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Experimental studies within the previous years showed that the behavior of concrete is improved by adding steel fibers. Due to bridging effect, steel fibers in a concrete matrix prevent crack propagation under static loads. This phenomenon increases the load-bearing capacity of steel fiber-reinforced concrete, specifically after the peak load. In contrast to similar studies, in this study the effect of fibers on steel fiber-reinforced concrete is directly described based on uniaxial compressive and tensile stress–strain curves. For this purpose, the effect of fiber on the stress variations is extracted from the difference between steel fiber-reinforced concrete and its corresponding concrete matrix uniaxial stress–strain curves. These differential stress curves were extracted from 103 experimental specimens, collected from the literature. Then, some equations were developed for them with appropriate accuracy, using genetic programming technique. These equations were only based on primary specifications of fibers and concrete matrix. In the next stage, an elastoplastic damage constitutive model initially developed for plain concrete was modified, using the developed steel fiber-reinforced concrete modeling equations. The proposed model was implemented in a finite element analysis software and successfully simulated the steel fiber-reinforced concrete behavior subjected to uniaxial and flexural experiments.

Here, we present a wearable potentiometric ion sensor for real-time monitoring of sodium ions (Na+) in human sweat samples using Na0.44MnO2 as the sensing material. Na0.44MnO2 is an attractive material for developing wearable electrochemical sensors due to its good Na+ incorporation ability, electrical conductivity, stability, and low fabrication cost. In the first step, the analytical performance of the electrode prepared using Na0.44MnO2 is presented. Then, a miniaturized potentiometric cell integrated into a wearable substrate is developed, which reveals a Nernstian response (58 mV dec–1). We achieved the detection of Na+ in the linear ranges of 0.21–24.54 mmol L–1, which is well within the physiological range of Na+. Finally, for on-body sweat analysis, the potentiometric sensor is fully integrated into a headband textile. This platform can be employed for non-invasive analysis of Na+ in human sweat for healthcare and disease diagnosis.

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