Browse Articles

Remotely Tuning the Electronic Structures of Cu Site Over N‐Heterocyclic Carbene‐Protected Cu ₇ Nanocluster for Steering CO ₂ Electroreduction to Hydrocarbons

ABSTRACT In this study, a remote‐control strategy for tuning the electronic structures of atomically precise Cu nanoclusters (Cu NCs) was developed, aiming to enhance the selectivity of the CO 2 RR toward high‐value hydrocarbons. Two Cu 7 NCs protected by tridentate N‐heterocyclic carbene (NHC) ligands with distinct functional groups on the remote benzimidazole ring, NHC H ‐Cu 7 and NHC Me ‐Cu 7 , were synthesized via a green and efficient ball‐milling approach. The main product obtained with NHC Me ‐Cu 7 is CO, with a selectivity of 82.8%, whereas the Faradaic efficiency (FE) for hydrocarbon production using NHC H ‐Cu 7 is 74.0%, affording 50.4% CH 4 and 23.6% C 2 H 4 at −1.5 V versus the reversible hydrogen electrode (RHE). Comprehensive theoretical calculations and operando spectroscopic analyses demonstrate that the effect of the remote substituent on the NHC ligand provides a greater population of active electrons in the highest occupied d‐orbital of NHC H ‐Cu 7 compared to that in NHC Me ‐Cu 7 , thus effectively regulating the binding strength of the *CO intermediate. This in turn promotes stabilization and further activation of the intermediate, ultimately steering the product selectivity from CO toward targeted hydrocarbons. This study establishes an atomic‐level paradigm for ligand engineering of Cu NCs, enabling remote tuning of the electronic structure of the active sites to realize highly selective hydrocarbon generation.

Effects of sensory IEQ comfort on employees’ indoor satisfaction and well-being in overall office spaces: a multi-group SEM approach

Tailoring Coordination Micro‐Environments in Metal‐Based Molecular Complexes to Homogeneously Catalyze Li─S Battery Reactions

ABSTRACT The performance of lithium‐sulfur (Li─S) batteries is severely constrained by fatal polysulfide shuttling, sluggish sulfur redox kinetics, and uncontrollable lithium deposition. Organic metal‐based molecules have recently emerged as a novel type of promoters capable of modulating sulfur and lithium species evolution through either heterogeneous or homogeneous mechanisms to respond these issues. Herein, homogeneous metal‐based phenanthroline molecular catalysts are developed by tailoring coordination micro‐environments within electrolyte. By altering metal center type, the Co‐based complex in the electrolyte (Co‐ETL) shows an identical coordination geometry of Co–N 4 , whereas the Fe‐based complex in the electrolyte (Fe‐ETL) exhibits dual Fe─N 2 /Fe─N 4 coordination structures. Specifically, the Fe─N 2 coordination enhances adsorption of sulfur and lithium species, whereas the Fe─N 4 coordination promotes lithium atom diffusion more efficiently. Such a rational functionality division remarkably enhance the homogeneous optimization activity of the Fe‐ETL toward the kinetically favorable sulfur cathode reactions and improved lithium anode stability. Therefore, the battery demonstrates stable cycling at 5.0 C over 500 cycles with a low degradation of 0.03% per cycle. Even under a sulfur loading of 7.1 mg cm −2 , the battery delivers a remarkable initial areal capacity of 6.4 mA h cm −2 and maintains a favorable cycling stability.

An enhanced diabetic retinopathy detection approach using optimized deep learning technique

Abstract Diabetic Retinopathy (DR) remains a leading cause of vision loss among diabetic patients, underscoring the importance of early detection through reliable retinal imaging analysis. Retinal fundus images are inherently physics-driven, capturing the interactions of light with retinal tissue, including absorption, reflection, and scattering phenomena, which define the intensity and structural patterns critical for diagnosis. However, existing machine learning and optimization approaches for DR screening face challenges in handling the high-dimensional, heterogeneous, and complex physical characteristics of these images. Conventional methods often suffer from suboptimal feature selection, limited generalization, and reduced classification accuracy due to their inability to adaptively exploit image-specific patterns. To address these challenges, this study introduces a Dynamic Grasshopper Optimization Algorithm (DGOA) for feature selection, leveraging its dynamic adaptation capabilities to explore and exploit the physically meaningful feature space effectively. By incorporating adaptive parameter control, DGOA mitigates premature convergence and ensures the selection of the most discriminative features, enhancing model robustness. To further improve classification reliability, an ensemble learning classifier is integrated, combining multiple base models to leverage complementary strengths, reduce overfitting, and maximize predictive performance. The proposed physics-aware AI framework was validated on the EyePACS Retinal Fundus Images dataset, a large and diverse collection of high-resolution images reflecting variations in illumination, contrast, and tissue properties. Comparative experiments with EfficientNetV2S, MGA-CSG, and BWO-DL highlight the advantages of our approach in balancing computational efficiency, generalization, and physically informed feature extraction. The DGOA-Ensemble model achieved an accuracy of 94.6%, F1-score of 0.94, and AUC-ROC of 0.96, demonstrating its effectiveness as a robust, interpretable, and generalizable framework that bridges the gap between physics-based retinal imaging and AI-driven automated DR detection.

Low‐Temperature Hydrogen Production From Liquefied Petroleum Gas via Mechanochemistry

ABSTRACT Steam reforming of hydrocarbons is currently the dominant method for hydrogen (H 2 ) production. As a petroleum refining byproduct rich in butane and propane, liquefied petroleum gas (LPG) offers a more accessible and easily transportable alternative feedstock of hydrocarbons relative to methane‐enriched natural gas. However, conventional steam reforming of LPG requires high temperatures to cleave stable C─H bonds, and the inevitable release of carbon oxides as byproducts limits H 2 selectivity ( < 76 vol%). To overcome these limitations, we report a low‐temperature (37°C) mechanochemical strategy for converting LPG into high‐purity H 2 with chromium (Cr) powder. The reaction proceeds without carbon emissions and achieves a high H 2 selectivity of 97.2 vol%, far surpasses that of the thermochemical route (21.3 vol% at 800°C). The H 2 yield rate exhibits at least 50 times enhancement compared to thermochemistry. The H 2 yield ratio reaches 94.6%, nearly 13 times greater than thermochemistry (7.3%). Mechanistically, strong metal‐carbon interactions promote dehydrogenation and C─C bond cleavage, and metal‐hydrogen interactions determine H 2 selectivity. These findings highlight mechanochemistry as a promising low‐temperature, carbon‐free approach for sustainable H 2 generation.

A security-oriented four-factor spatio-temporal framework for assessing and mitigating traffic congestion risks

In-silico identification of genetic variants associated with chronic lymphocytic leukemia for diagnostic and therapeutic applications

Dynamic Proton Allocation Drives High‐Efficiency Nitrate Electroreduction on High‐Entropy Alloy Aerogels Across Broad Concentration Ranges

ABSTRACT Efficiently reducing nitrate across wide‐range concentrations in wastewater remains a major challenge for electrochemical nitrate reduction (NO 3 RR) to ammonia (NH 3 ), where the dynamic control of active proton is critical. Here we proposed a dynamic proton allocator strategy featuring adaptive control of active proton availability in response to local nitrate levels. Applied to high‐entropy alloy aerogels, this approach achieved >90% Faradaic efficiencies (FE) over a wide nitrate concentration range from 0.01∼1.0 M, nearly an order‐of‐magnitude increase in NH 3 yield rate compared to other catalysts at identical nitrate concentrations. In situ spectroscopic investigations revealed that the high‐entropy element distribution modulated molecular structure of interfacial water, enhancing active proton availability for nitrate hydrogenation. Theoretical calculations demonstrated that the unique high‐entropy electronic configuration optimized intermediate adsorption, shifted the rate‐determining step and lowered the reaction energy, promoting NH 3 formation. These results highlight the pivotal role of proton management across wide‐ranging nitrate concentrations in NO 3 RR, demonstrating the potential for integrating sustainable chemical synthesis with environmental restoration.

Pathophysiology and histological anomalies in testicular tissues of Calosoma olivieri exposed to heavy metals generated by pesticide industries

Abstract Recently, there has been a critical demand for continuous investigations into environmental contamination with heavy metals to evaluate their detrimental impacts on different species inhabiting these contaminated areas. Therefore, we used Calosoma olivieri (Coleoptera, Carabidae) in the present study as a bioindicator for investigating pollution with heavy metals generated by pesticide industries in Kafr El-Zayat, Egypt. Toward this end, we probed the pathophysiological, histopathological, and ultrastructure anomalies of C. olivieri testicular tissues from the contaminated area in comparison to the clean site. Evaluation of heavy metal accumulation within testicular tissues was conducted employing energy-dispersive X-ray spectroscopy analysis. Furthermore, various biochemical parameters were measured to evaluate oxidative stress and the detoxification state of C. olivieri . Notably, significant inhibitions in antioxidant and detoxifying enzymes, including superoxide dismutase, catalase, glutathione S-transferase, glutathione peroxidase, reduced glutathione, and glutathione reductase, combined with elevated lipid peroxidation and protein carbonyl content were detected in testicular tissue of C. olivieri obtained from a polluted area due to the accumulation of multiple heavy metals. Additionally, severe structural aberrations were observed in the testicular tissues of C. olivieri obtained from the contaminated site compared to the control, including mitochondrial and nuclear destruction and deformed spermatogenic elements, along with obvious signs of tissue necrosis. Collectively, these results evinced impairment of male testicular tissues in beetles from the polluted location, which could serve as a reliable indicator of heavy-metal pollution in industrial areas.

Model test study on the vertical bearing performance of post-grouted piles based on different grouting materials

Cerebrospinal fluid and plasma metabolites in Parkinson’s disease: a Mendelian randomization study

Thermally Robust Hexagonally Perforated Lamellae Enabled by Asymmetric Bottlebrush Copolymers

ABSTRACT Hexagonally perforated lamellae (HPL) via self‐assembly of block copolymers (BCPs) represent one of the most sought‐after nanostructures for advanced applications, yet their practical implementation has remained elusive due to their inherent metastability in conventional linear BCPs. Here, we demonstrate a paradigm shift in HPL phase stability by introducing asymmetric bottlebrush block copolymers (BBCPs) with engineered architectural and conformational asymmetries. This molecular design strategy fundamentally eliminates the chain packing frustrations that have historically plagued HPL phases, yielding the stable HPL phases in bulk materials. Our approach achieves an unprecedented composition window and exceptional thermal stability up to 300°C without order‐to‐disorder transitions. Dissipative particle dynamics (DPD) simulations reveal that the synergy between backbone semi‐rigidity and asymmetric side chain lengths drives this remarkable stabilization. By transforming HPL phases from metastable phases into robust, readily accessible nanomaterials, this work opens new opportunities for their deployment in high‐performance photonic crystals, selective separation membranes, and mechanical metamaterials.

Machine learning-based prediction of residual flexural strength in fiber-reinforced ultra-high-performance concrete under elevated temperatures

Atomically Precise [Cu‐Cu ₅₄ ] Nanocluster‐Catalyzed Three‐Component Borylative Coupling of Alkynes with Alkyl Bromides and Chlorides

ABSTRACT The well‐defined metal nanoclusters (NCs) have emerged as versatile and sustainable catalysts for organic synthesis. However, development of catalyst for simultaneous C─C and C─B bond‐forming reactions based on NCs is still unknown. Herein, we developed an atomically precise, mixed‐valence (Cu I /Cu II ), high‐nuclearity binary NC, Cu 55 S 20 (S t Bu) 20 (O 3 S t Bu) 12 [ Cu‐Cu 54 ], synthesized in high yield via a reducing agent‐assisted trithiocarbamate dissociation approach. The [ Cu‐Cu 54 ] NC was characterized by single‐crystal X‐ray diffraction (SCXRD), X‐ray photoelectron spectroscopy (XPS), electron paramagnetic resonance (EPR), and nuclear magnetic resonance (NMR) spectroscopy. SCXRD uncovers a nested concentric layers architecture with a core {Cu@Cu 12 @S 12 @S 8 } and a shell {Cu 24 @Cu 12 @Cu 6 @(S t Bu) 20 (O 3 S t Bu) 1 2 }, featuring a metal‐centered icosahedral Cu@Cu 12 unit that has never been observed in copper sulfide [Cu–S] NCs. Distinctly, [ Cu‐Cu 54 ] NC serve as an efficient catalyst for the highly selective three‐component difunctionalization of alkynes with bis (pinacolato)diborane (B 2 pin 2 ) and alkyl electrophiles including alkyl chlorides under mild reaction conditions. The desired trisubstituted vinylboronate esters were obtained in excellent yields with a wide range of electronically diverse carbon electrophiles and alkyne. Additionally, in the absence of electrophiles, the hydroboration of alkynes efficiently afforded vinylboronate esters in high yields with excellent regioselectivity. The synthetic transformations and gram‐scale reaction further highlight the usefulness of this protocol.

Current-use and legacy pesticides in canal waters of Chiang Mai, Thailand, during longan flowering and fruit set: occurrence and ecological and human health risk assessment

Stabilizing Micro‐Sized Silicon Oxides by Durable Hydrogen Chemistry

ABSTRACT Micro‐sized silicon oxide (µSiO x ) is considered one of the most promising anodes for commercial high‐energy Li batteries owing to its low cost and high capacity. However, due to the instability of its solid electrolyte interphase (SEI), irreversible consumption of active lithium ions and continuous decomposition of the electrolyte occur, making long‐term stability of µSiO x a significant challenge. Herein, we effectively enhance the stability of the SEI on the surface of the µSiO x anode through the dual functionality of hydrogen chemistry, namely interface regulation and atmospheric protection. With the assistance of the highly reversible hydrogen evolution and oxidation redox reactions, the discharge capacity of the µSiO x anode can reach ∼1568 mAh g −1 at 1 C when the charge capacity is 1600 mAh g −1 . Meanwhile, the µSiO x anode can stably cycle for 2000 h with a Coulombic efficiency of ∼98% at a charge capacity of 700 mAh g −1 . Even at a high areal capacity of 3 mAh cm −2 , the µSiO x anode can still cycle 600 h with the discharge capacity remaining ∼2.93 mAh cm −2 (∼726 mAh g −1 ). This study provides a proof‐of‐concept stabilization strategy for µSiO x under high‐capacity conditions, bringing this challenging anode material one step closer to practical applications.

Paraspinal muscle fatty infiltration is associated with nonunion and cage subsidence after anterolateral lumbar interbody fusion: a level-specific analysis

Interfacial d‐Band Center Modulation via Si–Ir Coupling Enables Efficient and Durable Acidic Solar Water Splitting

ABSTRACT The pursuit of efficient and stable photoelectrochemical water oxidation in acidic media is impeded by issues of severe photo‐corrosion and sluggish reaction kinetics. This study presents a novel dual‐modification approach for hematite (α‐Fe 2 O 3 ) photoanodes, incorporating an acid‐resistant silicon oxide (SiO x ) passivation layer and an interconnected iridium oxide (IrO x ) cocatalyst. The optimized Fe 2 O 3 ‐Si/Ir photoanode achieves a record photocurrent density of 2.32 mA cm −2 at 1.23 V RHE in acidic electrolyte, along with exceptional stability over 60 min, significantly surpassing all previously reported hematite‐based systems under acidic conditions. A key innovation lies in the multifunctional role of the SiO x overlayer, which not only passivates surface states to improve bulk charge separation but also promotes the formation of a uniform IrO x network and inhibits over‐oxidation of Ir to soluble high valent species (e.g., IrO 4 2– ). Combined experimental and theoretical evidence reveals strong electronic interaction at the Si–Ir interface, modulating the d‐band center of Ir, enhancing interfacial charge transfer, and reducing the Gibbs free energies of the rate‐determining step in water oxidation. This work establishes a synergistic materials design strategy for highly efficient and durable solar water splitting in acidic environments, offering a viable route toward practical solar hydrogen production.

CT-to-MRI translation of medical volume data based on an enhanced diffusion model

Abstract In clinical practice, medical inter-modality imaging results can assist doctors in making better decisions, as different modalities imaging results can provide complementary information. Traditionally, obtaining these imaging results requires using various medical devices to scan patients, which can be time-consuming, costly, and potentially harmful to the patient. Motivated by the need to address these limitations, we propose an alternative method that facilitates the conversion of volume CT into volume MRI. The method is based on a Diffusion model and incorporates a post-processing approach to enhance the model’s output. To validate our approach, we conduct experiments and achieve good results on brain and pelvic datasets obtained from clinical practice, despite approximately 6% of the slices being incompletely paired. We also compare our method with state-of-the-art techniques, both qualitatively and quantitatively. Our experimental results show that our method outperforms state-of-the-art techniques, including MedSynthesisV1, CycleGAN, Pix2Pix and Diffusion, when using ground truth as a reference. Finally, we conduct an experiment to select the optimal hyperparameters, including the number of epochs and the parameters $$cutoffPercentage\_left$$ and $$cutoffPercentage\_right$$ .

Outside Front Cover: Neutral Octa‐Adamantane Chalcogenidometalate Clusters via Amine Complexation and Organotin Termination for Nanolithography (Angew. Chem. Int. Ed. 13/2026)