In the past decades, multi-functional materials have attracted significant attention for applications in electromagnetic interference (EMI) shielding, thermal management, and intelligent sensing. Extensive efforts have focused on developing conductive composites with enhanced functional performance, increasing evidence indicates that the structural characteristics of conductive networks plays a decisive role in determining material properties. Among various structural engineering strategies, oriented conductive networks have emerged as the highly effective platform for optimizing charge transport, heat transfer, and electromagnetic wave attenuation through the deliberate alignment of functional fillers. Unlike isotropic networks, oriented architectures provide new opportunities for achieving high performance with reduced filler loading by forming anisotropic transport pathways,. This review systematically summarizes recent advances in multi-functional materials based on oriented conductive networks, with particular emphasis on the underlying structure–property relationships governing sensing, EMI shielding, and thermal management performances. The effects of filler characteristics, orientation degree, and structural features on functional properties are critically analyzed. More importantly, this review highlights oriented conductive networks as a universal structural design strategy for multifunctional materials and discusses emerging opportunities associated with advanced fabrication technologies, AI-assisted materials design, and integrated material–structure engineering. Finally, the remaining challenges and future perspectives regarding scalability, structural precision, reliability, and multifunctional integration are discussed to guide the future development of next-generation multifunctional composites.

Supercapacitors (SCs) are critical for high-power energy storage, yet their practical deployment is still limited by insufficient energy density. MXenes have emerged as promising electrode materials owing to inherent metallic conductivity, hydrophilic terminations, and intercalation pseudocapacitance, but suffer from layer restacking and oxidative degradation. Hybridizing MXenes with 3D carbon scaffolds offers a synergistic strategy by providing interlayer spacers, hierarchical ion transport pathways, and oxidation barriers. To the best of our knowledge, this review is the first to systematically couple the structural design of MXene/3D-carbon composites with machine learning (ML) guided optimization, summarizing recent advances in MXene/3D-carbon composite electrodes. This review systematically evaluates MXene etching routes and representative composite assembly strategies, and classifies existing systems into three structural categories, critically comparing their performance metrics, strengths, and inherent limitations. It further highlights the frontier applications of ML in performance prediction, compositional optimization, and mechanical design, along with current challenges, including data bias, the black-box nature of models, and the gap between idealized predictions and real synthesis. Overall, this work aims to provide a framework for integrating advanced synthesis strategies, 3D architectures, and data-driven tools toward the rational design of high-performance SCs.

The flight of insects exemplifies nature’s use of resonance to achieve large-amplitude, high-frequency motion with exceptional energy efficiency. Emulating this resonant amplification effect (RAE) in artificial systems remains a key challenge in soft robotics. Conventional dielectric elastomers (DEs) can be tuned electrically but rely on in-plane deformation. This generates insufficient inertial forces for resonance and thus requires rigid external frames, which consequently add fabrication complexity and reduces energy density. Here, we present a material-level approach to achieve intrinsic resonance amplification using space charge-driven dielectric elastomers (SC-DEs), which generate asymmetric electric fields and self-induced bending without external support. The optimized materials exhibited efficient actuation at low driving fields (~1 V μm^-1), with bending angles amplified from 20° to 150° through resonance without increasing field strength. This work establishes a framework for realizing resonance-amplified electromechanical actuation intrinsically within soft materials, offering new design routes toward lightweight, energy-efficient, and high-performance soft robotic systems.