Browse Articles

Hydrophilic Janus Micelles From an ABC Triblock Copolymer

ABSTRACT We describe the creation of an amphiphilic triblock copolymer that drives lateral phase separation within micelle coronas. The design combines a hydrophobic poly(lactide) (PLA) core‑forming block with two distinct hydrophilic segments: poly(ethylene glycol) (PEG) and poly( N ‑vinylpyrrolidone) (PVP). In water, the copolymer assembles into spherical micelles, confirmed by cryogenic TEM and multi‑angle light scattering. Selective end‑labelling of PVP with an electron‑dense iridium complex enabled unstained TEM imaging, revealing clear contrast asymmetry that locates PVP to a single hemisphere of the corona. Complementary 2D 1 H‐Nuclear Overhauser Effect Spectroscopy ( 1 H‑NOESY) NMR confirmed this Janus‑type segregation of PEG and PVP. These results demonstrate how molecular architecture can encode asymmetry into soft nanostructures, offering a versatile route to polymer‑based Janus nanoparticles with dual surface functionality and broad technological potential.

Proteomic analysis of papillary thyroid carcinoma in the context of Hashimoto’s thyroiditis

Solvation‐Mediated Assembly for Large‐Scale Synthesis of Covalent Organic Framework Membranes

ABSTRACT Covalent organic framework (COF) membranes featuring rigid frameworks and ordered channels have surmounted the dilemma of ion permeability and selectivity trade‐off for traditional polymeric membranes. However, it remains a challenge regarding the scale‐up synthesis of COF membranes and the understanding of dynamic formation mechanisms therein. We report a solvation‐mediated assembly (SMA) approach to synthesize large‐scale freestanding COF membranes with ∼2400 cm 2 and a tensile strength of ∼65 Mpa. The solvation‐mediated nucleation, elongation, crystallization, and assembling processes are visualized via the in situ heating liquid transmission electron microscopy, which integrated with multiscale simulations provide elaboration on the solvation interactions during membrane formation. The as‐prepared membranes demonstrate selective ion separation for high‐salt water reclamation and rare‐earth ions recovery, endowing potential for the practical application of COF membranes.

Grammar error diagnosis using graph convolutional networks with knowledge graph integration

Enhancing credit card fraud detection with a hybrid approach using machine and deep learning

Abstract Credit card fraud is an important concern for banks, financial institutions and consumers, resulting in substantial financial losses annually. Traditional fraud detection systems are based on predefined rules, but as fraudsters develop more sophisticated techniques, these methods become less effective. Machine learning (ML) and deep learning (DL) offer powerful solutions to enhance the accuracy and efficiency of credit card fraud detection. However, a major challenge in credit card fraud detection is the highly imbalanced nature of transaction data, where fraudulent transactions are rare compared to legitimate ones. To address data imbalance, techniques such as Synthetic Minority Over-sampling Technique (SMOTE) and Mahalanobis distance Synthetic Minority Oversampling Technique–Edited Nearest Neighbors (SMOTE-ENN) hybrid sampling are applied to balance the dataset and improve model performance. The study evaluates various ML models and deep learning models for fraud detection and further evaluate learning dynamics, computational cost, and interpretability through SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations). Comprehensive error analysis confirms the robustness and transparency of the proposed approach. This study evaluated 37 models, and the two proposed stacking ensemble approaches showed significant advancements. The first proposed model effectively combines various algorithms: Extra Trees (ET), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and eXtreme Gradient Boosting(XGBoost) as a meta-learner and the second proposed stacking ensemble approach integrates ET, Adaptive Boosting(AdaBoost) with Extra Trees as base, AdaBoost with Random Forest as base, XGBoost as meta-learner to maximize performance. This research highlights the importance of combining machine learning, deep learning, and data balancing techniques to improve credit card fraud detection. The proposed stacking ensemble approaches achieved exceptional results, with accuracy, precision, recall, F1-score, and Area Under the Curve (AUC) reaching 1.0, 0.9999, 1.0, 1.0 and 1.0, respectively. Experimental results indicate that ensemble learning techniques like Categorical Boosting (CatBoost) and XGBoost outperform traditional models, while deep learning methods, especially Feedforward Neural Network (FFNN), ANN (Artificial Neural Network) and Multilayer Perceptron(MLP) demonstrate strong performance in detecting fraud patterns.

Industrial‐scale Aldehydes Electrification Via Localized Hydrogen‐affinity Engineering

ABSTRACT Electrifying aldehydes into high‐value chemicals presents a sustainable solution for environmental remediation, resource recovery and upgrade, yet its practical implementation has been limited by inefficient electrodes. Here, we develop a computation‐guided strategy—localized hydrogen‐affinity engineering—to synthesize heteroatom‐decorated Cu hydrogenase for aldehydes electrification. Remarkably, the as‐prepared Rh‐decorated Cu hydrogenase (Rh 1 Cu‐Hase) achieves a remarkable Faraday efficiency of >99.3% for formaldehyde conversion at an ultrahigh current density of 500 mA cm −2 with a minimal overpotential of 283 mV. A membrane‐free electrolyzer equipped with the Rh 1 Cu‐Hase operates stably for over 1200 h at 1000 mA cm −2 , continuously producing high‐purity potassium diformate (KDF) and hydrogen. Techno‐economic analysis reveals a significant $166.1/ton KDF revenue advantage over conventional methods. The paired dehydrogenation mechanism is proposed by a series of operando studies and theoretical calculations, unveiling that the Cu matrix facilitates aldehyde adsorption, while atomic Rh sites activate hydrogen, collectively reducing energy barriers for both C─H cleavage and H─H coupling. Furthermore, the universality of this strategy is demonstrated by its successful application in electrifying a broad range of industrially relevant aldehydes.

Ethical concerns about embodied brain organoids shaped by foundational distinctions and perceptions of consciousness

Uniform and Stable Dual Frustrated Lewis Pairs Enabling Highly Efficient Conversion of CO ₂ With Hydrogen‐rich Molecules

ABSTRACT Catalytic reduction of CO 2 with hydrogen‐rich small molecules (e.g., H 2 , C 3 H 8 , and CH 4 ) provides a promising route to valuable chemicals and fuels. However, achieving high catalytic efficiency requires balancing the effective activation of CO 2 and hydrogen‐rich small molecules with the precise control of dual‐site uniformity to ensure cooperative activity. Herein, we propose a high‐throughput screening strategy for ternary compounds based on descriptors of structural uniformity, coordination number, and phase stability. The screening identifies three wurtzite‐derived crystals, namely ZnGeN 2 , BeSiN 2 , and ZnSiN 2 , with uniform dual frustrated Lewis pairs (FLPs) on their (100) surfaces that are thermally stable up to 873 K. Among them, only the ZnGeN 2 (100) surface can selectively activate reactants, with Zn···N FLPs favoring CO 2 adsorption and Ge···N FLPs activating hydrogen‐rich small molecules, due to their intrinsic Lewis acid–base character. Importantly, kinetic Monte Carlo simulations show that the uniform distribution of Zn···N and Ge···N FLPs on ZnGeN 2 (100) enables efficient pathways, with CO 2 consumption rates of 19.67, 1.23, and 2.69 s −1 in the reactions with H 2 , C 3 H 8 , and CH 4 , respectively. Moreover, the dual FLP remains highly active in CO 2 hydrogenation under stoichiometric ratio, CO 2 ‐rich, and CO 2 ‐lean conditions, ensuring practical reliability.

Advanced channel estimation in OTFS and NOMA using deep bayesian gaussian processes and compressive sensing

Photoinduced Dynamic Electronic Asymmetry of Cu Dual‐Atom Sites Within Covalent Organic Frameworks Boosts Hydrogen Production

ABSTRACT The development of efficient and cost‐effective alternatives to noble metal cocatalysts for photocatalytic hydrogen evolution remains a significant challenge. Herein, we demonstrate a facile strategy for constructing atomically dispersed dual Cu sites within a covalent organic framework (COF), using molecular carboxylic acids as coordinating ligands. Through in situ spectroscopic characterization and theoretical calculations, we identified a light‐induced dynamic electronic restructuring involving the reduction of one Cu(II) to Cu(I) within the dual‐atom site, generating a mixed‐valence state with asymmetric electronic configuration. This dynamic asymmetry facilitates electron transfer process and optimizes hydrogen intermediate adsorption. Enhanced H 2 generation is achieved, and the performance exceeds that of benchmark Pt cocatalyst. Furthermore, the molecular carboxylic acid‐assisted strategy employed here is successfully extended to improve the H 2 evolution activity of Pt. This work offers an applicable method for constructing dual‐atomic‐site catalysts and provides insights into dynamic active sites in catalysis.

Expanded Heisenberg Hamiltonians from a Mn/Bi DFT+U study on hexagonal antiferromagnet CaMn2Bi2: excitations and strain-controlled magnetic anisotropy switching

Abstract The manganese pnictide CaMn $$_2$$ Bi $$_2$$ exhibits narrow-gap antiferromagnetism with Mn atoms arranged in a puckered honeycomb structure, and is currently a promising candidate for ultra-fast light control of AFM states. In this paper, we perform a detailed study of the magnetic properties of CaMn $$_2$$ Bi $$_2$$ using density functional theory (DFT) combined with the Hubbard U correction and spin-orbit coupling, which accurately describe the magnetic configurations. In DFT+U approach, we apply an on-site U not only to Mn-3d orbitals but also to Bi-6p ones to improve the description of Mn–Bi hybridization and the small SOC-driven gap. We show that a standard Heisenberg spin model is insufficient to describe these magnetic excitations, and an extended model accurately describes these using local on-site magnetization terms, linked to the Néel vector and inspired by Hubbard-model physics. We further investigate the role of the spin-orbit coupling, and find that the magnetic anisotropy of CaMn $$_2$$ Bi $$_2$$ shows an easy plane, with the preferred magnetization direction being exchanged between axes in the plane by applying small strain values. This strain-tunable magnetization, driven by the interplay between spin-orbit interactions and lattice distortions, highlights the potential for controlling magnetic states in Mn-pnictides for future applications in spintronic and magneto-optical devices.

Achieving Stable and Fast Ion Transport in Regenerated LiFePO ₄ Via Vacancy‐Mediated Upcycling

ABSTRACT The high stability and low cost of LiFePO 4 batteries have fueled their rapid expansion, resulting in a growing volume of spent battery materials that require effective recycling. While direct regeneration restores cathode performance to the original state, the intrinsic steric hindrance and susceptibility to anti‐site defect formation of one‐dimensional ion transport channels restrict lithium‐ion kinetics in regenerated LiFePO 4 . Herein, we propose a vacancy‐mediated upcycling strategy to regenerate LiFePO 4 , enabling stable and fast ion transport. It uses lithium vacancy defects in degraded cathodes to facilitate simultaneous lithium replenishment and dopant diffusion into the lattice, achieving lattice repair and modulation. This leads to contracted Fe─O bonds and elongated Li─O bonds, which form fast and stable ion transport channels. Regenerated LiFePO 4 exhibits exceptional rate capability (101.9 mAh g −1 at 10 C) and low‐temperature performance (64.3 mAh g −1 at −20°C). After 1000 cycles at 1 C, the cathode retains 95.7% capacity (137.6 mAh g −1 ), and the cycled cathode also exhibits reduced anti‐site defects and superior kinetics due to the lattice modulation. This vacancy‐mediated upcycling strategy for improving cathode performance presents significant economic and environmental benefits, providing a sustainable pathway for advanced battery recycling.

Integrated metabolomic, network pharmacological, and molecular docking analyses comparing the therapeutic effects of Strobilanthes sarcorrhiza from different origins

Single‐Nanoparticle Collision Revealing High‐Entropy Suppression of Elemental Segregation in Multi‐Element Alloys During Oxygen Evolution Reaction

ABSTRACT In the oxygen evolution reaction (OER), the structural reconstruction and elemental segregation of alloy catalysts are key factors influencing their activity and stability, while the irreversible structural evolution induced by high current density is the primary issue leading to performance degradation. Herein, we designed a multi‐element alloy nanoparticle (MEA‐NP) model electrocatalyst from binary (FeIr) to quinary alloy (FeCoNiIrRu), modulating the configuration entropy to explore its influence on structural stability. The single‐nanoparticle collision (SNC) based on scanning electrochemical cell microscopy (SECCM) was employed to facilitate efficient mass transfer and ultrahigh current density, thereby accelerating structural evolution during OER. By combining multidimensional feature extraction and clustering analysis of transient signals, it was found that increasing the number of constituent elements improves the structural stability under OER conditions, and high entropy effectively suppresses elemental segregation. Transmission electron microscopy (TEM), in situ Raman spectroscopy, and density functional theory (DFT) calculations further confirmed the advantages of the quinary alloy in terms of structural homogeneity and stability. This study established a statistical correlation between elemental segregation and single‐particle transient OER signals, proposed a strategy similar to “accelerated testing under extreme conditions”, providing new insights for the mechanistic study and rational design of OER catalysts.

Butterflies use humidity as a cue for wing-pattern and life history trait plasticity when temperature is unreliable

A Stable, Mesoporous Three‐Dimensional Covalent Organic Framework as a Versatile Functional Platform

ABSTRACT Introducing functionality into the pore channels of covalent organic frameworks (COFs) without compromising their crystallinity and porosity remains a formidable challenge. Herein, we present a stable, mesoporous 3D COF, JUC‐685, which exhibits a surface area of 2,188 m 2 g −1 and a pore size of 3.20 nm. This robust structure serves as a versatile platform for constructing functionalized COFs while preserving structural integrity. Using a solvent‐assisted linker exchange (SALE) strategy, we successfully incorporated a series of challenging functional moieties—including azobenzene, carbazole, and complex heterocycles—to generate an isoreticular series, JUC‐686 to JUC‐689. This methodology effectively decouples functionality from structural order. The azobenzene‐functionalized derivative, JUC‐686, retains a high surface area of 2,131 m 2 g −1 and a mesopore of 3.09 nm. Crucially, the photoresponsive azobenzene units within its spacious pores enable remarkable, light‐induced modulation of CO 2 adsorption capacity, with a change rate reaching 60.4% under UV irradiation—the highest performance reported for any azobenzene‐functionalized porous materials. This work establishes a general platform for the synthesis of highly crystalline COFs with pore‐wall functionality, unlocking new opportunities in smart adsorption, catalysis, and beyond.

Optimizing mechanized cleaning of Corcyra cephalonica eggs for stored-product biocontrol via DEM parameter calibration and enhanced vibratory separation

Self‐Assembled Ionic Clusters Accelerate Li‐Ion Transport Through Microphase‐Separated Polyelectrolytes

ABSTRACT Precise, molecular‐level control of ion coordination and mesoscale morphology is essential for pushing solid polymer electrolytes toward the conductivity and mechanical robustness metrics demanded by next‐generation batteries. Here we introduce an elastic microphase polyelectrolyte (EMP) whose thermodynamically driven microphase separation self‐assembles Li + ‐rich ionic clusters. These clusters stitch together a dynamic, percolating conduction network that achieves high ionic conductivity of 2.9 × 10 −4 S cm −1 and a high Li + transference number of 0.67 at room temperature. Operando galvanostatic impedance spectroscopy uncovers a field‐responsive boost in conductivity—from 4.1 × 10 −4 to 1.9 × 10 −3  S cm −1 as the current density increases from 25 to 200 µA cm −2 —evidence of bias‐induced cluster reconfiguration. Mechanically, the EMP combines high elasticity with self‐healing, ensuring intimate, long‐lived electrode contact. When paired with a LiNi 0.8 Co 0.1 Mn 0.1 O 2 cathode, solid‐state cells retain 93.92% of their initial capacity after 50 cycles under a high‐capacity loading of ∼2.0 mAh cm −2 . By demonstrating how supramolecular ionic assembly can be harnessed to couple ion transport, mechanics, and electrochemical stability, this work lays a versatile design platform for high‐performance, solid‐state lithium batteries.

Benthic foraminiferal colonisation of phytodetritus during spring bloom within the marginal sea ice zone off Northern Svalbard continental margin

Rare‐Earth‐Guided Hierarchical Assembly of Teddy‐Bear‐Like Giant Nickel‐Tungstate Polyoxometalates

ABSTRACT The controlled assembly of giant polyoxometalates (POMs) remains a significant challenge in inorganic chemistry. Herein, we demonstrate that rare‐earth ions can direct distinct structural outcomes in nickel‐substituted tungstate systems. Hydrothermal reaction of the flexible precursor [B‐ α ‐SbW 9 O 33 ] with KH 2 PO 4 , Er 2 O 3 , and NiCl 2 yielded a giant all‐inorganic cluster {W 88 Ni 39 } (1) , adopting an unprecedented “Teddy‐Bear”‐like architecture. Under identical conditions, omission of Er 2 O 3 (or replacement with Dy 2 O 3 ) afforded the smaller cluster {W 55 Ni 17 } (2) , corresponding to the “head” of the “Teddy‐Bear”. Notably, Dy 2 O 3 improves the crystallization yield of {W 55 Ni 17 } relative to the rare‐earth‐free reaction. Remarkably, replacing Er 2 O 3 with Gd 2 O 3 afforded a giant tetramer {W 140 Gd 10 Ni 48 } (3) , whose monomer is analogous to the [W 33 Ni 21 ] “Teddy‐Bear body” motif in {W 88 Ni 39 } . These clusters rank among the largest discrete tungsten‐based POM assemblies known. Importantly, the crystallization of {W 88 Ni 39 } and {W 140 Gd 10 Ni 48 } enables an efficient organic‐free separation of the rare‐earth oxides Er 2 O 3 and Gd 2 O 3 with a separation factor of 360.37, revealing a new strategy based on structure‐directed hierarchical assembly for selective crystallization in rare‐earth‐mediated POM systems.