Proximity sensors are essential for enabling non-contact pre-perception in robots and intelligent human–robot interaction. However, they are often limited by insufficient sensitivity and single functionality. Herein, a weakly electric fish-inspired flexible multifunctional proximity sensor is proposed to achieve high-sensitivity and environmentally adaptive perception. The sensing element is constructed using a flexible multilayer architecture based on AgNWs-WPU composite films, combined with a multi-capacitance coupling network and grounded shielding configuration to enhance weak electric field signal acquisition. To mitigate environmental interference, a dynamic frequency-adaptive strategy is further introduced, achieving a proximity sensing sensitivity of 0.212 mm ^−1 and a wide detection range of 0.5–200 mm. Based on this configuration, non-contact three-dimensional spatial localization and real-time trajectory tracking are demonstrated, and multi-attribute detection of target objects including size, material and shape is realized with a recognition accuracy exceeding 92%. In addition, integration with a robotic manipulator further demonstrates effective collision warning and active obstacle avoidance. This work advances active electric-field-based proximity sensing through the integration of a flexible five-channel sensing architecture and adaptive electromagnetic-noise suppression, offering a promising engineering strategy for robust non-contact perception in intelligent robotic systems.
Abstract The escalating demands from artificial intelligence, the Internet of Things, and wearable electronics are accelerating the rapid exploration of hardware that can deliver low-power, low-latency, and highly integrated information processing that transcends the limitations of conventional von Neumann architecture. To achieve this objective, memristor-based neuromorphic systems are significantly promising to enable the physical convergence of memory and computation. In particular, rare earth-based oxides (REOs) are particularly distinguished by their unique combination of multivalent states, versatile redox behavior, and highly tunable defect kinetics advanced by their specific 4f electronic configuration. These distinctive characteristics render REOs exceptionally promising for regulating resistive switching, stabilizing analog conductance modulation, and realizing synaptic plasticity with enhanced functional versatility. In this work, we review the remarkable progress of REOs-based memristors covering material design, switching mechanisms, synaptic emulation, array integration, and chip-oriented neuromorphic architectures. Further, we also systematically elaborate on their emerging applications in artificial intelligence hardware, neuroscience interfaces, and intelligent sensing systems. Finally, the key bottlenecks of REOs-based memristors constraining large-scale implementation are critically assessed in terms of variability, analog precision, endurance, and cross-level co-optimization. Therefore, REO memristors serve as a highly promising material system to bridge device-level innovation and next-generation brain-inspired hardware.
Abstract Body-centered cubic (BCC) metals often exhibit limited ductility at finite temperatures, and elemental synergy in multi-principal element alloys (MPEAs) offers a promising route to overcome this limitation. Here, we employ atomistic simulations with a high fidelity machine-learning potential—which outperforms traditional empirical potentials at capturing complex chemical interactions—to investigate mode-I crack propagation in the engineering-relevant NbMoTaW MPEA versus pure Mo. While Mo fails by brittle cleavage, the NbMoTaW undergoes ductile fracture mediated by dislocation activity. We demonstrate that the average-based Rice criterion demands local corrections to sample diverse chemical environments along the advancing crack. Specifically, the MPEA's intrinsic chemo-mechanical heterogeneity produces atomic-scale stress delocalization at the crack tip, generating a chemically-driven shielding effect that mitigates the singular stress concentration responsible for cleavage. In particular, Ta-related local chemical heterogeneities act as precursors that nucleate localized shear and dissipate plastic energy. By embedding such heterogeneities into a brittle Mo matrix, we demonstrate that a sufficient level of interconnectivity is required to amplify stress delocalization and promote dislocation nucleation, enabling a brittle-to-ductile transition of the fracture mode. These findings reveal a stress delocalization mechanism by which local chemical heterogeneities control intrinsic ductility in BCC alloys and provide a theoretical guide for composition design.
Short-wave infrared imaging holds transformative potential in semiconductor inspection, biomedical diagnostics, and autonomous driving. However, its broad adoption is hindered by the high cost of incumbent technologies such as InGaAs. Colloidal quantum dots (CQDs) offer spectral tunability and low-cost processing, yet they face a fundamental bottleneck when extending to longer wavelengths: increased quantum‐dot size degrades the interface with conventional transport layers (e.g. EDT), leading to surging dark current and deteriorated signal‐to‐noise ratio. Here, we propose a new interfacial‐engineering strategy to overcome this challenge. We design the 2D Bi _2 O _2 Te/PbS CQD heterojunction exhibiting an atomically flat interface and optimized band alignment, reducing the interfacial defect density by an order of magnitude. Based on this architecture, we fabricate high-performance infrared photodetectorsthat, at 1.7 μ m, simultaneously achieve a record‐low dark‐current density (98 nA cm ^−2 ), high external quantum efficiency (74%), and high specific detectivity (4.6 × 10 ^12 Jones). Furthermore, we successfully scale the process to produce a fully monolithic focal‐plane array with a 5 μ m pixel pitch and a format of 1920 × 1536, demonstrating exceptional imaging capabilities in complex scenarios such as silicon‐transparent imaging, haze‐penetrating vision, and moisture identification. This work not only provides a viable route to low‐cost, high‐performance SWIR imaging but, more importantly, establishes a general paradigm for precisely tailoring nano-crystal optoelectronic interfaces using 2D single crystals, opening a new pathway for the design of next‐generation on‐chip spectral‐sensing systems.
Generally, it is difficult to balance the comprehensive properties of saturation magnetization, effective permeability, and core loss in soft magnetic composites (SMCs), aiming to address the challenges of miniaturization, high-frequency, and high efficiency. Herein, we report a novel supranano multi-precipitate microstructure in amorphous SMCs via conventional cold compaction, which is located inside a nanosized surface layer of amorphous powders and was modulated by Ar and O _2 plasma treatments. The multi-precipitate contains 0.8 nm α -Fe, 1.6 nm Fe _3 O _4 , and 2.5 nm SiO _2 and Fe _2 O _3 , which are dispersedly distributed in the amorphous matrix. The SMCs showcase a coercivity of 0.13 Oe, achieving the minimum for typical amorphous and nanocrystalline SMCs so far, and consequently the balanced properties of high effective permeability of 37.3, and ultralow core loss of 191.18 kW m ^−3 at 1 MHz and 20 mT. This work paves the way for the development of next-generation SMCs via conventional cold compaction.
