Nano-Micro Letters最新文献

The widespread deployment of lithium iron phosphate (LiFePO₄, LFP) batteries has intensified the imperative to address the disposal challenges associated with retired LFP batteries, given their rapidly growing volumes. However, existing regeneration techniques remain constrained by their inherent complexity, high energy demands, and limited scalability, posing significant barriers to achieving efficient and economically viable solutions. Herein, inspired by medical injection therapy, a novel, non-invasive strategy for direct capacity rejuvenation is proposed by injecting recovery reagents into spent LFP batteries, circumventing the need for disassembly. This innovative approach leverages the I₃^-/I^- redox couple to activate residual/dead lithium on the graphite anode and selectively re-engineer the solid electrolyte interphase (SEI), preserving its functional components while optimizing interfacial dynamics. The restored lithium from the anode serves as an intrinsic source to replenish lithium deficits and rectify Li-Fe antisite defects within the degraded LFP cathode. The resulting regenerated pouch cells demonstrate remarkable recovery of electrochemical capacity, accompanied by superior kinetics performance and significantly extended cycle life. This pioneering strategy not only delivers an energy-efficient and cost-effective pathway for LFP battery regeneration but also holds transformative potential to redefine sustainable practices in lithium-ion battery reuse, thereby advancing their practical applications and prolonging their service life.

The rapid advancement of naturally microstructure-bioinspired flexible sensors has sparked interest in creating multifunctional systems for human-computer interaction (HCI). However, most existing biomimetic sensors struggle to integrate multiple sensing modes, limiting their practical applications. Herein, this study proposes a design concept for a fully biomimetic sensor. By employing hybrid manufacturing techniques to achieve layer-by-layer biomimicry of the natural layered structure of eggshells, a flexible sensor with multiple sensing modes is developed. The eggshell-inspired multifunctional hybrid flexible sensor (EMHFS) incorporates four functional layers: a triboelectric layer for noncontact sensing, a piezoresistive layer for pressure sensing, and hydrophilic-hydrophobic layers for directional moisture wicking, breathability, and antibacterial properties. The eggshell-inspired structure enables synergistic functionality, allowing seamless switching between contact and noncontact sensing modes. EMHFS demonstrates exceptional performance in multimodal HCI applications, including gesture-controlled robotic hands, wearable unmanned aerial vehicle control systems, and touchless screen password and gesture unlocking, while also exhibiting remarkable sensitivity to weak physiological signals such as breathing and pulse. This fully biomimetic approach offers a novel solution for advanced, flexible, and multifunctional HCI devices.

Recently, self-assembled monolayers (SAMs) have been confirmed as a promising hole-selective contact and interfacial modifier for inverted perovskite solar cells (IPSCs), contributing to an inspiring record power conversion efficiency close to 27%, along with excellent stability. This review demonstrates the critical role of SAMs in enhancing the performance of IPSCs. First, the structure-property and structure-stability relationship of SAMs is systematically expounded by examining their electronic structure, spatial configuration, and the resulting intermolecular forces. Second, it concludes the underlying mechanisms how their unique properties promote the performance of IPSCs, including energy-level alignment, defect passivation, improved interface carrier extraction/transport, and the suppression of ion migration. Third, the applications of SAMs in IPSCs are systematically summarized, covering their roles as hole-selective contacts, interface modifiers, and as components in Co-SAMs strategies. Large-scalable fabrication methods are also summarized to promote industrial processing of IPSCs. Finally, the prevailing challenges and future research directions are outlined, proposing a roadmap for designing SAM-based IPSCs with superior longevity. By critically evaluating the pivotal role of SAMs, this review provides a strategic framework to guide future research and accelerate the development of self-assembled molecules in high-performance and stable photovoltaic devices.

Conductive hydrogels are revolutionizing the fields of wearable sensors, implantable bioelectronics, and soft robotics. However, achieving both mechanical robustness and high conductivity within a single system remains challenging. Here, inspired by the cooperative vascular-neural networks in biological tissues, we develop a nanofiber-reinforced conductive hydrogel composed of poly(vinyl alcohol) (PVA), aramid nanofibers (ANFs), and in situ polymerized PEDOT:PSS. Through solvent- and thermally induced structural reorganization, the hydrogel evolves into a bi-continuous architecture in which the mechanical and conductive networks are intimately coupled. The tough, ANF-reinforced porous PVA mimics the vascular system, providing mechanical support and maintaining toughness, while the poly(3,4-ethylenedioxythiophene) (PEDOT) network resembles neural pathways, enabling efficient electron transport. This structural evolution enables a rare synergy of high tensile strength (10.72 MPa) and ultrahigh conductivity (452.75 S m^-1) with excellent biocompatibility. The hydrogel maintains stable conduction under impact and complex deformation, supporting multimodal sensing from large-amplitude joint motion to low-amplitude electrophysiological signals: electrocardiographic and electromyographic. When integrated with a convolutional neural network, it achieves 99.54% accuracy in recognizing five complex hand gestures. This bioinspired strategy paves the way for developing robust and conductive hydrogels toward next-generation intelligent wearable electronics.

The demand for accurate perception of the physical world has led to a dramatic increase in visual sensing data, accompanied by challenges in the energy efficiency of data processing. However, conventional vision systems with separated sensor and processing units struggle to handle increasingly intricate and large-scale data. As such, a rethinking of architecture design is necessary. Inspired by human visual systems, neuromorphic vision computing systems in which computation tasks are moved partly to the sensory or memory units offer transformative solutions to these challenges. As crucial hardware support, biomimetic synapses that replicate synaptic functions and dynamics are urgent for the development of future computing, while further progress requires materials that can support synaptic weight modulation. Given their excellent optical, electrical, and ion migration properties, halide perovskite materials have emerged as promising candidates for biomimetic synapses. Here we review the latest efforts of synaptic devices based on halide perovskite materials for neuromorphic vision computing. We demonstrate the operating mechanism of perovskite synapses and introduce their potential applications in realizing neuromorphic vision computing. We address challenges and future directions related to biomimetic perovskite synapses.

The I-III-VI silver indium gallium sulfide (AIGS) quantum dots (QDs) have gained extensive attention owing to their tunable emission wavelength and ecofriendly composition; however, the performance of AIGS QD-based light-emitting diodes (QLEDs) remains constrained by suboptimal surface state, significantly lagging behind that of other heavy-metal-containing QD counterparts. Herein, we propose a ligand-reshaped strategy aimed at optimizing the surface state of AIGS QDs to enhance the performance of QLEDs. A polyfunctional ligand, dimercaptosuccinic acid (DSA), is introduced to reshape the QD surface through passivation of uncoordinated Ga³⁺ and suppression of S vacancies. After DSA passivation, the QDs exhibit not only exceptional luminescent properties with a photoluminescence quantum yield of 89%, but also pure emission with a narrow full width at half maximum of 31 nm. Concurrently, DSA passivation markedly improves the electrical transport characteristic of QDs, thereby ensuring efficient carrier injection. Resultantly, the reshaped QLED achieves a maximum peak external quantum efficiency of 8.4% along with a narrow FWHM of 31 nm, representing a record performance reported thus far for the AIGS system. The proposed DSA ligand-reshaped strategy endows AIGS QLEDs with both high efficiency and color purity, substantially advancing their potential for the application in QD lightings and display technologies .

The ultrathin metal electrode in semitransparent organic photovoltaics (STOPVs) usually suffers from limited charge collection capability and conductivity and thus hinders the power conversion efficiency (PCE). Herein, a new strategy of enhancing the π-delocalization of electron transport layer (ETL) via lithium bis(trifluoromethanesulfonyl)imide doping is developed. The enhanced π-delocalization in ETL benefits sizeable intermolecular π-π overlap, prone to harvesting electrons and thereby improving charge collection range. Doping also improves the conductivity of both ETL and ultrathin silver electrode. Furthermore, the trap densities in ETL and STOPV devices are reduced after doping, contributing to suppressed recombination and higher PCE. Consequently, ETL doping maintains an average visible transmittance of ~ 30% while promotes the PCE of STOPVs from 13.0% to 14.3% and light utilization efficiency from 3.74% to 4.15%, which is among the highest values of optical structure-free STOPVs. This work provides a new insight of π-delocalization manipulation in ETL for efficient STOPVs.

Lithium metal batteries (LMBs) represent one of the most promising energy storage systems due to unparalleled energy density. However, in commercial electrolytes, their practical high-power performance is still hampered by unstable electrolyte interfaces, leading to severe anode dendrite growth and cathode degradation. Here, 4-fluoro-3-nitrophenylboronic acid is introduced as a dual-function additive, contributing to uniform N-/F-rich interphase layers at both electrodes of the LMBs. Therefore, in the optimized electrolyte, Li-metal electrodes demonstrate enhanced plating/stripping reversibility of > 700 h (vs. 250 h at 1 mA cm^-2 and 0.5 mAh cm^-2) and coulombic efficiency of 98.2% (vs. 84.2%). Moreover, the corresponding LMBs achieve 99.9% capacity retention (vs. 44.7%) after 500 cycles at 3C rate, simultaneously maintaining > 99.9% coulombic efficiencies. The impressive fast-charging performance attributes to not only the uniform and compact Li deposition at the anode, but also the inhibited uncontrolled electrolyte decomposition and active species loss at the cathode due to the robust electrolyte interphases. This work highlights that proper electrolyte additive is crucial for fast-charging metal batteries.

Given the inherent complexity of metabolic pathways and disease-associated agents, next-generation healthcare necessitates wearable, non-invasive, and customized approaches to continuously monitor a broad spectrum of physiologically relevant biomarkers for personalized health management. Moreover, existing data-based analytical strategies remain inadequate for delivering quantitative and predictive evaluations of health status in real-life settings. Here, we report an electronic multiplexed microneedle-based biosensor patch (eMPatch) that enables real-time, minimally invasive monitoring of key metabolic biomarkers in interstitial fluid, including glucose, uric acid, cholesterol, sodium, potassium, and pH. By integrating modular microneedle (MN) sensors into a skin-interfaced flexible platform, the eMPatch achieves robust mechanical stability and seamless skin conformity, thereby ensuring reliable and continuous sensing within the dermal space. In vivo validation in animal models under metabolic intervention highlights the strong capability of the eMPatch for real-time physiological tracking across diverse daily activities. Implemented with a machine learning algorithm, the eMPatch enables automatic feature extraction and multi-task health assessment, achieving a classification accuracy of 0.996 in distinguishing normal and diet-induced metabolic disorder for health condition identification and an R² score of 0.977 for the corresponding degree evaluation. This study highlights the potential of the MN-integrated, machine learning-enhanced biosensing platform toward personalized health management.

Two-dimensional/three-dimensional (2D/3D) perovskite heterojunctions at the contact interfaces have been proven to enhance the stability and power conversion efficiency (PCE) of perovskite solar cells (PSCs). The 2D/3D bilayer is typically formed via a solution post-treatment onto the 3D perovskite, where the 2D layer's dimensionality depends on the ligand size and its reactivity. Despite their stability, long-chain ligands typically form 2D perovskites with low dimensionality (n = 1, 2) which feature poor charge conductivity and mobility. Here, we propose an in situ fabrication method incorporating long-chain oleylammonium (OlyA⁺) ligands directly into the perovskite ink. This approach forms 2D perovskite with higher dimensionalities (n ≥ 3) with enhanced (001) crystal facet orientation of the 3D film, improved energetic alignment, charge extraction, and structural stability. The fabricated inverted PSCs with 1.55 eV bandgap achieved a maximum PCE of 26.22% for small area and 24.6% for 1cm² devices, as well as 21.1% for mini-modules (6.8 cm²). Additionally, the PSCs with in situ formed 2D/3D perovskite heterojunctions retained 90% and 80% of their initial PCE after 1200 h photothermal stability and 1050 h outdoor testing, respectively. Our one-step strategy produces uniform and stable 2D/3D perovskite heterojunctions with enhanced passivation capability, overcoming the limitations of conventional sequential methods and offering a promising and effective approach for highly stable and efficient PSCs.