Flexible strain-sensing yarns are crucial components in smart textiles. However, integrating high-performance tensile and pressure sensing into a single yarn to monitor comprehensive human activities remains a significant challenge. In this work, we present a dual-model strain-sensing nanofiber yarn fabricated by self-shrinking MXene-coated carbon black/thermoplastic polyurethane (MXene@CB/TPU) composite nanofiber films into Janus-structured slim scrolls, followed by double twisting using internal stress. Carbon black doping enables conductive nanofibers to bridge propagated cracks in MXene coating, forming a synergetic conductive network. This structure enhances the yarn’s tensile sensing linearity from 0.810 to 0.994, while achieving a broad range of 106% with a gauge factor of 56. The self-shrunk and double-twisted architecture also provides dual-stage pressure sensitivity, endowing the yarn with an ultrahigh pressure-sensing range of up to 10 MPa, a sensitivity of 17.74 MPa⁻¹, and a linearity of 0.997 (0–3 MPa). Furthermore, the yarn exhibits excellent washability (> 30 ultrasonic washing cycles) owing to crosslinked nanofibers that protect the MXene layer. We demonstrated the practical applicability of this yarn by stitching it into various smart textiles, which successfully detected both tensile and pressure signals from full-range human activities. As a proof-of-concept, a smart waist support developed using this yarn can monitor both dynamic and static waist status. This work achieves high-performance dual tensile and pressure sensing in smart textiles using a single yarn, opening new pathways for advanced wearable electronics.

Extreme environments challenge the structural health monitoring of advanced equipment. In-situ dynamic tracking temperature is of particular value due to its enormous impact on material properties. However, the realization of such integrated temperature sensors typically requires complicated layer-by-layer molding and sintering processes including additional thermal barrier coatings. Herein, we report a laser-induced in-situ conductive passivation strategy for the fabrication of a thin-film based wide-range temperature sensor. The instantaneous thermal effect of laser irradiation creates crystalline conductive traces in response to temperature variations. Synchronously, it also allows the formation of an amorphous antioxidative layer without necessitating extra protective coatings. Such configuration enables precise real-time sensing across −50 ℃ to 950 ℃ following the Steinhart-Hart equation. It also exhibits durable performance with only 1.2% drift over 20 hours during long-term high-temperature, instant thermal shock, frequent wearing, and severe vibration. This in-situ, facile laser manufacturing strategy holds great promise in structural health monitoring and fault diagnosis for advanced equipment working in extreme environments.

Over the past decade, global industrial and research interest in flexible sensors has boosted their applications in diverse fields across intelligent medicines, human–machine interactions, soft robotics and Metaverse. Among them, multimodal flexible sensor systems play a critical role due to their capability to simultaneously detect multiple stimuli. This review presents an overview of recent advances in decoupled multimodal flexible sensor systems exploring spatial decoupling, temporal decoupling, signal processing, and other methods. Several categories of the systems are highlighted based on anti-interference structure, combinations of multiple mechanisms, surface functional modification, interlayer additional electrical properties and layer-specific differentiated outputs. Furthermore, the significant roles of machine learning and circuit strategies in decoupling mixed stimuli are illustrated. The burgeoning innovations in this research field should benefit the intelligent transformation of society, particularly amid rapid rise of artificial intelligence and automation.

Textiles with electronic components offer a portable and personalized approach for health monitoring and therapy. However, there is a lack of reliable strategy to integrate layered circuits and high-density chips on or inside textiles, which hinders system-level functionality and untethered user experiences. Herein, we propose monolithically integrated textile hybrid electronics (THE) on a textile platform, with multimodal functions and reliable performances. The textile system encompasses flexible electrodes, laser-induced sensors, and surface-mount devices, along with double-layer circuits interconnecting all of them. Vertical conductive paths are rendered by liquid metal composites infiltrated into textiles, which allows resistances less than 0.1 Ω while reserving intact textile structures. The assembled THE exhibits endurance to handwashing and crumpling, as well as bendability. We customize a wireless textile patch for synchronously tracking multiple physiological indicators during exercise. Furthermore, a textile band is elaborated for monitoring and alleviating muscular fatigue, demonstrating potential in closed-loop diagnosis and treatment.

Integration of sensors with engineering thermoplastics allows to track their health and surrounding stimuli. As one of vital backbones to construct sensor systems, copper (Cu) is highly conductive and cost-effective, yet tends to easily oxidize during and after processing. Herein, an in-situ integrated sensor system on engineering thermoplastics via hybrid laser direct writing is proposed, which primarily consists of laser-passivated functional Cu interconnects and laser-induced carbon-based sensors. Through a one-step photothermal treatment, the resulting functional Cu interconnects after reductive sintering and passivation are capable of resisting long-term oxidation failure at high temperatures (up to 170 ℃) without additional encapsulations. Interfacing with signal processing units, such an all-in-one system is applied for long-term and real-time temperature monitoring. This integrated sensor system with facile laser manufacturing strategies holds potentials for health monitoring and fault diagnosis of advanced equipment such as aircrafts, automobiles, high-speed trains, and medical devices.