1e:T49c,A carbon nanotube polymer material was used to form a piezoresistive strain sensor for structural health monitoring applications. The polymer improves the interfacial bonding between the nanotubes. Previous single walled carbon nanotube buckypaper sensors produced distorted strain measurements because the van der Waals attraction force allowed axial slipping of the smooth surfaces of the nanotubes. The polymer sensor uses larger multi-walled carbon nanotubes which improve the strain transfer, repeatability and linearity of the sensor. An electrical model of the nanotube strain sensor was derived based on electrochemical impedance spectroscopy and strain testing. The model is useful for designing nanotube sensor systems. A biomimetic artificial neuron was developed by extending the length of the sensor. The neuron is a long continuous strain sensor that has a low cost, is simple to install and is lightweight. The neuron has a low bandwidth and adequate strain sensitivity. The neuron sensor is particularly useful for detecting large strains and cracking, and can reduce the number of channels of data acquisition needed for the health monitoring of large structures.1f:T521,It remains challenging to fabricate strain-sensing materials and exquisite geometric constructions for integrating extraordinary sensitivity, low strain detectability, high stretchability, tunable sensing range, and thin device dimensions into a single type of strain sensor. A percolation network based on Ti₃C₂T_x MXene/carbon nanotube (CNT) composites was rationally designed and fabricated into versatile strain sensors. This weaving architecture with excellent electric properties combined the sensitive two-dimensional (2D) Ti₃C₂T_x MXene nanostacks with conductive and stretchable one-dimensional (1D) CNT crossing. The resulting strain sensor can be used to detect both tiny and large deformations with an ultralow detection limit of 0.1% strain, high stretchability (up to 130%), high sensitivity (gauge factor up to 772.6), tunable sensing range (30% to 130% strain), thin device dimensions (<2 μm), and excellent reliability and stability (>5000 cycles). The versatile and scalable Ti₃C₂T_x MXene/CNT strain sensors provide a promising route to future wearable artificial intelligence with comprehensive tracking ability of real-time and in situ physiological signals for health and sporting applications.

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