Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604010
Guar gum production wastewater contains 1,2-propanediol, which in conventional anaerobic treatment causes propionate accumulation and microbial inhibition. Microaerobic conditions foster fermentative bacterial metabolism, enhancing organic substrate conversion, while biochar promotes anaerobic microbial aggregation and oxygen tolerance. This study treated actual guar gum wastewater using three configurations: blank control, anaerobic, and microaerobic-biochar (O2/BC) coupled systems. Under mesophilic conditions (37 °C), with micro-aeration at 0.2 mL/(g VS·d) and biochar dosage of 15 g/L, the O2/BC system achieved a COD removal efficiency of 90%, 10.6 percentage points higher than the anaerobic control. Effluent COD and propionate concentrations dropped to 3800 mg/L and 0.15 g/L, respectively, representing reductions of 49.6% and 98.4% versus the control. Biogas production was 1.64 times that of the control, with a maximum methane concentration of 77.2%. Fourier transform infrared spectroscopy (FT-IR) indicated increased abundance of –OH, –CH2–, and C–O functional groups on sludge surfaces, revealing biochar's adsorption enhancement. Scanning electron microscopy (SEM) showed dense microbial aggregates dominated by long bacilli, distinct from conventional anaerobic sludge. Microbial community analysis revealed increased abundance of Clostridium and Comamonas, modulating the propionate-to-acetate ratio and optimizing acidification efficiency, thereby promoting complex organic degradation. This study provides a novel technical pathway for biological treatment of alcohol-rich organic wastewater.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025101901
Hexachlorobutadiene (HCBD) is a persistent organic pollutant (POP) regulated under the Stockholm Convention. Chlorinated chemical production processes are major sources of unintentional HCBD emissions, posing potential threats to ecosystems and human health. This study systematically reviews the formation, emission, and environmental impact of HCBD from such processes. HCBD is widely generated as a by-product during chlorination stages of producing carbon tetrachloride, dichloroacetylene, tri-/tetrachloroethylene, and chlorobenzene, via free-radical mechanisms. It is released through waste gas, wastewater, and solid waste. In the environment, HCBD exhibits multimedia distribution, undergoing long-range atmospheric transport and adsorbing onto soil and sediments, thereby becoming secondary pollution sources. HCBD shows significant bioaccumulation and food-chain magnification; it is toxic to aquatic organisms and causes hepatic and renal damage with potential carcinogenicity in mammals. Effective pollution control requires combined process improvements and end-of-pipe treatments, supplemented by stringent emission standards and life-cycle management. Future research should focus on developing precise emission inventories, elucidating multi-media transport and transformation mechanisms, and assessing composite ecotoxicological effects, thereby providing scientific support for implementing international conventions and formulating effective prevention strategies.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3965-5
Liquid crystal elastomers (LCEs) have emerged as a promising material platform for soft robotics, effectively integrating programmable molecular orientation with the inherent flexibility of elastomers. This unique combination enables significant, reversible deformations responding to external stimuli, including heat, light, electric, and magnetic fields. Due to these characteristics, LCEs serve as an ideal material system for bridging biological principles with engineered soft robotic applications, enabling the development of adaptive and multifunctional systems with enhanced biomimetic capabilities. However, the mechanisms of bioinspired motion and the effective integration of biomimetic functions in LCE-based robots remain insufficiently explored. This review systematically examines recent advances in LCE-based biomimetic soft robots, focusing on multimodal actuation strategies, including contraction, crawling, rolling, jumping, swimming, and plant-inspired motions. It highlights integrated functional enhancements achieved via innovative material compositions, structural designs, and advanced manufacturing techniques. These developments have enabled novel robotic functionalities, including programmable actuation, self-healing and recycling, color morphing and camouflage, and tunable bioinspired surface characteristics.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4012-4
Stimuli-responsive fluorescent hydrogels, owing to their tunable optical properties and unique smart response characteristics, have significant potential in encryption applications and information security. However, most current systems are limited to single-stimulus responsiveness and lack the capability for programmable information erasure or multi-modal dynamic synergy. Hence, we propose a multi-stimuli-responsive phase-change hydrogel incorporating aggregation-induced emission hydrophobic carbon dots (AIE-HCDs) and polyethylene glycol (PEG)-cellulose network, demonstrating dynamic fluorescence chromism under various external triggers. The hydrogel exhibits solvent-exchange-triggered fluorescence color changes from blue to red, enabled by the concentration modulation of AIE-HCDs through the exchange between PEG and water. Additionally, the temperature-induced phase transition of PEG from crystalline to molten state modulates the aggregation and dispersion of AIE-HCDs, thereby enabling dynamic fluorescence color changes. The phase transition further confers excellent shape-memory behavior and adjustable mechanical properties, with the tensile modulus varying from 6.28 MPa in the molten state to 36.23 MPa in the crystalline state, while maintaining high transparency (~88% in the molten state). By utilizing micro-contact printing and the multi-stimulus response, an encryption platform enables information to be hidden, selectively read under sequential stimuli (thermal, UV, and solvent), and completely erased upon demand. This strategy demonstrates significant potential for advancing high-level information encryption and anti-counterfeiting technologies.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202608006
Organic waste is a potential phosphorus reservoir, and understanding the dynamics of available phosphorus (AP) during its resource utilization is critical for efficient phosphorus recovery. Composting, a key route for organic waste valorization, involves complex transformations of phosphorus alongside organic matter degradation and humification. However, the long duration and high cost of composting experiments, coupled with multifactorial influences, hinder efficient elucidation of AP dynamics via conventional methods. This study compiled data from 33 publications, constructing a dataset of 647 samples. Data preprocessing included iterative imputation, one-hot encoding, and standardization. A stacking ensemble learning model was developed to predict AP generation during composting. The optimal ensemble comprised XGBoost and SVR as base learners and ElasticNet as the meta-learner, achieving R² values of 0.954 and 0.928 on training and test sets, respectively, with low overall error. SHAP analysis revealed that key factors influencing AP content, in descending order of importance, were feedstock type, bulking agent type, turning interval, pH, electrical conductivity (EC), and C/N ratio. Notably, livestock manure as feedstock and straw-based bulking agents contributed positively to AP predictions. Partial dependence plots indicated that lower pH and C/N ratios generally favored AP accumulation throughout composting. During the initial stage, higher moisture content and lower EC enhanced AP; in the thermophilic phase, higher temperatures corresponded to higher AP; and during cooling and maturation, maintaining moisture below 48% and C/N below 14, while extending composting beyond 43 days, promoted AP accumulation. This study demonstrates accurate AP prediction via stacking ensemble learning and identifies critical factors, offering support for optimizing phosphorus management in composting engineering.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4332-3
This correction addresses an error in the affiliations of the authors of the article 'Intrinsic pseudocapacitive Na0.44MnO2 prepared by novel ion-exchange method for high rate and robust sodium-ion batteries' originally published in Science China Materials, volume 66, issue 10, 2023, pages 3810–3816. In the original publication, one affiliation of the first author (Yuge Cao) was missing, and the affiliations of the authors were incorrectly labeled. The corrected affiliations are as follows: Yuge Cao is affiliated with the State Key Laboratory of High-Performance Ceramics and Superfine Microstructures, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050, China; the Beijing National Laboratory for Molecular Sciences and State Key Laboratory of Rare Earth Materials Chemistry and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China; and the Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China. The other authors' affiliations are also corrected accordingly. The corresponding authors are Hui Bi ([email protected]) and Fuqiang Huang ([email protected]). This correction does not affect the scientific content of the original article.