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Water-stable proteins may offer a new field of applications in smart materials for buildings and infrastructures where hydraulic reactions are involved. In this study, cement mortars modified through water-soluble silk fibroin (SF) are proposed. Water-soluble SF obtained by redissolving SF films in phosphate buffer solution (PBS) showed the formation of a gel with the β sheet features of silk II. Electrical measurements of SF indicate that calcium ions are primarily involved in the conductivity mechanism. By exploiting the water solubility properties of silk II and Ca2+ ion transport phenomena as well as their trapping effect on water molecules, SF provides piezoresistive and piezocapacitive properties to cement mortars, thus enabling self-sensing of mechanical strain, which is quite attractive in structural health monitoring applications. The SF/cement-based composite introduces a capacitive gauge factor which surpasses the traditional resistive gauge factor reported in the literature by threefold. Cyclic voltammetry measurements demonstrated that the SF/cement mortars possessed memcapacitive behavior for positive potentials near +5 V, which was attributed to an interfacial charge build-up modulated by the SF concentration and the working electrode. Electrical square-biphasic excitation combined with cyclic compressive loads revealed memristive behavior during the unloading stages. These findings, along with the availability and sustainability of SF, pave the way for the design of novel multifunctional materials, particularly for applications in masonry and concrete structures. [ABSTRACT FROM AUTHOR]

Large structures need to be monitored to ensure safety for users and increase their service life through predictive maintenance. Self-sensing cementitious composites have been studied for structural health monitoring applications. By adding carbon nanotubes (CNTs) to a cement matrix, the resulting composite exhibits piezoresistive properties, making it capable of monitoring strain and mechanical stresses. However, due to their porous microstructure, the electrical properties of these cementitious composites are affected by moisture. This work studies the influence of water in the pores of a cement paste on the electrical resistivity, self-sensing capability, and electrification effects of cement pastes with different amounts of CNT. It was found that for pastes with lower amounts of CNT, the presence of water decreased electrical resistivity and increased electrical polarization effects and self-sensing sensitivity to strain, but not to failure. On the other hand, pastes with higher CNT content were less affected by the presence of water in the pores of the cementitious matrix. It was concluded that a minimum amount of CNT, above the percolation region, can minimize the effects of moisture variations on electrical properties. Practical Applications: The construction industry is one of the most traditional in the world. Nevertheless, it has undergone a significant transformation and evolution through the adoption of new materials. Nanotechnology has played a pivotal role in the development of cementitious materials with novel properties, such as self-healing, energy absorption, self-cleaning characteristics, and the ability to monitor deformations, among others. It is within this context that smart cementitious composites emerge, maintaining their pre-existing properties and functionalities while incorporating new ones. Among these, self-sensing cementitious composites are specialized cement-based materials designed to monitor the safety performance of construction structures. When incorporated into structures, they can correlate their electrical properties with the deformations experienced, providing real-time monitoring of the conditions of these buildings. Self-monitoring cementitious composites serve as sensors for monitoring pavements and large structures such as dams, bridges, and viaducts. Their significant advantage lies in being manufactured from the same material as most structures, ensuring excellent compatibility and greater durability compared to other commercial sensors. [ABSTRACT FROM AUTHOR]

Development of smart nanocomposites by reinforcing carbon nanomaterials into polymer composite materials has gained significant attention due to their extensive potential applications, especially in the field of monitoring of mechanical, aerospace and infrastructure systems. These smart nanocomposites exhibit excellent electro-mechanical sensing capability. Carbon nanotubes (CNTs) with outstanding electrical, mechanical, and thermal properties can be reinforced into polymer composite materials by appropriate dispersion to produce polymer/CNTs-based smart nanocomposites with excellent sensitivity. Understanding the processing, characterization and properties of the nanocomposites will help in yielding a deeper insight into the effect of incorporation of carbon nanotubes (CNTs) into the matrix of the polymer composites. This study provides a comprehensive overview (primarily in the last 2 decades) of the major influencing factors on the underlying mechanisms involved in the fabrication and performance of nanocomposites which can cause a paradigm shift in instrumentation and sensing for structural health monitoring (SHM). Therefore, this review article presents the recent advancement in the development of CNTs-reinforced polymer nanocomposites-based sensors encompassing the mechanism for electrical conductivity/piezo properties, fabrication, applications for various types of sensing, and the futuristic application for smart sensing through appropriate tailoring of nanocomposites using CNTs. [ABSTRACT FROM AUTHOR]

Conductive polymer composites (CPCs), obtained by incorporating conductive fillers into a polymer matrix, are suitable for producing strain sensors for structural health monitoring (SHM) in infrastructure. Here, the effect of the addition of inorganic semiconductor nanoparticles (INPs) to a poly (vinylidene fluoride) (PVDF) composite filled with multi-walled carbon nanotubes (MWCNTs) on the piezoresistive behavior is investigated. INPs with different morphologies and sizes are synthesized by a hydrothermal method. The added inorganic oxide semiconductors showed two distinct morphologies, including different phases. While particles with flower-like plate morphology contain phases of orth-ZnSnO3 and SnO, the cauliflower-like nanoparticles contain these metal oxides and ZnO. The nanoparticles are characterized by field-emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD), and the nanocomposites by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Cyclic tensile testing is applied to determine the strain-sensing behavior of PVDF/1 wt% MWCNT nanocomposites with 0–10 wt% inorganic nanoparticles. Compared to the PVDF/1 wt% MWCNT nanocomposite, the piezoresistive sensitivity is higher after the addition of both types of nanoparticles and increases with their amount. Thereby, nanoparticles with flower-like plate structures improve strain sensing behavior slightly more than nanoparticles with cauliflower-like structures. The thermogravimetric analysis results showed that the morphology of the semiconductor nanoparticles added to the PVDF/MWCNT matrix influences the changes in thermal properties. [ABSTRACT FROM AUTHOR]

Smart flexible materials with piezoresistive property are increasingly used in the field of sensors. When embedded in structures, they would allow for in situ structural health monitoring and damage assessment of impact loading, such as crash, bird strikes and ballistic impacts; however, this could not be achieved without a deep characterization of the relation between piezoresistivity and mechanical behavior. The aim of this paper is to study the potential use of the piezoresistivity effect of a conductive foam made of a flexible polyurethane matrix filled with activated carbon for integrated structural health monitoring (SHM) and low-energy impact detection. To do so, polyurethane foam filled with activated carbon, namely PUF-AC, is tested under quasi-static compressions and under a dynamic mechanical analyzer (DMA) with in situ measurements of its electrical resistance. A new relation is proposed for describing the evolution of the resistivity versus strain rate showing that a link exists between electrical sensitivity and viscoelasticity. In addition, a first demonstrative experiment of feasibility of an SHM application using piezoresistive foam embedded in a composite sandwich structure is realized by a low-energy impact (2 J) test. [ABSTRACT FROM AUTHOR]

Cementitious composites reinforced with conductive nanoparticles, also known as smart composite-based sensors, are emerging as novel sensors for real-time monitoring of structures. The present study deals with the development of embeddable smart composite-based sensor (called as e SCS), for monitoring the damage evolution in large-scale beam-column (B-C) sub-assemblages. Firstly, a systematic approach has been developed to fabricate the sensors through incorporation of functionalized (-COOH) multi-walled carbon nanotubes (MWCNTs). The optimum dosage of CNTs required for developing sensors with maximum conductivity and piezo-resistivity was ascertained by determining the percolation threshold limit. The best performing e SCS was then successfully embedded at the critical locations of full-scale B-C joint specimens. The embedded sensors are used, for the first time, for damage monitoring of the B-C sub-assemblages subjected to reverse cyclic loadings. From the study, it is found that e SCS with 0.50 wt.% COOH-MWCNT shows excellent piezoresistive behaviour and gauge factors are found to be approximately 730, 457 and 396 for the applied compressive stress ranges of 2–4, 2–6 and 2–8 MPa, respectively. The embedded sensors showed the excellent strain sensing capability under reverse cyclic loading. The present study demonstrates the suitability of embedded e SCS sensors for robust structural health monitoring applications. [ABSTRACT FROM AUTHOR]

Conductive polymer composites (CPCs) have shown potential for structural health monitoring applications based on repeated findings of irreversible transducer electromechanical property change due to fatigue. In this research, a high-fidelity stochastic modeling framework is explored for predicting the electromechanical properties of spherical element-based CPC materials at bulk scales. CPC dogbone specimens are manufactured via casting and their electromechanical properties are characterized via uniaxial tensile testing. Model parameter tuning, demonstrated in previous works, is deployed for improved simulation fidelity. Modeled predictions are found in agreement with experimental results and compared to predictions from a popular analytical model in the literature. [ABSTRACT FROM AUTHOR]

Smart geosynthetics have attracted significant interest for potential applications in geotechnical structures owing to their conductive properties. This paper presents an analysis of the electro-mechanical response of graphene-based geotextiles for application in pavements. Experimental and numerical studies were conducted on a commercially available graphene-coated geotextile to understand its response to induced strains. The material was subjected to tensile loading with the effect of transverse strains also being tested, utilizing Digital Image Correlation (DIC). Experimental results indicated a significant electro-mechanical behaviour in the geotextile, with the relative resistance change being non-linear with applied strain. Existing analytical solutions could not predict the observed behaviour; hence, a multi-physics numerical model was developed using concepts of piezoresistivity to capture the non-linear behaviour. The numerical model was calibrated using the experimental data and then validated with experimental data from tests conducted for different specimen sizes. The model could capture the non-linear electro-mechanical behaviour and the electrical response due to axial and transverse strains in the material. This study is expected to serve as a basis for using graphene-based geotextiles for structural health monitoring (SHM) purposes in geotechnical structures, such as in roads. • Smart geosynthetics have become increasingly popular in pavement health monitoring. • A graphene-based geotextile was assessed for potential road sensing applications. • Experimental testing was conducted to evaluate its electro-mechanical response. • A multi-physics numerical model was developed to capture the observed piezoresistive behaviour. • The model was validated with experimental data obtained for varying specimen sizes. [ABSTRACT FROM AUTHOR]

The current paper presents the results of an experimental study of carbon nano-, micro-, and hybrid-modified cementitious mortar to evaluate mechanical performance, energy absorption, electrical conductivity, and piezoresistive sensibility. Three amounts of single-walled carbon nanotubes (SWCNTs), namely 0.05 wt.%, 0.1 wt.%, 0.2 wt.%, and 0.3 wt.% of the cement mass, were used to prepare nano-modified cement-based specimens. In the microscale modification, 0.05 wt.%, 0.5 wt.%, 1.0 wt.% carbon fibers (CFs) were incorporated in the matrix. The hybrid-modified cementitious specimens were enhanced by adding optimized amounts of CFs and SWCNTs. The smartness of modified mortars, indicated by their piezoresistive behavior, was investigated by measuring the changes in electrical resistivity. The effective parameters that enhance the composites' mechanical and electrical performance are the different concentrations of reinforcement and the synergistic effect between the types of reinforcement used in the hybrid structure. Results reveal that all the strengthening types improved flexural strength, toughness, and electrical conductivity by about an order of magnitude compared to the reference specimens. Specifically, the hybrid-modified mortars presented a marginal reduction of 1.5% in compressive strength and an increase in flexural strength of 21%. The hybrid-modified mortar absorbed the most energy, 1509%, 921%, and 544% more than the reference mortar, nano-modified mortar, and micro-modified mortar, respectively. The change rate of impedance, capacitance, and resistivity in piezoresistive 28-day hybrid mortars improved the tree ratios by 289%, 324%, and 576%, respectively, for nano-modified mortars and by 64%, 93%, and 234%, respectively, for micro-modified mortars. [ABSTRACT FROM AUTHOR]

Cement-based sensors include conductive fillers to achieve a sensing capability based on the piezoresistivity phenomenon, in which the electrical resistivity changes with strain. The microstructural characterisation of cement-based sensors can be obtained using a promising non-destructive technique, such as AC impedance spectroscopy (ACIS), which has been recently used by many researchers. This paper reviews the fundamental concepts of piezoresistivity and ACIS in addition to the comparison of equivalent circuit models of cement-based sensors found in the literature. These concepts include piezoresistivity theory, factors affecting piezoresistivity measurement, resistance measurement methodology, strain/damage sensing, causes of piezoresistivity, theories of conduction, AC impedance spectroscopy theory, and the equivalent circuit model. This review aims to provide a comprehensive guide for researchers and practitioners interested in exploring and applying different techniques to self-sensing concrete. [ABSTRACT FROM AUTHOR]

This research explores Ultra-High-Performance Concrete (UHPC) reinforced with recycled carbon fibers to verify its potential application in self-sensing concrete for structural health monitoring. The improved electrical conductivity due to the inclusion of carbon fibers enables the emergence of piezoresistivity, transforming UHPC into a sensitive sensor for detecting mechanical stresses. By incorporating various characterization tests alongside investigations into fiber type (loose versus fibrillated sheets) and content variations, the study aims to establish a correlation between the electrical properties and the resulting piezoresistive response. Resistivity will be measured using impedance scanning, while piezoresistivity will be determined through loading and unloading cycles with a datalogger recording the variations in electrical resistance. The inclusion of carbon fibers suggests an improvement in mechanical performance, up to 42 % in flexural strength and 26 % in compression compared to UHPC without fibers. Resistivity ranges from 1 to 2 Ω⋅m and gauge factor reach 38. These results are comparable to those reported in other studies on UHPC with carbonaceous additions, highlighting the potential of recycled carbon fibers as a sustainable and effective reinforcement strategy. • Recycled carbon fibers enhance UHPC mechanical and electrical properties. • UHPC with recycled carbon fibers exhibits promising self-sensing capabilities. • Study establishes potential for sustainable, self-monitoring concrete structures. [ABSTRACT FROM AUTHOR]

Intelligent cementitious materials integrated with carbon nanofibers (CNFs) have the potential to be used as sensors in structural health monitoring (SHM). The difficulty in dispersing CNFs in cement-based matrices, however, limits the sensitivity to deformation (gauge factor) and strength. Here, we synthesise CNF by chemical vapour deposition on the surface of calcium oxide (CaO) and, for the first time, investigate this amphiphilic carbon nanomaterial for self-sensing in mortar. SEM, TEM, TGA, Raman and VSM were used to characterise the produced CNF@CaO. In addition, the electrical resistivity of the mortar, containing different concentrations of CNF with and without CaO, was measured using the four-point probe method. Furthermore, the piezoresistive response of the composite was quantified by means of compressive loading. The synthesised CNF was 5–10 μm long with an average diameter of ~160 nm, containing magnetic nanoparticles inside. Thermal decomposition of the CNF@CaO compound indicated that 26% of the material was composed of CNF; after CaO removal, 84% of the material was composed of CNF. The electrical resistivity of the material drops sharply at concentrations of 2% by weight of CNF and this drop is even more pronounced for samples with 1.2% by weight of washed CaO. This indicates a better dispersion of the material when the CaO is removed. The sensitivity to deformation of the sample with 1.2% by weight of CNF@CaO was quantified as a gauge factor (GF) of 1552, while all other samples showed a GF below 100. Its FCR amplitude can vary inversely up to 8% by means of cyclic compressive loading. The method proposed in this study provides versatility for the fabrication of carbon nanofibers on a tailored substrate to promote self-sensing in cementitious materials. [ABSTRACT FROM AUTHOR]

The concept of lightweight design is widely employed for designing and constructing aerospace structures that can sustain extreme loads while also being fuel-efficient. Popular lightweight materials such as aluminum alloy and fiber-reinforced polymers (FRPs) possess outstanding mechanical properties, but their structural integrity requires constant assessment to ensure structural safety. Next-generation structural health monitoring systems for aerospace structures should be lightweight and integrated with the structure itself. In this study, a multi-walled carbon nanotube (MWCNT)-based polymer paint was developed to detect distributed damage in lightweight structures. The thin film's electromechanical properties were characterized via cyclic loading tests. Moreover, the thin film's bulk conductivity was characterized by finite element modeling.

Piezoresistive and capacitive cement-based smart composites are promising candidates for stress monitoring applications in buildings. However, the drawbacks of designing cement-based smart composites with a piezoresistive mechanism sensitive to temperature variations or a capacitive mechanism sensitive to vibration can be solved with sensor designs based on two principles. To address this issue, cement-based smart composites with piezoresistive and capacitive stress sensitivity and significantly improved compressive strength were designed using carbon nanotubes (CNT) doped with graphene nanopowder. A maximum fractional change in electrical resistivity of 90.08% with a high linearity of 98% was obtained with a blend of 0.01 wt%, and the maximum fractional change in capacitance was 163.11% with a high linearity of 97% at 0.05 wt%. Cement-based smart composites have absolute piezoresistive stress sensitivities that vary from 1.38% MPa−1 to 4.16% MPa−1 and 2.54% MPa−1 to 2.57% MPa−1 for blended and impregnated low doses of 0.01 wt% to 0.05 wt% CNT doped with graphene. In addition, capacitive stress sensitivities of 22.74% MPa−1 and 5.1% MPa−1 were achieved by blending and impregnating 0.01 wt% CNT doped with graphene in cementitious composites. Furthermore, the conductive path, overlapping, and tunneling effect created by CNT doped with graphene in cementitious composites and the porous structure in the dielectric layer are responsible for the increased stress sensitivity. [Display omitted] • The piezoresistive and capacitive stress sensitivity were assessed. • A novel CNT doped with graphene cement-based sensors was produced. • CNT doped with graphene cement pastes exhibits remarkable self-sensing ability. • CNT doped with graphene improved the compressive strength. • The sensitivity mechanism of CNT doped with graphene cement pastes was evaluated. [ABSTRACT FROM AUTHOR]

Self-sensing cementitious composites containing nano carbon fillers have extensive application prospects in structural health monitoring (SHM) due to their excellent intrinsic piezoresistivity, good mechanical performances, high compatibility and durability. However, the piezoresistivity is prone to be affected by environmental factors, such as water content. Therefore, it is urgent to study the influence of water content on piezoresistivity to avoid unwanted effect. In the present study, piezoresistivity of self-sensing cementitious composites containing nano carbon fillers under cyclic compression with different water contents is investigated. Moreover, mechanisms are also explored comprehensively. The results indicate that the sensitivity, repeatability and stability of the piezoresistivity deteriorate with decreasing of water content. The maximum FCR and stress/strain sensitivity are decreased from 14.3 % to 4.5 % and 0.72 %·MPa−1/124–0.23 %·MPa−1/39, respectively, when water content decreases from 3.53 % to nearly 0 %. Variation of electrical conductivity pathways and networks caused by enclosed water film on surface of electrical conductive fillers take responsible for the changeable of piezoresistivity with different water content. The outcomes offered validity of self-sensing cementitious composites implementation in SHM withstand variation of water content. [Display omitted] • Piezoresistivity of nano fillers cementitious composites is investigated. • Mechanisms of water content effects on piezoresistivity are explored. • The piezoresistivity deteriorates with decreasing of water content. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) using self‐sensing cement‐based materials has been reported before, where nano‐fillers have been incorporated in cementitious matrices as functional sensing elements. A percolation threshold is always required in order for conductive nano‐fillers modified concrete to be useful for SHM. Nonetheless, the best pressure/strain sensitivity results achieved for any self‐sensing cementitious matrix are <0.01 MPa−1. In this work, we introduce for the first‐time novel partially reduced graphene oxide based electronic textile (e‐textile) embedded in plain and as well as in polymer‐binder‐modified cementitious matrix for SHM applications. These e‐textile embedded cementitious composites are independent of any percolation threshold due to the interconnected fabric inside the host matrix. The piezo‐resistive response was measured by applying direct and cyclic compressive loads (ranging from 0.10 to 3.90 MPa). A pressure sensitivity of 1.50 MPa−1 and an ultra‐high gauge factor of 2000 was obtained for the system of the self‐sensing cementitious structure with embedded e‐textiles. The sensitivity of this new system with embedded e‐textile is an order of magnitude higher than the state‐of‐the‐art nanoparticle based self‐sensing cementitious composites. The composites showed mechanical stability and functional durability over long‐term cyclic compression tests of 1000 cycles. Additionally, a two time‐constant model was used to validate the experimental results on decay response of the e‐textile embedded composites. [ABSTRACT FROM AUTHOR]

Improving mechanical properties and decreasing costs have significantly increased the use of fiber composites in automotive, aerospace, and civil engineering applications. Structural composites are bonded to traditional metallic materials in a variety of applications, and mechanical fasteners often cannot be used due to the low bearing strength of composites. With the increasing use of adhesives in load-bearing structures, novel techniques are required for monitoring the structural integrity of adhesive joints. Previously, carbon nanotubes (CNTs) have been added to adhesives and resins to create in-situ sensors, but the increased viscosity and potential for galvanic corrosion remains a challenge. In this research, a piezoresistive carbon nanotube-based sensing layer is embedded in a composite/steel adhesive joint for damage sensing. The use of a thin sensing layer with low-fiber volume fraction enables the use of existing adhesives without causing any major changes in the physical properties of the adhesives or the curing cycle and reduces the chances of galvanic corrosion. Different approaches of using an adhesive layer and a nonconductive fabric are investigated for insulation of the sensing layer. The nonconductive fabric approach for insulating the specimen yields better mechanical properties as the there are no weak interfaces in the adhesive bondline. Additionally, it is more convenient for scaling up for field applications as the adhesive is cured in one stage. The sensing layer can not only be used to detect incipient damage in the joint, but also identify different modes of failure.

The self-sensing ultra-high-performance concrete (UHPC) was developed in this study by incorporating nano carbon black (CB) and carbon nanofiber (CNF) as additives into the UHPC matrix. Single CB and hybrid CB/CNF filled UHPCs were compared in terms of strength, microstructures, percolation threshold, conductivity, and piezoresistive sensing performance. The results indicate that hybrid CB/CNF filled UHPC consistently exhibits superior compressive strength compared to the counterpart with single CB. The percolation threshold begins at approximately 0.5 % CB content, regardless of the inclusion of CNF. The CNF serves to link the surrounding conductive passages contributed by CB nanoparticles, demonstrating the positive effect of hybrid nanofillers with multiple dimensions. AC impedance spectroscopy (ACIS) and equivalent circuit modelling were performed to understand the synergetic effect of CB/CNF on the electrical network in UHPC matrix and to compare the conductive characteristics between single CB and hybrid CB/CNF filled self-sensing UHPC. The insights gained from this analysis contribute to comprehending the conductive behaviours and sensing mechanisms at the microstructural level, providing new insight into the material design strategy to enhance the electrical and sensing performances of UHPC-based cementitious sensors. Regarding piezoresistive performance, the stability of sensing performance in response to dynamic cyclic load improves with an increasing content of conductive fillers; the hybrid fillers of CB/CNF enhance the stability of piezoresistive sensing performance of self-sensing UHPC with less signal noise under monotonic compressive loading. The outcomes can integrate the piezoresistive self-sensing capacity with UHPC to promote the application of cement-based sensors in civil infrastructure, offerring potential benefits for structural health monitoring and maintenance. [ABSTRACT FROM AUTHOR]

The mutual effects of water content and carbon black nanoparticle (CBN) concentration on the electrical resistivity and self-sensing properties of mortars are reported in this paper. Previous works have focused on moisture effects in CBN-based composites whose conductivity mainly came from direct contact between nanofillers. This study found very distinct behaviors when the CBN concentration was within the percolation zone. Mortars containing different moisture and CBN contents were subjected to direct current (DC) measurements, biphasic DC, and piezoresistivity tests. Effects of water content on the intrinsic capacitance of CBN-based composites were reported. A deep investigation within the percolation zone allowed the design of a promising CBN-based composite whose resistivity and sensing properties are minimally dependent on the water content, because the effects on ionic conduction due to the elimination of pore water were compensated by the effects on contacting conduction due to the elimination of water films on CBN surface. [ABSTRACT FROM AUTHOR]

Carbon fibre (CF) is one of the most effective materials in improving the conductivity of the composites by developing a conductive network within the matrix, which also enhanced the piezoresistivity behaviour of the cementitious composites and has a potential application for structural health monitoring. A systematic study of the effect of sizing condition and fibre length on the piezoresistivity behaviour of cementitious composites by adopting unsized CF with the length of 3, 6 and 12 mm, and desized CF of 6 and 12 mm as functional fillers. Each type of CF was added at four different weight fractions of 0.1, 0.3, 0.5 and 0.7% to determine the optimal fibre content. Electrical resistivity and piezoresistivity tests were conducted for samples before and after drying treatment to evaluate the effect of water content on electrical properties. Besides, fresh properties of the fresh mixture, mechanical properties and microstructure of the composites were also investigated. Results showed that unsized CF is more effective in enhancing composites flexural strength and reducing the electrical resistivity, which also showed a stronger bonding with the cement matrix and also demonstrated a better dispersive ability. In terms of piezoresistivity behaviour, for a given fibre length, desized CF showed higher sensitivity and repeatability compared to unsized CF; however, the signals showed more noise. The best piezoresistivity behaviour was obtained for composites containing 3 mm CF at 0.7 wt%, which showed a fractional change in resistivity (FCR) value of approximately 70%. An equation was developed, which can successfully describe the relationship between the FCR of cementitious composites containing CF and the applied external stress. [ABSTRACT FROM AUTHOR]

Intelligent smart materials can not only monitor the damage and degradation of architectural structures in real time but also the health structure. In recent years, carbon nanotubes materials have emerged to possess both excellent mechanical and electrical properties. Moreover, when carbon nanotubes are added to epoxy resin, intelligent composite materials with significant sensitivity are created. In this study, the stress–strain curves and anelasticity of carbon nanotube/epoxy resin composites with different carbon nanotube concentrations is analyzed. Through changing the level of carbon nanotubes using the two-pole method, the percolation threshold of carbon nanotube/epoxy composites was determined. Thereafter, the effect of temperature on the composites' conductive properties was investigated. Moreover, using the stepwise cyclic loading method, the piezoresistivity of the carbon nanotube/epoxy composites was investigated. The test results show that the elastic limit, the yield point, and the elastic modulus range of the carbon nanotube/epoxy composites is approximately 45 MPa, 50 MPa, and 1–2 GPa, respectively. The anelasticity of the carbon nanotube/epoxy composites increases with the gradual increase of the stress level. The percolation threshold interval of carbon nanotube/epoxy composites ranges from 0.5 to 1.0 wt%. The rate of change of resistance for the different concentrations on carbon nanotube/epoxy specimens corresponds to the temperature. Notably, the carbon nanotube/epoxy composites have better discrimination and pressure sensitivity for different grades of load. When the carbon nanotube content is 0.5 wt%, the sensitivity of the carbon nanotube/epoxy composites pressure-sensitive property is the largest, which is in agreement with the threshold curve. The results of this investigation have implications for the application of carbon nanotube/epoxy composites in structural health monitoring. [ABSTRACT FROM AUTHOR]

In this study, different dosages of carbon black (CB) and polypropylene (PP) were added to develop functional cementitious composites as cement-based sensors. The results show that electrical conductivity increased with the amount of PP fibres, due to the enclosed CB nanoparticles and more conductive passages. The compressive strength slightly decreased, while the flexural strength was significantly increased with the increased amount of PP fibres. The improvement is mainly achieved by the reduced CB concentration in cement matrix and the excellent tensile strength of PP fibres. Under the cyclic compression, the piezoresistivity increased by three times for 0.4 wt% PP fibres filled CB/cementitious composite, regardless of the loading rates. The flexural stress sensing efficiency was considerably lower than that of compressive stress sensing, but it increased with the amount of PP fibres. Moreover, fitting formulas were proposed and used to evaluate the self-sensing capacity, with the attempts to apply cement-based sensors for structural health monitoring. Unlabelled Image • Enclosed CB nanoparticles on the surface increase the conductive passages by PP fibres. • Carbon black agglomerations were more significant to affect the mechanical properties. • Flexural strength of specimen considerably improved with the increase of PP fibres. • Compressive stress sensing efficiency linearly increased with the increase of PP fibre. • Flexural failure can be recorded by suddenly increased electrical resistivity of the specimen. [ABSTRACT FROM AUTHOR]

Conductive nanocomposites have been explored extensively for structural health monitoring (SHM) due to their self-sensing nature via the piezoresistive effect. Combined with a non-invasive conductivity imaging modality such as electrical impedance tomography (EIT), piezoresistivity is a powerful tool for SHM. To date, however, the combination of the piezoresistive effect and EIT has been limited to just damage detection. From a SHM perspective, it may be more beneficial to pre-emptively predict failure before it occurs. To that end, we propose a novel methodology for failure prediction in nanocomposites using piezoresistive inversion. Our approach makes use of a genetic algorithm (GA) to determine the mechanical state of the structure using conductivity changes observed via EIT. First, a rectangular nanocomposite specimen with a central hole is manufactured. Second, the specimen is loaded in tension to induce stress concentrations near the hole. Third, EIT is used to image the resulting stress concentration-induced conductivity changes near the hole. Fourth, GA-enabled piezoresistive inversion is implemented to determine the underlying displacements from the observed conductivity changes. The strains are then determined from kinematic relations and the stresses from constitutive relations. Lastly, a failure criterion is used to predict failure. By validating our results with finite element analysis and digital image correlation, we demonstrate that the proposed approach can accurately predict the onset of failure and therefore enable unprecedented SHM capabilities in piezoresistive nanocomposites. [ABSTRACT FROM AUTHOR]

Improving mechanical properties and decreasing costs have significantly increased the use of fiber composites in automotive, aerospace, and civil engineering applications. Structural composites are bonded to traditional metallic materials in a variety of applications, and mechanical fasteners often cannot be used due to the low bearing strength of composites. With the increasing use of adhesives in load-bearing structures, novel techniques are required for monitoring the structural integrity of adhesive joints. Previously, carbon nanotubes (CNTs) have been added to adhesives and resins to create in-situ sensors, but the increased viscosity and potential for galvanic corrosion remains a challenge. In this research, a piezoresistive carbon nanotube-based sensing layer is embedded in a composite/steel adhesive joint for damage sensing. The use of a thin sensing layer with low-fiber volume fraction enables the use of existing adhesives without causing any major changes in the physical properties of the adhesives or the curing cycle and reduces the chances of galvanic corrosion. Different approaches of using an adhesive layer and a nonconductive fabric are investigated for insulation of the sensing layer. The nonconductive fabric approach for insulating the specimen yields better mechanical properties as the there are no weak interfaces in the adhesive bondline. Additionally, it is more convenient for scaling up for field applications as the adhesive is cured in one stage. The sensing layer can not only be used to detect incipient damage in the joint, but also identify different modes of failure. [ABSTRACT FROM AUTHOR]

Featured Application: Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory. This work aims to investigate piezoresistive behavior in plain-woven carbon fiber reinforced polymer (CFRP). Measurement method for electric resistant alteration in the woven CFRP under tensile loading by using a Wheatstone bridge circuit is introduced. Reversibility of the resistant alteration is also investigated whereas the gauge factor of the woven CFRP is evaluated. The result shows that the positive piezoresistive properties of the woven CFRP can be observed by the Wheatstone bridge circuit. The specific resistances of 43.8 μΩm and 10.1 μΩm are obtained for wrap and thickness directions, respectively. Reversibility with a hysteresis of the woven CFRP can also be confirmed with the gauge factor of 22.9 at loading conditions and 17.7 at unloading conditions. Positive piezoresistive behavior which has been revealed in this work can be utilized for structural health monitoring technology development. [ABSTRACT FROM AUTHOR]

Self-sensing cementitious composites can enable structures that are capable of carrying the loads applied on them while monitoring their condition. Most of earlier research has focused on the incorporation of nanofillers or microfibers into cement paste or mortar composites. However, there have been very limited number of studies on the development of steel-fiber-reinforced cementitious composites with self-sensing capabilities. This study explores strain sensitivity of concrete mixtures that include coarse aggregates up to 15 mm diameter and steel fibers with a length of 13 mm and a diameter of 0.25 mm. Five different concrete mixtures with steel fibers at 0%, 0.2%, 0.35%, 0.5%, and 0.8% volume ratios were fabricated. Compression tests with simultaneous measurement of strain and electrical resistance were conducted on the cubic specimens. Gauge factor and percent linearity that is a measure of error in strain sensing were calculated. Concrete mixtures with 0.5% steel fibers possess a strong linear relationship between applied strain and electrical resistance change with a gauge factor over 20 times larger than that of traditional metal strain gauges. Phenomenological models for different resistivity and gauge factors of cement paste/mortar with respect to concrete with large aggregates and short–long fiber cement composites were presented. [ABSTRACT FROM AUTHOR]

The mechanical behavior of mortar joints directly affects the structural performance and failure mechanisms of masonry. Since previous research did not evaluate the effects of different lime/cement ratios on intrinsic self-sensing properties, this study developed a factorial experiment to investigate the electrical resistivity, gauge factor, stress sensitivity and compressive strength of mortars with different lime/cement proportions (0.25, 0,50, 1.00, 2.00, by volume) and carbon black nanoparticles (CBN) contents (0%, 3%, 6%, 9% by weight of binders). Results were explained based on X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (FEGSEM) analyses. Increases in lime content delayed the percolation threshold and decreased the mortars' strength. Portlandite and calcite structures of lime increased the distance between CBN, modifying the electron conduction mechanisms. At the end of the percolation zone, the addition of lime increased self-sensing properties, whereas the opposite behavior was observed at the beginning of the percolation zone. • Increases in lime content delayed the percolation threshold of the nanomodified mortars. • CH and calcite increased the distance between CBN, changing electronic conduction mechanisms. • At the end of the percolation zone, lime addition statistically increased self-sensing properties. • At the beginning of the percolation zone, lime addition reduced GF and caused negligible changes in SS. • Increases in the contents of lime or CBN decreased compressive strength of the mortars. [ABSTRACT FROM AUTHOR]

Graphene nanoplatelet (GNP)/poly(methyl methacrylate) (PMMA) nanocomposite solution was spray coated on a glass fibre reinforced polymer composite (GFRP) beam with different initial electrical resistance (R0). Scotch tape erosion method was used to tailor the R0 of the sensors. Beams and the sensors were characterized by computed tomography (CT) and scanning electron microscopy (SEM) respectively. The piezoresistive behaviour of these sensors was evaluated in monotonic, step and cyclic loading conditions. These spray coated sensors offered good sensitivity (38.5 times) as compared to a strain gauge. A gauge factor (GF) of 55±0.5, 70±2, and 77±1 was obtained for R0 of 1, 7 and 21 kΩ GNP layers, respectively. Sensors showed good response and stability under the step and cyclic loading conditions. The ease in the process of application coupled with good sensitivity demonstrates that the GNP/PMMA spray coated sensor can be a potential candidate for the futuristic multi-functional materials for structural health monitoring. [ABSTRACT FROM AUTHOR]

Summary: The intrinsic vulnerability of masonry structures to seismic events makes structural health monitoring of the utmost importance for the conservation of the built heritage. The development of piezoresistive bricks, also termed smart bricks, is an innovative technology recently proposed by the authors for the monitoring of such structures. Smart bricks exhibit measurable variations in their electrical properties when subjected to external loads or, alternatively, strain self‐sensing capabilities. Therefore, the deployment of a network of smart bricks into a masonry structure confers self‐diagnostic properties to the host structure. In this light, this paper presents a theoretical investigation on the application of smart bricks to full‐scale masonry structures for seismic assessment. This includes the study of the convenience of providing electrical isolation conditions to the sensors, as well as the effectiveness of smart bricks when installed into either new constructions or in pre‐existing structures. Secondly, numerical results are presented on the seismic analysis of a three‐dimensional masonry building equipped with a network of smart bricks. Finally, in order to map the strain field throughout the structure exploiting the outputs of a limited number of sensors, an interpolation‐based strain reconstruction approach is proposed. [ABSTRACT FROM AUTHOR]

Certain traditional sensors like lead zirconate titanate (PZT) wafers and ultrasonic probes can respond to extremely weak disturbances such as ultrasonic guided waves (UGWs). However, their further development for applications to meet increasing engineering demands is limited on account of their hardness, brittleness, and complex manufacturing processes. Now, emerging nanotechnology ushers in a brand-new world for nanocomposite-based strain sensors, endowing them with higher flexibility, better surface compatibility and easier fabrication. Yet there are few reports of composites which can be used to perceive high frequency UGWs with an ultralow magnitude. Here, we present a novel graphene-based nanocomposite possessing strong sensitivity for sensing ultrasonic waves by virtue of a neoteric sensing mechanism − the tunneling effect. By designing and optimizing the microstructure of the conductive network in the nanocomposite sensor, we successfully capture ultrasonic waves with high signal-to-noise ratio in a broad frequency range up to 1 MHz. With the feature of high sensitivity and rapid response times, the graphene-based nanocomposite becomes a promising candidate for structural health monitoring in developing prospective applications. [ABSTRACT FROM AUTHOR]

Abstract The present paper investigates the damage monitoring using the piezoresistive effect on the glass fiber-reinforced polymer (GFRP) omega stringers reinforced through-the-thickness by tufting. The experiments consisted of the electric resistance measurements from the tufted yarns during the pull-off tests on omega stringers. Acoustic emission (AE) and digital image correlation (DIC) techniques were also performed throughout the tests in order to evaluate the acoustic activity and the strain field respectively. Furthermore, non-supervised AE clustering was carried out and aided to determine the main damage events. The results presented that electric resistance measurements are in good correlation with the AE clusters, especially with those related to the delamination and tuft yarns fracture. Besides, these damage events are well distinguished from the electric resistance data. Also, DIC images exhibited that electric resistance is sensitive to local strain field as expected to piezoresistivity measurements. Therefore, tufting reinforcements have shown to be an interesting monitor of the structural health in real time, further their well-known ability to increase the mechanical out-of-plane properties of laminate composites. [ABSTRACT FROM AUTHOR]

• Sodium hydroxide one-part alkali activated materials are self-sensing without additives. • Their piezoresistivity is sensitive to the elemental composition. • They can have a gauge factor of 141 and a compressive strength of 53 MPa. The future of smart construction relies on the development of smarter construction materials that offer multifunctional properties. Alkali-activated materials are smart, self-sensing construction materials that are more scalable, affordable, and reproducible than conventional self-sensing composites. This study presents the first self-sensing alkali-activated material that achieves compressive strength above 50 MPa and highly piezoresistive (58% at 10 MPa) without the need for conductive additives. This is an exceptional improvement to conventional smart construction materials for structural health monitoring. [ABSTRACT FROM AUTHOR]

This work aims to investigate piezoresistive behavior in plain-woven carbon fiber reinforced polymer (CFRP). Measurement method for electric resistant alteration in the woven CFRP under tensile loading by using a Wheatstone bridge circuit is introduced. Reversibility of the resistant alteration is also investigated whereas the gauge factor of the woven CFRP is evaluated. The result shows that the positive piezoresistive properties of the woven CFRP can be observed by the Wheatstone bridge circuit. The specific resistances of 43.8 μΩm and 10.1 μΩm are obtained for wrap and thickness directions, respectively. Reversibility with a hysteresis of the woven CFRP can also be confirmed with the gauge factor of 22.9 at loading conditions and 17.7 at unloading conditions. Positive piezoresistive behavior which has been revealed in this work can be utilized for structural health monitoring technology development.

Highlights: • Piezoresistivity of HPCFRCC containing different Vol.% of carbon fiber was evaluated. • Crack detection of a HPCFRCC thin plate under bending was carried out using resistivity measurement. • Self-sensing capability for cement composites is gained by carbon fiber incorporation. • Crack formation can be monitored with sufficient precision by electrical resistivity measurement. Abstract Electrical resistivity measurement has been used as a test for studying the durability-related properties of cement composites for decades. Applications of electrical resistivity measurement namely health monitoring and crack detection are of great importance for increasing the service life of structures. The former is the capability of cement composite to sense its own strain (piezoresistivity) and the latter is based on the irreversible change of resistivity in the presence of crack. In this study, at first the effect of different fractions of silica fume and carbon fiber on piezoresistivity of cement composites were evaluated by monitoring the variations of resistivity under compression. Secondly, a high performance carbon fiber-reinforced cement composite (HPCFRCC) thin plate specimen was subjected to four-point bending while the variations of resistivity were recorded so that the zone at which the initiation of crack occurs can be detected. Results showed that both compressive strength and water absorption are highly affected by silica fume content while flexural strength slightly changed by increasing silica fume. While the addition of carbon fiber increased water absorption, it marginally affected mechanical strengths. Piezoresistivity test showed the ability of carbon fiber as a functional filler and the facilitated dispersion of fibers in high concentration of silica fume particles. It was confirmed that when carbon fiber content increases to more than 0.4 volumetric percentage, conductivity of specimen substantially increases and required sensitivity from piezoresistivity test is obtained. Crack detection test showed that when cracks are formed the planar surface resistivity of thin plate significantly changes. Thus, the formation and propagation of cracks can be monitored using electrical resistivity measurement in self-sensing cement composites. [ABSTRACT FROM AUTHOR]

Abstract Buckling of slender structures constitutes a hazardous failure mechanism that can yield partial or total collapses. Nonetheless, given that buckling failure is characterized by a highly non-linear and sudden loss of stability, most off-the-shelf monitoring systems fail to detect buckling and very few research works in the literature can be found in this regard. Recent advances in the field of Nanotechnology have fostered the development of innovative composite materials with multifunctional properties, offering vast possibilities in the field of Structural Health Monitoring. Along these lines, the present work proposes a novel concept of smart beams for buckling detection applications. This consists of the deployment of carbon nanotube-reinforced epoxy strip-like sensors on the upper and bottom faces of a beam-like structure. Carbon nanotube-reinforced composites exhibit strain self-sensing capabilities, that is to say, these composites provide measurable variations in their electrical properties under the action of mechanical strains. In this way, the proposed sensing strips not only act as mechanical reinforcements, but also confer self-diagnostic properties to the system. The failure detection principle of the proposed smart beams consists of the assessment of the bending-induced variations of the normal strains during buckling. To do so, the electrical resistance of the sensing strips is continuously monitored through a two-probe resistivity measurement scheme. The present research furnishes detailed numerical parametric analyses to investigate the effectiveness of the proposed smart beams to detect buckling under uniaxially compression, as well as to evaluate the influence of design parameters such as filler volume fraction, boundary conditions and electrodes layouts. The macroscopic behaviour of the smart beams is simulated by a micromechanics-based piezoresistivity model and a multiphysics finite element code. The numerical results demonstrate that the buckling failure can be tracked through sudden disturbances in the electrical output of the smart strips. Highlights • A novel smart beam concept is proposed for buckling detection applications. • A micromechanics-based FEM is used to model macroscopic CNT-based sensors. • Electromechanical constitutive properties are benchmarked against experimental data. • Buckling is shown to be traceable from the electrical output of the sensors. • Study on the electrodes layout is presented, including their length and position. [ABSTRACT FROM AUTHOR]

Within the novel approach for structural health monitoring of civil engineering structures based on smart self-sensing structural materials, Carbon NanoTube (CNT)-reinforced cement-based composites, often termed “smart concretes”, have drawn rising interest. These composites exhibit self-sensing capabilities resulting in measurable variations of their electrical properties under applied mechanical deformations. This, along with the similarity between these composites and conventional structural concrete, makes it possible to devise cost-efficient distributed monitoring systems for large-scale Reinforced Concrete (RC) structures. While several papers in the literature have focused on pilot applications of smart concrete strain sensors embedded into large RC components, the response of these sensors is not yet fully understood at the fundamental physical level and, as a consequence, their output is not properly interpreted. In order to shed some light on this issue, previous work by the authors focused on laterally unconstrained uni-axial loading conditions. This work extends the previous studies by presenting a mixed micromechanics and finite element approach for the analysis of CNT-reinforced composites subjected to arbitrary strain states. The two mechanisms that contribute to the electrical conductivity of CNT-reinforced composites, namely electron hopping and conductive networking, are contemplated within a percolation framework in the micromechanics model. On the basis of the micromechanics model, the 3D piezoresistivity matrix is determined, for the first time in the literature, by means of virtual dilation and distortion tests. Afterwards, the electro-mechanical modeling of three-dimensional composite elements is conducted by a multi-physics finite element code. The potential of the presented approach is illustrated by extensive parametric analyses, as well as a comparison against experimental data, including application of the mixed micromechanics-finite-element multi-physics formulation for electro-mechanical modeling of three-dimensional elements. [ABSTRACT FROM AUTHOR]

A new method for monitoring 3D braided composite structure health in real time by embedding the carbon nanotube yarn, based on its piezoresistivity, in the composite axially has been designed. The experimental system for piezoresistive effect detection of the carbon nanotube yarn in the 3D braided composite was built, and the sensing characteristics has been analyzed for further research. Compared with other structural health monitoring methods, the monitoring technique with carbon nanotubes yarns is more suitable for internal damage detection immediately, in addition the strength of the composite can be increased by embedding carbon nanotubes yarns. This method can also be used for strain sensing, the development of intelligent materials and structure systems. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography is a method of noninvasively imaging the internal conductivity distribution of a domain. Because many materials exhibit piezoresistivity, electrical impedance tomography has considerable potential for application in structural health monitoring. Despite its numerous benefits such as being low cost, providing continuous sensing, and having the ability to be employed in real time, electrical impedance tomography is limited by several important factors such as the ill-posed nature of the inverse problem and the requirement for large electrode arrays to produce quality images. Unfortunately, current methods of mitigating these limitations impose upon the benefits of electrical impedance tomography. Herein, we propose a multi-physics approach of enhancing electrical impedance tomography without sacrificing any of its benefits. This approach is predicated on coupling global conductivity changes with the electrical impedance tomography inversion process thereby adding additional constraints and rendering the problem less illposed. Additionally, we leverage physically motivated global conductivity changes in the context of piezoresistive nanocomposites. We demonstrate this proof of concept with numerical simulations and demonstrate that by incorporating multiple conductivity changes, the rank of the sensitivity matrix can be improved and the quality of electrical impedance tomography reconstructions can be enhanced. The proposed method, therefore, has the potential of easing the implementation burden of electrical impedance tomography while concurrently enabling high-quality images to be produced without imposing on the major advantages of electrical impedance tomography. [ABSTRACT FROM AUTHOR]

A hybrid additive manufacturing process is proposed to incorporate piezoresistive sensors into a polyamide matrix for real-time structural health monitoring. 3D-printed samples were tested under tensile, flexural, and indentation testing using various sizes, numbers, and locations of the sensors, while the electrical resistance was recorded in real-time. Under uniaxial tensile loading, strength reached 36 MPa, and the resistance values linearly increased by up to 105% at ∼150% of strain. During flexural testing, the sensor had higher resistance when it was located above the supports rather than under the loading roller. The conductive paths were placed near the plate's top, middle and bottom sections to localise the damage during indentation testing. The energy absorbed during indentation testing reached 34–36 J. Resistance readings of sensors with 1 cm width showed better linearity and sensitivity than their wide (10 cm) counterparts. Three 2D sensors were interconnected to make a 3D sensor. The resistance values gradually increased after each strike during repeated indentation, but the overall strength remained similar. In summary, this work demonstrates a novel approach toward customisable 3D-printed piezoresistive sensors for detecting global or local damage. • Piezoresistive sensors were embedded inside a polymer shell by additive manufacturing. • The method allows to customize sensors and detect global or local damage. • Change in resistance recorded in real-time during tensile, flexural and indentation testing. • Able to detect multiple low-energy indentation strikes. [ABSTRACT FROM AUTHOR]

The concept of lightweight design is widely employed for designing and constructing aerospace structures that can sustain extreme loads while also being fuel-efficient. Popular lightweight materials such as aluminum alloy and fiber-reinforced polymers (FRPs) possess outstanding mechanical properties, but their structural integrity requires constant assessment to ensure structural safety. Next-generation structural health monitoring systems for aerospace structures should be lightweight and integrated with the structure itself. In this study, a multi-walled carbon nanotube (MWCNT)-based polymer paint was developed to detect distributed damage in lightweight structures. The thin film's electromechanical properties were characterized via cyclic loading tests. Moreover, the thin film's bulk conductivity was characterized by finite element modeling. [ABSTRACT FROM AUTHOR]

Carbon nanotubes polymer nanocomposites have attracted a significant research, which provide interesting aspects for the realization of cost effective, highly sensitive piezoresistive strain sensors. Here, we report on an extensive piezoresistive performance investigation of multi-walled carbon nanotubes (MWCNTs)/epoxy nanocomposite under uniaxial cyclic tensile and compressive loading in low strain range. Dispersion quality of MWCNTs in the epoxy polymer matrix was monitored by scanning electron microscopy. MWCNTs/epoxy nanocomposite was deposited directly on a glass-reinforced epoxy cantilever beam on the same axis with a commercial metallic strain gauge. The strain sensitive nanocomposite presents high-performance properties, including gauge factor up to 78, good stability of ±0.26% for 10 h and durability of −0.08% after cyclic loading and unloading. Furthermore, MWCNTs/epoxy nanocomposites show quite small creep up to ±0.26%, fast response and recovery times, low hysteresis under cyclic tensile and compressive loadings and temperature response make the proposed nanocomposites suitable in various potential strain sensor applications including structural health monitoring. [ABSTRACT FROM AUTHOR]

• An extrusion-based 3D printer was used to print hollow square column segments. • Self-sensing cementitious composite mix to 3D print the column. • Another column was created using mould cast concrete for comparison. • 3D printed column performance can be monitored until the printed shell cracks. • 3D printed column did show superior electrical properties. Self-sensing cementitious composites can be used as an economical method of structural health monitoring. This is achieved by using the piezoresistivity effect to assist in the detection of defects and enabling repairs to be conducted early which can therefore avoid structural failures. This study uses an established self-sensing cementitious composite mix to 3D print column to examine its structural performance and sensing capabilities in components of large-scale concrete structures. An extrusion-based 3D printer was used to print hollow square column segments. These segments were then joined and filled with steel rebar reinforcement and cast concrete. Another column was created using mould cast concrete for comparison. The specimens were tested under static axial compression to determine their compressive properties, electrical resistivity and piezoresistivity response. The results showed that the 3D printed column performance can be monitored using the self-sensing composite until the printed shell cracks. The 3D printed column did show superior electrical properties with a lower electrical resistance of 274.2 Ω.cm. These results indicate that a different manufacturing approach to creating a 3D printed column should utilise the advantages of 3D printing for use in self-sensing concrete structures. [ABSTRACT FROM AUTHOR]