Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025122101
Phenolic compounds, widely used in petrochemical, textile, and pharmaceutical industries, pose severe risks to ecosystems and human health due to their toxicity and persistence. Traditional Fe2+-mediated Fenton oxidation, while effective, suffers from external H2O2 and Fe2+ addition, low H2O2 utilization, narrow pH adaptability, and iron sludge generation. This study develops a g-C3N4-based heterogeneous photo-Fenton system that operates without external H2O2 or Fe2+ salts, exhibiting a wide pH range and minimal iron sludge. The synthesized Fe3O4@UiO/IKCN catalyst, under visible light, selectively reduces dissolved oxygen to H2O2 via a two-electron pathway and activates it to hydroxyl radicals (·OH), achieving efficient degradation of phenolic compounds. The integration of photocatalytic H2O2 formation and Fenton activation enables sustained production of oxidative species, demonstrating superior performance at circumneutral pH. This work provides new insights into the rational design of heterogeneous Z-scheme photo-Fenton catalysts and offers experimental and theoretical support for photocatalytic H2O2 synthesis and phenolic wastewater treatment.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025122102
Uranium is a key resource for nuclear energy, but its mining and processing generate large amounts of uranium-containing wastewater, posing persistent threats to the environment and human health. In this study, a cyano-functionalized C3N4/ZnIn2S4 (CCN/ZIS) heterojunction system was constructed for efficient removal of U(VI) from uranium mining wastewater. The introduction of cyano groups significantly enhanced the adsorption capacity of CCN/ZIS, reaching a maximum of 123.65 mg·g−1. Characterization techniques (UV-vis DRS, EIS, i-t, PL, TRPL) confirmed that cyano groups effectively suppress charge carrier recombination, improving photogenerated carrier separation. Under visible light, the modified material achieved over 95% removal of U(VI) within 10 minutes, demonstrating a 20-fold efficiency increase compared to pristine materials. Even in simulated uranium mining wastewater containing high concentrations of CO3^2− and F−, CCN/ZIS maintained excellent performance, overcoming the technical challenge of U(VI) removal efficiency being constrained by water quality conditions. Quenching experiments identified e− and ·O2− as the primary reactive species responsible for U(VI) reduction. This study reveals the synergistic mechanism of selective U(VI) enrichment and photoreduction, providing theoretical innovation and technological breakthroughs for uranium pollution control.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3786-8
Conventional cancer diagnostic techniques, such as tissue sampling and microscopy, are invasive and prone to misdiagnosis, driving the need for non-invasive, precise alternatives. Chiral biophotonics, exploiting circularly polarized light (CPL), offers unique polarization-selective interactions with biological tissues, enabling higher imaging contrast and molecular-level discrimination. However, current CPL detection technologies are passive and single-mode, lacking dynamic tunability and parallel processing capabilities. Meanwhile, AI-assisted diagnostics rely on separated sensing and computing units, suffering from poor integration and transmission inefficiency. Here, we report a near-infrared (NIR) chiral organic synaptic photodiode with electrically tunable dual-mode operation, enabling simultaneous CPL detection and neuromorphic processing. Under negative bias, the device operates as a highly sensitive CPL detector for chiroptical signal acquisition. Under positive bias, it exhibits history-dependent synaptic behavior with photocurrent dissymmetry factor (g_ph) dynamically tunable up to -0.06. By integrating this device into an optical convolutional neural network (OCNN), we achieved intelligent cancer detection with CPL-based imaging. Experimental results demonstrate that CPL detection accuracy reaches 83%, approaching the theoretical 87%, significantly outperforming natural light detection at 65%. The device enhances image contrast and feature extraction, laying a foundation for intelligent, adaptive diagnostic systems.