SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3848-7
Conventional heterogeneous photocatalysts often suffer from insufficient light absorption, rapid charge recombination, and a lack of specific reactive sites for efficient photocatalytic oxidation. To overcome these limitations, we propose a molecular polarization engineering approach utilizing structurally well-defined donor (D)-acceptor (A) covalent triazine frameworks (CTFs). The construction of dipole-induced built-in electric fields within the D-A-structured CTFs enables enhanced exciton dissociation and facilitates directional charge transfer. Specifically, the asymmetric A1-D-A2 moiety enhances molecular polarization in the dual-acceptor system CTF-TBT (A1-D-A2), enabling efficient charge separation through multiple electron-withdrawing units. This structural design promotes directional electron transfer toward the secondary acceptor (benzothiazole, A2), while simultaneously concentrating holes on the donor unit. Consequently, the A2 moiety acts as a site for efficient O2 activation via electron accumulation, whereas the highly oxidized donor unit provides strongly positive holes (h+) that facilitate substrate oxidation. Experimental and DFT calculation results confirm that CTF-TBT demonstrates highly enhanced photocatalytic oxidation performance, which can be attributed to its multi-channel charge separation mechanism and spatially separated redox-active sites. This study highlights the effectiveness of molecular dipole engineering in designing heterogeneous photocatalysts with controlled charge transfer pathways and improved redox capabilities. The proposed design principles provide a universal approach for promoting solar-driven chemical synthesis applications.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3738-1
The escalating demand for intelligent and functional textiles, driven by technological advancements, has shifted focus from conventional attributes like warmth and aesthetics to smart functionalities. Natural biomass-derived polysaccharides, owing to their biocompatibility, biodegradability, renewability, and unique chemical structures, are pivotal for next-generation flexible wearable smart textiles. This review systematically outlines common natural polysaccharides (e.g., cellulose, chitosan, starch, alginate) used in such textiles, detailing their structural features and modification strategies. It critically evaluates current fabrication methods, highlighting their advantages and limitations. The performance characteristics, action mechanisms, and application scenarios of polysaccharide-based smart textiles are examined, with emphasis on healthcare, motion tracking, smart clothing, and energy storage/management. The review concludes by addressing existing challenges and proposing future directions for integrating polysaccharide materials into smart textile systems, aiming to guide the development of efficient, green flexible wearable devices.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604025
To meet the minute-level early-warning requirements for odor and multi-pollutant emissions at waste treatment facilities, this study proposed a multivariate short-term time-series prediction framework applicable to multi-tier scenarios covering source and boundary points (i.e., workshops and plant boundaries). Based on continuous online monitoring data with a 5-second resolution, a long short-term memory (LSTM) model using a sliding-window and recursive multi-step prediction strategy was constructed to jointly model odor concentration (OU) and pollutants including VOCs, NH3, H2S, and CH3SH (mg/m³). An evaluation protocol aligned with environmental supervision practice was established, incorporating mean absolute error (MAE), root mean square error (RMSE), goodness-of-fit (R²), skill scores (SS) relative to a persistence baseline, and threshold-based error stratification to characterize uncertainty during peak emission periods. The results showed that at workshop monitoring sites with relatively stable operating conditions, VOCs, NH3, H2S, and CH3SH exhibited a high goodness of fit and low prediction errors. In contrast, at boundary sites affected by plume arrival delays and diffusion-dilution non-stationarity, OU and VOCs displayed significantly amplified errors during peak episodes, and the skill score advantage over the baseline became unstable at certain sites. Stratified analysis consistently revealed that non-peak periods outperformed peak periods, indicating that event-driven fluctuations were the main sources of error. Accordingly, this study suggested incorporating exogenous variables such as wind speed and direction, ventilation and gate access control, and operational rhythms, along with peak-sensitive loss functions, into the model to enhance its capacity to characterize and provide early warnings for transient emission pulses. Overall, this study established a reusable methodological baseline and evaluation paradigm for minute-scale multi-pollutant prediction, providing quantitative support for the operational management and source-to-boundary coordinated control of waste treatment facilities.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025010804
Heterogeneous Fenton technology employs solid catalysts to activate H2O2, generating hydroxyl radicals (·OH) that oxidatively degrade organic pollutants. Among reported catalysts, iron-based materials are most prevalent but suffer from insufficient active sites and sluggish Fe(III)/Fe(II) cycling. Compositing iron with carbon materials increases active site density and accelerates Fe(II) regeneration, thereby enhancing catalytic efficiency. This review summarizes recent advances in carbon/iron-based heterogeneous Fenton catalysts, analyzing reaction mechanisms and characteristics for organic pollutant removal. It also discusses external energy field-assisted strategies (e.g., photo-, electro-, and ultrasound-assisted) that augment reaction kinetics. The paper concludes with perspectives on future development of carbon/iron-based Fenton-like materials, emphasizing the need for scalable synthesis and mechanistic elucidation. Key challenges include maintaining stability under continuous operation and achieving cost-effective production. The review highlights that carbon/iron composites with optimized interfacial properties can significantly improve H2O2 utilization and broaden pH applicability, addressing limitations of conventional Fenton processes. Future research directions include designing catalysts with tailored porosity and surface functionality, and integrating physical fields to synergistically enhance pollutant mineralization.
The Chinese Journal of Process Engineering•2026•DOI: 10.12034/j.issn.1009-606X.225250
Slag foaming is a critical phenomenon in electric arc furnace (EAF) steelmaking, enhancing thermal efficiency, suppressing metal splashing, and stabilizing the refining process. Accurate prediction and control of slag foaming are essential for green and efficient steelmaking. This review systematically examines research progress on slag foaming prediction, clarifying the applicability, advantages, and limitations of different predictive methods to support intelligent control of foamy slags. Following the framework of 'influencing factors-prediction methods-development trends', the study summarizes the coupling effects of multiple variables such as basicity, viscosity, surface tension, suspended particles, gas parameters, and temperature on foam formation and stability. It compares five major prediction approaches: empirical formulas, dimensionless modeling, thermodynamic calculations, computational fluid dynamics (CFD) simulations, and machine learning models, analyzing their core concepts, merits, and constraints. Results indicate that single models often struggle to balance real-time capability and accuracy, particularly under multi-variable coupling and complex operating conditions. Therefore, a hybrid prediction framework combining mechanism-based and data-driven models is proposed, emphasizing physical constraints, multi-scale coupling, and multi-source data fusion. This integrated approach is expected to advance slag foaming prediction from 'computable' to 'controllable and adjustable', offering methodological insights for the development of green and intelligent EAF steelmaking.
The Chinese Journal of Process Engineering•2026•DOI: 10.12034/j.issn.1009-606X.225141
This study established a three-dimensional transient gas-liquid two-phase flow model based on a 150-tonne converter to investigate the influence of the number of clogged bottom-blowing elements on the stirring efficiency of the molten pool. The numerical simulation results were validated against actual converter operating conditions. The findings revealed that the primary reason for deteriorated flow characteristics under multiple clogged tuyeres was the overall reduction in stirring energy input from the bottom-blowing gas. Specifically, when the number of clogged tuyeres reached three, the numerically simulated mixing time increased from 150.6 s to 219.3 s, a significant increase of 45.62%. This numerical result was in good agreement with water model experiments, indicating that prompt furnace bottom maintenance and tuyere replacement should be considered under such circumstances. At the same bottom-blowing intensity, the effective stirring area of a single inner-ring tuyere was 0.919 m2, while that of a single outer-ring tuyere was 1.651 m2. The combined effective area achieved through the synergy of inner and outer ring tuyeres was 2.940 m2, which was 14.4% greater than the sum of their individual areas. Clogging disrupted this synergistic stirring effect. A single clogged tuyere had a negligible impact on the distribution of dead zones. However, when tuyeres in both the inner and outer rings were clogged, dead zones became more numerous and concentrated. With 3 and 4 clogged tuyeres, the dead zone volume reached 3.703 and 5.946 m3, accounting for 17.31% and 27.79% of the total molten pool volume, respectively. An industrial plant trial conducted based on the numerical simulation scheme showed that key performance indicators deteriorated as the number of clogged tuyeres increased. With three clogged tuyeres, the average end-point oxygen content reached 0.0669wt%, which was 22.1% higher than that under non-clogged conditions. Concurrently, the total iron content in the slag reached 19.44%, a 24.5% increase compared to the non-clogged baseline.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202511076
This study investigated the altitudinal distribution and enrichment characteristics of heavy metals in the soil-plant system of the northern and southern mountains of Lhasa on the Tibetan Plateau. Soil and dominant plant samples were collected from three sites along an elevation gradient from 3,650 to 4,150 m, and concentrations of Cr, Cd, Cu, Zn, Ni, As, and Pb were analyzed. Soil heavy metal concentrations ranged from 0.06 to 184.4 mg·kg−1, with all elements except Cd and Pb exceeding local background values. Plant heavy metal concentrations were within normal ranges, indicating no obvious stress. Correlation analysis revealed significant positive correlations between soil Zn and Cd, Cr and Ni, and plant Zn and Cu. Except for Cr, Cu, and Cd, plant and soil concentrations of the same element were significantly correlated. Bioconcentration factor (BCF) analysis showed that most plants had weak enrichment capacity (BCF < 1), but five species, including Ephedra sinica and Rheum likiangense, exhibited BCF > 1 for Cd, with R. likiangense showing the highest BCF of 4.01. The enrichment capacity varied with altitude and species. Potential ecological risk assessment indicated that Cd posed a relatively high risk in plants, warranting attention. This study fills a gap in understanding the spatial distribution and enrichment of heavy metals in this region, providing a scientific basis for ecological management and environmental protection.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4107-x
Aqueous fiber zinc-iodine batteries (FZIBs) with four-electron redox exhibit inherent safety and high energy density for wearable electronics. Nevertheless, their practical implementations are hindered by unsatisfactory cycling stability and low realistic energy density, mainly caused by severe H2O-induced nucleophilic attack toward iodine species and poor zinc anode reversibility. Here, we report a quaternary ammonium-mediated coordination strategy to simultaneously address the irreversible cathode/anode redox behavior and thus promote the electrochemical performance of four-electron FZIBs. The cationic choline ion (Ch+) induces complexation with ICl2− via electrostatic interaction, homogenizing the electron cloud density and suppressing irreversible hydrolysis of I+ species, enabling a reversible near-theoretical high capacity of 418.3 mAh g−1. Meanwhile, preferentially adsorbed Ch+ on the zinc anode surface creates positively charged shielding layers, mitigating the tip effect caused by localized electric field and achieving robust zinc stripping/plating. The enhanced cathode/anode reversibility and improved interfacial stability enable stable FZIBs operation for over 20,000 cycles at 20.0 A g−1. Moreover, successful integration of FZIBs into electronic textiles with glucose and cardiac rhythm sensors demonstrates great potential for next-generation wearable electronics.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4057-4
The escalating use of ionizing radiation in medical and industrial applications necessitates lead-free, flexible, and sustainable shielding materials. Current development relies on empirical trial-and-error, which is inefficient. This study introduces a machine learning-assisted Monte Carlo simulation strategy for rapid optimization of metal filler compositions for X-ray attenuation across 40–120 kV. Guided by this AI-driven approach, polyvinyl alcohol (PVA)-based gels containing uniformly dispersed Bi/W/Gd2O3 nanoparticles were developed, forming within 1 minute at -20°C using a PVA-DMSO/H2O co-solvent system. The optimized gel with 50 wt% metal loading exhibits exceptional mechanical properties: tensile strength of 1.76 MPa, toughness of 6.3 MJ m−3, and elongation of 600%. It achieves >98% X-ray shielding efficiency at 5 mm thickness, outperforming lead composites at 120 kV. The physically cross-linked network provides recyclability and anti-freezing capability, retaining flexibility at -50°C. This work establishes a data-driven paradigm for designing high-performance radiation-shielding materials, demonstrating AI's potential to accelerate materials discovery and enable scalable fabrication of eco-friendly protective systems.