparation processes were applied while using the pristine MWCNTs as the starting material. Fig. 4 shows X-ray diffraction patterns (M21Mac Science) of the (a) aluminum hydroxide–MWCNT mixture, (b) dehydrated product and (c) sintered body, respectively. It is difficult to distinguish the MWCNT peaks from all XRD patterns, probably due to the small quantity of MWCNTs. The diffraction peaks corresponding to the aluminum hydroxide and the intermediate were observed in the aluminum hydroxide–MWCNT mixture. However, the diffraction peaks corresponding to the aluminum hydroxide and the intermediate disappeared completely in the sintered body, suggesting the phase transformation of the aluminum hydroxide to form α-alumina via an amorphous phase (b). These results clearly indicate that alumina was successfully synthesized by SPS at 1500˚C under 20 MPa in vacuum.
Figure 2.
Typical low-magnification TEM images of acid-treated MWCNTs treated with the various conditions of (a) 1 hour, (c) 2 hours and (e) 4 hours. The insets show the high magnification images. (b), (d), (f) Corresponding depth distribution of the nanodefects in the sample (a), (c) and (e), respectively. The solid lines in (b), (d), (f) represent the Gaussian fitting curves. The observation was made for approximately 200 defects.
Figure 3.
a) Zeta potential values of MWCNTs and acid-treated MWCNTs at different pH. (b) Undistributed one-day old aqueous suspensions of (left) pristine MWCNTs and (right) acid-treated MWCNTs.
Figure 4.
XRD patterns of the (a) aluminum hydroxide–MWCNT mixture, (b) dehydrated product and (c) sintered body, respectively.
2.3. Micro- and nanostructures of MWCNT/alumina composites
We now discuss the micro- and nanostructures of the acid-treated MWCNT/alumina composites using SEM and TEM analysis. An interesting geometric structure was observed between the individual MWCNT and the alumina matrix, as shown in Fig. 5. It is revealed that a nanodefect on the acid-treated MWCNT is filled up with alumina crystal, which may be intruding into the nanodefect during grain growth. This nanostructure is novel in that its structure resembles a nanoscale anchor with an alumina crystal spiking the surface of the MWCNT.
From the SEM observations on the fracture surface, the following features can be noted. First, numerous individual MWCNTs protrude from the fracture surface, and the pullout of the MWCNTs can be clearly observed (Fig. 6a), which had not been obtained until now for conventional CNT/ceramic composites. Most of MWCNTs are located in the intergranular phase and their lengths are in the range 0~10 μm. The alumina grains have sizes in the micron range, around 1.5 μm (The grain size of the composite was obtained using SEM images, and the observation was made for 224 grains.). No clear difference in the grain size is observed between the acid-treated MWCNT/alumina composites and the pristine MWCNT/alumina composites, even though the incorporation of MWCNTs seems to suppress the grain growth of the alumina. Second, in the case of the smaller amount of the acid-treated MWCNTs, no severe phase segregation was observed, whereas the composites made with the pristine MWCNTs revealed an inhomogeneous structure even for MWCNT addition as low as 0.9 vol.%. In addition to the above features, some MWCNTs on the fracture surface showed a ″clean break″ near the crack plane, and that the diameter of MWCNT drastically slenderized toward their tip, as illustrated in Figs. 6 b and 6c, respectively. As SEM cannot clearly resolve the thickness of a single MWCNT, TEM was used to determine if the fracture phenomenon of MWCNTs was indeed occurring during crack opening.
Figure 5.
MWCNT morphology in the composites. (a) It is demonstrated that a nanodefect on the acid-treated MWCNT is filled up with alumina crystal. (b) Enlarged TEM image, taken from the square area. (c) Schematic description of MWCNT morphology in the composites.
TEM observations on the fracture surface demonstrated that a diameter change in the MWCNT structure was evidently observed for a certain percentage of the MWCNTs (Fig. 7a). At least, 25% MWCNT appear to have an apparent diameter change (The observation was made for 281 MWCNTs.). As shown in Fig. 7b, the high magnification TEM image clearly showed a change in diameter, and this morphology is quite similar to a ″sword-in-sheath″-type failure (Yu et al., 2000; Peng et al., 2008; Yamamoto et al., 2010). Key features are illustrated in enlarged TEM image, taken from the square area in Fig. 7b. The inset showed that outer-walls having approximately 10 shells were observed to break up at the location where the MWCNT undergo failure, and that the edges of the broken outer shells were observed to be perpendicular to the cylinder axis. Since no apparent variation in the diameter of the MWCNTs has been observed along the axis in the as-received MWCNTs, these results imply that some MWCNTs underwent failure in the sword-in-sheath manner prior to pullout from the matrix. Note that MWCNT failure was also observed in fracture surfaces of alumina composites made with arc-discharge-grown and chemical vapor deposition-grown MWCNTs prepared under the same processing conditions (Yamamoto et al., 2011).
Figure 6.
Fracture surface of acid-treated MWCNT/alumina composites. (a) Numerous individual MWCNTs protrude from the fracture surface. (b,c) Some MWCNTs have broken in the multi-wall failure.
Figure 7.
TEM images of the fracture surface of the composite acquired (a) low and (b) high magnification images.
2.4. Physical and mechanical properties of MWCNT/alumina composites
The bending strength of the composites was measured by the three-point bending method under ambient conditions, in which the size of the test specimens was 2.0 mm (width) × 3.0 mm (thickness) × 24.0 mm (length). The span length and crosshead speed for the strength tests were 20.0 mm and 0.83 μm/s, respectively. The fracture toughness was measured by the single-edge notched beam (SENB) method (Japanese Industrial Standards, 1995) under ambient conditions, in which the size of test specimens was 2.0 mm (width) × 3.0 mm (thickness) × 15.0 mm (length). A notch with depth and width of 0.3 mm and 0.1 mm was cut in the center part of the test specimens. A span length of 12.0 mm and crosshead speed of 0.83 μm/s were applied for the toughness test. The bending strength (σb) and fracture toughness (KIc) are given by the following equations:
σb=3PbL/2bh2E1
KΙc=(3PbL/2bh2)⋅a1/2YE2
where Pb is the maximum load, L is the span length, b is the specimen width, h is the specimen thickness, a is the notch depth and Y is the dimensional factor. All surfaces of the specimens were finely ground on a diamond wheel, and the edges were chamfered. The indentation tests were done on a hardness tester (AVK-A, Akashi) with a diamond Vickers indenter under ambient conditions. The 0.9 vol.% acid-treated MWCNT/alumina composite with surface roughness of 0.1 μm (Ra) was indented using a Vickers diamond pyramid with a load of 98.1 N (P) applied on the surface for 15 s. The diagonal (d) and the radial crack length (C) were measured by the SEM. The hardness (Hv) and indentation toughness values (KIc) were calculated by the following equations:
Hv=0.1891P/d2E3
KΙc=0.016(E/Hv)1/2(P/C3/2)E4
where E is the Young’s modulus of the composite (E = 362.8 GPa) measured by a pulse-echo method.
It was found that surface modification of the MWCNTs is effective in improvement of bending strength and fracture toughness of the MWCNT/alumina composites. Figs. 8 a and 8bshow the dependence of the bending strength and the fracture toughness on MWCNT content in the composites. There are few papers which report significant improvement in the mechanical properties such as toughness (Zhan et al., 2003), and the improvement by MWCNT addition has been limited so far in previous studies (Ma et al., 1998; Sun et al., 2002; Wang et al., 2004; Sun et al., 2005; Cho et al., 2009). In our composites, however, the bending strength and the fracture toughness simultaneously increased with the addition of a small amount of the acid-treated MWCNTs. The bending strength and the fracture toughness of the 0.9 vol.% acid-treated MWCNT/alumina composite reached 689.6 ± 29.1 MPa and 5.90 ± 0.27 MPa m1/2,respectively. At the same time, the bending strength and the fracture toughness of the acid-treated MWCNT/alumina composites were always higher than those of the pristine MWCNT/alumina composites with identical MWCNT content, indicating enhanced stress transfer capability from the alumina to the acid-treated MWCNTs. The Vickers indentation toughness calculated by using the Eq. (4) was 6.64 MPa m1/2, which is a slightly larger value than that measured by using SENB method (5.90 MPa m1/2). These observations revealed that the high structural homogeneity and enhanced frictional resistance of the structural components led to a simultaneous increase in the strength and the toughness of the acid-treated MWCNT/alumina composites. In contrast, for the larger amount of the MWCNTs, the degradation of mechanical properties of both the composites may be primarily attributed to the severe phase segregation. Because a bundle of segregated CNTs has poor load-carrying ability, the effect of this kind of CNT aggregate in the matrix may be similar to that of pores (Yamamoto et al., 2008a, 2008b).
Figure 8.
a) Bending strength and (b) fracture toughness as a function of MWCNT content.
3. Evaluation of crack bridging characteristics
Ceramic-CNT interfacial behavior is another key factor in controlling the mechanical and physical properties of fiber reinforced composite materials (Evans, 1990; Hull & Clyne, 1996; Chen et al., 2011). In general, strong interfacial connectivity facilitates effective load transfer effect, but it prevents CNT pull-out toughening from occurring. Weak interfacial connectivity favors CNTs pull-out but fails to toughen the ceramic matrix. Thus, a balance must be maintained between CNT pull-out and toughening mechanics. It is well recognized that improved toughness of fiber-reinforced ceramic composites is obtained under moderate fiber-ceramic interfacial connectivity. In this regard, suitable (neither too strong nor too weak) ceramic-CNT interfacial connectivity is needed to ensure effective load transfer, and to enhance the toughness and strength of ceramic-CNT composites. Here, the failure mechanism of the MWCNTs during crack opening in a MWCNT/alumina composite is investigated through TEM observations and single nanotube pullout tests. Achieving tougher ceramic composites with MWCNTs is discussed based on these results.
3.1. Pullout experiment sample preparation
The MWCNT failure during crack opening motivated our research of the crack bridging characteristics through the single nanotube pullout tests. The single nanotube pullout experiments were carried out using an in-situ SEM (Quanta 600 FEG; FEI) method with a nanomanipulator system (Yu et al., 2000; Yamamoto et al., 2010). An atomic force microscope (AFM) cantilever (PPP-ZEILR, nominal force constant 1.6 N/m; NANOSENSORS) was mounted at the end of a piezoelectric bender (ceramic plate bender CMBP01; Noliac) on an X–Y linear motion stage, and the composite with fracture surface (that was coated with platinum) was mounted on an opposing Z linear motion stage. The piezoelectric bender was used to measure the resonant frequency of each cantilever in vacuum. A single MWCNT on the fracture surface was clamped onto a cantilever tip by local electron-beam-induced deposition (EBID) of a carbonaceous material (Ding et al., 2005). As a precursor source for the EBID, we used n-docosane (C22H46, Alfa Aesar), which was dissolved in toluene to make a 3 mass% solution. A small amount of the solution was dropped on a cut-in-half copper TEM grid. After the solution evaporated, the TEM grid with paraffin source was mounted on the AFM chip, as shown in Fig. 9. The deposition rate of the EBID depends on several factors (Ding et al., 2005). Thus, the amount of the paraffin source, deposition time, and distance between the paraffin source and the cantilever tip were experimentally-optimized. The cantilevers serve as force-sensing elements and the spring constants of each were calculated in-situ prior to the pullout test using the resonance method (Sader et al., 1999). In brief, for the case of a rectangular cantilever, the force constant (k) is given by following equation,
k=MeρcbhLωvac2E5
where ωvac is the fundamental radial resonant frequency of the cantilever in vacuum, h, b, and L are the thickness, width, and length of the cantilever, respectively, ρc is the density of the cantilever (= 2.33 Mg/m3), and Me is the normalized effective mass which takes the value Me = 0.2427 for L/b > 5 (Sader et al., 1995). We measured ωvac, h, b and L of each cantilever in the SEM and used the measured, not the nominal provided, values to calculate k. The h, b and L are determined by counting the number of pixels in the acquired SEM images. The applied force is calculated from the angle of deflection at the cantilever tip in the acquired SEM images (Ding et al., 2006). The deflection (δ) and angle of deflection (θ) at the cantilever tip are given by
δ=PL3/3EIE6
Figure 9.
SEM image showing the experimental setup for pullout experiments.
θ=PL2/2EIE7
where P is the load applied at the cantilever tip, L is the cantilever length, E is the elastic modulus and I is the moment of inertia of the cantilever (Ding et al., 2006). Thus, the deflection at the cantilever tip can be represented by the angle of deflection with the following relationship (Ding et al., 2006):
δ=2θL/3E8
A crosshead speed – i.e., movement rate of the cantilever – of about 100 nm/s was applied for the pullout tests.
We fractured a composite specimen by conducting the fracture tests, which caused single MWCNT to project from the crack plane, as exemplified in Fig. 6a. This allows single MWCNT ″pickup″ with cantilever tip for subsequent tensile loading using the nanomanipulator. As mentioned above, however, the MWCNTs crossing the crack planes were strained during crack opening and possibly underwent failure, as shown in Figs. 6b, 6c and 7. Therefore, by observing the fracture surface on the composites, MWCNTs with no apparent damages were selected for the pullout tests. The physical and mechanical properties, and electrical conductivity of the composite used for the pullout testes are shown in Table 2.
Relativedensity(%)
Grainsize(μm)
Bendingstrength(MPa)
Fracturetoughness(MPa·m1/2)
Hardness(GPa)
Young’smodulus(GPa)
Poisson’sratio
98.9
1.43±0.31
543.8±60.9
4.74±0.12
17.0 ± 0.4
358.0
0.20
Table 2.
The properties of the composite with 0.9 vol.% pristine MWCNTs. The Young’s modulus and Poisson’s ratio were measured by the ultrasonic pulse echo method.
3.2. Nanotube fracture during the failure of MWCNT/alumina composites
Results obtained from the pullout experiments revealed that strong load transfer was demonstrated, and no pullout behavior was observed for all 15 MWCNTs tested in this present research. Eight of these MWCNTs fractured at the composite surface and the remaining 7 MWCNTs underwent failure in the region between the fixed point on the cantilever and the crack plane, as illustrated in Fig. 10.
Figure 10.
Fracture location of single MWCNTs under pullout loading. Of the 15 MWCNTs tested here, 8 MWCNTs fractured on the composite surface (sample numbers: 3, 4, 7, 8, 11–14) and remaining 7 MWCNTs fractured in the middle (sample numbers: 1, 2, 5, 6, 9, 10, and 15).
Two series of SEM and TEM images for each of two individual MWCNTs, captured before and after their breaking, are shown in Figs. 11 and 12. In the first series (Fig. 11; sample number 14), a MWCNT projecting 5.72 ± 0.01 μm from the fracture surface (Fig. 11a) was ″welded″ to a cantilever tip by local EBID, and then loaded in increments until failure. The resulting fragment attached on the cantilever tip was at least 10.9 μm long (Fig. 11b), whereas the other fragment remained lodged in a grain boundary of the alumina matrix (Fig. 11c), suggesting that MWCNT underwent failure in a sword-in-sheath manner. TEM images show a change in diameter at the location where the MWCNT underwent failure, and that the inner core protruding from the outer shells has a multi-walled closed-end structure, as shown in Figs. 11d and 11e, respectively. Given that uniformity of the interwall spacing of 0.34-nm-thick cylinder structure, approximately 11 shells underwent failure. There results strongly suggest that the MWCNTs broke in the outer shells and the inner core was then completely pulled away, leaving the companion fragment of the outer shells in the matrix. The sword-in-sheath failure did not always occur. Instead a few MWCNT failed leaving either a very short sword-in-sheath failure or a clean break. As for one example (Fig. 12; sample number 10), a MWCNT projecting 5.34 ± 0.01 μm from the crack plane (Fig. 12a) underwent failure on the composite fracture surface. The resulting fragment attached on the cantilever tip was at least 5.7 μm long (Fig. 12b), and no fragment was observed at the original position on the crack plane, suggesting that in this case the MWCNT failed by breaking inside the matrix, and did not pull out. Fig. 12c shows the TEM image of the tip of the same MWCNT which underwent very short sword-in-sheath failure or clean break during crack opening.
Figure 11.
SEM images show (a) a free-standing MWCNT having a 5.72 ± 0.01 μm-long on the fracture surface of the composite. (b) After breaking, one fragment of the same MWCNT attached on the cantilever tip had a length ~10.9 μm. (c) The other fragment remained in the matrix. (d,e) TEM images show a change in diameter at the location where the MWCNT underwent multi-wall failure, and that it clearly has a multi-walled closed-end structure.
Figure 12.
In the second series, (a) a tensile-loaded MWCNT with a length of 4.46 ± 0.01 μm fractured on the crack plane. (b) The resulting fragment on the cantilever tip had a length ~5.7 μm. (c) TEM image shows the MWCNT which underwent the very short sword-in-sheath failure or clean break.
Figure 13.
Schematic description of possible fracture mechanisms of the MWCNT (sample number 14). (a) Initial state of a MWCNT. (b) Tensile stresses lead to matrix crack and partial debonding formation. (c,d) As displacement increases, the MWCNTs, rather than pulling out from the alumina matrix, undergo failure in the outer shells and the inner core is pulled away, leaving the fragment of the outer shells in the matrix.
Next, we schematically describe possible processes and mechanics, explaining the MWCNT failure during crack opening (Fig. 13). As for one example, considering the sample number 14 (Fig. 11), the initial state of the MWCNT in an ideal case is a completely impregnated and isolated embedded in the matrix (Fig. 13a). Tensile stresses parallel to the axis of MWCNT length lead to matrix crack formation. Subsequently, interfacial debonding between two phases may occur (Fig. 13b), perhaps over a limited distance (but this is unlikely to make a major contribution to the fracture energy.). Since there is variability in the MWCNT strength in the debonded region on either side of the crack plane, and it is possible for the MWCNT to break at a certain position, when the stress in the MWCNT reaches a critical value. As displacement increases, the MWCNTs, rather than pulling out from the alumina matrix, undergo failure in the outer shells and the inner core is pulled away, leaving the fragments of the outer shells in the matrix (Figs. 13c and 13d).
4. Conclusion
Creating tough, fracture-resistant ceramics has been a central focus of MWCNT/ceramic composites research. In this research, the MWCNT/alumina composite with enhanced mechanical properties of 689.6 ± 29.1 MPa for bending strength and 5.90 ± 0.27 MPa m1/2 for fracture toughness have been successfully prepared by a novel processing method. A combination of the precursor method for synthesis of the alumina matrix, the acid treatment of the pristine MWCNTs and the spark plasma sintering method can diminish the phase segregation of MWCNTs, and render MWCNT/alumina composites highly homogeneous. The universality of the method developed here will be applicable to a wide range of functional materials such as tribomaterials, electromagnetic wave absorption materials, electrostrictive materials, and so on. Our present work may give a promising future for the application of MWCNTs in reinforcing structural ceramic components and other materials systems such as polymer- and metal-based composites.
We have also shown from TEM observations and single nanotube pullout experiments on the MWCNT/alumina composites that strong load transfer was revealed, and no MWCNT pullout behavior was observed. It is well recognized the fracture properties of fiber-reinforced composites are dominated by the fiber bridging force resulting from debonding and sliding resistance, which dictates the major contribution to the strength and toughness (Evans, 1990; Hull & Clyne, 1996). The results reported here suggest that modest improvements in toughness reported previously may be due to the way MWCNT’s fail during crack opening in the MWCNT/ceramic composites. Our finding suggests important implications for the design of tougher ceramic composites with MWCNTs. The important factor for such tougher ceramic composites will thus be the use of MWCNT having a much higher load carrying capacity (as well as a good dispersion in the matrix).
Acknowledgement
The authors thank our colleague, Dr. M. Omori, Mr. K. Shirasu, Mr. Y. Nozaka, Mr. Y. Aizawa and Ms. N. Suzuki of Fracture and Reliability Research Institute (FRRI), Tohoku University, for their helpful discussions, and Mr. T. Miyazaki of Technical Division, School of Engineering, Tohoku University, for technical assistance in the TEM analysis. The authors acknowledge Prof. R.S. Ruoff of The University of Texas at Austin for his useful guidance. This work is partially supported by Grand-in-Aids for Scientific Research (Nos. 23860004 and 21226004) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. This work is performed under the inter-university cooperative research program of the Advanced Research Center of Metallic Glasses, Institute for materials Research, Tohoku University.
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Introduction",level:"1"},{id:"sec_2",title:"2. A novel approach for preparation of MWCNT/alumina composites",level:"1"},{id:"sec_2_2",title:"2.1. Materials and specimen preparation",level:"2"},{id:"sec_2_3",title:"Table 1.",level:"3"},{id:"sec_3_3",title:"2.1.2. Acid treatment of MWCNTs",level:"3"},{id:"sec_5_2",title:"2.2. Preparation of MWCNT/alumina composites",level:"2"},{id:"sec_6_2",title:"2.3. Micro- and nanostructures of MWCNT/alumina composites",level:"2"},{id:"sec_7_2",title:"2.4. Physical and mechanical properties of MWCNT/alumina composites",level:"2"},{id:"sec_9",title:"3. Evaluation of crack bridging characteristics",level:"1"},{id:"sec_9_2",title:"3.1. Pullout experiment sample preparation",level:"2"},{id:"sec_10_2",title:"3.2. Nanotube fracture during the failure of MWCNT/alumina composites",level:"2"},{id:"sec_12",title:"4. Conclusion",level:"1"},{id:"sec_13",title:"Acknowledgement",level:"1"}],chapterReferences:[{id:"B1",body:'ChenJ.HamonM. A.HuH.ChenY.RaoA. 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Fracture and Reliability Research Institute (FRRI), Tohoku University, Japan
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1. Introduction
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Nowadays digital video is widely used to present information. This is because a video is richer in information compared to a single image, and generally a video has more pictures and sound. However, digital data such as video have advantages and disadvantages. Digital video could be edited, manipulated, or altered easily by using a video editor or other tools. For example, someone could change contrast of the video, resize, remove or add some frames, or add a new object to the video. Unfortunately, once a digital video is manipulated, its integrity is questionable. In some cases, we need to know authenticity of the video. For example, a court need to decide if a video as evidence is genuine or has been manipulated. If the video has been manipulated, how to prove it?
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The integrity problem of digital video could be solved by using a fragile watermarking technique. In the fragile watermarking technique, we could embed one or more watermarks into frames of video. Once the watermarked video is manipulated, altered, or modified, the watermark inside will be fragile or damage. The damaged watermark is indication that the video has been manipulated. Therefore, fragile watermarking can be used to prove authentication of a video.
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A watermarking algorithm consists of two processes: embedding and extraction of watermark. Watermark is an information that refers to the video owner. Usually the watermark is a binary image such as logo, random bits, or other information. The watermark is inserted into a host video, frame by frame, become to a watermarked video without affecting its perceptual (and audio) quality. Through an inverse process, the embedded watermark can be extracted again from the video. When the extracted watermark is compared to the original watermark, we could conclude if the video has been altered. The damage extracted watermark is indication that the video has been altered.
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Digital watermarking schemes can operate on spatial domain or frequency domain. Assume the watermark is represented as string of bits. Watermarking schemes that operate in spatial domain embed watermark bits into pixel values of the video frame directly [1, 2]. Otherwise, on watermarking schemes that operate in transform domain, a host video has to be transformed first into a transform domain by using a specific transformation (DCT, DWT, DFT, etc.) [3]. Next embedding bits of watermark is performed by modifying the transform coefficients [2, 4].
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Generally watermarking in transform domain is more robust than spatial domain through non-malicious attacks such as cropping, compression, scaling, rotation, etc. Therefore, it is used to the problems of copyright protection, proving ownership, illegal copying, and transaction tracking of video. Otherwise, watermarking in spatial domain is suitable to solve the problem of tamper detection of video content. The watermark in the video must be fragile when the video is manipulated. Robustness is not important for fragile watermarking.
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The watermark could be originated from internal or external. The internal watermark means that the watermark is derived from host video directly, and then it is embedded into frames of the video. The second is external watermark which means that the watermark is an input from the user, and usually the watermark is a meaningful binary image such as logo or other image.
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Much research on fragile watermarking for digital video has been done by many scientists. This means that the fragile watermarking is interesting research topics. Some related research is from Elgamal et al. [1], Zhi-yu et al. [4], and Rupali et al. [5]. Elgamal et al. [1] proposed a fragile video watermarking algorithm on transform. The original video is transformed from RGB model to YCbCr model and then Cr-component is partitioned into non-overlapping blocks of pixel. The watermark is a binary image from the video owner. Bits of the binary image are embedded for each block separately.
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Like Elgamal et al. [1], Zhi-yu et al. [4] also proposed a fragile watermarking algorithm on transform domain. The original video is transformed from RGB model to YST model. The T-component is divided 4 × 4 blocks and then each block is transformed to frequency domain using DCT. The watermark is generated from the quantized DCT coefficient and then it is embedded into the last non-zero DCT coefficient.
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Rupali et al. [5] also proposed a fragile video watermarking algorithm on transform domain. The original video is transformed from spatial domain to frequency domain using DCT. Rupali et al. [5] used two watermarks to embed. Both of these watermarks are internal, that means from the original video itself. The first watermark is used to detect tampering and the second watermark is used to localize tampered area.
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All of the watermarking algorithms above operated on transform domain. A digital video contains more frames, generally hundreds to thousands frames. Transformation of each frame from the spatial domain to the transform domain consumes a lot of computing time. We need a simple fragile watermarking for the digital video but still meet the security aspect. A simple fragile watermarking on spatial domain is by using LSB (least significant bit) modification method. This method is fast and it can detect tampering on video until pixel level. To fulfill the security aspect, we use the watermarking key(s) in embedding and extraction process, so that embedding and extraction of watermark are performed by an authorized party who has the secret key(s).
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The watermark itself is confidential, only the video owner knows about it. Therefore, the watermark needs to be encrypted using the secret key(s). The secret key(s) also serve to prevent the watermark from being extracted and used in the reassembling of videos by an authorized party, thus avoiding counterfeiting of the videos.
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The chaos system can be used to get a secure fragile watermarking scheme. In recent years, chaos theory has attracted the attention of scientists, especially in the information security field. Chaos has been used to increase security [6]. The reason is the chaotic systems that have sensitivity on initial conditions. It means if we perform a little bit change to the initial conditions of the chaos system, after some iterations, the system will result values that differ significantly. In the field of cryptography and watermarking, generally a chaos map is used to generate pseudo-random numbers [7, 8].
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Munir et al. [9] used a chaos map, i.e. Arnold Cat’s map, to encrypt the watermark before embedding it into video frames. The original watermark is encrypted by XOR-ing it with a random image. The random image is generated from the replicated watermark by using an Arnold Cat Map. The encrypted watermark is embedded into each frame of the video using LSB modification method.
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Unfortunately, the random image generated using Arnold Cat’s map still shows patterns of the replicated watermark, so it is not completely random. The embedding algorithm is also redundant, because the random image is XOR-ed with the replicated watermark. Therefore, the watermarking algorithm has redundancy.
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In this paper, we modified the previous algorithm by using another chaos map so that the random image is generated from the chaos map directly. We used a random bit generator based on two Skew Tent Maps. The generator is abbreviated as CCCBG (Cross-Coupled Chaotic random Bit Generator) [10].
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The paper is organized into six sections. The first section is this introduction. The second section will review some supported theories. The algorithm to embed and extract the watermark will be explained in the third section. The fourth and fifth section will present the experiment results and discussion. Finally, the last section will resume the conclusion and future work.
\n
\n
\n
2. Chaos map
\n
One of the popular chaotic maps is a Logistic Map, described by
where μ is a parameter of map and 0 < μ ≤ 4. According to [7], the map is in chaotic state when 3.57 < μ ≤ 4. In this state, the resulting values appear random. Because of its random behavior, a logistic map can be used as a pseudo-random generator. Hence, initial value of the chaos map, x\n0, and constant μ serve as secret keys. When we iterate Eq. (1) from an initial value (x\n0), we get a random sequences between 0 and 1. The random values generated from the chaos Logistic Map are sensitive to small changes of the initial values. By changing x\n0, the random values generated different significantly from the previous chaotic values with initial value x\n0.
\n
Another chaos map is Tent Map. It iterates a point x\n0 and gives a sequence xi\n in [0, 1]:
where μ is system parameter and x\n0 is initial condition of map. When a Skew Tent Map is iterated from x\n0 value, it produces a sequence in the interval [0, 1] and distributed uniformly.
\n
Narendra et al. in [10] proposed a random bit generator based on two Skew Tent Maps. The generator is abbreviated as CCCBG (Cross-Coupled Chaotic random Bit Generator). In the CCCBG, random bit stream is generated by comparing outputs of the couple maps. If fμ\n(xi\n) and gμ\n(yi\n) are two Skew Tent Maps and are given as:
where μ is system parameter and is same for both maps. The CCCBG generated a sequence of random bits by comparing the outputs of the maps in the following way:
Based on several tests performed by Narendra et al., the CCCBG successfully passes all the randomness tests [10], therefore the random binary sequences can be used for encryption.
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In digital watermarking, the random bits play important role to increase security. We will use CCCBG Map to generate random bits. The random bits will be-XOR-ed to the original watermark to yield the encrypted watermark. For example, by iterating (6) 240,000 times (i.e., 480 × 854) and using parameter μ = 0.48999, initial conditions x\n0 = 0.500684, and y\n0 = 0.538167586, we get a sequence of random bits figured as a binary bit image (\nFigure 1\n).
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Figure 1.
A random image generated by using the CCCBG.
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\n
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3. Proposed algorithm
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This section will explain the proposed fragile video watermarking on spatial domain based on the chaotic map. The watermark is a binary image. To detect manipulation in the video frames until pixel level, the watermark must have the same size as the video frame size. Therefore, if watermark size is less than video frame size, the watermark need to be replicated by duplicating it a number of times in order to produce a new watermark that has the same size with the host video frame size. \nFigure 2\n shows example of replication. The original watermark “ASEAN logo” has a size of 200 × 194 pixels, whereas the video frames have a size of 480 × 854 pixels. This original watermark must be duplicated a number of times so that produce a replicated watermark that has size 480 × 854.
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Figure 2.
Left: the original watermark; right: the replicated watermark.
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Next, to increase security, before embedding, the replicated watermark is encrypted by XOR-ing it with a random image. A random image is generated by iterating CCCBG a number of mn times where m and n are frame sizes (\nFigure 1\n). The replicated watermark is encrypted with the random image by using XOR operation to produce an encrypted watermark (\nFigure 3\n). Next, we embed the encrypted watermark into the host video.
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Figure 3.
Left: the replicated watermark. Right: the encrypted watermark.
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We design a simple, but secure, fragile video watermarking based on chaos. The fragile video watermarking algorithm consists of two processes: embedding algorithm and extraction algorithm, each will be described below.
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3.1 Watermark embedding algorithm
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There are two scenarios for embedding the watermark into a digital video. The first scenario is embedding each frame of the video with the same watermark. The second scenario is embedding each frame of the video with the different watermark. The second scenario is not practical because the video owner have to provide the watermark of as many frames. Actually, the watermarks can be generated from the video itself (i.e., internal watermarks), we generate the watermark for each video frame that depend on the frame content itself. However, the resulting watermark is meaningless and cannot be perceived visually. We want the watermark to be meaningful and can be perceived visually. Therefore, we choose the watermark is a meaningful binary image and, for practical reason, the same watermark is embedded to each video frame.
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Now, we can describe the watermark embedding algorithm into the digital video in more detail as follows:
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\nInput: a host video file (v), a watermark file (w), and CCCBG’s parameter and initial conditions (μ, x\n0, y\n0).
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\nOutput: a watermarked video (v’).
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Step 1: Read the frames of video v, the watermark w, and CCCBG’s parameter and initial conditions (μ, x\n0, and y\n0). If the video has an audio, then separate the audio.
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Step 2: If size(w) < size(video frame of v), copy the single watermark to produce a replicated watermark w’ which has the same size with the host video frames.
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Step 3: Iterate CCCBG mn times to produce a random image r.
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Step 4: Encrypt w’ by XOR-ing it with r as follows:
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\n\nw\n”\n=\nw\n’\n⊕\nr\n\nE7
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Step 5: Embed the encrypted watermark, w”, into each frame of the video by manipulating the least significant bit (LSB) of pixels. If the frame has R, G, and B component, then it performs embedding to each component.
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Step 6: If the original video has audio, merge it to the watermarked frames to produce a watermarked video.
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\n\nFigure 4\n shows stages in the watermark embedding algorithm. The watermark is embedded into each frames of video. If the video has audio, the audio has not been changed. After embedding of the watermark, audio is merged back into the video.
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Figure 4.
Watermark embedding algorithm.
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3.2 Watermark extraction algorithm
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Watermark extraction from the video is performed to prove video authentication. Only the video owner can do it, because the owner has the original watermark. The original watermark is required to compare it with the extracted watermark. If the extracted watermark is the same as the original watermark (can be observed visually), then we decide that the video is authentic, otherwise the video has been altered, tampered, or manipulated. The original watermark is also required to localize the tampered region in a frame. Watermark extraction can be performed on all video frames or only on certain frames.
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Now, we can describe the watermark extraction algorithm from the digital video in more detail as follows:
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\nInput: a watermarked video file (v’), an original watermark file (w), and CCCBG’s parameter and initial conditions (μ, x\n0, and y\n0).
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\nOutput: an extracted watermark, location of tampered frame (if any).
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Step 1: Read the frames of video v’, watermark w, and CCCBG’s parameter and initial conditions (μ, x\n0 and y\n0).
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Step 2: If size(w) < size(video frame of v), copy the single watermark to produce a replicated watermark w’ which has the same size with the host video frames.
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Step 3: Iterating CCCBG mn times to produce a random image r.
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Step 4: For each frame, extract all of the least significant bit (LSB) of pixels. This step yields an extracted watermark w”.
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Step 4: Decrypt the watermark w” by XOR-ing it with r as:
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\nw”’ = w” ⊕ r.(8)
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Step 5: Compare w”’ with w’. If w”’ = w’, we conclude that the integrity of video is authenticated. If not, go to step 6 and 7.
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Step 6: To localize tampered region, subtract w’ to w”’. If a pixel is not changed, the subtraction yields 0, else the subtraction yields 1.
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Step 7: Identify pixels in the watermarked framed in position where the subtraction above yields 1. Those are pixels that have been manipulated.
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\n\nFigure 5(a)\n shows stages in the watermark extraction algorithm. The watermark is extracted from each frame of video and then compares the extracted watermark to the original watermark. The decision is binary (1 or 0), 0 means the watermarked video has not changed (authentic), 1 means the watermarked video has been manipulated, altered, or tampered. \nFigure 5(b)\n shows how to localize tampered region in a frame.
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Figure 5.
(a) Watermark extraction algorithm and (b) localize tampered region.
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4. Experiment and results
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We have implemented the proposed algorithm to be a computer program. Next we test the algorithm on a sample video to determine authentication of the video. The sample video was a video clip which has 394 frames and long 16 seconds, each frame has a size 480 × 854 (\nFigure 6a\n). This video contains audio inside. \nFigure 6b\n and \nc\n show two frames of the video (frame 1 and frame 175).
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Figure 6.
(a) A host video to be watermarked, (b) frame 1, and (c) frame 175.
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The watermark to be embedded into the host video is “ASEAN logo” as shown in \nFigure 3\n (after replicated). In these experiments below, we used parameters of CCCBG as follows: μ = 0.48999, initial conditions x\n0 = 0.5006841, and y\n0 = 0.538167586. The two initial conditions serve as the secret keys. These keys were used in both watermark embedding algorithm and extraction algorithm.
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This algorithm can only be used to test the authentication of digital videos that have been spatially manipulated. Spatial manipulation such as changing the contrast of the image, adding noise, changing the size of the frame, copy and paste an object into the frame, and others. The algorithm cannot temporarily detect video manipulation, for example, by removing one or more frames.
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In the section below, we divide experiments into two cases: (i) no attack case and (ii) tamper detection test, each will be described below.
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4.1 No-attack case
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If the watermarked video is not manipulated, we categorized it as no attack case. To prove the authentication of the video, we extracted all watermarks from each video frame. All watermarks should be the same as the original watermark. \nFigure 7\n shows the extracted watermarks but only from frame number 1 and frame number 283.
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Figure 7.
The watermarked frames and the extracted watermarks.
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Visually, there are no damages in the extracted watermarks. When we compare the extracted watermark to the original watermark by subtracting them, we get the difference is a black image (all of pixels are 0). Therefore, we conclude no tampering performed to the watermarked video. In this algorithm, parameter and initial condition of CCCBG behave as secret keys. Embedding and extraction of the watermark could be done by the authorized party only. If the receiver did not have the same keys, then the extracted watermark is not the same as the original watermark.
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\n
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4.2 Sensitivity to initial condition
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As mentioned before, the chaos system has a sensitivity to the slightest change on initial conditions. This characteristic provides the security aspect of watermarking. For example, the receiver used μ = 0.4900 (before was 0.48999), initial conditions x\n0 = 0.5006840 (before was 0.5006841), and y\n0 = 0.538167585 (before was 0.5381675865) to extract the watermark. \nFigure 8\n shows the extracted watermarks from two frames. The extracted watermarks are wrong! Compared to the original watermark, this extracted watermarks look like the random images. This happens because CCBG produces random bits that are very different from previous bits.
\n
Figure 8.
The watermarked frames and the extracted (wrong) watermarks.
\n
\n
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4.3 Tamper detection test
\n
In most cases, a digital video is often edited or manipulated using the video editor. If a video has been manipulated, the video is no longer original. Main goal of fragile watermarking is to determine if the video has been manipulated or not. If the video has been manipulated, the algorithm should able to locate where the alteration made on the video frames. In these experiments, we performed some typical attacks to the watermarked video. The attacks are (1) adding a text to the watermarked video, (2) copy-paste attack, (3) adding some noises, (4) modifying video contrast, and (5) cropping the frames. The following are the attacks.
\n
\n
\n
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5. Detection test against text addition
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We attack the watermarked video by writing a text “GLASS and WATER” at the left top of the frames (\nFigure 9a\n). To prove the authentication of the video, we extracted the watermarks from the video frames to get the extracted watermarks. The extracted watermarks contain the text (\nFigure 9b\n). Therefore, we conclude that the watermarked video has been manipulated. \nFigure 9c\n shows detection of pixels that have been manipulated by adding a text “GLASS and WATER.” \nFigure 9d\n shows the tampered pixels in the correspondence frame.
\n
Figure 9.
(a) Watermarked frame after adding a text; (b) extracted watermark; (c) and (d) detected tampering region.
\n
\n
\n
6. Detection test against copy-paste attack
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In the second attack, we copied an object “coca-cola bottle” and then pasted it into the watermarked video (\nFigure 10a\n). When we extracted the watermarks from the video, we got an extracted watermark as shown in \nFigure 10b\n. The extracted watermark contains a silhouette of strange object inside. Localize the tampered region and we can detect copy-paste object in the video frames as shown in \nFigure 10c\n and \nd\n.
\n
Figure 10.
(a) Watermarked frame after copy-paste attack; (b) extracted watermark; (c) and (d) detected tampering region.
\n
\n
\n
7. Detection test against adding some noises
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There are some kinds of noise such as Gaussian noise, salt and pepper noise, Poisson noise, etc. In the third attack, we added “salt and pepper” noise with density 0.1 into the watermarked video (\nFigure 11a\n). When we extracted the watermarks from the video, we got the watermarks also contained noise. The noisy watermarks indicated that the video has been altered (\nFigure 11b\n). The tampering region is entire of frame (\nFigure 11c\n and \nd\n).
\n
Figure 11.
(a) The watermarked frames after adding noise “salt and pepper”; (b) the extracted watermark; (c) and (d) detected tampering region.
\n
\n
\n
8. Detection test against contrast change
\n
A digital video can be changed so that the contrast becomes brighter or darker. In this attack, we manipulated the watermarked video by changing the contrast so that make it brighter. After that, we extracted the watermarks from the video (\nFigure 12\n, top right). We can see that the extracted watermarks are damaged and cannot be recognized anymore. Localization of tampered region shows that whole of image has been manipulated (\nFigure 12\n, bottom right).
\n
Figure 12.
Top left: the watermarked frame after changing the brightness; top right: the extracted watermark. Bottom right: the tampered region.
\n
\n
\n
9. Detection test against cropping
\n
One of the geometrical attacks is cropping. In this attack, we manipulated the watermarked video by cropping the video frames. The cropping can be performed horizontally or vertically. In this experiment, we cropped a left side of the video. To extract the watermarks, we returned the frame size into original size first by adding white or black pixels (in this experiment we added white pixels). We found the extracted watermarks contained the black region that indicated the cropped region in the frames (\nFigure 13\n).
\n
Figure 13.
The watermarked frames after cropping and the extracted watermarks.
\n
\n
\n
10. Discussion
\n
The proposed chaos-based fragile watermarking algorithm is simple but secure; it can be used to authenticate the digital video. Some experiments have been done to test performance of the algorithm. If there is no manipulation done to the watermarked video (no attack case), then the extracted watermark is same exactly to the original watermark. Therefore, we conclude that the video is still original, has not been changed or manipulated.
\n
Common manipulations of video have been done to test authentication and localize altering in the watermarked video. These manipulations are adding a text label into video frames, inserting a new object into the video, changing contrast, and cropping some pixels. In the case of adding text and inserting an object into the video frames, we got the extracted watermarks that contain silhouette of the object or text. The silhouettes can be seen visually. When we compared to the original watermark, the extracted watermark is not the same. Therefore we conclude that the video has been manipulated. By subtracting the original watermark from the extracted watermark and adjusting the results on the watermarked video, we can find the video frame portion that has been changed.
\n
Common manipulation of video is changing the contrast or brightness of the video. By changing the contrast or brightness of the video, it means changing all pixel values in the video frame. When the watermarks are extracted from the video, we found that extracted watermarks also change entirely. The extracted watermarks are totally damaged; therefore we can conclude that the video has been manipulated.
\n
When a block area in the watermarked video frame is cropped, the extracted watermark is also cropped in the correspondence block. The extracted watermark has a black region in the cropped area of the correspondence frame.
\n
This proposed algorithm has some weakness. It cannot detect manipulation of the watermarked video if one or more fames are removed. However, if some video frames are inserted to the watermarked video, the algorithm can still detect this manipulation, because the new frames do not contain the embedded watermarks.
\n
Other weakness is LSB modification method itself. Bits of the watermark are only embedded to one least significant bit of pixel values. If manipulation of the watermarked video is performed on other than the least significant bit, the algorithm cannot detect it. However, this manipulation is considered uncommon so it can be ignored.
\n
\n
\n
11. Conclusion and future works
\n
We have proposed a fragile video watermarking based on the chaotic map. In order to increase security, the watermark is encrypted using XOR operation with a random image. The random image is generated by using Cross-Coupled Chaotic random Bit Generator (CCCBG). The encrypted watermark is embedded to every RGB component of each frame. In the extraction process, the encrypted watermark is extracted from the watermarked video and compared to the original watermark.
\n
Some experiments have been done to test capability of the algorithm to detect tampering to the watermarked video. We have tried some common attacks to the watermarked video. The experiment results showed that the algorithm could detect tampering on the watermarked video. This algorithm has also capability to localize the area being tampered in the video frames.
\n
The algorithm can only be used to the uncompressed videos. It can be developed for the compressed video format such as MPEG-4. Embedding of watermarks is performed in encoding and decoding must be operated in transform domain. Some transform methods such as Fourier Transform, DCT, or wavelet transform can be used.
\n
This algorithm can also be developed so that it can detect the manipulation that removes one or more frames from the watermarked video. This can be done by using the internal watermarks that depend on the entire video content. Therefore, if some video frames are removed, the internal watermarks also change.
\n
\n\n',keywords:"fragile watermarking, authentication, digital video, chaos",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/72803.pdf",chapterXML:"https://mts.intechopen.com/source/xml/72803.xml",downloadPdfUrl:"/chapter/pdf-download/72803",previewPdfUrl:"/chapter/pdf-preview/72803",totalDownloads:150,totalViews:0,totalCrossrefCites:0,dateSubmitted:"February 21st 2020",dateReviewed:"June 10th 2020",datePrePublished:"July 13th 2020",datePublished:"September 30th 2020",dateFinished:null,readingETA:"0",abstract:"Fragile watermarking algorithm is a technique used to authenticate of digital data multimedia such as video. A watermarking algorithm consists of two processes: embedding and extraction of watermark. In this paper, a secure video fragile watermarking algorithm in spatial domain based on chaos is proposed. The watermark is a binary image which has the same size with frame size of the video. Before embedding, in order to increase security, the watermark is encrypted using XOR operation with a random image. The random image is generated by using Cross-Coupled Chaotic random Bit Generator (CCCBG). The encrypted watermark is embedded to each frame. In the extraction process, the encrypted watermark is extracted from the watermarked video, decrypted it, and then compared to the original watermark. This algorithm has capability to localize the area being tampered in the video frames. We have performed some typical attacks to the watermarked video and then authenticated it. Based on the experiment results, the algorithm can detect and localize the modified region of video frames very well. Sensitivity to the slightest change on initial conditions of the chaos map provided security of the algorithm.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/72803",risUrl:"/chapter/ris/72803",signatures:"Rinaldi Munir and Harlili Harlili",book:{id:"8321",title:"Digital Forensic Science",subtitle:null,fullTitle:"Digital Forensic Science",slug:"digital-forensic-science",publishedDate:"September 30th 2020",bookSignature:"B Suresh Kumar Shetty and Pavanchand Shetty H",coverURL:"https://cdn.intechopen.com/books/images_new/8321.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"70242",title:"Dr.",name:"B Suresh",middleName:"Kumar",surname:"Shetty",slug:"b-suresh-shetty",fullName:"B Suresh Shetty"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"318974",title:"Dr.",name:"Rinaldi",middleName:null,surname:"Munir",fullName:"Rinaldi Munir",slug:"rinaldi-munir",email:"rinaldi@informatika.org",position:null,institution:null},{id:"320665",title:"MSc.",name:"Harlili",middleName:null,surname:"Harlili",fullName:"Harlili Harlili",slug:"harlili-harlili",email:"harlili@informatika.org",position:null,institution:{name:"Institut Teknologi Bandung",institutionURL:null,country:{name:"Indonesia"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Chaos map",level:"1"},{id:"sec_3",title:"3. Proposed algorithm",level:"1"},{id:"sec_3_2",title:"3.1 Watermark embedding algorithm",level:"2"},{id:"sec_4_2",title:"3.2 Watermark extraction algorithm",level:"2"},{id:"sec_6",title:"4. Experiment and results",level:"1"},{id:"sec_6_2",title:"4.1 No-attack case",level:"2"},{id:"sec_7_2",title:"4.2 Sensitivity to initial condition",level:"2"},{id:"sec_8_2",title:"4.3 Tamper detection test",level:"2"},{id:"sec_10",title:"5. Detection test against text addition",level:"1"},{id:"sec_11",title:"6. Detection test against copy-paste attack",level:"1"},{id:"sec_12",title:"7. Detection test against adding some noises",level:"1"},{id:"sec_13",title:"8. Detection test against contrast change",level:"1"},{id:"sec_14",title:"9. Detection test against cropping",level:"1"},{id:"sec_15",title:"10. Discussion",level:"1"},{id:"sec_16",title:"11. Conclusion and future works",level:"1"}],chapterReferences:[{id:"B1",body:'\nElgamal AF, Mosa NA, ElSaid WK. A fragile video watermarking algorithm for content authentication based on block mean and modulation factor. International Journal of Computer Applications. 2013;80(4):0975-8887\n'},{id:"B2",body:'\nJayamalar T, Radha V. Survey on digital watermarking techniques and attacks watermark. International Journal of Engineering, Science and Technology. 2010;2(12):6963-6937\n'},{id:"B3",body:'\nMaryam A, Mansoor R, Hamidreza A. A novel robust scaling image watermarking scheme based on Gaussian mixture model. Expert Systems with Applications. 2015;42(4):1960-1971. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0957417414006381\n\n'},{id:"B4",body:'\nZhi-Yu H, Xiang-Hong T. Integrity authentication scheme of color video based on the fragile watermarking. In: Proceedings of 2011 International Conference on Electronics, Communications and Control (ICECC). 2011. Available from: https://ieeexplore.ieee.org/document/6067709\n\n'},{id:"B5",body:'\nRupali DP, Shilpa M. Fragile video watermarking for tampering detection and localization. Proceedings of 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2015\n'},{id:"B6",body:'\nDawei Z, Guanrong C, Wenbo L. A chaos-based robust wavelet-domain watermarking algorithm. Chaos, Solitons & Fractals. 2004;22:47-54\n'},{id:"B7",body:'\nBose R, Banerjee A. Implementing symmetric cryptography using chaos function. In: Proceeding 7th International Conference on Advanced Computing and Communication (ADCOM). Indian Institute of Technology; 20 Decembe 1999. pp. 318-321\n'},{id:"B8",body:'\nStojanovski T, Pihl J, Kocarev L. Chaos-based random number generators - part II: Practical realization. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications. 2001;48(3):382-385\n'},{id:"B9",body:'\nMunir R, Harlili H. A secure fragile video watermarking algorithm for content authentication based on Arnold Cat’s map. Proceedings of the 4th International Conference on Information Technology (InCIT2019). Bangkok, Thailand; 24-25 October 2019\n'},{id:"B10",body:'\nNarendra KP, Vinod P, Krishan K. A random bit generator using chaotic maps. International Journal of Network Security. 2010;10(1):32-38\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Rinaldi Munir",address:"rinaldi@informatika.org",affiliation:'
School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
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Transportation system became part of the infrastructure due its connection between two destinations, using maritime, land, or aerial methods, creating a link for social and economic activity. Bridges are widely used to cross rivers, valleys, and roads, providing a passage with other parts of the land since ancient times to modernity. Each structure has different requirements to cover, such span clearage, traffic flow, geometry and characteristics of the place to build; therefore, a great variety of bridges can be developed. Common materials used on construction are structural steel, reinforced concrete, pre-stressed concrete, or post-tensioned concrete; depending on the structural behavior of each type of bridge, there will be a maximum clear span to cover, which depends directly on the project’s budget. There are a variety of loads and environmental conditions that the new and existing structure needs to support effectively, including dead load, traffic, rain, wind, flood, and seismic events, using effective structural design process and techniques; on the other hand, there are long-term deterioration process, such as corrosion, wear, and fatigue, which should be considered on the maintenance process, avoiding additional costs, several damages, and catastrophic failures. Prevention and control of degradation process is achieved by effective maintenance methods applying protection technology such as paints, coating and cathodic protection. The purpose of this chapter is to show a brief review of ancient and modern bridges, including the process of design, material selection, construction, and maintenance.",signatures:"Arturo Gonzalez, Michael Schorr, Benjamin Valdez and Alejandro Mungaray",authors:[{id:"16436",title:"Dr.",name:"Michael",surname:"Schorr",fullName:"Michael Schorr",slug:"michael-schorr",email:"mschorr2000@yahoo.com"},{id:"65522",title:"Dr.",name:"Benjamin",surname:"Valdez",fullName:"Benjamin Valdez",slug:"benjamin-valdez",email:"benval@uabc.edu.mx"},{id:"311533",title:"MSc.",name:"Arturo",surname:"Gonzalez",fullName:"Arturo Gonzalez",slug:"arturo-gonzalez",email:"arturo.gonzalez17@uabc.edu.mx"},{id:"311534",title:"Dr.",name:"Alejandro",surname:"Mungaray",fullName:"Alejandro Mungaray",slug:"alejandro-mungaray",email:"alejandro.mungaray@uabc.edu.mx"}],book:{title:"Infrastructure Management and Construction",slug:"infrastructure-management-and-construction",productType:{id:"1",title:"Edited Volume"}}}],collaborators:[{id:"27002",title:"Dr.",name:"Vittorio",surname:"Rosato",slug:"vittorio-rosato",fullName:"Vittorio Rosato",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/27002/images/system/27002.jpg",biography:"Vittorio Rosato received the Laurea degree (M.Sc.) in Physics from the University of Pisa (Italy) and a Ph.D. in Condensed Matter Physics from the University of Nancy (France). He has extensively been working in Computational Physics, particularly in Condensed Matter and Material Science in his positions as Research Assistant at the University College of Wales in Aberystwyth (UK) and at the Centre d'Etudes Nucleaires in Saclay (France). Staff Scientist at ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) since 1990, he is currently Head of the Laboratory of Analysis and Protection of Critical Infrastructures and Manager of the Italian Node of the European Infrastructure Simulation and Analysis Centre (EISAC.it).\nHis current research activities span from risk analysis to the design of Decision Support Systems for the management of complex technological networks. He acts as Supervisor and Project Evaluator for EU, for the Italian Ministry of University and Research, and that of Economic Development; he is also consultant for several Italian Regions and the Italian Ministry of Defense. 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He is also an Unmanned Aerial Vehicles (UAV) ENAC-certifed pilot to perform critical operations involving aerial photogrammetry tasks for biological and Infrastructure monitoring applications. He took part in several European and Italian national research projects and acted as an advisor in some Evaluation Studies commissioned by the EU. He has also been advisor of several M.Sc. students and also a teacher in several professional courses on Software Engineering and Databases.",institutionString:"ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development)",institution:null},{id:"284590",title:"Dr.",name:"Maurizio",surname:"Pollino",slug:"maurizio-pollino",fullName:"Maurizio Pollino",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"292438",title:"Dr.",name:"Luigi",surname:"La Porta",slug:"luigi-la-porta",fullName:"Luigi La Porta",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null}]},generic:{page:{slug:"refund-policy",title:"Refund Policy",intro:"
IntechOpen will act in accordance with its published Refund Policy if requests for refunds are made.
",metaTitle:"Refund Policy",metaDescription:"IntechOpen will act in accordance with its Refund Policy if requests for refunds are made.",metaKeywords:null,canonicalURL:"/page/refund-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"
Refunds are possible in the following cases:
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1. A double payment, in which case a full refund will be made.
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2. A justified withdrawal of work by the Author, which had already been accepted during or after production but prior to publication. In this situation, a 50% refund will be made. (IntechOpen reserves the right to determine, at its discretion, whether withdrawal is justified and, consequently, whether a refund should be issued).
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3. In those rare instances where IntechOpen declines to publish a book that had been previously accepted, full refunds will be made to the same account or credit card from which the Author made the original payment.
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Please note that refunded amounts will not always be exactly the same as original payment amounts due to bank transaction fees and expenses. Any such costs will be split evenly between IntechOpen and the Author.
1. A double payment, in which case a full refund will be made.
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2. A justified withdrawal of work by the Author, which had already been accepted during or after production but prior to publication. In this situation, a 50% refund will be made. (IntechOpen reserves the right to determine, at its discretion, whether withdrawal is justified and, consequently, whether a refund should be issued).
\n\n
3. In those rare instances where IntechOpen declines to publish a book that had been previously accepted, full refunds will be made to the same account or credit card from which the Author made the original payment.
\n\n
Please note that refunded amounts will not always be exactly the same as original payment amounts due to bank transaction fees and expenses. Any such costs will be split evenly between IntechOpen and the Author.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). 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I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/55578/images/4574_n.png",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. 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