Fractional Change In Resistance Research Articles

Large-scale deformation and damage detection of 3D printed continuous carbon fiber reinforced polymer-matrix composite structures

For the efficient monitoring regional deformation and damage of continuous carbon fiber reinforced polymer-matrix composite structures, a dual-material three-dimensional printing process was developed, in which continuous carbon fiber tows were integrated within the polymer matrix to construct smart sensing grids. Strategies based on the electrical-mechanical behavior of continuous carbon fiber tow for locating loading position and recognizing deformation field distribution, as well as damage detection, have been presented. The loading location can be determined through the maximum fractional change in electrical resistance of continuous carbon fiber tows in the longitudinal and transverse direction. A model based on the electrical-mechanical behavior of carbon fiber tow has been developed to identify the deformation field distribution. Both micro-damage and macro-damage can be detected according to the dramatic change in the slope of fractional change in electrical resistance with the strain. The effectiveness of above methods has been verified through experiments.

Self-monitoring of smart concrete column incorporating CNT/NCB composite fillers modified cementitious sensors

In this paper, cementitious sensors were fabricated with electrostatic self-assembled carbon nanotubes (CNT)/nano carbon black (NCB) composite fillers, and embedded into concrete columns to develop smart structural components. Self-sensing properties of the sensor/smart column were evaluated under cyclic loading and monotonic loading through measuring the fractional change in resistivity (FCR) of sensor. The effect of sensor on the mechanical strength of column was also studied. Experimental results showed that whether the sensor is embedded in concrete column or not, its piezoresistivity presents high stability and repeatability under cyclic loading within the elastic regime. The relationship between stress/strain and FCR of the sensor under monotonic loading obeys polynomial formulas. As the sensor is embedded into column, regardless of the concrete strength grade is C30 or C50, the piezoresistive behavior of the embedded sensor undergoes two phases, which is different from that of the sensor before embedded. This difference between the output signal characteristics results from the Poisson’s ratio and elastic modulus differences of sensor and concrete. In addition, the presence of sensor does not impact the bearing capacity of concrete column. The developed sensor is therefore suitable to be embedded into prefabricated components to make smart building products which can be calibrated for structural monitoring in real applications.

Evaluating the Self-Sensing Ability of Cement Mortars Manufactured with Graphene Nanoplatelets, Virgin or Recycled Carbon Fibers through Piezoresistivity Tests

This paper presents the resistivity and piezoresistivity behavior of cement-based mortars manufactured with graphene nanoplatelet filler (GNP), virgin carbon fibers (VCF) and recycled carbon fibers (RCF). GNP was added at 4% of the cement weight, whereas two percentages of carbon fibers were chosen, namely 0.05% and 0.2% of the total volume. The combined effect of both filler and fibers was also investigated. Mortars were studied in terms of their mechanical properties (under flexure and compression) and electrical resistivity. Mortars with the lowest electrical resistivity values were also subjected to cyclic uniaxial compression to evaluate the variations in electrical resistivity as a function of strain. The results obtained show that mortars have piezoresistive behavior only if they are subjected to a prior drying process. In addition, dry specimens exhibit a high piezoresistivity only when loaded with 0.2 vol.% of VCF and 0.4 wt.% of GNP plus 0.2 vol.% RCF, with a quite reversible relation between their fractional change in resistivity (FCR) and compressive strain.

Exploring scalable fabrication of self-sensing cementitious composites with graphene nanoplatelets

Graphene nanoplatelets (GNPs) have the same chemical structures as carbon nanotubes but their internal structure consists of multiple layers of graphene with thicknesses of only a few nanometers. Compared to carbon nanotubes, GNPs are less prone to agglomeration and entanglement when they are used as nanofillers in composite materials. This paper investigates the development of self-sensing cement composites using a simple fabrication method that does not require special preparation procedures such as ultrasonication and chemical (covalent) preparation for the dispersion of GNPs. Three fabrication methods were evaluated, two of which used variations of polycarboxylate-based superplasticizer and mechanical mixing to disperse GNPs into mortar matrix while the third served as a benchmark and relied on ultrasonication for the dispersion of nanomaterials. Standard prismatic mortar specimens containing different GNP concentrations were prepared to evaluate bulk resistivity at different curing ages and piezoresistive characteristics of the developed composites. Cyclic compressive tests were conducted to assess the relationship between the fractional change in electrical resistivity and applied load or strain. Scanning electron microscopy was employed to study the microstructure of the mortar composites and dispersion of GNPs. In addition, the effect of various factors on the electrical properties of the composites cast using the most promising fabrication method was evaluated. Results indicate that mechanically mixing GNPs first with water and superplasticizer, and then mixing the suspension with dry materials can lead to the development effective self-sensing mortar composites when the GNP concentration is at least 7.5% by weight of the cement (1.1% by volume). The incorporation of silica fume into GNP-reinforced mortar composites enhanced the piezoresistive characteristics of the composite. It was also shown that the piezoresistive behavior of GNP mortar composites are highly affected by the composition of the composition of superplasticizer.

Electrochemical impedance-based DNA sensor using pyrrolidinyl peptide nucleic acids for tuberculosis detection

A label-free electrochemical DNA sensor based on pyrrolidinyl peptide nucleic acid (acpcPNA)-immobilized on a paper-based analytical device (PAD) was developed. Unlike previous PNA-based electrochemical PAD (ePAD) sensors where the capture element was placed directly on the electrode, acpcPNA was covalently immobilized onto partially oxidized cellulose paper allowing regeneration by simple PAD replacement. As an example application, a sensor probe was designed for Mycobacterium tuberculosis (MTB) detection. The ePAD DNA sensor was used to determine a synthetic 15-base oligonucleotide of MTB by measuring the fractional change in the charge transfer resistance (Rct) obtained from electrochemical impedance spectroscopy (EIS). The Rct of [Fe(CN)6]3-/4- before and after hybridization with the target DNA could be clearly distinguished. Cyclic voltammetry (CV) was used to verify the EIS results, and showed an increase in peak potential splitting in a similar stepwise manner for each immobilization step. Under optimal conditions, a linear calibration curve in the range of 2–200 nM and the limit of detection 1.24 nM were measured. The acpcPNA probe exhibited very high selectivity for complementary oligonucleotides over single-base-mismatch, two-base-mismatch and non-complementary DNA targets due to the conformationally constrained structure of the acpcPNA. Moreover, the ePAD DNA sensor platform was successfully applied to detect PCR-amplified MTB DNA extracted from clinical samples. The proposed paper-based electrochemical DNA sensor has potential to be an alternative device for low-cost, simple, label-free, sensitive and selective DNA sensor.

Hybrid effects of steel fiber and carbon nanotube on self-sensing capability of ultra-high-performance concrete

This study aims to examine the feasibility of using steel fibers and carbon nanotubes (CNTs) on developing self-sensing ultra-high-performance concrete (UHPC). For this, four steel fiber types with two different shapes (straight vs. twisted) and three different aspect ratios from 65 to 100 were considered at a fiber volume fraction of 2%. 0.5% by volume of CNTs were simultaneously added. A plain UHPC with only 0.5% CNTs was also fabricated and tested as a control specimen. Test results indicated that the addition of 2% steel fibers was effective in enhancing compressive strength, elastic modulus, tensile strength, and strain capacity of the plain UHPC. The compressive behaviors of UHPC and ultra-high-performance fiber-reinforced concrete (UHPFRC) with CNTs were not predicted based on a fractional change in resistance (FCR) measurement, whereas the total tensile behaviors in terms of both stress-strain and stress-crack opening displacement (COD) curves were quite well simulated based on the FCR measurement and curve-fitting equations suggested. The unintended noise in the FCR of the plain UHPC was largely mitigated by adding the steel fibers, while the highest gauge factor (GF) under tensile load was found for the plain UHPC with CNTs. Using micro steel fibers was more effective in increasing the GF than using macro steel fibers, and better predictive results were obtained for the UHPFRC with straight steel fibers as compared to that with twisted steel fibers.

Self-sensing capability of ultra-high-performance concrete containing steel fibers and carbon nanotubes under tension

The feasibility of achieving self strain and damage sensing in an ultra-high-performance concrete (UHPC) mixture by incorporating micro steel fibers and multi-walled carbon nanotubes (CNTs) was investigated. Based on a preliminary study, the volume content of the CNTs was determined to be 0.5%, and 2% (by volume) micro steel fibers were included in the mixture to fabricate ultra-high-performance fiber-reinforced concrete (UHPFRC) that is similar to a commercially available product. Dog-bone specimens were fabricated using UHPC and UHPFRC with CNTs to evaluate the tensile performance and their self-sensing capability. Digital image correlation (DIC) and scanning electron microscopy (SEM) were also adopted to precisely analyze their mechanical and electrical properties. Test results indicated that the hybrid use of steel fibers and CNTs provided a significant improvement in tensile performance, including strength and post-peak ductility, compared to the use of CNTs alone. Crack bridging by CNTs was not achieved in the UHPC mixture, resulting in brittle tensile failure. Severe signal noise in the fractional change in resistance (FCR) and very high electrical resistance were observed in UHPC with CNTs, whereas very smooth FCR data with minor noise and much smaller resistance were obtained in the UHPFRC with CNTs. Furthermore, both pre- and post-peak tensile performance of UHPFRC with CNTs were well simulated based on the measured FCR with a high coefficient of determination (greater than 0.9). Consequently, the use of both steel fibers and CNTs in a UHPC mixture was recommended to improve post-cracking tensile performance and self strain and damage sensing capabilities.

Strain sensing ability of metallic particulate reinforced cementitious composites: Experiments and microstructure-guided finite element modeling

This paper evaluates the capability of waste iron powder-reinforced cementitious matrices as self-sensing materials in lieu of more expensive carbon fiber and nanoparticle reinforced matrices. Electrical impedance spectroscopy coupled with equivalent circuit modeling is used to determine the bulk resistance of the composite beams containing up to 40% by volume of iron particulates under flexural loading. The fractional change in resistance and the gage factor, as functions of the applied stress, increases with increasing iron particulate content, demonstrating the ability of these composites in self-sensing. A microstructure-guided electro-mechanical finite element model is used to simulate the strain sensing response of these composites. The 2D microstructure is subjected to different applied tensile stresses, and the deformed geometry subjected to an electrical potential to simulate the change in resistance. Debonding at the inclusion-paste interface under load, which is found to significantly influence the fractional change in resistance, is accounted for by using a bilinear softening model. The model is found to correlate well with the experimental data, and has the potential to facilitate microstructural design of materials to achieve desired degrees of self-sensing.

Self-Sensing of Position-Related Loads in Continuous Carbon Fibers-Embedded 3D-Printed Polymer Structures Using Electrical Resistance Measurement.

Condition monitoring in polymer composites and structures based on continuous carbon fibers show overwhelming advantages over other potentially competitive sensing technologies in long-gauge measurements due to their great electromechanical behavior and excellent reinforcement property. Although carbon fibers have been developed as strain- or stress-sensing agents in composite structures through electrical resistance measurements, the electromechanical behavior under flexural loads in terms of different loading positions still lacks adequate research, which is the most common situation in practical applications. This study establishes the relationship between the fractional change in electrical resistance of carbon fibers and the external loads at different loading positions along the fibers’ longitudinal direction. An approach for real-time monitoring of flexural loads at different loading positions was presented simultaneously based on this relationship. The effectiveness and feasibility of the approach were verified by experiments on carbon fiber-embedded three-dimensional (3D) printed thermoplastic polymer beam. The error in using the provided approach to monitor the external loads at different loading positions was less than 1.28%. The study fully taps the potential of continuous carbon fibers as long-gauge sensory agents and reinforcement in the 3D-printed polymer structures.

Electrical and piezoresistive properties of cement composites with carbon nanomaterials

This study investigates the effect of nanomaterials on the piezoresistive sensing capacity of cement-based composites. Three different nanomaterials—multi-walled carbon nanotubes, graphite nanofibers, and graphene oxide—were considered along with a plain mortar, and a cyclic compressive test was performed. Based on a preliminary test, the optimum flowability was determined to be 150 mm in terms of fiber dispersion. The electrical resistivity of the composites substantially decreased by incorporating 1 wt% multi-walled carbon nanotubes, but only slightly decreased by including 1 wt% graphite nanofibers and graphene oxide. This indicates that the use of multi-walled carbon nanotubes is most effective in improving the conductivity of the composites compared to the use of graphite nanofibers and graphene oxide. The fractional change in resistivity of the composites with nanomaterials exhibited similar behavior to that of the cyclic compressive load, but partial reversibility in fractional change in resistivity was obtained beyond 60% of the peak load. A linear relationship between the fractional change in resistivity and cyclic compression strain (up to 1500 με) was observed in the composites with multi-walled carbon nanotubes, and the gauge factor was found to be 166.6. It is concluded that cement-based composites with 1 wt% multi-walled carbon nanotubes can be used as piezoresistive sensors for monitoring the stress/strain generated in concrete structures.

An Experimental Study on Static and Dynamic Strain Sensitivity of Embeddable Smart Concrete Sensors Doped with Carbon Nanotubes for SHM of Large Structures.

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia

This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., x- and y-axis) by increasing the MMI in the x- and y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion.

Pressure sensitivity of multiscale carbon-admixtures–enhanced cement-based composites

The pressure-sensitive cement-based composites added with multiscale carbon materials, that is, carbon blacks, carbon fibers, and carbon nanotubes are investigated. In the article, the sensing property of cement-based composites with seven different proportions of carbon blacks, carbon fibers, and carbon nanotubes under cyclic loading is discussed and then the optimized formula among these seven proportions is chosen to investigate the influences of temperature and saturation degree on its sensing properties. In addition, the maximum perceivable frequency of multiscale carbon-admixtures–enhanced cement-based composite is obtained from the experimental results. The results indicate that the fractional change in resistance of the cement-based sensing composites increases at first and then decreases with the increase of temperature, but decreases with the increase of humidity. Additionally, the fractional change in resistance has a decrease with the increase of loading frequency, and the cement-based sensing composites prepared can perceive the biggest loading frequency of 0.5 Hz.

Electrical and Self-Sensing Properties of Ultra-High-Performance Fiber-Reinforced Concrete with Carbon Nanotubes.

This study examined the electrical and self-sensing capacities of ultra-high-performance fiber-reinforced concrete (UHPFRC) with and without carbon nanotubes (CNTs). For this, the effects of steel fiber content, orientation, and pore water content on the electrical and piezoresistive properties of UHPFRC without CNTs were first evaluated. Then, the effect of CNT content on the self-sensing capacities of UHPFRC under compression and flexure was investigated. Test results indicated that higher steel fiber content, better fiber orientation, and higher amount of pore water led to higher electrical conductivity of UHPFRC. The effects of fiber orientation and drying condition on the electrical conductivity became minor as sufficiently high amount of steel fibers, 3% by volume, was added. Including only steel fibers did not impart UHPFRC with piezoresistive properties. Addition of CNTs substantially improved the electrical conductivity of UHPFRC. Under compression, UHPFRC with a CNT content of 0.3% or greater had a self-sensing ability that was activated by the formation of cracks, and better sensing capacity was achieved by including greater amount of CNTs. Furthermore, the pre-peak flexural behavior of UHPFRC was precisely simulated with a fractional change in resistivity when 0.3% CNTs were incorporated. The pre-cracking self-sensing capacity of UHPFRC with CNTs was more effective under tensile stress state than under compressive stress state.

Comparative study on piezoresistive properties of CFRP tendons prepared by two different methods

Abstract Carbon fiber reinforced polymer (CFRP) material is an exceptionally and light fiber-reinforced polymer that can be used as a smart sensor due to its remarkable piezoresistivity. This study presents a comparative study on piezoresistive characteristics of CFRP tendons manufactured by two different methods, i.e., the vacuum process method (VPM) and the brush process method (BPM). The tensile and resistance tests were conducted simultaneously on two groups of CFRP tendon specimens respectively by VPM and BPM to investigate their differences in initial resistances, piezoresistive performance and sensitivity. Test results showed that the initial resistance of the CFRP tendons prepared by the VPM is larger than those prepared by the BPM. The resistances of the CFRP tendon specimens by two methods increase uniformly with increasing strain. The resistance increases more quickly at the same strain increment for specimens prepared by BPM compared with those for VPM. Three stages can be observed according to the variation of fractional change in resistance (d R / R ) with tensile strain. The scope of d R / R varies from 0% to 55% for BPM specimens, which is much wider than that for VPM specimens, which fall within 8.5%. The result is that BPM specimens are more sensitive than that of VPM. The values of sensitivity ‘ K ’ obtained for BPM specimens varying from 22 to 28 are much bigger than that for VPM ranging from 2.7 to 3.5. For BPM specimens, the pre-tension process can tighten up the fibers to reduce crimp and significantly reduce the amounts of bubbles during the brush process. However, the specimens prepared by VPM without undergoing the pre-tension process showed a relative looser state and carbon fibers might crimp.

Self-sensing piezoresistive cement composite loaded with carbon black particles

Strain sensors can be embedded in civil engineering infrastructures to perform real-time service life monitoring. Here, the sensing capability of piezoresistive cement-based composites loaded with carbon black (CB) particles is investigated. Several composite mixtures, with a CB filler loading up to 10% of binder mass, were mechanically tested under cyclic uniaxial compression, registering variations in electrical resistance as a function of deformation. The results show a reversible piezoresistive behaviour and a quasi-linear relation between the fractional change in resistivity and the compressive strain, in particular for those compositions with higher amount of CB. Gage factors of 30 and 24 were found for compositions containing 7 and 10% of binder mass, respectively. These findings suggest that the CB-cement composites may be a promising active material to monitor compressive strain in civil infrastructures such as concrete bridges and roadways.

A Low Energy-Noise 65nm CMOS Switched-Capacitor Resistive-Bridge Sensor Interface

A low energy-noise switched-capacitor (SC) sensor interface for resistive bridge sensor is presented. The SC amplifier achieves low-power metric with two operating modes using operation-phase-dependent biasing and compensation scheme in the op-amp design. This novel op-amp works in high-bandwidth high-power mode to sample the bridge signal for $13\mu \text {s}$ twice and in low-bandwidth low-power mode for $474\mu \text {s}$ over $500\mu \text {s}$ measurement interval. To further reduce the power of the SC amplifier in system level, a SC level-shift design is adopted. Regarding offset calibration, a capacitor divider based trimming scheme is implemented to generate the mid-point DC output voltage under the constraint of the feedback capacitor size. Implemented in 65 nm CMOS, the SC interface together with the regulator, voltage reference and trimming circuit occupies an area of 0.358 mm2. For the first test setup utilizing Half Wheatstone Bridge, the proposed SC amplifier consumes $12.3\mu \text {W}$ at 1 V regulated supply with a 2 kHz system clock. The measured Signal-to-Noise Ratio (SNR) of SC circuit is 55.6 dB. In the second test setup using a commercial sensor with 0.092 mV/kPa sensitivity, the interface has demonstrated the sensing function with sensitivity of 3.52 mV/kPa. Finally, compared to the representative prior-arts, this work has achieved the best energy-noise figure-of-merit at identical fractional resistance change.

Evaluation of carbon fiber-embedded 3D printed structures for strengthening and structural-health monitoring

This paper presents a technique for both structural reinforcement and self-monitoring of thermoplastic parts manufactured by fused deposition modeling (FDM). Continuous carbon fiber tows were embedded into FDM printed structures during the printing process, and the strength and piezoresistive behavior of the printed structures were evaluated. The specimens reinforced with carbon fibers have a tensile strength increase of 70% and flexural strength increase of 18.7% compared to non-reinforced specimens. In addition, the slope of fractional change in electric resistance with strain became a good indicator of strain measurement within the elastic region and damage detection in the yield region. Furthermore, lightweight and print duration reductions were achieved by decreasing the fill density while maintaining the structural strength, where up to 26.01% weight reduction and 11.41% print time reductions were achieved without decreasing the tensile strength. Finally, an artificial hand printed by FDM with embedded carbon fibers is discussed as a demonstration of this approach.

Effects of Surface Modification of n-Cu&lt;sub&gt;2&lt;/sub&gt;O/p-Cu&lt;sub&gt;x&lt;/sub&gt;S Thin Film Heterostructures for Enhanced Liquefied Petroleum Gas Sensing Properties

We report a novel mechanism to effectively detect LP gas based on surface modification through sulphidation followed by passivation of electrodeposited n-type cuprous oxide (Cu2O), forming a thin film nCu2O/p-CuxS semiconducting heterostructure. Electrochemically deposited n-type cuprous oxide (n-Cu2O) thin films on Ti substrates in acetate bath were sulphided using Na2S to fabricate n-Cu2O/pCuxS heterostructures. Subsequent passivation of these thin film structures using (NH4)2S vapor enhanced the sensitivity (fractional change in thin film resistance) when exposed to liquefied petroleum (LP) gas. Scanning electron micrographs (SEM) confirmed that typical unsulphided n-type Cu2O thin films exhibit polycrystalline surface morphology, while SEM of both sulphided and passivated thin films revealed micro/nano-crystalline surface morphological features with porous structures. As expected, the thin film structures obtained through sulphidation followed by passivation of n-type Cu2O films decreased the resistance (100 kΩ) in comparison to the resistance (1 MΩ) of the unsulphided n-type Cu2O thin films. Upon exposure to LP gas, the resistance of these thin film structures increased while, sensitivity to LP gas depended on the sensing temperature. Exposure of thin film structures fabricated by electrodepositing n type Cu2O thin films for 45 min, sulphided and passivated for 5 s and maintained at a sensing temperature of 45 oC to LP gas with a flow rate of 2.5 ml/min recorded the highest sensitivity of 48 %.

Self-sensing cementitious composites incorporated with botryoid hybrid nano-carbon materials for smart infrastructures

The botryoid hybrid nano-carbon materials were incorporated into cementitious materials to develop a new type of self-sensing cementitious composites, and then the mechanical, electrically conductive, and piezoresistive behaviors of the developed self-sensing cementitious composites with botryoid hybrid nano-carbon materials were comprehensively investigated. Moreover, the modification mechanisms of botryoid hybrid nano-carbon materials to cementitious materials were also explored. The experimental results show that the compressive strength and the elasticity modulus of the self-sensing cementitious composites botryoid hybrid nano-carbon materials decrease with the increase in the botryoid hybrid nano-carbon material content, while the Poisson’s ratio does the opposite. The percolation threshold zone of the self-sensing cementitious composites botryoid hybrid nano-carbon materials is from 2.28 to 3.85 vol.%. The optimal content of botryoid hybrid nano-carbon materials is 3.38 vol.% for piezoresistivity of the self-sensing cementitious composites botryoid hybrid nano-carbon materials. The amplitude of fractional change in resistivity goes up to 70.4% and 28.9%, respectively, under the monotonic compressive loading to failure and under the repeated compressive loading within elastic regime. The piezoresistive stress/strain sensitivity reaches (3.04%/MPa)/354.28 within elastic regime. The effective modification of botryoid hybrid nano-carbon materials to electrically conductive and piezoresistive properties of cementitious materials at such low content is attributed to their botryoid structures, which are beneficial for the dispersion of botryoid hybrid nano-carbon materials and the formation of conductive network in cementitious materials. The use of botryoid hybrid nano-carbon materials provides a new bottom–up design and fabrication approach for nano-engineering multifunctional cementitious composites.