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Smart cementitious nanocomposites for self-sensing and continuous health monitoring of structures
Smart cementitious nanocomposites for self-sensing and continuous health monitoring of structures
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Saptarshi Sasmal, B.S. Sindu Scientist, Special and Multifunctional Structures Laboratory, CSIR-Structural Engineering Research Centre, Taramani, Chennai, India
Chapter outline 1. Introduction 485 2. Materials and methods 2.1 2.2
2.3
3. Results and discussion 3.1 3.2
489
Dispersion of CNTs/CNFs 489 Strain-based sensor 491 2.2.1 Material preparation 491 2.2.2 Testing 492 Acceleration-based sensor 493 2.3.1 Material preparation 493 2.3.2 Testing 493 Strain-based sensor 493 Acceleration-based sensor
493 495
4. Conclusions and future scope of work Acknowledgments 497 References 497
496
1. Introduction There is a rapid advancement in the development of cementitious composite during the last two decades. The advancements have been made in all areas including materials, mix proportionating, durability, recycling and environmental-friendliness. Initial research aimed at improving the mechanical properties like strength, strain carrying capacity and durability of cementitious composite. High strength concrete, ultrahigh performance concrete, fiber reinforced concrete, strain hardened cementitious composite, ferro-cement are some of the examples. The next stage of research includes
Smart Nanoconcretes and Cement-Based Materials. https://doi.org/10.1016/B978-0-12-817854-6.00021-0 Copyright © 2020 Elsevier Inc. All rights reserved.
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development of eco-friendly concrete by utilising industrial wastes and recycled aggregates, light weight concrete, etc. In the world of smart technologies, in addition to development of cementitious composite with improved mechanical properties, there is a need to develop smart composites with multifunctional capabilities and that can take care of its own shortcomings. For example, self-compacting concrete which is highly flowable and does not require vibration; self-curing concrete which contains capsules of membrane-forming curing compound which open up when the surface becomes dry; self-healing concrete in which micro-cracks/damages, caused in the material, are sensed automatically and healed by releasing the healing agent; and self-sensing concrete which can be used for sensing purposes. Self-sensing composites are developed by incorporating electrically conductive materials like carbon fibers, carbon nanotubes (CNTs), carbon nanofibers (CNFs), piezo-ceramics, piezo-polymers, etc into the parent (matrix) material. Incorporation of these materials into a matrix has been proven to be effective in converting it into a piezo-resistive composite which exhibits change in electrical resistance with the change in mechanical load acting on it. These self-sensing composites are extremely promising and are being used in variety of applications, like traffic monitoring, temperature sensing, pressure sensing and structural health monitoring. The utilization of selfsensing nanocomposites as temperature sensors has been demonstrated by Qin et al. (2013). They developed a temperature sensitive nanocomposite by incorporating 0.4% of carbon fibers and 1.5% of CNTs which had a temperature sensitivity coefficient of 8 104/ C. Zhao (2014) developed a nanocomposite by incorporating phase change materials which improved its thermal conductivity by 26%. It was also demonstrated that nanocomposite developed by incorporation of 0.5% of CNTs had thermoelectric power improved by 260% (Zuo et al., 2015). The conductive properties of nanocomposite were explored to develop self-heating and deicing material by Gomis et al. (2015). Electric potential difference is applied through the smart composite which causes heating of the material. The maximum temperature which could be attained depends on the electric power that had been applied, which in turn depends on the electrical resistance of the material. This causes melting of the ice deposited on the roads or prevent its formation from freezing of the moisture. Han et al. (2009) demonstrated the use self-sensing nanocomposite in traffic monitoring applications such as traffic flow detection, weigh-in-motion measurement and vehicle speed detection. Yu and Kwon (2009) explored the feasibility of using nanocomposite for traffic flow measurements in roadways, levees and bridges. Smart nanocomposite was also used to detect the acoustic emission (AE) activities in concrete (Qin et al., 2010). Karimov et al. (2015) demonstrated the performance of nanocomposite as a novel pressure and displacement capacitive sensor. Similarly, a flexible pressure sensor that uses micro-patterned films coated with CNTs was fabricated and used to measure the fluid pressure in the curved microtube by Yao et al. (2016). The feasibility of nanocomposite as pressure sensors was also demonstrated by Hasan et al. (2016). Nanocomposites have also proven to be promising candidates for sensing gas (Barthwal et al., 2018) and lead pollutants (Shirsat et al., 2018). Self-sensing nanocomposites have enormous potential to be applied as embedded sensors for continuous monitoring in structural health monitoring applications.
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Incorporation of CNTs into a matrix has proven to convert it into a piezo-resistive composite which exhibits change in electrical resistance with the change in mechanical load acting on it. It was demonstrated that the nanocomposites exhibited relatively higher sensitivities than conventional strain gauges under tensile and compressive strain and also exhibited a stable and durable response (Sanli et al., 2017). The conductive network formation, and thus, the strain sensitivity of the conductive nanocomposite can be tailored by controlling nanotube loading, degree of nanotube dispersion and film fabrication process (Pham et al., 2008). The electrical conductivity of the nanocomposite also greatly depends on the processing parameters of the composite like sonication time and curing time of the composite (Bouhamed et al., 2017). Yazdani et al. (2016) demonstrated that there are two stages of curing in polymer nanocomposite e in the first stage, firm bonds are formed between CNTs and polymer; with increasing curing time, evaporation of low-molecular fractions will take place and diffusion of isolated CNT aggregates takes place which reduces the volume of composite, which in turn increases the CNT-CNT contact. Similarly Das et al. (2002) explained the decrease in the electrical resistivity of polymer filled with carbon black upon curing based on two mechanisms: formation of charged species for current conduction that can be helpful for bridging the discontinuity of the conductive networks caused from the presence of aggregations and reducing of free volume due to curing reaction. The nanocomposites also performed well as dynamic strain sensors. The ability of MWCNTs/epoxy nanocomposites to serve as a dynamic strain sensor was demonstrated by Yin et al. (2011) and Spinelli et al. (2018). A study concerning the development of embedded sensors by using polymer nanocomposite for structural health monitoring in aeronautic structural parts was presented by Vertuccio et al. (2016).The piezo-resistive behavior of nanocomposite was investigated when the specimens were subjected to a low number of cycles and different levels of strain loaded in both axial tension and flexural mode. Electrically conductive nanocomposite was developed by Panozzo et al. (2017) for damage detection of a laminate. It was observed that there are two main causes for variation of electrical resistance in a CNT based laminate: first one is an irreversible electrical resistance change, caused by the onset and subsequent propagation of damage and other is a reversible electrical resistance change, due to the piezoresistive nature of the semi-conductive polymer, dependent of the strain level. Georgousis et al. (2015) also demonstrated the potential of MWCNTs/PVDF nanocomposites as a strain and damage detection sensor. Inam et al. (2014) investigated the damage sensing ability of three types of carbon nanofiller [graphene nanoplatelets (GNP), CNTs and carbon black (CB) nanoparticles] reinforced alumina. Change in electrical conductivities was analyzed after indentation to understand structural damage. It was identified from their investigations that CNTs impart superior damage sensing capability in alumina nanocomposites, in comparison to GNP and CB, due to their fibrous nature, high aspect ratio and high electrical conductivity. Due to the extraordinary conductive properties and high aspect ratio, CNTs are primarily used to impart conductivity into highly resistive materials. Vertuccio et al. (2015) demonstrated that there are two primary actions through which CNT
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Fig. 21.1 Schematic representation of conductivity in cementitious nanocomposite through percolation and tunneling effect.
incorporated composite becomes conductive: one is through the conductance of connected CNTs in the matrix and the other is through tunneling transport of electrons in the non-connected CNTs (shown in Fig. 21.1). It is also reported that the tunneling resistance plays an important role in imparting conductivity to the composite and the maximum tunneling distance of CNT is found to be around 1.8 nm. The resistivity of the nanocomposite greatly depends upon the type of CNT and its dosage. It was found that CNTs with short aspect ratio and curved shapes exhibit linear piezo-resistive response and the ones with high aspect ratio and straight shape exhibits non-liner response due to the dominant role of the tunneling resistance (Yin et al., 2011). The electrical conductivity of the nanocomposite greatly depends upon the dosage of CNTs. The conductivity of the composite increases steadily with the increase in the dosage of CNTs. Beyond certain dosage level, the conductivity improves drastically even with a meagre increase in the amount of CNTs. This corresponding dosage is called percolation threshold and the sudden rise in conductivity beyond the threshold limit is due to development of electrical conducting path of CNTs (as shown in Fig. 21.1C) within the composite (Yang et al., 2014). Several statistical (Chen et al., 2004) and micromechanics-based approach has been developed to determine the percolation threshold of the CNT nanocomposite (Yang et al., 2014; García-Macías et al., 2017). The promising improvement in electrical conductivity of polymer and metal nanocomposites encouraged the researchers to attempt in imparting conductivity into highly resistive material (in the order of 106e109 U cm), such as cementitious composite which can be used in structural health monitoring applications. However, unlike polymer and metal nanocomposites, the microstructure and behavior of cementitious composite is very complex. Since cementitious composite is highly porous in nature, the mode of conduction in the nanocomposite varies with variation in presence of water inside it. It has been identified that when cementitious nanocomposite is in saturated condition, the ionic conduction dominates, and in the dry state (after complete hydration), the conduction happens primarily through movement of electrons (Garboczi et al., 1995). The performance of the cementitious nanocomposite also depends upon the type of input voltage supplied to it. Han et al. (2012) identified that cementitious nanocomposite had both resistance and capacitance characteristics.
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In order to improve the pressure sensitivity of the composites and to remove the capacitor effect, low-amplitude AC voltage should be supplied rather than the DC supply. Conductive cementitious nanocomposites have been used in wide-range of applications. Lim et al. (2017) demonstrated the feasibility of using cementitious nanocompositefor crack monitoring of concrete structures. Ubertini et al. (2014) developed CNT-cement composite with 1% of CNTs that was able to track the excitation frequencies in the range of 0.25e15 Hz and detect the frequency of the fundamental vibration modes. Use of cementitious composite for developing the smart material through nanoengineering poses a great challenge due to its complicated microstructure with pores, time varying properties, extremely high electric resistance, non-repetitive structure/ property. Further, appropriate and uniform incorporation of nano material solutions to a viscous medium of cement composite is also challenging. In this chapter, the preparation of nano material solution, incorporation in cementitious composites, development of specimen, circuit design, experimental investigations under cyclic loading and dynamic condition are presented, in a thorough and systematic manner.
2. Materials and methods 2.1
Dispersion of CNTs/CNFs
As mentioned in preceeding section, the major challenge in developing cementitious nanocomposite is the uniform dispersion of nanofibers. The nanofibers like CNTs and CNFs (properties presented in Table 21.1) have a huge degree of self-attraction due to which they remain as bundles (called, agglomerates). Before incorporating into cementitious composite, they should be separated into individual fibers. This is done through a process called ultrasonication. During ultrasonication, high frequency mechanical vibrations are imparted into the solution. This causes the particles in the solution to collide with each other at high velocities. Due to this, the van der Waals forces in the agglomerates break, thereby, leading to proper dispersion of nanofibers in the liquid media. It has been proven that separation of nanofibers through sonication process is effective only in the presence of surfactants. These surfactant particles wrap around the surface of CNTs which prevents them to get re-agglomerated and creates stable suspension. In this work, sodium dodecylbenzene sulphonate (SDBS) is used as the surfactant. The surfactant powder is mixed with distilled water and subjected to magnetic stirring Table 21.1 Physical properties of nano tubes and fibers used in the present study. Nano material
Appearance
Outer diameter
Inner diameter
Length
Purity (%)
CNT
Black
50e80 nm
5e15 nm
10e20 mm
>95
CNF
Black
200e600 nm
5e50 nm
5e50 mm
>70
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to obtain uniform surfactant solution. To this surfactant solution, CNTs/CNFs are added at a concentration of 0.005 g/mL and subjected to magnetic stirring for 10 min. This aqueous solution is then subjected to sonication at room temperature for 1 h. Parameters like amplitude, frequency and duration of sonication play a key role in the quality of dispersion. The quality of dispersion can also be ascertained by certain techniques like particle size analysis and UVeVis spectroscopy. Spectroscopy is the study of the absorption and emission of light and other radiations by matter, as a function of the wavelength of the radiation. UVeVis spectroscopy is based on absorption spectroscopy or reflectance spectroscopy in the ultraviolete visible region collected using a UVeVis spectrometer. When nanofibers are dispersed in the surfactant solution, it becomes darker and will absorb more light and hence the maximum absorbance can be used as an indicator of dispersion quality (Njuguna et al., 2015). In this study, the stability of CNT-surfactant solution is characterized using UVeVis spectroscopy (MODEeDRS, Carry 5000 UV-VIS NIR, Agilent Technologies) operated at 200e800 nm range. Pure surfactant solution is used for baseline correction in this case. Dynamic Light Scattering (DLS) technique is used to carry out particle size analysis. In this study, the Z average hydrodynamic particle diameter and poly-dispersive index (PDI) are used to evaluate the quality of dispersion. The hydrodynamic particle diameter denotes the average size of the agglomerate in the aqueous solution. As a general rule, the PDI value higher than 0.5 is considered to be associated with poly-disperse/non-homogeneously distributed samples. In this study, these parameters are obtained from Malvern Zetasizer. Physical appearance of the CNT dispersed solution at different stages as mentioned above is depicted in Fig. 21.2. The sonicated solutions are subjected to centrifugation and the dispersion characteristics of the solution are evaluated before and after centrifugation to identify the optimum parameters. It has been identified in our studies that in order to obtain good dispersion, the following optimum parameters should be adopted: (i) amplitude of sonication should be maintained between 50% and 70%, (ii) frequency should be
Fig. 21.2 CNT dispersed solution (A) CNT þ Water, (B) CNT þ Water þ SDBS, (C) CNT þ Water þ SDBS þ Sonication, (D) CNT þ Water þ SDBS þ Sonication þ centrifuge at 3,000 rpm for 10 min.
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maintained between 40% and 50 % and (iii) minimum duration of sonication is 30 min. Surfactant to CNT (S/C) ratio also plays a key role in the quality of dispersion. The optimum S/C ratio has found to between 0.5 and 0.6. The detailed investigations carried out to identify the optimum parameters can be found in (Sasmal et al., 2017a).
2.2 2.2.1
Strain-based sensor Material preparation
Measured quantities of cement (Ordinary Portland Cement, Grade 53) and sand (sieved through 2.75 mm sieve) were mixed thoroughly in a rotary mixer with flat beater (as shown in Fig. 21.3). To this mix, sonicated CNT/CNF solution and the remaining water (pertaining to w/c ratio 0.35) were poured and mixed for 3 min at high speed. Since the surfactant entraps more air into the mix, defoamer (tributyl phosphate) of 0.25% of total volume was slowly added to the mix to neutralize the air bubbles. The mix was then poured into the prism specimens of size 160 40 40 mm. Four copper meshes (of size 1.6 mm) were embedded inside the prism specimens with a spacing of 10 mm, 40 mm and 10 mm. These copper meshes serve as electrodes for input supply and output measurement. The specimens were placed in the vibration table to achieve compactness. The specimens were cured in air at a temperature of 20 C for 7 days. The specimens were then kept in an oven at a temperature of 60 C for 3 days before testing to eliminate water in it.
Fig. 21.3 Process (schematic representation) of synthesising cementitious nanocomposite.
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2.2.2
Testing
Four probe method was employed to evaluate the electrical conductive nature of the developed cementitious nanocomposite. The circuit of the four-probe method is provided in Fig. 21.4. In four-probe method, the input power supply (AC or DC) is provided to the outer two copper electrodes and the conductivity of the nanocomposites is determined by measuring the potential difference between inner two electrodes embedded inside the specimen. In order to assess the piezo-resistive behavior of the cementitious nanocomposite, the fabricated prism specimens were subjected compressive loading in a compression testing machine (CTM). The specimens were subjected to elastic-cyclic compressive loading with the load varying from 5 to 35 kN at a rate of 40 N/s. Due to the change in load, the microstructure of the cementitious nanocomposites get altered which causes change in potential difference between the electrodes. The electrical resistivity (r) of sample is measured using, a r¼ r l
(21.1)
LOAD
(A)
AC o or DC sup pply
(B)
V
Data Acquisition System m
(C)
Fig. 21.4 Test set-up (A) Schematic, (B) Experimental specimen, and (C) Instrumentation with DAQ and voltage stabilizer) to evaluate the piezo-resistivity of cementitious nanocomposite using four-probe method.
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where, a is area of cross section of sample (cm2), l is the distance between inner electrodes (cm) and r is the electrical resistance (U). The change in potential difference during cyclic compressive test can be measured from, DVð%Þ ¼
V V0 100 V0
(21.2)
where, V0 is the potential drop before loading and V is the varying potential drop at any loading time. The rate of change of output voltage with respect to the applied cyclic load was recorded continuously in order to assess the dynamic sensing capacity of the developed cementitious nanocomposite.
2.3 2.3.1
Acceleration-based sensor Material preparation
Measured quantities of cement (Ordinary Portland Cement, Grade 53) was mixed in a rotary mixer to crumble the lumps present in it. To this, sonicated CNT/CNF solution and the remaining water were poured and mixed for 3 min at high speed. Defoamer was then slowly added and mixed thoroughly. The mix was poured in a prism molds of size 160 40 40 mm. Four copper electrodes were embedded inside the specimen during casting. The specimens were compacted well by subjecting it to machine vibration and cured in air at a temperature of 20 C. The excess water in the specimens were then removed by subjecting them to a temperature of 60 C for 3 days before testing.
2.3.2
Testing
The performance of the developed cementitious nanocomposite as acceleration sensors was evaluated by carrying out a free vibration test on a simply supported reinforced concrete (RC) beam (shown in Fig. 21.5). The span of the RC beam is 1500 mm and the cross-section is 150 200 mm. An initial prestress was applied to the cementitious nanocomposite through a special mechanical arrangement to get better signal resolution. Three conventional accelerometers (with the frequency range of 0.4e6 kHz) were placed at the bottom of the beam to validate the response obtained from cementitious nanocomposite. Free vibration tests were performed on the RC beam using impulse hammer. The beam was randomly hit to generate ambient vibration.
3. Results and discussion 3.1
Strain-based sensor
The response of the piezo-resistive cementitious nanocomposite (CNT and CNF based) under static cyclic loading is provided in Fig. 21.6. In both the type of composites, the resistivity decreases when being subjected to compressive loading and the
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Fig. 21.5 Test set-up (A) Schematic, (B) Experimental specimen to evaluate the performance of the developed cementitious nanocomposite as acceleration sensors.
Fig. 21.6 Piezo-resistive nature of (A) CNT and (B) CNF based cementitious nanocomposite.
counter-action takes place when the load is released. It is also observed from the figure that the response of the composite varies with the change in filler content. In both the cases, the piezo-resistivity is excellent at low filler content (0.05% CNT and 0.1% CNF). This may be due to the fact that at low filler content, the width of the matrix reduces which makes electronic conduction easier by tunneling process. However, at higher filler content, a stable conducting network is formed, which is hard to deform under applied stress. Hence, nanocomposite with higher filler content is less sensitive
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Fig. 21.7 Sensitivity of the developed cementitious nanocomposite.
to change in stress. It is also to note that, nanocomposites with low filler content needs longer time to get polarised. The piezo-resistive nature of cementitious nanocomposite also depends upon many factors like the applied electric field (input current/voltage), hydration time of the composite, etc. The influence of these parameters on the piezoresistive response of cementitious nanocomposite and the optimum parameters are explained in detail in (Sasmal et al., 2017b). The sensitivity of the developed piezo-resistive cementitious nanocomposites is quantified by means of gauge factor (shown in Fig. 21.7). It is worth mentioning that the gauge factor, which is the measure of fractional change in resistivity over change in strain of the developed cementitious nanocomposite (CNT and CNF based) is found to be 189 and 228, respectively.
3.2
Acceleration-based sensor
The response of the beam when subjected to ambient vibration was captured by cementitious nanocomposite and conventional accelerometers using data acquisition system. High sampling rate was used to capture the data. A high pass filter (above 10 Hz) was used to minimize the noise in the measured acceleration data of cementitious nanocomposite. From the obtained response, the fundamental frequencies corresponding to first five vertical vibrational modes were identified between 0 and 200 Hz (shown in Fig. 21.8). No clear peaks were detected at frequencies above 140 Hz. A comparison of the fundamental frequencies obtained from cementitious nanocomposite with the conventional accelerometers and analytical results is provided in Table 21.2. The signals obtained from the developed cementitious nanocomposite demonstrates the feasibility of using it as acceleration sensor to capture the fundamental frequencies of the structures.
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–20 –30
[dBm]
–40 –50 –60 –70 –80 –90
0
120 140 160 180 80 100 Frequency [Hz] (Red: Cementitious nanocomposite, Blue: Conventional accelerometer) 20
40
60
200
Fig. 21.8 Frequency response obtained from developed cementitious nanocomposite and conventional accelerometer (showing three fundamental frequencies under 5 V), (Red: Cementitious nanocomposite, Blue: Conventional accelerometer).
Table 21.2 Fundamental frequencies (in Hz) of RC beam subjected ambient vibration identified by cementitious nanocomposite, conventional accelerometer and from analytical response. Cementitious nanocomposite
Conventional accelerometer
Analytical response
17.5
15
15.6
e
e
27.1
44
45.5
46.6
66
69.1
70.2
136
140
143.9
4.
Conclusions and future scope of work
Since the need and complexity of continuous health monitoring of structures are increasing day by day, development of appropriate and smart sensors is pivotal for the success. Generally, the electric resistant strain gauges and piezo based acceleration sensors which are affixed or mounted on structure are being used for capturing the structural signal. Many attempts are in place to develop cement based sensors which can be embedded inside the structures and can be used for continuous sensing during monitoring the structures. It will not only reduce the requirement of affixing the sensors time to time, it will dramatically expand the scope of embedded sensors for health monitoring of large scale reinforced and prestressed concrete structures. In this chapter, the methodology for development of smart cementitious nano composites for strain and acceleration sensing is presented. Cement based composite is used as the base material and carbon nano tube/Carbon nano fibers are incorporated suitably.
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Performance of the developed sensors under cyclic and dynamic loading conditions are presented. It is found that the developed sensors are able to capture the response parameters with considerable accuracy. The investigations carried out and the observations made showed that the development can further be expanded for developing (i) smart composite sensor for large area monitoring, (ii) smart skins for inaccessible structures, (iii) smart composite for temperature and pressure sensing, (iv) energy harvesting from the open structures, etc. However, since the investigation is trans-disciplinary in nature and needs deep understanding in material synthesis, micromechanics, electric conductivity, electronics and signal processing, a concerted and well-conceived approach would be extremely helpful to develop the innovative, smart and functional cementitious nanocomposites.
Acknowledgments The authors would like to acknowledge the support received from the scientists and staff of Special and Multifunctional Structures Laboratory, CSIR-SERC. Special thanks to Mr. N. Ravivarman, and Mr. K. Vignesh, former Senior Project Fellows (as part of CSIR funded XII FYP project entitled “e-NanoTics”), for their immense help rendered during material characterization, specimen preparation and experimentations.
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Vertuccio, L., Vittoria, V., Guadagno, L., De Santis, F., 2015. Strain and damage monitoring in carbon-nanotube-based composite under cyclic strain. Composites Part A: Applied Science and Manufacturing 71, 9e16. Vertuccio, L., Guadagno, L., Spinelli, G., Lamberti, P., Tucci, V., Russo, S., 2016. Piezoresistive properties of resin reinforced with carbon nanotubes for health-monitoring of aircraft primary structures. Composites Part B: Engineering 107, 192e202. Yang, B.J., Cho, K.J., Kim, G.M., Lee, H.K., 2014. Effect of CNT agglomeration on the electrical conductivity and percolation threshold of nanocomposites: a micromechanicsbased approach. Computer Modeling in Engineering and Sciences 103 (5), 343e365. Yao, J.L., Yang, X., Shao, N., Luo, H., Zhang, T., Jiang, W.G., 2016. A flexible and highly sensitive piezoresistive pressure sensor based on micropatterned films coated with carbon nanotubes. Journal of Nanomaterials 2016, 3024815. Yazdani, H., Smith, B.E., Hatami, K., 2016. Multi-walled carbon nanotube-filled polyvinyl chloride composites: influence of processing method on dispersion quality, electrical conductivity and mechanical properties. Composites Part A: Applied Science and Manufacturing 82, 65e77. Yin, G., Hu, N., Karube, Y., Liu, Y., Li, Y., Fukunaga, H., 2011. A carbon nanotube/polymer strain sensor with linear and anti-symmetric piezoresistivity. Journal of Composite Materials 45 (12), 1315e1323. Yu, X., Kwon, E., 2009. A carbon nanotube/cement composite with piezoresistive properties. Smart Materials and Structures 18 (5), 055010. Zhao, Y.H., 2014. Effect of CNT/CNF on thermal and mechanical properties of cement mortars. In: Advanced Materials Research, vol. 1049. Trans Tech Publications, pp. 234e237. Zuo, J., Yao, W., Wu, K., 2015. Seebeck effect and mechanical properties of carbon nanotubecarbon fiber/cement nanocomposites. Fullerenes, Nanotubes, and Carbon Nanostructures 23 (5), 383e391.
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Saptarshi Sasmal, B.S. Sindu Scientist, Special and Multifunctional Structures Laboratory, CSIR-Structural Engineering Research Centre, Taramani, Chennai, India
Chapter outline 1. Introduction 485 2. Materials and methods 2.1 2.2
2.3
3. Results and discussion 3.1 3.2
489
Dispersion of CNTs/CNFs 489 Strain-based sensor 491 2.2.1 Material preparation 491 2.2.2 Testing 492 Acceleration-based sensor 493 2.3.1 Material preparation 493 2.3.2 Testing 493 Strain-based sensor 493 Acceleration-based sensor
493 495
4. Conclusions and future scope of work Acknowledgments 497 References 497
496
1. Introduction There is a rapid advancement in the development of cementitious composite during the last two decades. The advancements have been made in all areas including materials, mix proportionating, durability, recycling and environmental-friendliness. Initial research aimed at improving the mechanical properties like strength, strain carrying capacity and durability of cementitious composite. High strength concrete, ultrahigh performance concrete, fiber reinforced concrete, strain hardened cementitious composite, ferro-cement are some of the examples. The next stage of research includes
Smart Nanoconcretes and Cement-Based Materials. https://doi.org/10.1016/B978-0-12-817854-6.00021-0 Copyright © 2020 Elsevier Inc. All rights reserved.
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development of eco-friendly concrete by utilising industrial wastes and recycled aggregates, light weight concrete, etc. In the world of smart technologies, in addition to development of cementitious composite with improved mechanical properties, there is a need to develop smart composites with multifunctional capabilities and that can take care of its own shortcomings. For example, self-compacting concrete which is highly flowable and does not require vibration; self-curing concrete which contains capsules of membrane-forming curing compound which open up when the surface becomes dry; self-healing concrete in which micro-cracks/damages, caused in the material, are sensed automatically and healed by releasing the healing agent; and self-sensing concrete which can be used for sensing purposes. Self-sensing composites are developed by incorporating electrically conductive materials like carbon fibers, carbon nanotubes (CNTs), carbon nanofibers (CNFs), piezo-ceramics, piezo-polymers, etc into the parent (matrix) material. Incorporation of these materials into a matrix has been proven to be effective in converting it into a piezo-resistive composite which exhibits change in electrical resistance with the change in mechanical load acting on it. These self-sensing composites are extremely promising and are being used in variety of applications, like traffic monitoring, temperature sensing, pressure sensing and structural health monitoring. The utilization of selfsensing nanocomposites as temperature sensors has been demonstrated by Qin et al. (2013). They developed a temperature sensitive nanocomposite by incorporating 0.4% of carbon fibers and 1.5% of CNTs which had a temperature sensitivity coefficient of 8 104/ C. Zhao (2014) developed a nanocomposite by incorporating phase change materials which improved its thermal conductivity by 26%. It was also demonstrated that nanocomposite developed by incorporation of 0.5% of CNTs had thermoelectric power improved by 260% (Zuo et al., 2015). The conductive properties of nanocomposite were explored to develop self-heating and deicing material by Gomis et al. (2015). Electric potential difference is applied through the smart composite which causes heating of the material. The maximum temperature which could be attained depends on the electric power that had been applied, which in turn depends on the electrical resistance of the material. This causes melting of the ice deposited on the roads or prevent its formation from freezing of the moisture. Han et al. (2009) demonstrated the use self-sensing nanocomposite in traffic monitoring applications such as traffic flow detection, weigh-in-motion measurement and vehicle speed detection. Yu and Kwon (2009) explored the feasibility of using nanocomposite for traffic flow measurements in roadways, levees and bridges. Smart nanocomposite was also used to detect the acoustic emission (AE) activities in concrete (Qin et al., 2010). Karimov et al. (2015) demonstrated the performance of nanocomposite as a novel pressure and displacement capacitive sensor. Similarly, a flexible pressure sensor that uses micro-patterned films coated with CNTs was fabricated and used to measure the fluid pressure in the curved microtube by Yao et al. (2016). The feasibility of nanocomposite as pressure sensors was also demonstrated by Hasan et al. (2016). Nanocomposites have also proven to be promising candidates for sensing gas (Barthwal et al., 2018) and lead pollutants (Shirsat et al., 2018). Self-sensing nanocomposites have enormous potential to be applied as embedded sensors for continuous monitoring in structural health monitoring applications.
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Incorporation of CNTs into a matrix has proven to convert it into a piezo-resistive composite which exhibits change in electrical resistance with the change in mechanical load acting on it. It was demonstrated that the nanocomposites exhibited relatively higher sensitivities than conventional strain gauges under tensile and compressive strain and also exhibited a stable and durable response (Sanli et al., 2017). The conductive network formation, and thus, the strain sensitivity of the conductive nanocomposite can be tailored by controlling nanotube loading, degree of nanotube dispersion and film fabrication process (Pham et al., 2008). The electrical conductivity of the nanocomposite also greatly depends on the processing parameters of the composite like sonication time and curing time of the composite (Bouhamed et al., 2017). Yazdani et al. (2016) demonstrated that there are two stages of curing in polymer nanocomposite e in the first stage, firm bonds are formed between CNTs and polymer; with increasing curing time, evaporation of low-molecular fractions will take place and diffusion of isolated CNT aggregates takes place which reduces the volume of composite, which in turn increases the CNT-CNT contact. Similarly Das et al. (2002) explained the decrease in the electrical resistivity of polymer filled with carbon black upon curing based on two mechanisms: formation of charged species for current conduction that can be helpful for bridging the discontinuity of the conductive networks caused from the presence of aggregations and reducing of free volume due to curing reaction. The nanocomposites also performed well as dynamic strain sensors. The ability of MWCNTs/epoxy nanocomposites to serve as a dynamic strain sensor was demonstrated by Yin et al. (2011) and Spinelli et al. (2018). A study concerning the development of embedded sensors by using polymer nanocomposite for structural health monitoring in aeronautic structural parts was presented by Vertuccio et al. (2016).The piezo-resistive behavior of nanocomposite was investigated when the specimens were subjected to a low number of cycles and different levels of strain loaded in both axial tension and flexural mode. Electrically conductive nanocomposite was developed by Panozzo et al. (2017) for damage detection of a laminate. It was observed that there are two main causes for variation of electrical resistance in a CNT based laminate: first one is an irreversible electrical resistance change, caused by the onset and subsequent propagation of damage and other is a reversible electrical resistance change, due to the piezoresistive nature of the semi-conductive polymer, dependent of the strain level. Georgousis et al. (2015) also demonstrated the potential of MWCNTs/PVDF nanocomposites as a strain and damage detection sensor. Inam et al. (2014) investigated the damage sensing ability of three types of carbon nanofiller [graphene nanoplatelets (GNP), CNTs and carbon black (CB) nanoparticles] reinforced alumina. Change in electrical conductivities was analyzed after indentation to understand structural damage. It was identified from their investigations that CNTs impart superior damage sensing capability in alumina nanocomposites, in comparison to GNP and CB, due to their fibrous nature, high aspect ratio and high electrical conductivity. Due to the extraordinary conductive properties and high aspect ratio, CNTs are primarily used to impart conductivity into highly resistive materials. Vertuccio et al. (2015) demonstrated that there are two primary actions through which CNT
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Fig. 21.1 Schematic representation of conductivity in cementitious nanocomposite through percolation and tunneling effect.
incorporated composite becomes conductive: one is through the conductance of connected CNTs in the matrix and the other is through tunneling transport of electrons in the non-connected CNTs (shown in Fig. 21.1). It is also reported that the tunneling resistance plays an important role in imparting conductivity to the composite and the maximum tunneling distance of CNT is found to be around 1.8 nm. The resistivity of the nanocomposite greatly depends upon the type of CNT and its dosage. It was found that CNTs with short aspect ratio and curved shapes exhibit linear piezo-resistive response and the ones with high aspect ratio and straight shape exhibits non-liner response due to the dominant role of the tunneling resistance (Yin et al., 2011). The electrical conductivity of the nanocomposite greatly depends upon the dosage of CNTs. The conductivity of the composite increases steadily with the increase in the dosage of CNTs. Beyond certain dosage level, the conductivity improves drastically even with a meagre increase in the amount of CNTs. This corresponding dosage is called percolation threshold and the sudden rise in conductivity beyond the threshold limit is due to development of electrical conducting path of CNTs (as shown in Fig. 21.1C) within the composite (Yang et al., 2014). Several statistical (Chen et al., 2004) and micromechanics-based approach has been developed to determine the percolation threshold of the CNT nanocomposite (Yang et al., 2014; García-Macías et al., 2017). The promising improvement in electrical conductivity of polymer and metal nanocomposites encouraged the researchers to attempt in imparting conductivity into highly resistive material (in the order of 106e109 U cm), such as cementitious composite which can be used in structural health monitoring applications. However, unlike polymer and metal nanocomposites, the microstructure and behavior of cementitious composite is very complex. Since cementitious composite is highly porous in nature, the mode of conduction in the nanocomposite varies with variation in presence of water inside it. It has been identified that when cementitious nanocomposite is in saturated condition, the ionic conduction dominates, and in the dry state (after complete hydration), the conduction happens primarily through movement of electrons (Garboczi et al., 1995). The performance of the cementitious nanocomposite also depends upon the type of input voltage supplied to it. Han et al. (2012) identified that cementitious nanocomposite had both resistance and capacitance characteristics.
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In order to improve the pressure sensitivity of the composites and to remove the capacitor effect, low-amplitude AC voltage should be supplied rather than the DC supply. Conductive cementitious nanocomposites have been used in wide-range of applications. Lim et al. (2017) demonstrated the feasibility of using cementitious nanocompositefor crack monitoring of concrete structures. Ubertini et al. (2014) developed CNT-cement composite with 1% of CNTs that was able to track the excitation frequencies in the range of 0.25e15 Hz and detect the frequency of the fundamental vibration modes. Use of cementitious composite for developing the smart material through nanoengineering poses a great challenge due to its complicated microstructure with pores, time varying properties, extremely high electric resistance, non-repetitive structure/ property. Further, appropriate and uniform incorporation of nano material solutions to a viscous medium of cement composite is also challenging. In this chapter, the preparation of nano material solution, incorporation in cementitious composites, development of specimen, circuit design, experimental investigations under cyclic loading and dynamic condition are presented, in a thorough and systematic manner.
2. Materials and methods 2.1
Dispersion of CNTs/CNFs
As mentioned in preceeding section, the major challenge in developing cementitious nanocomposite is the uniform dispersion of nanofibers. The nanofibers like CNTs and CNFs (properties presented in Table 21.1) have a huge degree of self-attraction due to which they remain as bundles (called, agglomerates). Before incorporating into cementitious composite, they should be separated into individual fibers. This is done through a process called ultrasonication. During ultrasonication, high frequency mechanical vibrations are imparted into the solution. This causes the particles in the solution to collide with each other at high velocities. Due to this, the van der Waals forces in the agglomerates break, thereby, leading to proper dispersion of nanofibers in the liquid media. It has been proven that separation of nanofibers through sonication process is effective only in the presence of surfactants. These surfactant particles wrap around the surface of CNTs which prevents them to get re-agglomerated and creates stable suspension. In this work, sodium dodecylbenzene sulphonate (SDBS) is used as the surfactant. The surfactant powder is mixed with distilled water and subjected to magnetic stirring Table 21.1 Physical properties of nano tubes and fibers used in the present study. Nano material
Appearance
Outer diameter
Inner diameter
Length
Purity (%)
CNT
Black
50e80 nm
5e15 nm
10e20 mm
>95
CNF
Black
200e600 nm
5e50 nm
5e50 mm
>70
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to obtain uniform surfactant solution. To this surfactant solution, CNTs/CNFs are added at a concentration of 0.005 g/mL and subjected to magnetic stirring for 10 min. This aqueous solution is then subjected to sonication at room temperature for 1 h. Parameters like amplitude, frequency and duration of sonication play a key role in the quality of dispersion. The quality of dispersion can also be ascertained by certain techniques like particle size analysis and UVeVis spectroscopy. Spectroscopy is the study of the absorption and emission of light and other radiations by matter, as a function of the wavelength of the radiation. UVeVis spectroscopy is based on absorption spectroscopy or reflectance spectroscopy in the ultraviolete visible region collected using a UVeVis spectrometer. When nanofibers are dispersed in the surfactant solution, it becomes darker and will absorb more light and hence the maximum absorbance can be used as an indicator of dispersion quality (Njuguna et al., 2015). In this study, the stability of CNT-surfactant solution is characterized using UVeVis spectroscopy (MODEeDRS, Carry 5000 UV-VIS NIR, Agilent Technologies) operated at 200e800 nm range. Pure surfactant solution is used for baseline correction in this case. Dynamic Light Scattering (DLS) technique is used to carry out particle size analysis. In this study, the Z average hydrodynamic particle diameter and poly-dispersive index (PDI) are used to evaluate the quality of dispersion. The hydrodynamic particle diameter denotes the average size of the agglomerate in the aqueous solution. As a general rule, the PDI value higher than 0.5 is considered to be associated with poly-disperse/non-homogeneously distributed samples. In this study, these parameters are obtained from Malvern Zetasizer. Physical appearance of the CNT dispersed solution at different stages as mentioned above is depicted in Fig. 21.2. The sonicated solutions are subjected to centrifugation and the dispersion characteristics of the solution are evaluated before and after centrifugation to identify the optimum parameters. It has been identified in our studies that in order to obtain good dispersion, the following optimum parameters should be adopted: (i) amplitude of sonication should be maintained between 50% and 70%, (ii) frequency should be
Fig. 21.2 CNT dispersed solution (A) CNT þ Water, (B) CNT þ Water þ SDBS, (C) CNT þ Water þ SDBS þ Sonication, (D) CNT þ Water þ SDBS þ Sonication þ centrifuge at 3,000 rpm for 10 min.
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maintained between 40% and 50 % and (iii) minimum duration of sonication is 30 min. Surfactant to CNT (S/C) ratio also plays a key role in the quality of dispersion. The optimum S/C ratio has found to between 0.5 and 0.6. The detailed investigations carried out to identify the optimum parameters can be found in (Sasmal et al., 2017a).
2.2 2.2.1
Strain-based sensor Material preparation
Measured quantities of cement (Ordinary Portland Cement, Grade 53) and sand (sieved through 2.75 mm sieve) were mixed thoroughly in a rotary mixer with flat beater (as shown in Fig. 21.3). To this mix, sonicated CNT/CNF solution and the remaining water (pertaining to w/c ratio 0.35) were poured and mixed for 3 min at high speed. Since the surfactant entraps more air into the mix, defoamer (tributyl phosphate) of 0.25% of total volume was slowly added to the mix to neutralize the air bubbles. The mix was then poured into the prism specimens of size 160 40 40 mm. Four copper meshes (of size 1.6 mm) were embedded inside the prism specimens with a spacing of 10 mm, 40 mm and 10 mm. These copper meshes serve as electrodes for input supply and output measurement. The specimens were placed in the vibration table to achieve compactness. The specimens were cured in air at a temperature of 20 C for 7 days. The specimens were then kept in an oven at a temperature of 60 C for 3 days before testing to eliminate water in it.
Fig. 21.3 Process (schematic representation) of synthesising cementitious nanocomposite.
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2.2.2
Testing
Four probe method was employed to evaluate the electrical conductive nature of the developed cementitious nanocomposite. The circuit of the four-probe method is provided in Fig. 21.4. In four-probe method, the input power supply (AC or DC) is provided to the outer two copper electrodes and the conductivity of the nanocomposites is determined by measuring the potential difference between inner two electrodes embedded inside the specimen. In order to assess the piezo-resistive behavior of the cementitious nanocomposite, the fabricated prism specimens were subjected compressive loading in a compression testing machine (CTM). The specimens were subjected to elastic-cyclic compressive loading with the load varying from 5 to 35 kN at a rate of 40 N/s. Due to the change in load, the microstructure of the cementitious nanocomposites get altered which causes change in potential difference between the electrodes. The electrical resistivity (r) of sample is measured using, a r¼ r l
(21.1)
LOAD
(A)
AC o or DC sup pply
(B)
V
Data Acquisition System m
(C)
Fig. 21.4 Test set-up (A) Schematic, (B) Experimental specimen, and (C) Instrumentation with DAQ and voltage stabilizer) to evaluate the piezo-resistivity of cementitious nanocomposite using four-probe method.
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where, a is area of cross section of sample (cm2), l is the distance between inner electrodes (cm) and r is the electrical resistance (U). The change in potential difference during cyclic compressive test can be measured from, DVð%Þ ¼
V V0 100 V0
(21.2)
where, V0 is the potential drop before loading and V is the varying potential drop at any loading time. The rate of change of output voltage with respect to the applied cyclic load was recorded continuously in order to assess the dynamic sensing capacity of the developed cementitious nanocomposite.
2.3 2.3.1
Acceleration-based sensor Material preparation
Measured quantities of cement (Ordinary Portland Cement, Grade 53) was mixed in a rotary mixer to crumble the lumps present in it. To this, sonicated CNT/CNF solution and the remaining water were poured and mixed for 3 min at high speed. Defoamer was then slowly added and mixed thoroughly. The mix was poured in a prism molds of size 160 40 40 mm. Four copper electrodes were embedded inside the specimen during casting. The specimens were compacted well by subjecting it to machine vibration and cured in air at a temperature of 20 C. The excess water in the specimens were then removed by subjecting them to a temperature of 60 C for 3 days before testing.
2.3.2
Testing
The performance of the developed cementitious nanocomposite as acceleration sensors was evaluated by carrying out a free vibration test on a simply supported reinforced concrete (RC) beam (shown in Fig. 21.5). The span of the RC beam is 1500 mm and the cross-section is 150 200 mm. An initial prestress was applied to the cementitious nanocomposite through a special mechanical arrangement to get better signal resolution. Three conventional accelerometers (with the frequency range of 0.4e6 kHz) were placed at the bottom of the beam to validate the response obtained from cementitious nanocomposite. Free vibration tests were performed on the RC beam using impulse hammer. The beam was randomly hit to generate ambient vibration.
3. Results and discussion 3.1
Strain-based sensor
The response of the piezo-resistive cementitious nanocomposite (CNT and CNF based) under static cyclic loading is provided in Fig. 21.6. In both the type of composites, the resistivity decreases when being subjected to compressive loading and the
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Fig. 21.5 Test set-up (A) Schematic, (B) Experimental specimen to evaluate the performance of the developed cementitious nanocomposite as acceleration sensors.
Fig. 21.6 Piezo-resistive nature of (A) CNT and (B) CNF based cementitious nanocomposite.
counter-action takes place when the load is released. It is also observed from the figure that the response of the composite varies with the change in filler content. In both the cases, the piezo-resistivity is excellent at low filler content (0.05% CNT and 0.1% CNF). This may be due to the fact that at low filler content, the width of the matrix reduces which makes electronic conduction easier by tunneling process. However, at higher filler content, a stable conducting network is formed, which is hard to deform under applied stress. Hence, nanocomposite with higher filler content is less sensitive
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Fig. 21.7 Sensitivity of the developed cementitious nanocomposite.
to change in stress. It is also to note that, nanocomposites with low filler content needs longer time to get polarised. The piezo-resistive nature of cementitious nanocomposite also depends upon many factors like the applied electric field (input current/voltage), hydration time of the composite, etc. The influence of these parameters on the piezoresistive response of cementitious nanocomposite and the optimum parameters are explained in detail in (Sasmal et al., 2017b). The sensitivity of the developed piezo-resistive cementitious nanocomposites is quantified by means of gauge factor (shown in Fig. 21.7). It is worth mentioning that the gauge factor, which is the measure of fractional change in resistivity over change in strain of the developed cementitious nanocomposite (CNT and CNF based) is found to be 189 and 228, respectively.
3.2
Acceleration-based sensor
The response of the beam when subjected to ambient vibration was captured by cementitious nanocomposite and conventional accelerometers using data acquisition system. High sampling rate was used to capture the data. A high pass filter (above 10 Hz) was used to minimize the noise in the measured acceleration data of cementitious nanocomposite. From the obtained response, the fundamental frequencies corresponding to first five vertical vibrational modes were identified between 0 and 200 Hz (shown in Fig. 21.8). No clear peaks were detected at frequencies above 140 Hz. A comparison of the fundamental frequencies obtained from cementitious nanocomposite with the conventional accelerometers and analytical results is provided in Table 21.2. The signals obtained from the developed cementitious nanocomposite demonstrates the feasibility of using it as acceleration sensor to capture the fundamental frequencies of the structures.
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–20 –30
[dBm]
–40 –50 –60 –70 –80 –90
0
120 140 160 180 80 100 Frequency [Hz] (Red: Cementitious nanocomposite, Blue: Conventional accelerometer) 20
40
60
200
Fig. 21.8 Frequency response obtained from developed cementitious nanocomposite and conventional accelerometer (showing three fundamental frequencies under 5 V), (Red: Cementitious nanocomposite, Blue: Conventional accelerometer).
Table 21.2 Fundamental frequencies (in Hz) of RC beam subjected ambient vibration identified by cementitious nanocomposite, conventional accelerometer and from analytical response. Cementitious nanocomposite
Conventional accelerometer
Analytical response
17.5
15
15.6
e
e
27.1
44
45.5
46.6
66
69.1
70.2
136
140
143.9
4.
Conclusions and future scope of work
Since the need and complexity of continuous health monitoring of structures are increasing day by day, development of appropriate and smart sensors is pivotal for the success. Generally, the electric resistant strain gauges and piezo based acceleration sensors which are affixed or mounted on structure are being used for capturing the structural signal. Many attempts are in place to develop cement based sensors which can be embedded inside the structures and can be used for continuous sensing during monitoring the structures. It will not only reduce the requirement of affixing the sensors time to time, it will dramatically expand the scope of embedded sensors for health monitoring of large scale reinforced and prestressed concrete structures. In this chapter, the methodology for development of smart cementitious nano composites for strain and acceleration sensing is presented. Cement based composite is used as the base material and carbon nano tube/Carbon nano fibers are incorporated suitably.
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Performance of the developed sensors under cyclic and dynamic loading conditions are presented. It is found that the developed sensors are able to capture the response parameters with considerable accuracy. The investigations carried out and the observations made showed that the development can further be expanded for developing (i) smart composite sensor for large area monitoring, (ii) smart skins for inaccessible structures, (iii) smart composite for temperature and pressure sensing, (iv) energy harvesting from the open structures, etc. However, since the investigation is trans-disciplinary in nature and needs deep understanding in material synthesis, micromechanics, electric conductivity, electronics and signal processing, a concerted and well-conceived approach would be extremely helpful to develop the innovative, smart and functional cementitious nanocomposites.
Acknowledgments The authors would like to acknowledge the support received from the scientists and staff of Special and Multifunctional Structures Laboratory, CSIR-SERC. Special thanks to Mr. N. Ravivarman, and Mr. K. Vignesh, former Senior Project Fellows (as part of CSIR funded XII FYP project entitled “e-NanoTics”), for their immense help rendered during material characterization, specimen preparation and experimentations.
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