Artificial intelligence reforges intelligent fibers

Abstract

Intelligent fibers serve as versatile functional interfaces facilitating bidirectional human-environment interaction and constitute foundational elements for next-generation wearable computing/human interaction systems. These intelligent fibers and wearables exhibit multifunctional capabilities, including perception or response to external stimuli, energy harvesting/storage, microclimate regulation, information transmission, and expansive multifunctionality [1][2][3]. The design of intelligent fibers entails complex multiscale parameter coupling, spanning from nanoscale building block feature to macrostructure optimized for wearable applications. The intricate multiscale composition-structure-property relationship, sensitive dependence of the fabrication parameters and unpredictable performance optimization in varied application scenarios, exceed the management and decoupling capability of conventional data systems, computational resources, and modeling approaches. Artificial intelligence (AI) provides essential methodologies for addressing these multi-scenario and cross-scale complexities, enabling a compelling synergy. For instance, intelligent fiber could serve as AI-driven terminals for signal acquisition and processing, while conversely, AI-accelerated algorithm and modeling could accelerate the cross scale structural design of intelligent fibers. This dual role necessitates a paradigm shift toward AI for Science (AI4S) frameworks in fiber materials research [4], driving concerted efforts to integrate AI throughout the material design and discovery pipeline. Figure 1 schematically illustrates this multiscale design paradigm and the AI-empowered workflow for intelligent fibrous materials.