Metagenomic and molecular simulation insights into plastic degradation: Microenvironmental matching and the key role of residue Phe392.

Due to their chemical inertness, polyethylene (PE) and polystyrene (PS) persistently accumulate in the environment. This study integrates metagenomics, degradation profiling, and molecular simulations to elucidate their divergent microbial degradation pathways. PE degradation was dominated by Burkholderia (97 %), with selective C-C bond cleavage causing a 29.

Enhancing anomaly detection in plant disease recognition with knowledge ensemble.

Plant diseases pose a significant threat to agriculture, impacting food security and public health. Most existing plant disease recognition methods operate within closed-set settings, where disease categories are fixed during training, making them ineffective against novel diseases. This study extends plant disease recognition to an open-set scenario, enabling the identification of both known and unknown classes for real-world applicability.

Nanoconfinement assists the selective generation of singlet oxygen to efficiently remove emerging organic contaminants in soil with a low consumption of oxidant.

The application of advanced oxidation processes (AOPs) to remove emerging organic contaminants (EOCs) in soil is a powerful and rapid soil remediation technology, but the diversity of soil components makes the contact between reactive oxygen species (ROS) and pollutants limited, while the large consumption of oxidant still seriously restricts the decontamination performance in soil. Herein, a nanoconfinement strategy has been applied to encapsulate metal oxide FeO to the channels of carbon nanotube, thereby synthesizing a FeO@CNT catalyst to activate peroxydisulfate (PDS) for the selective removal of carbamazepine (CBZ) in soil. FeO@CNT can efficiently activate PDS to oxidize CBZ in soil through a nonradical pathway dominated by singlet oxygen (O).

Unveiling the social and environmental benefits of electric vehicles: A case study of Shanghai.

The economic viability of battery electric vehicles (BEVs) relies on effectively balancing carbon mitigation benefits with development costs. This study addresses this issue by establishing a comprehensive social and environmental benefit (SEB) assessment model integrating life cycle assessment and life cycle cost methodologies. The aim is to quantify and analyze the economic costs and carbon reduction potential of BEVs throughout their life cycle, focusing on the case study of Shanghai.

Synergistic carbon-sulfur co-roasting driven sustainable and selective recovery of lithium from spent ternary lithium-ion batteries.

Spent lithium-ion batteries (LIBs) contain high-value strategic metals which are essential for the sustainable resource utilization and eco-environment conservation. Conventional recycling technologies usually involve complicated procedures, high energy consumption and hazardous gas emissions. Hence, a novel process based on "C/S synergistic roasting - water leaching" is put forward to selective and environment-friendly recovery of lithium from spent LIBs.

Recent Advances in Cellulose-Derived Organic Afterglow Materials.

Cellulose-based organic afterglow materials have gained considerable interest due to their low toxicity, cost-effectiveness, and environmental benefits compared to traditional phosphors, with promising applications in anti-counterfeiting, bioimaging, and sensing. Although extensive research has been conducted on cellulose and organic afterglow materials, a comprehensive review systematically discussing the underlying mechanisms and applications of cellulose-based organic afterglow systems remains scarce. This review provides an in-depth analysis of the origin of long-lived afterglow emission in cellulose-based materials, highlighting the critical roles of intramolecular and intermolecular interactions, and proposes strategic design principles for optimizing performance.

Regulating Donor Aggregation via Alkyl Side-Chain Engineering for Green-Solvent Processed Organic Solar Cells.

Scalable fabrication of organic solar cells (OSCs) demands the replacement of toxic halogenated solvents with environmentally benign alternatives. However, processing with nonhalogenated solvents often leads to uncontrolled donor aggregation and suboptimal morphology, severely limiting device performance. Here, we report a molecular design strategy that enables efficient morphology control under green processing conditions through rational side-chain engineering.

Regulation of Octahedral Distortions and Interlayer Spacing in 2D Perovskite Capping Layer Toward Efficient and Stable Solar Cells.

2D perovskites as interfacial modifiers have demonstrated potential for improving the stability of perovskite solar cells (PSCs); however, 2D structures based on flexible long-chain cations often lead to a high degree of octahedral distortions and larger interlayer spacing. These factors hinder efficient charge extraction between the perovskite and charge transport layers and affect the stability of 2D/3D devices. Here, imidazolyl spacers with rigid ring structures are employed as interfacial modifiers.

Sulfamoylbenzoic Acid Derivatives as Molecular Additives through Fine Dipole Moment Regulation for Highly Reproducible Perovskite Solar Cells.

An excellent reproducibility of high-quality perovskite thin films is imperative for the commercialization of perovskite solar cells. Multifunctional additive engineering is a promising strategy to tackle this challenge as it facilitates simultaneous control over crystallization processes and defect passivation. Here, an innovative strategy is proposed, leveraging -OH, -NH, and -Cl to precisely tune the dipole moment and electronic configuration of multifunctional modified 4-chloro-3-sulfonamide benzoic acid (CSBA) through substituent inductive and conjugation effects.

Reed biochar by microwave-assisted pyrolysis for the removal of tetracycline in water.

This study uses reed straw and phosphoric acid to synthesize reed biochar and modified reed biochar through tubular furnace pyrolysis and microwave-assisted pyrolysis, respectively. The effects of pyrolysis temperature and phosphorous acid on the structure, composition, porosity, and adsorption performance of tetracycline (TC) were further investigated. The results showed that the modified biochar prepared by microwave-assisted pyrolysis had better performance.

Controlling transient and coupled diffusion with pseudoconformal mapping.

Diffusion in physical, chemical, and biological systems often occurs under transient conditions and involves coupling across multiple physical fields, challenging conventional control methods limited to steady-state, single-field settings. Here, we present a general geometric framework for regulating diffusion in time-dependent and multiphysics-coupled environments based on pseudoconformal mapping. This method preserves material isotropy and ensures smooth interface matching, enabling robust and flexible modulation of diffusion governed by Fick's second law and beyond.

Large-Scale Roll-to-Roll Manufacturing of Flexible, Hydrophobic, and Fire-Resistant Mica/SiO Nanofiber Aerogel Paper.

Oxide ceramic aerogels offer exceptional thermal insulation and chemical stability but face limitations due to brittleness, moisture sensitivity, and costly, complex manufacturing. Here, we present a roll-to-roll method for producing flexible, hydrophobic, and fire-resistant silica/mica hybrid aerogel paper. The process bypasses the need for expensive polymer sacrificial templates and high temperature sintering, instead forming aerogels directly through electrospinning stabilized tetraethyl orthosilicate and a synthetic fluorophlogopite sol.

A redox-responsive NIR fluorescent nanoprobe for tumor microenvironment-activated surgical navigation with submillimeter precision.

Surgical precision in tumor resection critically relies on real-time intraoperative imaging, yet conventional probes face limitations in specificity and spatiotemporal control. Here, we present a tumor microenvironment (TME)-activated near-infrared (NIR) fluorescent nanoprobe (DNS-DYE/PEG-NI) that integrates dual responsiveness to hypoxia and glutathione (GSH) for submillimeter-level surgical navigation. The system comprises a GSH-activatable NIR fluorophore ( = 679/730 nm) quenched by 2,4-dinitrobenzenesulfonyl (DNS) moieties and hypoxia-sensitive amphiphilic PEG-NI micelles.

Study on Separation of Desulfurization Wastewater in Ship Exhaust Gas Cleaning System with Rotating Dynamic Filtration.

Current treatment methods for desulfurization wastewater in the ship exhaust gas cleaning (EGC) system face several problems, including process complexity, unstable performance, large spatial requirements, and high energy consumption. This study investigates rotating dynamic filtration (RDF) as an efficient treatment approach through experimental testing, theoretical analysis, and pilot-scale validation. Flux increases with temperature and pressure but decreases with feed concentration, remaining unaffected by circulation flow.

A deep learning-based computer-aided diagnosis system for detecting atypical endometrial hyperplasia and endometrial cancer through hysteroscopy.

Timely diagnosis of endometrial cancer (EC) and atypical endometrial hyperplasia (AEH) is crucial, yet traditional hysteroscopy faces accuracy challenges. This study introduces ECCADx, a deep learning-based computer-aided diagnosis system utilizing contrastive learning for hysteroscopic identification of AEH and EC. This is the system to integrate contrastive learning for this specific differentiation.

Deep learning-based screening approach for priority pollutants: a case study on retired power battery recycling.

With the rapid increase in the production of retired power batteries, the potential environmental risks during recycling must urgently be identified and assessed. This study presented a novel screening framework for pollutant prioritization utilizing deep learning algorithms coupled with hierarchical clustering analysis. An integrated model for pollutant screening called McA was constructed based on five deep learning methods with performance-based weighting.

MCRFS-Net: single image dehazing based on multi-scale contrastive regularization and frequency selection.

The primary goal of image dehazing is to restore the clarity and detail of hazy images. However, addressing non-uniform haze in atmospheric scattering models remains a significant challenge. While some methods tackle image-level non-uniformity using multi-scale fusion mechanisms, others focus on feature-level non-uniformity with content-guided attention mechanisms.

High-precision Electromagnetic Flowmeter with Empty Pipe Detection via Complex Programmable Logic Device-based Waveform Recognition.

Traditional electromagnetic flowmeters are inherently prone to external interference and uneven velocity distribution during measurement, which severely limits their accuracy. In this study, an improved method is proposed, which optimizes the excitation drive waveform, performs multiple filtering and amplification of the electrode input, and uses a Complex Programmable Logic Device to achieve rapid switching between positive and negative induction signals. This enables smooth rectification and, in combination with software filtering techniques, achieves highly precise performance.

Ultrasound enhances the recycling process and mechanism of lithium from spent LiFePO batteries by Acidithiobacillus ferrooxidans.

In this study, the ability of Acidithiobacillus ferrooxidans to oxidize Fe to Fe and recover battery black powder was investigated, establishing a system for leaching decommissioned lithium iron phosphate battery black powder from A. ferrooxidans. Black powder reduced the consumption of reagents and subsequent pressure for treating iron-bearing minerals using the iron source in waste LiFePO batteries.

Innovative municipal sludge dewatering: High efficiency and high-dryness through the synergistic effect of MoS piezoelectric catalysis and electro-dewatering.

The rapid development of urbanization has heightened the need for efficient sludge dewatering in wastewater treatment. Traditional sludge dewatering technologies encounter numerous challenges regarding moisture content (M) and efficiency. This paper introduces a novel approach for achieving high efficiency and high-dryness sludge dewatering, which innovatively integrates MoS piezoelectric catalysis with sludge electro-dewatering to establish the piezoelectric-electric synergistic dewatering (P-EDW) method.

Heterointerfacial Charge Modulation of p-Type Covalent Organic Frameworks on Graphene Achieving High-Performance Cl Ion Storage with Ultralong Cycling Life.

The charge and ion transport dynamics, storage capacity, and cycling performance of Faradaic Cl ion storage electrodes have recently constrained advancements in supercapacitor (SC) and capacitive deionization (CDI). Herein, a high-performance p-type COF (TAPA-COF)-based Cl ion storage material (TAPArGO) with exceptional cycling stability was synthesized via an in situ condensation reaction utilizing graphene as a conductive substrate. The interfacial coupling involving graphene and TAPA-COF increases the interfacial electron density, boosting local charge accumulation and Cl ion storage capacity.

Pollution source apportionment and health risk assessment of VOCs in automobile gearbox remanufacturing facilities.

The progress of the transmission remanufacturing industry is in line with the development requirements of the circular economy, but its environmental pollution problems are easily ignored. This study conducted an analysis of pollutant sources and health risks associated with VOCs in gearbox remanufacturing plants. A method for prioritising air pollution control based on health risks and environmental impacts, alongside offering suggestions for VOC prevention and control from an environmental standpoint is established.

Image colorization based on transformer.

This paper presents a transformer-based method for colorizing grayscale image. By employing a deep architecture with stacked encoder-decoder layers, the model effectively captures intricate features, significantly improving its expressive capacity. The encoder primarily extracts features from the input grayscale image, while the decoder utilizes these features alongside the self-attention mechanism and contextual information to predict the corresponding [Formula: see text] and [Formula: see text] chrominance components in CIELAB color space, and combines the channel [Formula: see text] of the input image to achieve image colorization.

Evaluation study on gas-phase passivation inhibiting the spontaneous combustion tendency of ferrous sulfide compounds.

The iron sulfide compound FeS, present in petrochemical plants, is prone to spontaneous combustion when exposed to air, posing a significant threat to the safety of production processes in the petrochemical industry. Accurately assessing the spontaneous combustion tendency of FeS is crucial for preventing fire and explosion hazards in petrochemical storage tanks. In this study, FeS was passivated with 3%, 6%, and 9% concentrations of passivator for 2 to 8 h, and the effects of gas-phase passivation on FeS were investigated.

Catalytic mechanism of yavapaiite confined in interlayer space of graphite oxide in heterogeneous electro-Fenton oxidation.

Conventional iron-based catalysts are prone to aggregation and deactivation in the heterogeneous electro-Fenton (hetero-EF) process resulting in electrocatalytic activity reduction. Herein, a simple one-pot strategy using potassium ferrate (KFeO) as both oxidant and iron source was developed to synthesize a novel yavapaiite confined in graphite oxide (KFe(SO)-in-GO) nano-electrocatalyst. GO with spatial confinement effect and surface negativity could in-situ incorporate KFe(SO) nanoparticles inside the interlayer space and inhibit the agglomeration.