Browse Articles

Boosting Photocatalytic Overall Water Splitting Activity of Phosphorene Through Five‐Coordinate Passivation Enabled by Carbene Addition

ABSTRACT Phosphorene is a promising two‐dimensional semiconductor for solar‐driven redox reactions, yet its practical deployment is severely restricted by rapid degradation under ambient conditions. Conventional covalent functionalization typically forms phosphorus–carbon single bonds (P─C), leaving phosphorus atoms in a four‐coordinate environment and thus failing to fully quench the intrinsic reactivity associated with one residual unpaired electron. Here, we develop a selective strategy to achieve five‐coordinate passivation of phosphorene by constructing phosphorus–carbon double bonds (P═C) through a one‐step photochemical carbene addition reaction. Using a carbene precursor, adamantane groups are grafted onto phosphorene to afford a robust P═C‐bonded architecture. Comprehensive spectroscopic analyses, together with density functional theory (DFT) calculations, validate the preferential formation of the P═C bonds. The resulting P═C‐passivated phosphorene exhibits markedly improved ambient stability compared to the pristine and four‐coordinate‐passivated phosphorene. When utilized as a metal‐free photocatalyst, the P═C‐passivated phosphorene enables highly efficient overall water splitting without sacrificial agents under visible light, delivering record‐high evolution of H 2 and H 2 O 2 with rates of up to 612 and 658 µmol h −1 g −1 , respectively, along with excellent cycling stability.

Sebum levels are associated with the relationship between skin properties and microbiota in Japanese women

Abstract The diversity of the skin microbiota in Japanese women increases with skin aging and is accompanied by decreased sebum content. However, the impact of changes in skin microbiota on skin aging remains unclear. We conducted a cross-sectional subgroup analysis based on age, menopausal status, and sebum content in a cohort of Japanese women aged 30–60 years to elucidate the differences in the relationship between skin properties and microbiota under various conditions. As a fundamental characteristic of this cohort, we confirmed that older participants had lower sebum content and a higher alpha-diversity index. Subgroup analysis based on menopausal status and sebum content revealed differences in the correlations between several skin properties and the conditional dependence structure estimated by Graphical Lasso in groups with varying sebum levels. Additionally, in groups with higher sebum levels, multiple bacterial genera were identified as significantly associated with pH, sebum content, and transepidermal water loss, whereas none were detected in groups with lower sebum levels. These findings suggest that sebum may be associated with differences in the relationship between skin properties and microbiota and may provide a basis for future studies on skincare approaches tailored to sebum levels and specific bacterial features or diversity.

Cobalt‐Catalyzed Migratory <i>E</i> ‐Selective Asymmetric Aza‐Nozaki–Hiyama–Kishi Coupling

ABSTRACT Transition‐metal–catalyzed migratory cross‐coupling offers an attractive strategy for converting readily available precursors into complex molecular architectures. However, current methods are typically restricted to a single migratory mode (e.g., chain‐walking, through‐space shift, or E/Z isomerization). Integrating multiple mechanistically distinct migratory events within a selective cross‐coupling manifold to unlock new chemical space and diverse isomeric products remains a formidable challenge. Herein, we report a cobalt‐catalyzed, migratory E ‐selective asymmetric aza‐NHK (Nozaki–Hiyama–Kishi) coupling of ortho ‐iodophenylethylenes with imines. The key to this process is a synergistic sequence that combines a through‐space 1,4‐Co/H shift with alkenylcobalt E/Z isomerization. Notably, mixtures of E/Z ‐alkenyl bromides are also viable substrates, undergoing an unprecedented alkenylcobalt E/Z isomerization prior to E ‐selective asymmetric coupling. This method provides efficient access to high‐value α‐chiral ( E )‐allylic amines with exceptional control over regio‐, E/Z ‐, and enantioselectivity.

Cooperative search algorithm for UAV swarm based on heterogeneous sensor fusion

A Photocurable Covalent Polyoxometalates‐Membrane With Hierarchical Proton Conduction Pathways for High‐Performance Vanadium Flow Batteries

ABSTRACT Developing proton exchange membranes (PEMs) that integrate high conductivity, selectivity, and processability is highly challenging. Although polyoxometalates (POMs) are promising proton conductors, their practical application is hindered by poor processability, susceptibility to leaching, and difficulty in forming continuous proton conduction pathways within polymers. Herein, a new photocurable polyoxometalate (POM)‐organic membrane (PAPOM‐AMPS) is synthesized via ultrafast UV‐initiated copolymerization of an acrylamide‐functionalized arsenomolybdate cluster (APOM), 2‐acrylamido‐2‐methylpropanesulfonic acid (AMPS), and acrylic acid (AA). This molecular‐level design ingeniously constructs hierarchical proton transport channels: the covalently immobilized APOM clusters serve as long‐range highways, while sulfonic (–SO 3 H) and carboxylic (–COOH) acid groups synergize with water molecules to facilitate efficient proton dissociation and dynamic short‐range hopping. The membrane exhibits an exceptional proton conductivity of 0.417 S·cm −1 at 80°C and 100% RH, surpassing Nafion 117. With confined ionic domains (∼2.27 nm), it achieves ultrahigh proton/vanadium selectivity (18.1 × 10 4 S·min·cm −3 ), 4.6 times that of Nafion 117. When configured into a sandwich‐structured membrane for vanadium flow batteries (VFBs), it delivers outstanding performance, including 98.2% coulombic efficiency, 86.7% energy efficiency, and exceptional cycling stability (0.12% capacity decay per cycle at 120 mA·cm −2 ). This work provides a groundbreaking strategy for next‐generation high‐performance proton‐conductive membranes.

DCFNet: dual-domain cross-modal fusion network for RGB-D mirror segmentation

Investigation of slime mould algorithm optimized PI controller for solar powered hybrid DC–DC converter fed PMBLDC drive applications

An Oxygen‐Defect‐Induced Unsaturated Coordination Strategy Boosts High‐Selective PET Upcycling via Suppressing Oxygen Evolution

ABSTRACT Electrochemical upcycling of polyethylene terephthalate (PET) plastics coupled with hydrogen production offers a sustainable pathway for carbon reutilization and energy sustainability. However, PET‐derived ethylene glycol electro‐oxidation reaction (EGOR) in alkaline conditions inevitably competes with oxygen evolution reaction (OER) due to enhancing OH − utilization for OER under industrially relevant high‐current conditions, reducing electrolysis efficiency and degrading catalyst stability. In this study, we precisely regulate oxygen‐defect concentration to construct an unsaturated CoFeO x (OH) y /CFP catalyst, achieving 93% ± 2% Faradaic efficiency (FE) for formic acid and over 700 h of stability. In situ characterizations and theoretical calculations show that oxygen defects tune the surface electronic structure and promote the timely consumption of electrochemically generated MO x (OH) y species by EG preventing the excessive accumulation of high‐valence species and suppressing OH − evolution into oxygenated OER intermediates. By balancing MO x (OH) y formation with its spontaneous reaction with EG, OH − utilization toward EGOR is enhanced, enabling efficient OER suppression at high anodic potentials. Furthermore, a large‐scale three‐cell electrolyzer (300 cm 2 per piece) achieves 17.4 A at 3 V with nearly 100% FE for hydrogen production, reducing energy consumption by &gt; 21.05% compared with overall water splitting. This work provides mechanistic insights and a practical strategy for industrial PET upcycling integrated with low‐energy hydrogen production.

Threshold conditions for employee innovation: qualitative evidence from hierarchical organizations

Interfacial Hydrogen Bonding for Efficient and Robust Flexible Tin Perovskite Solar Cells

ABSTRACT Flexible tin perovskite solar cells (F‐TPSCs) have attracted substantial attention owing to their high theoretical efficiency, eco‐friendliness, and promising applications in wearable electronics and the internet of things. However, the inferior quality of perovskite buried interfaces caused by low interfacial adhesion and large deformation of plastic substrates has seriously impaired the performance of F‐TPSCs. Here, a biocompatible functional material, 1‐chloro‐1‐deoxy‐D‐fructose (1‐CDF), has been introduced into the poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) hole‐transporting layer, which enables hydrogen‐bonding interactions between PEDOT:PSS and both the underlying ITO and the top perovskite layer, thus significantly enhancing the interfacial adhesion. It can also regulate the crystallization dynamics of the perovskite, resulting in the growth of pinhole‐free perovskite film with high crystallinity and homogeneous bottom contact. Besides, the incorperation of 1‐CDF leads to conformation changes of the PEDOT:PSS, rendering higher conductivity and more matched energy level alignment with perovskites. The power conversion efficiencies (PCEs) of 15.56% (14.67% certified) and 11.06% are reached for F‐TPSCs with active areas of 0.049 cm 2 and 1 cm 2 , respectively. In addition, the F‐TPSC obtains an unprecedented PCE of 22.21% under 1000 lux indoor light illumination. The unencapsulated devices also exhibit excellent stability.

An enhanced intelligent framework for 5G V2X communication using multi-objective optimization and mobility-aware transformer networks

A knowledge graph and multi-agent reinforcement learning model for psychological risk identification and intervention in online learning

Abstract As the scale of online learning expanded, students tended to exhibit declining learning behaviors and accumulating task backlogs during self-directed study. These issues further led to reduced learning motivation and increased psychological pressure. To address this, this study constructed an innovative model that integrated a knowledge graph with multi-agent reinforcement learning. The model enabled learning state risk identification and personalized intervention. The study conducted a systematic evaluation using comprehensive learning behavior data from seven selected courses. The results indicated that the model achieved a high level of risk identification at an early stage. The recall values for all courses ranged from 0.879 to 0.896. As the learning process progressed, accuracy steadily increased to above 0.889. The F1-score remained between 0.842 and 0.871 across all stages, which demonstrated strong stability. Furthermore, the intervention strategies significantly improved learning trajectories across two experimental semesters. Students’ learning activities showed continuous improvement over time. Behavioral fluctuations and breakpoint frequency were both markedly reduced. These findings confirmed that the model consistently enhanced learning motivation, stabilized learning rhythms, and optimized patterns of resource utilization.

Multi‐Atom Sub‐Nanometer Assemblies on Interpenetrating Multi‐Chambered N/C Nanospheres

ABSTRACT The atomically dispersed catalysts have received much attention due to maximum atom utilization and enhanced catalytic performance. Compared with the widely studied single‐atom catalysts and dual‐atom catalysts, the multi‐atom catalysts (MACs) have unique features of collective effect of multiple metal atoms and more designable and tunable coordination environments that are desirable for catalytic reactions. Up to now, the research on MACs remains quite scarce, mainly restricted by the synthetic difficulty in precisely controlling the composition and arrangement of multiple metal atoms in MACs. Herein, we report a versatile soft–hard dual template route for the synthesis of both mononuclear MACs and heteronuclear MACs, which are stabilized on interpenetrating multi‐chambered N/C nanospheres. The as‐synthesized Ni/Cu‐MAC exhibits high performance for electrocatalytic CO 2 reduction reaction, delivering a CO Faraday efficiency of &gt;99% at low required potentials (−0.26 V to −0.56 V). A cathode energy efficiency &gt;75% is achieved at an industrial current density of 0.60 A cm −2 , representing highly competitive performance among the reported CO 2 ‐to‐CO electrocatalysts. The experimental and computational results demonstrate the synergistic effect between the atomically dispersed Ni and Cu for promoting the catalytic conversion of CO 2 to CO.

Investigation of early-age cracking experiments in concrete and research on improvement methods

A Sacrificial Seed Layer Strategy for Hierarchical MFI Zeolite Membranes With Enhanced Butane Isomer Separation Performance

ABSTRACT Zeolite membranes hold significant promise for industrially relevant gas separations; however, balancing high permeance and selectivity remains a persistent challenge. Although thinning the selective layer improves permeance, achieving precise fabrication remains a major bottleneck. Herein, we demonstrate a sacrificial seed layer strategy enabling the fabrication of hierarchical MFI zeolite membranes (HMFI) on commercial α‐Al 2 O 3 tubes. Through precise modulation of synergistic ionic interactions within the synthetic gel and the nutrient supply rate during crystallization, the seed layer functions as both a porogen to generate a macroporous sublayer and a “fertilizer” to promote surface gel crystallization, forming a dense top layer. The resulting HMFI membrane delivers more than a fourfold enhancement in the ideal selectivity of n ‐butane and isobutane ( n‐ / i‐ butane), accompanied by a 37% rise in n ‐butane permeance compared with conventional MFI membranes. Moreover, with a 10/90 n‐ / i‐ butane mixture, it exhibits an excellent separation factor of 158, along with a high n ‐butane permeance (188 × 10 −9  mol m −2 s −1 Pa −1 ), representing the highest performance for reported membranes on tubular supports. The strategy not only enables a novel route to high‐performance membranes, but also enriches the conceptual framework of the conventional secondary growth protocol, offering new avenues for microstructural engineering.

Information-theoretic grid topology reconstruction using low-precision smart meter data

Abstract Accurate knowledge of power grid topology is a prerequisite for effective state estimation and grid stability. While data-driven methods for topology reconstruction exist, the minimum requirements for measurement quality, specifically regarding quantization, precision, and sampling frequency, remain under-explored. This study investigates the data fidelity required to reconstruct distribution grid topologies using voltage magnitude measurements. Adopting an information-theoretic approach, we utilize the Chow–Liu algorithm to generate maximum spanning trees based on mutual information. Rather than proposing a new reconstruction algorithm, our primary contribution is a comprehensive sensitivity analysis of the measurement data itself. We systematically evaluate the impact of data bit-depth, significant digit truncation, time-window length, and different mutual information estimators on reconstruction accuracy. We validate this approach using IEEE test cases (via MATPOWER) and time-series data from GridLAB-D. Our results demonstrate that grid topology can be successfully recovered even with highly quantized 8-bit data or millivolt-level precision. However, performance degrades significantly when downsampling intervals exceed 20 min or when data availability is limited to short durations. These findings establish an optimistic theoretical lower bound, suggesting that costly high-precision instrumentation may not be strictly necessary for structural inference under ideal conditions. This rigorous baseline provides a foundation for future evaluations of noisy real world smart meter data and hybrid approaches that incorporate existing engineering priors.

Tailoring the Electric Double Layer for Advanced Rechargeable Batteries: Mechanisms, Strategies, and Outlook

ABSTRACT The structure of the electric double layer (EDL) at the electrode/electrolyte interface functions not only as the physical arena for electrochemical reactions, but also as the fundamental determinant of battery kinetics, interface stability, and cycle life. Although the solid electrolyte interphase (SEI)/cathode electrolyte interphase (CEI) film has been extensively studied, the microstructure and macroscopic performance of the EDL as precursor to interfacial film formation lacks systematical elucidation. This review aims to provide a comprehensive overview of the theoretical evolution of EDL models alongside their pivotal roles and regulation strategies in advanced batteries. We first retrace the development from classical Helmholtz models to modern microscopic theories. Subsequently, we delve into distinct regulation mechanisms and strategies tailoring EDL chemistry across various rechargeable battery systems such as Li‐based, Zn‐based and other metal‐ion batteries. These approaches encompass electrolyte optimization, electrode engineering, interface modification, and external field regulation, intending to suppress side reactions, guide uniform metal deposition, and stabilize electrode interfaces. Furthermore, advanced techniques for simulating and characterizing the microstructure of the EDL are discussed. Finally, the review outlines current challenges and forward‐looking perspectives on multidimensional rational design, data‐driven screening, operando characterizations, and applications under extreme conditions, providing theoretical guidelines for interface engineering of next‐generation batteries.

Combined nectar nonsugar compounds enhance bumblebee cognition

Technical and economic assessment of seven nanoparticle families for enhanced oil recovery in the Azadegan oil field

Abstract This study bridges the critical gap between laboratory promise and field-scale economic decision-making for nanoparticle-enhanced oil recovery (EOR) by developing an integrated, field-calibrated techno-economic framework specifically for the Azadegan Sarvak reservoir. We evaluate seven nanoparticle families-silica (SiO₂), nanoclay, magnetic Fe₃O₄, titania (TiO₂), graphene oxide (GO), zinc oxide (ZnO), and polymeric nanocapsules. Key innovations include: (1) a novel Laboratory-to-Field scaling procedure that translates core-flood metrics into field recovery estimates, (2) a risk-adjusted discounting method incorporating technical and environmental uncertainty, and (3) a quantitative Environmental Risk Index (ERI) to guide sustainable deployment. These components are integrated into a Monte Carlo–enhanced Discounted Cash Flow (DCF) model to provide a robust, transparent decision-support tool. The model incorporates a 10,000-run Monte Carlo uncertainty analysis, a risk-adjusted discounting method, and a quantitative Environmental Risk Index (ERI). Under a base oil price of 70 USD/bbl, SiO₂ and nanoclay emerge as the most economically attractive options (positive median NPV, IRR &gt; 40%, median payback ≈ 3 years), benefiting from low cost and robust performance. TiO₂ and ZnO are conditionally economic, dependent on thermal stability and operational constraints. In contrast, GO and polymeric nanocapsules present high-risk/high-reward profiles at current unit prices, while Fe₃O₄ is uneconomic when the substantial CAPEX for magnetic guidance is included. Sensitivity analysis identifies oil price, incremental recovery (ΔRF), and nanoparticle unit price as the dominant value drivers. The study provides prioritized pilot recommendations, explicit technical/cost thresholds for scale-up, and a zonal implementation guide, delivering a practical decision-support tool for nano-EOR deployment in Azadegan.

Scalogram-CNN fusion with interactive 3D parameter exploration for inter-patient ECG classification