Bimorph Soft Actuators Based on Isostructural Heterogeneous Janus Films.

Bimorph soft actuators, traditionally composed of two materials with distinct responses to external stimuli, often face durability challenges due to structural incompatibility. Here, we propose an alternative design employing free-standing, isostructural heterogeneous Janus (IHJ) films that harmonize stability with high actuation efficiency. These IHJ films were fabricated through a vacuum self-assembly process, consisting of TiCT MXene nanosheets and hybrid graphene oxide (GO)-biomass bacterial cellulose (BC), with a well-matched two-dimensional lattice structure.

Reliable Strategy for the Covalent Bonding of MOFs to SiC Membranes for Ultrastable Noble Metal Capture in Harsh Environments.

Silicon carbide (SiC) membranes combine exceptional chemical, thermal, and mechanical stability but suffer from surface inertness that precludes functionalization. Conversely, MOFs offer unmatched molecular selectivity but are typically powders, severely limiting their practical use. To address this, we develop a generalizable route to fabricate ultrastable MOF@SiC membranes via sequential oxidation and acidification, creating abundant Si-OH sites on SiC surfaces that covalently bond with Zr-MOF crystals; the bonding mechanism between MOFs and substrates has been extensively studied.

FEA-based optimal design of special suction cups temperature-controlled coatings.

To address the growing demand for temperature control precision and uniformity in wafer processing, a specialized electrostatic chuck temperature control system based on thermal control coatings is proposed, aiming to enhance thermal management robustness and homogeneity. This study employs a zoned control methodology using metal-oxide conductive coatings on silicon carbide wafer heating plates. A quadrant-based thermal control coating model was established, and finite element analysis was conducted to compare temperature distribution characteristics across three geometric configurations: sectorial, spiral, and zoned designs.

A diffractive element-based chromatic confocal thickness measurement device and thickness correction method.

Wafer thickness is a critical parameter in semiconductor manufacturing, influencing production costs, and chip performance. Traditional measurement methods using clamping devices often introduce errors due to uneven positioning or unstable clamping. This study enhances the dual-probe chromatic confocal system by incorporating a diffractive optical element that splits white light into three beams, with spectrometer wave peak counts detecting wafer tilt.

Cu-Mn Bimetallic Mesoporous Silica Nanosonosensitizers Enable Oxeiptosis-Mediated Sonodynamic Therapy for Ultra-Minimally Invasive Treatment of Benign Prostatic Hyperplasia.

Benign prostatic hyperplasia (BPH) presents a significant clinical challenge, with conventional therapies carrying substantial risks, including urinary retention, sexual dysfunction, and prolonged recovery. To address the urgent need for safer, ultra-minimally invasive alternatives, we developed a sonosensitizing nanoplatform using copper-manganese-doped mesoporous silica nanoparticles (Cu-Mn@SiO) for ultrasound-induced sonodynamic therapy (SDT). Here, we demonstrate that this innovative strategy provides highly effective and precisely targeted therapy for BPH.

Predictive modeling and optimizing lactic acid recovery from co-fermentation of food waste and waste activated sludge using a modified ADM1 approach.

The recovery of lactic acid (LA) from the co-fermentation of food waste and waste activated sludge is shifting from feasibility studies to process optimization and predictive modeling. This study extends the widely used International Water Association Anaerobic Digestion Model No.1 (ADM1) by incorporating lactic acid bacteria-mediated pathways and adjusted stoichiometry to simulate LA generation from sugars, implemented in the GPS-X simulation platform.

Tetrahedral DNA Framework-Engineered Magnetic Nanozyme for Visual Biomarker Sensing via Alkaline Phosphatase-Triggered Signal Switching.

Point-of-care (POC) detection of prostate-specific antigen (PSA) is critical for the early screening and monitoring of prostate cancer (PCa), which facilitates timely intervention and personalized treatment. However, existing POC platforms suffer from inadequate detection sensitivities, susceptibility to matrix interference, and complex sample pretreatment. To address these issues, we proposed a naked-eye and colorimetric sensing platform based on magnetic nanozyme (FeO@ZIF-67@Pt) integrated with a tetrahedral DNA framework (TDF) and alkaline phosphatase (ALP)-triggered hydrolysis reaction for PSA detection with superior sensing performances.

SrZnSiS: Shattering the 4.0 eV Threshold toward Dual-Optimized Bandgap and Second-Harmonic Generation.

Infrared (IR) nonlinear optical (NLO) crystals are crucial for mid-IR lasers, yet their intrinsic narrow band gaps cause low laser-induced damage thresholds (LIDTs) and detrimental two-photon absorption, thus limiting their widespread application. Herein, a synergistic strategy involving d-orbital exclusion and polarization motif construction is employed to synthesize novel chalcogenide SrZnSiS by introducing [SiS] and [ZnS] tetrahedral polarization subunits. Performance evaluation demonstrates that SrZnSiS breaks through the "4.

Non-iridescent yet angle-dependent structural colors on titanium surfaces induced by laser oxidation.

Optically variable features are widely used in product design and anti-counterfeiting. However, current industrial methods rely heavily on chemical inks, which pose environmental concerns and suffer from poor wear and corrosion resistance. We experimentally demonstrate the generation of non-iridescent yet angle-dependent structural colors on titanium surfaces using a nanosecond laser-induced oxidation.

A Deep Learning-Augmented Density Functional Framework for Reaction Modeling with Chemical Accuracy.

Accurate prediction of reaction energetics remains a fundamental challenge in computational chemistry, as conventional density functional theory (DFT) often fails to reconcile high accuracy with computational efficiency. Here, we introduce Deep post-Hartree-Fock (DeePHF), a machine learning framework that integrates neural networks with quantum mechanical descriptors to achieve CCSD-(T)-level precision while retaining the efficiency of DFT to solve the reaction problems. By establishing a direct mapping between the eigenvalues of local density matrices and high-level correlation energies, DeePHF circumvents the traditional accuracy-scalability tradeoff.

Improving large language models for adverse drug reactions named entity recognition via error correction prompt engineering.

The monitoring and analysis of adverse drug reactions (ADRs ) are important for ensuring patient safety and improving treatment outcomes. Accurate identification of drug names, drug components, and ADR entities during named entity recognition (NER) processes is essential for ensuring drug safety and advancing the integration of drug information. Given that existing medical name entity recognition technologies rely on large amounts of manually annotated data for training, they are often less effective when applied to adverse drug reactions due to significant data variability and the high similarity between drug names.

Magnetite-enhanced chain elongation via endogenous electron donors through a novel fungi-bacteria microbiome.

Anaerobic fermentation of organic waste stream into medium-chain fatty acids (MCFA) through chain elongation (CE) has emerged as a sustainable and eco-friendly approach for resource recovery. Co-culture of yeast with chain elongator achieved a promising endogenous electron donor (ED)-driven CE but was limited by the weak yeast-bacteria synergy. This study presents a novel approach to optimizing the CE process through the regulation of magnetite (0-15 g/L).

Radial-Hierarchical Chromatomimetic E-Nose for Spatiotemporal VOC Diffusion Mapping.

This study introduces a radial-hierarchical, diffusion-enhanced spatiotemporal sensing paradigm for volatile organic compound (VOC) analysis via an integrated microchamber paper-based chromatomimetic e-nose. The proposed system synergizes interlayer spatiotemporal dynamics with planar spatial variance by employing a radially symmetric electrode array and a hierarchical porous chemoresistive ink (CuP@G). This design leverages molecular diffusion gradients across the sensing plane, enabling precise discrimination of complex VOC mixtures through multidimensional "spatiotemporal fingerprints".

A hybrid phosphorus-free nanoparticle with flame retardancy, antibacterial and wound healing promotion for cellulose.

The flammability and bacterial susceptibility of cellulose have always posed significant safety hazards in its application. A multifunctional agent (SiCA) combining flame retardancy and antibacterial activity was developed using nano-hybridization in this study. The SiCA was centered around nano-SiO, which was modified with a quaternary ammonium salt and a Schiff base.

Superelastic and Washable Micro/Nanofibrous Sponges Based on Biomimetic Helical Fibers for Efficient Thermal Insulation.

Extreme cold weather seriously harms human thermoregulatory system, necessitating high-performance insulating garments to maintain body temperature. However, as the core insulating layer, advanced fibrous materials always struggle to balance mechanical properties and thermal insulation, resulting in their inability to meet the demands for both washing resistance and personal protection. Herein, inspired by the natural spring-like structures of cucumber tendrils, a superelastic and washable micro/nanofibrous sponge (MNFS) based on biomimetic helical fibers is directly prepared utilizing multiple-jet electrospinning technology for high-performance thermal insulation.

Multifunctional nanofiber-based electronic skin with moisture-wicking, piezoelectric motion sensing and thermochromic temperature response.

Electronic skin (e-skin) faces challenges in achieving long-term signal stability and wearability due to the poor breathability, sweat accumulation, and limited sensitivity. This paper reports a multifunctional nanofibrous e-skin (PTZ-PPPB-PPT) fabricated via layer-by-layer electrospinning, integrating a hydrophobic layer (PVDF-TrFE/ZnO), a piezoelectric enhancement layer (PAN/PVP/PDA@BTO), and a thermochromic layer (PAN/PVP/TCM). Benefited from the asymmetric wettability and hierarchical fiber structure, the device enables unidirectional sweat transport (contact angle reduces from 132.

One-step carbonization preparation of peanut shell porous carbon and its excellent microwave-absorbing property.

Biomass-derived porous carbon is expected to become a lightweight and efficient microwave-absorbing material. In this paper, peanut shell porous carbon (PSC) materials was successfully prepared by a one-step carbonization method using peanut shells (PS) as raw material and KOH as activator. The prepared PSC samples had excellent microwave absorption performance.

S TU-Net: Structured convolution and superpixel transformer for lung nodule segmentation.

Accurate segmentation of lung adenocarcinoma nodules in computed tomography (CT) images is critical for clinical staging and diagnosis. However, irregular nodule shapes and ambiguous boundaries pose significant challenges for existing methods. This study introduces STU-Net, a hybrid CNN-Transformer architecture designed to enhance feature extraction, fusion, and global context modeling.

Molecular Insights into the Effect of S262 Phosphorylation on the Binding of Tau to Microtubule and Its Self-Aggregation.

Aberrantly phosphorylated Tau protein dissociating from microtubule and aggregating into intracellular fibrillary inclusions is closely associated with tauopathies, including Alzheimer's disease, chronic traumatic encephalopathy, and corticobasal degeneration. Previous experiments reported that the tauopathies-associated post-translational modification serine 262 phosphorylation (S262p) is linked to the Tau-microtubule interaction and Tau self-aggregation. However, the underlying molecular mechanism is not well understood.

Advancements in Enhancement Strategies for Piezoelectric Nanogenerator Output Performance and Their Applications in Self-Powered Sensors.

Given the increasing prevalence of the Internet of Things (IoT) in various aspects of modern society, issues concerning environmental problems and the limited lifespan of batteries are becoming more acute. As a renewable energy technology with multiple advantages such as environmental friendliness, compact size, and long lifespan, piezoelectric nanogenerators (PENGs) have broad application prospects in wearable devices and self-powered sensors. However, compared to triboelectric nanogenerators (TENGs) and pyroelectric nanogenerators (PyNGs), the output performance of PENG is not ideal, which limits its practical application in sensors.

Hierarchical FeO@C@MnO nanozymes: bridging structural engineering to on-site biosensing of tannic acid.

Manganese dioxide (MnO)-based heterogeneous catalysts have gained significant attention in nanozyme research due to their exceptional oxidase-mimicking capabilities. This work reports the rational design of MnO functionalized magnetic carbon nanotubes (FeO@C@MnO) through a multistep synthesis strategy. The magnetic N-doped hollow carbon substrate (FeO@C) was first synthesized via controlled pyrolysis of FeOOH-coated polydopamine precursors.

Microstructural transformation for robust and high-efficiency Zintl thermoelectrics.

Thermoelectric materials offer an exceptional opportunity to convert waste heat into electricity directly, yet their widespread application remains hindered by intrinsic brittleness and poor processability. Here, we introduce a graded ball milling strategy that fundamentally enhances the mechanical robustness and processability of YbZnSb-based thermoelectrics. By refining grain microstructure, increasing dislocation density, and promoting intermediate-angle grain boundaries, this approach enables the fabrication of crack-free, large-size, disc-shaped, and microscale dices while maintaining excellent thermoelectric performance.

Detection of Surface Defects in Steel Based on Dual-Backbone Network: MBDNet-Attention-YOLO.

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies-ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity-robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces.

Effects of Performance Variations in Key Components of CRTS I Slab Ballastless Track on Structural Response Following Slab-Replacement Operations.

Slab-replacement operations are crucial for restoring deteriorated CRTS I slab ballastless tracks to operational standards. This study investigates the structural implications of the operation by evaluating the strength characteristics and material properties of track components both prior to and following replacement. Apparent strength was measured using rebound hammer tests on three categories of slabs: retained, deteriorated, and newly installed track slabs.

A novel image segmentation network with multi-scale and flow-guided attention for early screening of vaginal intraepithelial neoplasia (VAIN).

Background: Vaginal intraepithelial neoplasia (VAIN) is a rare precancerous lesion, and early diagnosis is crucial for preventing its progression to invasive vaginal cancer. However, the subtle differences in morphology and color between VAIN lesions and normal vaginal tissue make the automatic segmentation of VAIN highly challenging. Existing methods struggle to achieve precise segmentation, impacting the efficiency of early screening.