Fractional Change In Resistance Research Articles

Electrical properties of low temperature-sensitive coating sensor for fatigue crack monitoring in steel bridges

Coating sensors are used for high-precision monitoring of fatigue cracks in steel bridges. However, the time-variation temperature has a considerable impact on the monitoring precision of fatigue cracking of steel bridges. This study developed a coating sensor using silver-plated copper powder (conductive filler)/acrylate composites as a sensing layer of a coating sensor to monitor fatigue cracks considering variable ambient temperatures. The synthesis and preparation of the composite were presented, and the microstructures of the coating sensor composites were observed by scanning electron microscopy. The bulk conductivity of the sensing layer at different conductive filler contents was measured by the four-probe method to investigate the effect of the concentration of the conductive filler on the electrical conductivity and temperature sensitivity of the resistivity. Moreover, the fractional change in resistivity (FCR) of the sensing layer was tested over a range of temperatures to investigate the temperature sensitivity of resistivity at different conductive filler contents. Finally, the composite with the lowest temperature sensitivity of resistivity was selected to prepare a coating sensor for fatigue crack monitoring. The composite of the sensing layer with 60 wt% of conductive filler content had the lowest temperature sensitivity of resistivity with a minimum value (5.1%) of FCR. The maximum range of the FCR did not exceed 6.4% under cyclic loading and variation-time ambient temperatures. The temperature variation had minimal effects on the output signal of the coating sensor compared with the output signal variation caused by fatigue cracking. The proposed coating sensor can be used for high-precision monitoring of fatigue cracking in steel bridges under different ambient temperatures.

Piezoresistive behavior in cement-based sensors: Nonlinear modeling and preliminary application

Self-sensing cement sensors detect stress/strain by measuring the fractional change in electrical resistivity. However, neglecting the nonlinear portion of the FCR-stress/strain curves may limit monitoring range. Existing functional models lack versatility and physical meanings of parameters. A new model based on Ramberg-Osgood relation, incorporating the gauge factor, fractional change in resistance, and strain was proposed to cover linear and nonlinear regions. To validate the model, compression and tension cement sensors made of ultra-high toughness cementitious composite and multi-walled carbon nanotubes were tested. Results from various types of cement-based sensors validated the model's versatility. A four-point bending test on a C70 steel-reinforced concrete beam with an embedded cement sensor confirmed the feasibility of the proposed functional model.

An Experimental Approach to Assess the Sensitivity of a Smart Concrete

Structural health monitoring of concrete infrastructure is a critical concern for timely repair and maintenance. This study provides an innovative approach utilizing smart concrete integrated with multi-walled carbon nanotubes (MWCNTs) to enhance electrical conductivity. The smart concrete’s self-sensing capability is assessed through fractional change in electrical resistance (FCR) measured using a four-probe technique. Four-point bending and compressive tests explore the material’s response to cyclic and monotonic loads. Additionally, the impact of saturation levels on self-sensing sensitivity is investigated through compressive tests on varying saturation degrees. Remarkably, a substantial correlation between crack mouth opening displacement (CMOD) and FCR is observed during cyclic bending tests, where FCR increases significantly (from 0.019% to 154%) as CMOD rises from 0.004 mm to 0.55 mm. Digital image correlation (DIC) further validates CMOD measurements and their correlation with FCR. Moreover, this study reveals that amplitude of loading and degree of saturation have a significant effect on the self-sensing of the smart concrete. In saturated conditions, the self-sensing response of the material is insensitive to the mechanical strain, while with reduction in the saturation degree, a quasi-linear response is observed. To assess the sensitivity of the smart concrete, stress and strain sensitivities were evaluated, revealing a noteworthy enhancement of approximately 33% and 50% in stress and strain sensitivity, respectively, as saturation levels decreased. The self-sensing response of the material is very sensitive to the mechanical strain during monotonic loading and damage. These findings indicate the potential of smart concrete as a promising tool for comprehensive, real-time structural health monitoring for infrastructure during its entire life.

Effect of micro steel fibre contents on compressive and self-sensing properties of polyethylene fibre-reinforced cement composite (PE-FRCC) in cyclic compression

This study is conducted to develop a cement-based strain-detecting sensor with high cost-effectivity, large strain measuring range and good compatibility with concrete infrastructures. The paper describes experimental results on the compressive properties and piezoresistive behaviour of polyethylene(PE) fibre-reinforced cement composite(PE-FRCC) with different contents of micro steel fibres (SFs) under cyclic compression. The synthetic PE fibres were added into cement-based mortar to improve the strain capacity in compression and micro SFs at 0.25-1.5% by volume fraction of cement were incorporated to improve the compressive properties and electrical conductivity. Test results show that for the PE-FRCC with compressive strength of 32MPa, the increase in the micro SF content to 0.5% increased about 45% in the compressive strength compared to PE-FRCC without SFs. The addition of micro SFs into PE-FRCC improved the compressive properties, such as modulus of elasticity and lateral confinement. The incorporation of micro SFs is also effective to reduce the signal noise in the relationship between fractional change in resistance (FCR) and axial strain of PE-FRCC. PE-FRCC sensor with more 1.0% micro SF (PE0.75+SF1.00 composite) possess a strong linear relationship between FCR and axial strain during repeated compression at different stress amplitudes.

Carbon nanotubes-coated cement particles for cement-based sensors with excellent piezoresistivity

Typically, self-sensing cement composites are prepared by directly mixing cement particles with conductive additives, such as carbon black, carbon nanotubes (CNT), and graphene. This study proposes a novel approach to directly coat cement particles with CNT as the conductive filler (CNT@cement) before contact with water, aiming to develop a high-performance self-sensing cement-based sensor. CNT@cement nano/micro hybrid fabrication relies on a simple and efficient method that enables the uniform absorption of CNT on the surface of cement particles without any surfactants, thereby not diminishing the workability and mechanical properties of cement composites. This cement composite exhibits improved microstructure, bending strength, and electrical conductivity. Remarkably, the formulation with the addition of 0.1 wt% CNT@cement hybrid increases the bending strength by about 23% and improves the electrical conductivity by approximately two orders of magnitude, outperforming previously reported cement composites with similar CNT content. Additionally, outstanding piezoresistivity with a fractional change in resistivity of 1.26 is achieved for our cement-based sensor. These findings represent a major step toward the practical application of CNT in structural health monitoring.

Relation between electrically conductive properties and flexural behaviors of ultra‐high‐performance concrete

AbstractThe ability of the resistivity measurement to study the crack propagation behavior of the ultra‐high‐performance concrete (UHPC) under flexural loading was analyzed, and focused on investigating the effects of crack length and the fracture process zone (FPZ) on the change in electrical resistivity in the post‐cracking stage. The results indicated that the strain‐dependent resistivity characteristic was able to drawn by a linear‐fitting equation before the crack initiated (stage I). After the crack initiated, the change in electrical resistance of the UHPC can be good to reflect the crack development in the post‐cracking stages (II and III), then, the relationship between the crack propagation behavior and the fractional change in electrical resistance (FCR) can be quantitative analysis by using an exponential function. It was also found that the evolution of the crack length and FPZ also had an appreciable impact on the variation tendency of the FCR. The crack length increased dramatically at first and then increased smoothly with the increase of FRC, while the FPZ showed the reverse change trend.

Flexible and Stretchable Piezoresistive Sensor with Decoupled Pressure Sensing Capability

AbstractPressure sensors made on a mechanically deformable substrates are widely available for health monitoring systems, tactile sensors, and human–machine interfaces. While their sensitivity typically exceeds that of the human skin, it is highly challenging to perceive multiple kinds of mechanical inputs, such as normal, stretching, bending, and/or twisting forces, in a decoupled manner. For example, the interpretation of the specific pressure‐related distortion requires differentiation of such pressure stimuli from the simultaneously measured mixed deformation. This report proposes a sensor with an engineered geometrical configuration that dramatically reduces its mechanical distortion made by non‐pressure related stimuli. Such decoupled‐sensing capability for normal force is characterized by a linear response of fractional resistance change at 2.07 kPa−1and negligible responses to other deformations such as stretching and bending. An in vitro sensor demonstration for the diagnosis of stress urinary incontinence presents one mode of practical application of the sensor. Facile fabrication allows an interconnected array and wireless network to capture the spatial distribution of normal force and to record the data with consumer devices, respectively.

Development and Investigation of Repair Self-Sensing Composites Using S-CNT

This study analyzed the mechanical and electrical characteristics of repair self-sensing composites. In order to ensure homogeneous dispersion of carbon nanotubes (CNTs) in the repair mortar, porous powder was impregnated with the liquid MWCNT, dried, and then pulverized. This CNT powder was named S-CNT, and a repair self-sensing cement composite was fabricated using it with different dosages, by weight, of 3, 6, and 9%. Mechanical and electrical performances of the developed materials were investigated through flexural, compressive, and bonding strengths, dry shrinkage, porosity, and fractional change in resistance (FCR) tests. There was little difference in terms of strength, between the three different composites made with the different dosages of S-CNT. The strength of the composite with 9% of S-CNT was even higher than that of the plain specimen. As a result of measuring drying shrinkage, conducted to evaluate the effect of improving dispersion, the length change rate decreased as the amount of S-CNT increased. As a result of the porosity results of the specimens incorporating the same mass of CNT as S-CNT, it was confirmed that the dispersibility was clearly improved. In addition, as an electrical characteristic, when the S-CNT mixed specimen was repeatedly loaded with a bending load, FCR appeared, confirming the self-sensing performance.

Multifunctional Concrete with Graphene-Based Nanomaterials and Superabsorbent Polymer

This study reports on the development of a multifunctional concrete using graphene nanoplatelet (GnP) and sodium polyacrylate (SP) superabsorbent polymer. A combination of concrete functionalities was convened to improve, i.e., high strength and durability along with smart properties such as self-healing and self-sensing. GnP (0.05% by weight of cement) and SP (0.11% by weight of cement) were dispersed in concrete. Compared to the control concrete mix (no GnP and SP), the compressive strength increased 14% by GnP and decreased 9% by SP, and their combination resulted in a 6% enhancement in strength. The durability performance of concrete samples under coupled degradation mechanisms of freeze-thaw and chloride ion ingress suggested that SP in concrete has a better performance than GnP in concrete. SP in concrete shows self-sealing abilities resulting in less chloride ion penetration. However, the combined effect of both GnP and SP in concrete resulted in the maximum reduction in chloride ion penetration depth under freeze-thaw, a 42% reduction compared to the control mix. Microstructural analysis was conducted and found to resist the effects of freeze-thaw and reduce chloride ion penetration in modified concrete compared to the control concrete mix. GnP developed self-sensing abilities in concrete, resulting in about 12.7% fractional change of electrical resistance under 10 KN of cyclic compressive loading. The synergic impact of GnP and SP possesses a new prospect for developing highly efficient multifunctional concrete.

Experimental Investigation on Flexural Behaviour of Sustainable Reinforced Concrete Beam with a Smart Mortar Layer

This paper deals with an experimental study of the flexural behavior of sustainable reinforced cement concrete (RCC) beams with a smart mortar layer attached to the concrete mixture. In total, nine RCC beams were cast and tested. Two types of reinforced concrete beams were cast, and three different beams of sizes 1000 × 150 × 200 mm and six different beams of sizes 1500 × 100 × 250 mm were considered. The flexural behavior of these RCC beams was studied in detail. The electrical resistivity of these beams was also calculated, which was derived from the smart mortar layer. Research on the application of smart mortars within structural members is limited. The experimental results showed that the smart mortar layer could sense the damage in the RCC beams and infer the damage through the electrical measurement values, making the beam more sustainable. It was also observed that the relationship between the load and the fractional change in electrical resistance was linear. The fractional change in electrical resistivity was found to steadily increase with the increase in initial loading. A significant decrease in the fractional change in electrical resistivity was seen as the load approached failure. When a layer of mortar with brass fiber was added to the mortar paste, the ultimate load at failure was observed and compared with the reference beam specimen using Araldite paste. Compared to the hybrid brass-carbon fiber-added mortar layer, the brass fiber-added mortar layer increased the fractional change in the electrical resistivity values by 14–18%. Similarly, the ultimate load at failure was increased by 3–8% in the brass fiber-added mortar layer when compared to the hybrid brass-carbon fiber-added mortar layer. Failure of the beam was indicated by a sudden drop in the fractional change in electrical resistivity values.

Carbon nanotube polymer nanocomposites coated aggregate enabled highly conductive concrete for structural health monitoring

Recently, we proposed a new strategy to develop a three-dimensional conductive network within a cement mortar by coating sand with graphene. In such a design, the interfacial transition zone (ITZ) was directly embedded in the conductive network, thus resulting in high piezoresistive performance. Considering that the ITZ between coarse aggregate and paste is typically much more vulnerable than that of the ITZ between fine aggregate and paste, here we extend this strategy to concrete, whose piezoresistive property has been rarely reported yet intimately relevant for practical application. Conductive fine and coarse aggregates are readily prepared by dipping coating with carbon nanotube (CNT) polymer slurry. Because of the high volume percentage of aggregates (∼70%) in concrete, the obtained concrete exhibit very high conductivity at low CNT usage of 0.41% (by weight of cement), several orders of magnitude higher than that reported before at similar CNT load. We find that the mixture incorporating conductive aggregates has a 28-day electrical resistivity of 1076 Ω cm with a compressive strength loss of 17.8%. On this basis, we further optimize the high-conductivity concrete by connecting conductive aggregates with a small amount of 0.25 wt% carbon fibre, which demonstrates an outstanding 28-day electrical resistivity of 235 Ω cm and an excellent fractional change in resistivity of ∼80%, more than one order of magnitude higher than those obtained in comparable systems. The experimental results also testify that our smart concrete exhibits acceptable mechanical properties and durability. The simple operation and low-cost benefits make our smart concrete demonstrate great potential for large-scale practical application.

Growing Nanocrystalline Graphene on Aggregates for Conductive and Strong Smart Cement Composites

Highly conductive concrete/mortar has been long pursued to realize structural health monitoring in the development of smart-cement-based facilities. However, it remains challenging to significantly increase the electrical conductivity of concrete/mortar without lowering the compressive strength and flowability. Here, nanocrystalline-graphene-coated aggregates (termed Gr@AGs) are synthesized to break this conductivity-strength tradeoff. Admixing Gr@AGs with cement enables the construction of a conductive network of graphene that simultaneously strengthens the interfacial transition zone between aggregates and paste. As a result, high conductivity and improved mechanical properties have been simultaneously realized in Gr@AGs-based smart mortars. The significant positive effects of Gr@AGs are further enhanced by combining them with a low percentage of carbon fiber. Typically, the 28-day compressive/flexural strength of the optimized mortar increases by 12.2%/19.4%, with the electrical resistivity reduced by over 3 orders of magnitude from ∼4.6 × 105 to 182 Ω cm. On this basis, we demonstrate high-sensitivity cement-based piezoresistive sensors with a fractional change in resistivity as high as ∼25%, which is more than 1 order of magnitude higher than those reported in comparable systems. This study provides a solution to the critical issues in developing smart cementitious composites by taking full advantage of graphene's properties.

Effect of multiwalled carbon nanotube size on electrical properties of cement mortar composites

Cement mortars (CM) containing different contents and sizes of multiwalled carbon nanotubes (MWCNTs) were prepared using surfactants in combination with ultrasonic dispersion. The effects of the content, diameter and length of MWCNTs on the electrical conductivity of cement mortar and the self-inductive piezoresistive rate under single and cyclic loading were studied using the four-electrode method. The results show that the conductive percolation thresholds of CMs containing MWCNTs with different length–diameter ratios occur at an approximate MWCNT content of 0.1 wt%. The electrical conductivity of cement mortars with MWCNT diameters of 10–20 nm was the largest for a content of 0.1 wt%, and the values were 112% and 128.3% of the conductivity of the MWCNTs/CM with diameters of 20–40 nm and 40–60 nm, respectively. In addition, the fractional change in resistivity of the cement mortar specimens varied most significantly at a content of 0.75 wt% of MWCNTs; the fractional change in resistivity reached 14.27%. Adding small-diameter MWCNTs to cement mortar can maximise the sensitivity of electrical resistance of cement mortar to compressive stress.

A novel measurement system for self-sensing graphite-cement composites

Carbon-based conductive fillers have been incorporated into cement matrix to develop smart self-sensing materials with piezoresistive properties. However, accurately measuring the sensing property of the cement composite without compromising its mechanical performance is not easy to achieve in practical engineering. Therefore, in this study, a novel experimental setup for measuring the self-sensing properties of conductive fillers embedded cementitious composites was developed. This multi-functional measurement system is able to measure specimens under compressive and flexural stress with different loading profiles, apply various loading rates, obtain the electrical properties, and measure the strain using both LVDT and Particle Image Velocimetry (PIV) or Digital Image Correlation (DIC) techniques with all the data synchronised to one file sharing the same time stamp controlled by Python codes. In this study, the piezoresistivity and the performance on damage detection of the cementitious composites with low graphite concentration (5%) in a bulk form were investigated through monotonic compressive and flexural tests. Experiment results include the specimens’ stress, strain and Fractional Change in Resistivity (FCR). Data analysis showed that the set-up and methodology developed in this study are effective to test self-sensing cementitious composites, and the graphite-cement composites used in this study have a stable piezoresistivity and able to detect damage upon failure.

Stress self-monitoring performance of grouted sleeves with smart grout in fabricated reinforced concrete beams

Currently, grouted sleeves are widely used in the connection of prefabricated RC members. In this study, the smart grout with stress self-sensing performance was adopted to encapsulate grouted sleeves in which the structural and sensing functions are perfectly combined. Three parameters were investigated: grouted sleeve types, cycle index, and loading amplitude. In addition, a theoretical model was proposed to address the relationship between the fractional change in resistance (FCR) and the vertical load. The results revealed that with the increase in the bending moment, the FCR of the smart grouted sleeves increased at the bottom of the RC beams. Moreover, the repeatability and stability of the stress self-monitoring performance decreased with the increase in the vertical pressure P, which was positively correlated with the residual value of the deflection. Then the agreement between the experimental and calculated FCR demonstrated the validity of the proposed model.

Structural performance of reinforced concrete beams with 3D printed cement-based sensor embedded and self-sensing cementitious composites

Cementitious composites containing conductive functional fillers can achieve self-sensing and continuous monitoring of the damages and cracks through piezoresistive characteristics defined as the electrical resistivity change under external deformation. Previous studies developed two types of self-sensing cementitious composites expressing superior piezoresistive characteristics, as well as good linearity, repeatability, and sensitivity. This research further investigates the flexural damage sensing capability of the developed self-sensing cementitious composites by applying them to reinforced concrete beams. The 3D printed self-sensing cementitious composites containing carbon fibre (CF) at 0.7 wt% and activated carbon powder (ACP) at 0.25 wt% were tested as the embedded sensors in this study. Mould cast self-sensing cementitious composites developed by 100 wt% of magnetite aggregate (MA), 0.3 wt% of CF, and 0.05 wt% of carbon nanotube (CNT) were examined in bulk form. The corresponding fractional change in resistivity (FCR) was attained on the tension face of the reinforced concrete beams when subjected to flexural loading. Experimental findings suggest that the embedded 3D printed cement-based sensors in beam elements can contribute to the load-carrying capacity of the reinforced concrete beam, achieving an average load of yielding at 88.65 kN and a maximum loading capacity of 111.09 kN, which is 10% and 12% higher compared with the controlled reinforced concrete beam, respectively. In terms of sensing performance, both 3D printed self-sensing cementitious composites in sensor form and mould cast self-sensing cementitious composites in bulk form could reflect stress and strain changes and detect crack formation in reinforced concrete beams, which demonstrate gage factors at 318 and 527, respectively. However, 3D printed cementitious sensors are more effective when reinforced concrete beams are severely damaged. In terms of self-sensing cementitious composites in bulk form, the randomly distributed CF and CNT could provide a more pronounced crack and damage sensing capability, with fluctuations that can be observed at both low and high levels of damage.

Mechanical Characteristics and Self-Monitoring Technique of Smart Cementitious Mixtures with Carbon Fiber and Graphite Powder as Hybrid Functional Additives

In this paper, the self-sensing properties of cementitious composites under compressive loads were investigated by utilizing hybrid functional fillers, which are responsible for creating an electrical network that is used to build the self-sensing capability within the traditional cement-based mixtures. Most of the previous works depict the self-sensing capability with the aid of one type of functional fillers or fibers. The present paper attempts to utilize two types of functional fillers, representing a gap filling within the subject. Four hybrid proportions of Graphite (G) (wt.%) and carbon fibers (CF) (vol.%) were introduced. These are (0.5, 1.0), (1.0, 0.75), (1.5, 0.50) and (2.0, 0.25) respectively. In addition to carbon-based materials, polypropylene, polyolefin, and steel fibers are used as reinforcing fibers. One type of fiber was utilized in each manufactured mixture with a constant rate of 2% by volume of the mixture. A plain mixture without functional fillers has also been manufactured. The samples were non-destructively tested by an ultrasonic device before a uniaxial compression test was performed. To verify the self-sensing properties of the manufactured samples, the electrical resistance of the samples was recorded during load application each second. The self-sensing behavior was better for mixtures containing high dosages of graphite with respect to the fractional change in electrical resistivity (FCER). Steel and polyolefin fibers showed good results in terms of compressive strength behavior. However, polypropylene fibers showed the lowest compression strength among all types of reinforcing fibers used.

Graphene coated sand for smart cement composites

• The GO on the GO-coated sand anneals and then microwaves to graphene-coated sand. • Self-sensing cement composites enable by nano-engineers cement-aggregate interfaces. • The conductive path in mortar mainly consists of G@sand with ITZ located in between. • M-G@FAg mortar demonstrates electrical resistivity of 960 Ω·cm and an FCR of ∼ 18%. Unlike conventional approaches of direct addition of carbon-based conductive fillers into cement matrix in developing smart sensing composites, this study proposes a targeted and therefore more efficient approach through nano-surface engineering of the sand. Specifically, a simple method that enables uniform adsorption of graphene oxide onto the surface of the sand particles, followed by simple annealing and microwave treatment to prepare graphene-coated sand (conductive aggregates). Scanning electron microscopy indicates that about 62.2% of the sand surface area is successfully coated by graphene, with an average thickness of approximately 8.8 nm. The mortar incorporating conductive aggregates demonstrates outstanding electrical conductivity (resistivity of 960 Ω·cm) and a high fractional change in resistivity of ∼ 18% under cyclic compressive loading, which outperforms previously reported results obtained by direct addition of graphene or carbon nanotubes at equivalent concentrations. The use of conductive aggregates in mortars also results in other minor benefits such as a slight enhancement in flowability and reduction in water sorptivity. All of these were achieved without substantial reduction in 28-d compressive strength. These findings demonstrate a great potential of aggregate surface nano-engineering for developing smart cement-based composites for practical sensing applications.

Highly conductive and sensitive piezoresistive cement mortar with graphene coated aggregates and carbon fiber

Traditionally, conductive fillers are mixed directly with cement matrix before binding with aggregates to develop piezoresistive cement-based sensors. This results in the most vulnerable region, interfacial transition zone (ITZ), from which microcracks are initiated, merely located at the periphery of the conductive network and thus limits the sensitivity of the smart sensor. This study proposes a strategy to construct a three-dimensional (3D) conductive network in the mortar with ITZ directly embedded in it, thus greatly increasing both the conductivity and piezoresistivity without significantly sacrificing mechanical property. Highly conductive graphene-coated fine aggregates (termed conductive G@FAg particles) are prepared by adsorption of graphene oxide (GO) onto the fine aggregates (FAg) surface, followed by simple annealing and microwave treatment. The combined usage of conductive G@FAg particles and 0.1 wt% 6 mm-CF results in an outstanding electrical conductivity (resistivity of 580 Ω cm) and an excellent fractional change in resistivity (FCR of 30%) under cyclic compressive loading, with a negligible compressive strength loss of 3.1%. Remarkably, the addition of conductive G@FAg particles together with 0.5 wt% 10 mm-CF leads to an excellent conductivity (resistivity of 165 Ω cm) and self-sensing ability (FCR of ∼90%), which outperforms the previously reported mortar directly incorporated with the same concentration of CF and graphene. The much-improved conductivity and FCR value with such a low weight percentage of conductive carbon materials are attributed to the unique 3D network of conductive channels.

An Experimental Study on Electrical Properties of Self-Sensing Mortar

Self-sensing cementitious composites are a combination of conventional materials used in the construction industry along with any type of electrically conductive filler material. Research has already been carried out with various types of conductive fillers incorporated into cement mortars to develop a self-sensing material. Carbon fibres have been used as conductive fillers in the past, which is uneconomical. In order to overcome this drawback, brass fibres have been introduced. This study concentrates on the behaviour of self-sensing mortar under two different curing conditions, including air and water curing. The main aim of this paper is to determine the self-sensing ability of various types of smart mortars. For this purpose, an experimental study was carried out, with the addition of various brass fibres of 0.10%, 0.15%, 0.20%, 0.25%, and 0.30% by volume, to determine the electrical properties of cementitious mortar. In addition, different combinations of brass and carbon fibres were considered, such as 95% brass fibre with 5% carbon fibre, 90% brass fibre with 10% carbon fibre, and 85% brass fibre with 15% carbon fibre by volume, to determine the piezoresistive behaviour. A fractional change in electrical resistance was determined for all the mortar cubes. A fractional change in electrical resistance (fcr) is defined as the change in its electrical resistance with respect to its initial resistance (ΔR/R). Additionally, the temperature effects on self-sensing mortar under compressive loading were observed for various temperatures from room temperature to 800 °C (at room temperature, 200 °C, 400 °C, 600 °C, and 800 °C). It was observed that the addition of brass fibre to the cement mortar as an electrically conductive filler improved the self-sensing ability of the mortar. After 28 days of water curing, when compared to conventional mortar, the percentage increase in change in electrical resistance (fcr) was observed to be 26.00%, 26.87%, 27.87%, 38.55%, and 35.00% for 0.10%, 0.15%, 0.20%, 0.25%, and 0.30% addition of brass fibres, respectively. When the smart mortar was exposed to elevated temperatures, the compressive strength of the mortar was reduced. Additionally, the fractional change in electrical resistance values was also reduced with the increase in temperature. In addition to this, the self-sensing ability of smart mortars showed improved performance in water curing rather than in air-cured mortars. Compressive strengths, stress, strain, and change in electrical resistance (fcr) values were determined in this study. Finally, microstructural analysis was also performed to determine the surface topography and chemical composition of the mortar with different fibre combinations.