SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3827-3
Chiral functional materials, characterized by intrinsic spatial asymmetry, hold transformative potential in photonics, enantioselective synthesis, quantum technologies, and biomedicine. However, their rational design and discovery are impeded by the vast chemical space and complex structure-property relationships, rendering traditional trial-and-error approaches inefficient and costly. This review critically examines the paradigm-shifting role of artificial intelligence (AI) in accelerating the discovery and optimization of chiral functional materials. We highlight recent AI-driven breakthroughs, emphasizing machine learning (ML) algorithms that excel in identifying patterns within high-dimensional data, thereby enabling rapid virtual screening and elucidation of intricate structure-property correlations. Key applications span from predicting enantioselectivity in asymmetric catalysis to designing circularly polarized luminescent materials and chiral metamaterials. Notably, ML models have achieved predictive accuracies exceeding 90% in classifying chiral structures and have reduced computational screening times by orders of magnitude. The integration of AI with automated synthesis platforms further enables closed-loop optimization, as demonstrated in the autonomous discovery of optically active chiral perovskite nanocrystals. This review underscores that AI not only accelerates materials discovery but also fosters cross-disciplinary innovation, positioning itself as an indispensable tool for the next generation of chiral functional materials. By synthesizing recent progress, we provide a roadmap for leveraging AI to navigate the complex landscape of chiral materials, ultimately expediting the translation of laboratory innovations into practical applications.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202606011
Hexavalent chromium (Cr(VI)) contamination in chromite ore processing residue (COPR) and associated soils poses a persistent environmental challenge. This study developed a dispersedly stabilized iron-sulfur-based slurry (DSS-ISB) modified with an inorganic dispersant to enhance nanoparticle suspension stability and interfacial reactivity. The slurry, with a particle size of approximately 200 nm, efficiently reduced and immobilized Cr(VI) without pH adjustment. Under optimal conditions (liquid-to-solid ratio of 5 mL:10 g, DSS-ISB dosage of 1.8 mg/g, reaction time of 20 h), the removal efficiency exceeded 97%, reducing the leaching concentration from 15.03 mg/L to 0.03 mg/L, well below the GB 5085.3—2007 limit of 5 mg/L. X-ray photoelectron spectroscopy (XPS) and Brunauer-Emmett-Teller (BET) analyses revealed a synergistic mechanism of chemical reduction (Fe2+/S2- as dual electron donors) and surface adsorption, converting toxic Cr(VI) to stable Cr(III). Compared with traditional reductants ferrous sulfate (FeSO4) and sodium sulfide (Na2S), DSS-ISB increased removal efficiency by 28.24% and 6.23%, respectively, and unit mass removal capacity by 92.43% and 77.08%. The reagent cost per ton of COPR was reduced to RMB 36.40, achieving savings of 33.82% and 26.02% versus FeSO4 (RMB 55.00) and Na2S (RMB 49.20). The process eliminates pH adjustment and subsequent passivation, simplifying remediation. DSS-ISB offers an economical and green solution for Cr(VI) remediation in both industrial residues and contaminated soils.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202607009
Resource utilization of food waste is a key measure for implementing waste classification and constructing zero-waste cities in China. However, the technical route based on anaerobic digestion currently faces developmental bottlenecks. In this study, engineering-scale facilities located in Northeast, North, Northwest, and Southeast China were selected, and material flow analysis was employed to comprehensively assess the current status of anaerobic digestion of food waste. The results indicated that, during the pretreatment stage, both leachate and organic slurry from all surveyed regions exhibited high COD/TN ratios, and the leachate contained high concentrations of lipids. Following three-phase (oil-water-solid) separation, the oil recovery rate could reach over 98%. Anaerobic digestion of each ton of food waste from the four regions generated approximately 70 to 80 Nm³ of biogas, while simultaneously producing liquid digestate accounting for 69% to 80% of the total mass and solid digestate accounting for 2.7% to 3.6%. However, the annual continuous production of digestate was not aligned with the seasonal demand for land use, thereby restricting the pathway for resource utilization. Converting food waste into an external carbon source can significantly enhance its resource utilization efficiency, with the economic benefits increasing by more than 203% compared to the methanogenesis pathway. The selection of the carbon source production technology route should be comprehensively determined by taking into account factors such as the specific nitrogen removal requirements of the target wastewater treatment process, the quality requirements for the carbon source products, and the substitution rate of commercial carbon sources.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025041505
To combat severe air pollution, China has implemented a series of air pollution control action plans since 2013, effectively alleviating PM2.5 pollution. However, PM2.5 concentrations in most cities within the Fenwei Plain still exceed national standards. This study systematically evaluates PM2.5 concentration changes across two policy phases (2013–2020) using the Community Multiscale Air Quality (CMAQ) model, quantifying contributions of meteorology and emissions, and analyzing sectoral source changes. Results show that annual average PM2.5 concentration declined cumulatively by 19% during 2013–2020. In the first phase (2013–2017), regional PM2.5 decreased by 3% annually, with most improvement in winter; however, due to unfavorable meteorology, concentrations increased in Xi'an and Xianyang. In the second phase (2017–2020), PM2.5 declined by an additional 16%, with more effective control measures, particularly in spring and autumn. Emission reductions dominated in both phases, with stronger effects in the second phase (−8 μg·m−3), significantly outweighing adverse meteorological contributions (+3.5 μg·m−3). Nevertheless, many cities still face challenges from unfavorable meteorology, highlighting the need for future policies to account for meteorological influences. Emissions from industrial, energy, and agricultural sources decreased significantly across both phases. However, during winter heating periods, residential emissions emerged as a source equal in importance to industrial emissions, becoming a key target for future emission controls.