Browse Articles

Low‐Power‐Activated Afterglow Nanoprobes With Naked‐Eye Visibility for High‐Contrast Imaging of Brain Inflammation

ABSTRACT Afterglow luminescence imaging ingeniously circumvents the need for real‐time excitation, thereby substantially eliminating background interference. Nevertheless, its application in brain imaging has been hindered by low afterglow brightness under aqueous conditions. Here, we present naked‐eye‐visible afterglow nanoprobes excited by low‐power light for high‐contrast imaging of brain inflammation. By strategically integrating highly efficient donor–acceptor–donor (D–A–D) luminescent molecules into photochemical afterglow systems, we developed a series of ultrabright afterglow materials emitting in the yellow, orange, and red spectral regions. The resulting afterglow nanoparticles remain naked‐eye detectable even under ultralow excitation power (0.73 mW cm −2 ). Their afterglow brightness is over 1300 times higher than that of commonly used afterglow nanoparticles, and they still maintain a 3‐fold advantage compared to previously developed blue‐emitting nanoparticles based on molecular fusion strategies. Leveraging this exceptional performance, we accomplished real‐time naked‐eye observation of freely moving mice. Moreover, macrophage‐encapsulated nanoparticles enabled blood–brain barrier (BBB) penetration and high‐contrast imaging of brain inflammation. This work introduces a new paradigm for constructing high‐brightness afterglow materials and opens transformative avenues for real‐time visualization of brain disorders.

Comparative optimization of overcurrent relay coordination in DG-integrated distribution networks: water cycle algorithm versus genetic algorithm and big bang–big crunch

Abstract The increasing penetration of distributed generation (DG) has significantly complicated protection coordination in modern distribution networks by introducing bidirectional power flows and variable fault current levels. These challenges become more pronounced under different operating modes, particularly in islanded operation, where reduced fault current levels place severe constraints on overcurrent relay (OCR) coordination. This paper presents a comparative assessment of metaheuristic optimization techniques for coordinating overcurrent protection in DG-integrated distribution networks. Two distribution systems with different topological characteristics are examined. A radial 9-bus system is analyzed under three operating modes: conventional grid-connected operation without DG, DG-integrated grid-connected operation, and islanded operation. In contrast, a meshed 30-bus distribution system is evaluated exclusively under islanded operation to represent the most demanding coordination conditions, where fault current support is limited to inverter-based DG sources. Relay coordination is formulated as a constrained optimization problem aimed at minimizing total relay operating time while satisfying coordination time interval (CTI) requirements. Three metaheuristic optimization algorithms are applied under identical protection models and fault conditions: the Genetic Algorithm (GA) as a conventional reference approach, and the Water Cycle Algorithm (WCA) and Big Bang–Big Crunch (BB-BC) algorithm as more recent techniques. Short-circuit calculations are performed for three-phase faults in accordance with IEC 60909 standards. The results indicate that all investigated algorithms successfully achieve coordinated relay settings under the examined operating modes.

Hybrid Computational Strategy for Predicting Complex Ligand–Metal Architectures

ABSTRACT Understanding how metals coordinate to organic ligands is a precondition for the rational design of metal complexes and catalysts. Whereas certain types of ligands are capable of just one easy‐to‐predict coordination modality, others may present tens and sometimes even hundreds of coordination options (mono‐, bi‐, or polydentate), and predicting the correct one may be a challenge even to seasoned chemists. The current paper describes a “hybrid” computational approach in which a Machine Learning, ML, algorithm learns to predict complex coordination patterns using knowledge‐based “rules” derived from the Cambridge Structural Database, CSD. This model is applicable to a broad scope of ligands (including hemilabile and haptic ones as well as those with denticity > 6) and different metals at different oxidation states. The algorithm's code is disclosed and can be readily deployed in RDKit via our RDMetallics python‐wrapper. It is also deployed as a publicly accessible web portal for demonstration and use.

Evaluating the impact of anthropogenic activities and climate change on distribution dynamics and habitat suitability of Lophira alata in Nigeria

Initial Iron‐Phthalocyanine Covalent Organic Polymer Based Three‐Dimensional Porous Cathode Catalysts Layer Directly for Proton‐Exchange Membrane Fuel Cells

ABSTRACT Covalent organic polymers (COPs), with their well‐defined and tunable structures, show promising prospects as molecular electrocatalysts for the oxygen reduction reaction (ORR). However, the conjugated two‐dimensional structures assemble through direct π–π stacking into molecularly dense layers that severely obstruct the multidimensional oxygen transport pathways, thus compromising performance in proton exchange membrane fuel cells (PEMFCs). Herein, we constructed a three‐dimensional nitrogen‐doped graphene scaffold for the in situ growth of an iron‐phthalocyanine‐based covalent organic polymer, yielding the composite material denoted as COP Fe @3D‐NG. By leveraging nondestructive x‐ray computed tomography and Avizo processing, we reconstructed their realistic porous structures. The further pore‐scale multiphysics simulations demonstrated that the 3D porous network significantly enhances mass transport with an increase of oxygen diffusion coefficient compared to the 2D structure. As a result, the PEMFCs fabricated with COP Fe @3D‐NG as the cathode catalyst demonstrated a ∼2.7‐fold increase of higher peak power density than the 2D analogue. These findings highlight a fundamental principle for next‐generation cathode design that engineering 3D porosity to create multidimensional mass transport pathways is crucial for accelerating oxygen transfer and achieving high‐performance PEMFCs.

Fungal-mediated green synthesis of ZnO–MnO nanocomposites with antimicrobial and anticancer properties

Lewis Base‐Catalyzed DYKAT of Racemic Chlorohydrosilanes With Grignard Reagents <i>En</i> Route to <i>Si</i> ‐Stereogenic Hydrosilanes

ABSTRACT Enantioenriched hydrosilanes bearing a Si ‐stereogenic center have garnered considerable attention due to the relevance in diverse areas of organic chemistry. Their synthesis has predominantly been limited to stereospecific reduction of chiral silylethers or silazanes, or catalytic desymmetrization of prochiral dihydrosilanes. Herein, we disclose a mechanistically distinct strategy: a ( S , R )‐benzotetramisole‐catalyzed dynamic kinetic asymmetric transformation (DYKAT) of racemic chlorohydrosilanes with Grignard reagents. The method enables enantioconvergent Si*─C bond formation, giving Si ‐stereogenic hydrosilanes—many of which are challenging to access via desymmetrization—in high yields and with high enantioselectivity (34 examples, up to 99% yield, 99:1 er ).

Effectiveness of platelet-rich plasma therapy in promoting wound healing and shoulder function recovery after shoulder surgery

Abstract This retrospective propensity score–matched cohort study examined whether Platelet-Rich Plasma (PRP) use was associated with improved wound healing and functional recovery after shoulder surgery. We analyzed records from Changsha Hospital of Traditional Chinese Medicine (January 2018–December 2023) and included 170 patients undergoing rotator cuff repair (n = 100), shoulder replacement (n = 40), or subacromial decompression (n = 30). Within each surgery type, patients receiving PRP (treatment group [TG]) were matched 1:1 to patients not receiving PRP (control group [CG]) using propensity scores derived from age, sex, comorbidities, and baseline pain. Outcomes included wound healing time, postoperative pain (Visual Analog Scale [VAS]), shoulder function (Constant–Murley score), complications, length of hospital stay, and patient satisfaction. In matched analyses, PRP use was associated with shorter wound healing time and improved postoperative pain and functional outcomes across procedures, with the largest and most robust differences observed in the rotator cuff repair cohort. PRP was also associated with a shorter hospitalization duration in all three surgery cohorts. Complication rates were lower in the rotator cuff repair cohort, while no clear between-group differences were observed in the shoulder replacement or subacromial decompression cohorts. Overall patient satisfaction was higher in the PRP groups. Given the retrospective design, potential residual confounding, and smaller sample sizes in non–rotator cuff cohorts, these findings should be interpreted cautiously and warrant confirmation in prospective, surgery-specific studies using standardized PRP protocols.

Simultaneous Imaging of Cu ⁺ and Cu ² ⁺ in Neural Cells Using DNAzyme Probes Reveals Mechanistic Link Between Copper Redox Imbalance and Amyloid Pathology

ABSTRACT Copper dysregulation is implicated in neurodegenerative diseases such as Alzheimer's disease (AD), yet its precise role in neuronal death remains unclear. To address this issue, here, we introduce a pair of Cu + and Cu 2 + specific DNAzymes‐based fluorescent probes, for the first time, enabling simultaneous visualization of both redox states of copper in single living neurons. Using this dual‐color system, we found that amyloid‐beta (Aβ) oligomerization promotes intracellular copper accumulation, distinct from that induced by artificial ionophore loading. Elevated Cu + drives reactive oxygen species (ROS) generation, lipoylated protein aggregation, and FDX1‐dependent cuproptosis, while Cu + chelation or FDX1 knockdown completely prevents cell death. In contrast, ROS scavengers only partially rescue viability, demonstrating that neuronal death is driven by copper overload, not oxidative stress itself. These findings redefine the mechanistic framework linking copper redox imbalance to Aβ pathology and neuronal vulnerability and demonstrate a selective, sensitive approach for monitoring copper homeostasis and its disruption in neurodegenerative disease.

Artificial intelligence-driven optimal charging strategy for EV with integrated power quality enhancement in electric power grids

Modular and Direct Synthesis of γ‐Sultines From Simple Unactivated Alkenes

ABSTRACT Despite long‐standing interest in sultines, their efficient and general synthesis remains elusive. Existing methods typically rely on oxidative or rearrangement pathways or on prefunctionalized homoallylic substrates, thus limiting practicality and scope. For the first time, we demonstrate a visible‐light‐driven relay that directly converts simple unactivated alkenes into γ‐sultines using sulfoxonium ylides and DABSO as an SO 2 source. The reaction involves a highly electrophilic distonic radical cation, generated through polarity inversion, which initiates addition to unactivated alkenes and, acting as an intrinsic leaving‐group precursor, orchestrates radical relay and cyclization in a single photochemical sequence. This modular and operationally simple strategy exhibits broad substrate scope and excellent functional‐group tolerance and is applicable to late‐stage functionalization of complex molecules, opening new avenues for γ‐sultine synthesis and diversification.

Comparative behavior of steam turbine model for dynamical power system analyses by means of multiple fractional and artificial neural network techniques

Spin‐Orbit Coupling of Ln ³⁺ Induces and Modulates Thermally Activated Delayed Fluorescence in Heterometallic LnAgP ₃ Clusters

ABSTRACT The rational design of Ag(I)‐based thermally activated delayed fluorescence (TADF) materials requires fundamental understanding of structure–property relationship governing their emission characteristics. In this work, coordination with Ln 3+ ions endows the resulting compounds LnAgP 3 (Ln = Gd/Eu/Y) with pronounced photoluminescence. Temperature‐dependent emission spectra and decay lifetime measurements reveal that Y 3+ and Gd 3+ incorporation induces distinct TADF activity in the [AgP 3 ] moiety. In EuAgP 3 , combined the experimental results supports efficient energy transfer from [AgP 3 ] to Eu 3+ via both singlet energy transfer (SET) and triplet energy transfer (TET) pathways. Modulating the Eu:Gd molar ratio within a lattice enables precise control over the TADF performance of the [AgP 3 ] unit. At a Eu:Gd ratio of 0.5:0.5, optimal TADF performance of the [AgP 3 ] moiety is observed with a larger k (S 1 →S 0 ) value of 1.05 × 10 7 s −1 and a shorter TADF decay time of 6.45 µs. Theoretical calculations further reveal that the SOC of the 4 f orbitals perturbs the electronic structure of [AgP 3 ], compressing Δ E (S 1 ‐T 1 ) to &lt;0.2 eV, which enables reverse intersystem crossing (RISC) and thus TADF. Consequently, varying the Eu:Gd ratio provides an indirect handle over the SOC‐mediated Ag↔Eu energy‐transfer pathway, offering an effective route to regulate the TADF performance of the [AgP 3 ] moiety.

Developmental coordination disorder traits persistently affect physical activity and sedentary behavior in adults

Tailoring Electronic Properties of Precision Graphene Nanoribbons via Nanopore Engineering

ABSTRACT The precise incorporation of nanopores into graphene nanoribbons (GNRs) offers a complementary strategy for modulating their opto‐electronic properties beyond conventional width and edge engineering. However, a systematic understanding of the relationship between the structure and electronic properties of porous GNRs ( pGNRs ) remains experimentally unexplored due to the lack of rational synthetic strategies. Herein, we report two novel porous GNRs ( pGNR 1 and pGNR 2 ) synthesized via solution‐phase methods, featuring periodically arranged [18]annulene nanopores and gulf‐edged architectures, along with a nonporous GNR ( npGNR ) as a counterpart. Utilizing efficient Diels‐Alder polymerization and Scholl‐type cyclization, these GNRs attain average lengths of up to 60 nm. The chemical identities of the synthesized GNRs were comprehensively characterized by IR, Raman, and solid‐state NMR spectroscopy, complemented by theoretical calculations. To further elucidate the structural features underlying the observed properties, three representative model compounds ( 1 , 2 , and 3 ) corresponding to segments of the respective GNRs were synthesized and analyzed. UV–vis and THz spectroscopic analyses demonstrate that npGNR exhibits a relatively narrow optical bandgap of 1.63 eV and a high intrinsic charge carrier mobility of ∼40 cm 2  V −1  s −1 , whereas pGNR 2 displays a wider bandgap of 1.91 eV with a reduced mobility of ∼27 cm 2  V −1  s −1 . This study systematically elucidates the effects of nanopore incorporation on the electronic structure and charge transport properties of GNRs, offering a rational design framework for the design of nanopore‐engineered carbon‐based electronic materials.

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given that its success depends heavily on the quality of pseudo boxes. While many earlier researches have mainly centered on cross-domain transferability, they often neglect the rich intra- and inter-domain semantic structures. As a result, this neglect empirically restricts the discriminative abilities of the learning model. In our study, we have found a notable alignment and synergy across contrastive learning, prototype learning, and mean-teacher self-training. Building on this insight, we introduce the P rototype- o riented C o ntrastive M ean T eacher (PoCoMT) for UDA-OD, a thorough and flexible framework that seamlessly integrates these three techniques to extract the most beneficial learning signals. Specifically, PoCoMT firstly generate more diverse and reliable probabilistic outputs from self-training through maximizing information entropy and maintaining semantic consistency; secondly, PoCoMT strives to reduce both intra-domain and inter-domain prototypical contrastive learning losses by elaborately designing a Prototype Alignment Network (ProtoAN) module, which fosters intra-domain feature aggregation, aligns inter-domain class structures, and reduces semantic loss between weak and strong augmentations of target domain data. Our ProtoAN can serve as a plugin module for traditional self-training frameworks to tackle the key problem of semantic loss in UDA-OD. Extensive experiments demonstrate that PoCoMT attains new state-of-the-art performance.

Interlayer Covalent Reinforcement‐Enabled Lattice Reprogramming for Durable Capacitive Deionization

ABSTRACT Capacitive deionization (CDI) offers a low‐energy route for desalination but is hindered by electrodes lacking both high ion storage and durability. Here we present a covalently supported interlayer engineering strategy that transforms layered molybdenum sulfide (MoS 2 ) into a high‐performance electrode with exceptional capacity and stability. By precisely intercalating butane‐1,4‐diol, we replace weak van der Waals interactions with rigid covalent linkages, simultaneously expanding interlayer spacing and inducing local 2H‐to‐1T lattice reconstruction. This dual structural reprogramming fundamentally reconfigures Mo‐S orbital hybridization, generating high‐energy antibonding states that promote strong Na + chemisorption while preventing framework collapse. Consequently, the engineered electrode delivers an ultrahigh salt removal capacity of 77.4 mg g −1 , over threefold higher than pristine MoS 2 , without measurable decay over 50 cycles, and demonstrates scalable brine treatment outperforming state‐of‐the‐art 2D electrodes. This work establishes a generalized paradigm for covalently reinforced 2D frameworks, resolving the long‐standing performance‐stability paradox in CDI and advancing practical, high‐capacity desalination.

Tracking the dynamic evolution of lithium-ion battery recycling technology using natural language processing

Piezo‐Activated Metal‐Free Donor‐Acceptor Photocatalytic Overall Water Splitting System Toward Highly‐Efficient Simultaneous H ₂ and H ₂ O ₂ Production

ABSTRACT The potential mismatch of band structures to water redox potentials for most of photocatalysts restricts the development of photocatalytic overall water splitting (OWS). Herein, a well‐defined donor‐acceptor polymer model photocatalyst (HFPTP‐Bpy‐Hz), featuring an unsuitable band structure for OWS, was designed. It was demonstrated that the OWS ability of HFPTP‐Bpy‐Hz for H 2 and H 2 O 2 generation was activated by the bending of its unmatched conduction band in the piezo‐induced built‐in electric field, as well as the thermodynamically favorable two‐electron pathway for H 2 O 2 ‐evolved water oxidation on bipyridine structure. HFPTP‐Bpy‐Hz showed excellent metal‐free photo/piezo‐catalytic OWS performance for H 2 and H 2 O 2 generation (1795 and 1571 µmol·g −1 ·h −1 , respectively) better than the performances in literatures. Effective separation of photo‐generated carriers achieved by piezo‐induced built‐in electric field and hydrazone bond‐based electron transfer channel, and low energy barriers of water splitting in the presence of hydrazone bond linkage, collectively contributed to the outstanding photo/piezo‐catalytic OWS performance of HFPTP‐Bpy‐Hz. Furthermore, the hydrazone bond‐based positive correlation between the polarity of the polymer backbone and piezo/photocatalytic activity at the molecular level was clearly demonstrated through targeted regulation of connecting bonds and building blocks. This work offers valuable insights for constructing the promising solar light‐driven OWS systems using photocatalysts with unsuitable band structures.

Development and temporal validation of five year retinal arteriosclerosis risk prediction in high risk adults from an East China cohort