A new surfactant combination compatible with concrete formulation is proposed to avoid unwanted air bubbles created during mixing process in the absence of a defoamer and to achieve the uniform and the maximum possible dispersion of multiwalled carbon nanotubes (MWCNTs) in water and subsequently in concrete. To achieve this goal, three steps have been defined: (1) concrete was made with different types and amount of surfactants containing a constant amount of MWCNTs (0.05 wt%) and the air bubbles were eliminated with a proper defoamer. (2) Finding a compatible surfactant with concrete compositions and eliminating unwanted air bubbles in the absence of a common defoamer are of fundamental importance to significantly increase concrete mechanical properties. In this step, the results showed that the polycarboxylate superplasticizer (SP-C) (as a compatible surfactant) dispersed MWCNTs worse than SDS/DTAB but unwanted air bubbles were removed, so the defoamer can be omitted in the mixing process.(3) To solve the problem, a new compatible surfactant composition was developed and different ratios of surfactants were tested and evaluated by means of performance criteria mentioned above. The results showed that the new surfactant composition (SDS and SP-C) can disperse MWCNTs around 24% more efficiently than the other surfactant compositions.

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Concrete sensors, which are manufactured by mixing conductive fibres (such as carbon nanotubes (CNTs)) with concrete, are one of the most significant and economical types of sensor. Two main factors affecting the performance of concrete sensors are the amount of CNTs and the quality of their dispersion in the mixture with regard to the combined effects of the surfactant composition and CNTs dispersed with different levels of energy. The goal of this research was to evaluate the effects of the main parameters affecting concrete sensor performance using various criteria (sensitivity of the sensor, standard deviation of the prediction error, repeatability, cross-correlation and hysteresis) in both static and dynamic loading regimes. Dynamic criteria such as sensitivity, internal repeatability, cross-correlation and hysteresis showed that the energy levels for the dispersion of CNTs have a greater effect on improving sensor performance than the amount of CNTs. On the contrary, the repeatability indicated that the amount of CNTs has a greater effect on sensor performance than the dispersion quality (energy level) of the CNTs. On the whole, the sensor produced with 0·15 wt% (by weight of cement) CNTs, superplasticiser and sodium dodecyl sulfate as a surfactant using the maximum energy level (ultrasonic bath for 2 h and 90 min of probe's ultrasonication) offered the best performance both in the static and dynamic load regimes.

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Assessing the damage level in concrete infrastructures over time is a critical issue to plan their timely maintenance with proper actions. Self-sensing concretes offer new opportunities for damage assessment by monitoring their electrical properties and relating their variations to damage levels. In this research, fatigue tests were conducted to study the response of a self-sensing concrete under high-cycle dynamic loading. The concept of G-value was defined as the slope of the voltage response baseline of the self-sensing concrete over time that reflects the damage created under the fatigue-loading test. Based on this definition, log (G)–log (N) curves were obtained using a linear regression approach, with N representing the number of cycles during the fatigue tests. While traditional fatigue curves S-log (N) are used to estimate the remaining life under fatigue loading, log (G)–log (N) diagrams can be used to determine the damage level based on the voltage response of the self-sensing concrete as a function of the loading history. This finding can be useful for the estimation of the lifetime and remaining life of self-sensing concrete structures and infrastructure, eventually helping to optimize the related maintenance operations.