Silver nanowire (AgNW) networks are promising electrode candidates for flexible organic solar cells (FOSCs) due to their outstanding optoelectronic properties and mechanical flexibility. However, their practical deployment remains hindered by high junction resistance and inherent surface irregularities, which lead to non-uniform current distribution and increased energy dissipation. Here, we report a hyaluronic acid (HA)-assisted Joule-heating strategy that enables spatially uniform yet junction-selective sintering within AgNWs. The HA treatment increases the density of effective inter-nanowire contacts and improves interfacial adhesion, thereby preconditioning the network for a more homogeneous current distribution. As a result, Joule heating is preferentially localized at electrically active junctions, leading to efficient welding without damaging the overall network. This synergistic regulation produces AgNW electrodes with reduced sheet resistance, improved surface smoothness, and enhanced mechanical robustness, while preserving high optical transparency. Based on the transition from localized current crowding to a homogenized transport regime, which contributes to reduced resistive losses and suppressed recombination, the FOSCs achieve a power conversion efficiency increased from 16.85% to 18.09%, which is the highest reported value of inverted FOSCs. This work establishes a general strategy for coupling network densification with electrically driven selective sintering, offering a scalable route toward high-performance transparent electrodes for next-generation flexible optoelectronics.

Heavy metal ions (HMIs) pose persistent risks to ecosystems and human health owing to their toxicity, environmental persistence, and bioaccumulation. Conventional laboratory techniques provide high sensitivity and accuracy, but their dependence on bulky instruments, skilled operators, and complex pretreatment restricts rapid on-site screening. Portable electrochemical systems offer a complementary strategy by integrating sensing electrodes, potentiostatic control, weak-current readout, and software-based signal processing to convert interfacial redox reactions into measurable electrical signals. This review examines portable electrochemical HMI detection from three perspectives: detection principles, hardware architectures, and field applications. It summarizes redox and stripping mechanisms, baseline correction, limit-of-detection (LOD) estimation, potentiostat evolution, and single- and multi-metal detection in complex matrices. Key bottlenecks include matrix-induced peak drift and fouling, coexisting-ion interference, limitations in weak-current readout, and insufficient field standardization. Future progress will require co-optimized sensing interfaces, low-noise electronics, multichannel and flow-cell formats, field calibration, and data-driven peak analysis.

Conductive microneedles (CMNs) combine the minimally invasive characteristics of microneedles with the electrical functionality required for sensing, recording, stimulation, and controlled drug delivery. By penetrating the stratum corneum with reduced pain and tissue damage, they provide efficient access to the skin microenvironment and have shown strong potential in wearable healthcare, precision diagnostics, and intelligent therapeutics. Despite these advantages, challenges remain in balancing mechanical robustness with electrical functionality, improving fabrication precision and reproducibility, maintaining interfacial stability, and achieving scalable manufacturing. In this review, the major fabrication routes for CMNs are summarized and compared in terms of forming principles, material compatibility, and conductivity-introduction strategies. Secondly, research on the key performances of CMNs is discussed. After that, the applications of CMNs in electrochemical sensing, bioelectrical signal acquisition, electrostimulation therapy, and drug delivery are overviewed, followed by a brief discussion of current challenges and future perspectives.

Friction dampers dissipate seismic energy through sliding but lack self-sensing capability. This study integrates friction dampers with triboelectric nanogenerators (TENGs), which convert mechanical energy into electrical signals, creating a self-sensing damper. Using friction pairs with large triboelectric differences, the system simultaneously achieves energy dissipation and sensing. During sliding, mechanical energy is partially converted into heat (dissipation) and electricity (sensing). Theoretical models link displacement and velocity to voltage and current, validated through cyclic loading tests varying velocity, displacement, and friction force. Results show stable energy dissipation (300-770 J/cycle) comparable to conventional dampers. Sensing performance is strong: voltage correlates linearly with displacement (0.00526 V/mm, R² = 0.94), and current with velocity (0.01914 μA/(mm/s), R² > 0.99). Unlike conventional TENGs, high friction alters triboelectric behavior via wear and heating, producing a unique voltage-velocity relationship. Scanning electron microscopy analysis confirms maximum wear at 34.2 kN, aligning with inflection points in electrical response. An empirical Q-V-f formula for high-friction conditions enriches triboelectric theory and guides damper design, emphasizing friction optimization for balanced dissipation and sensing stability.