SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3652-2
Existing robotic end-effector gripping technologies often encounter challenges such as poor adaptability to environmental changes, incomplete deformation sensing, and insufficient adhesion stability, which can compromise operational safety and reliability. Here, we present the bio-inspired self-sensing suction cup, in which the core self-sensing capability is achieved by combining high-performance, laser-induced graphene/Ag NWs flexible sensors with a Wheatstone bridge design. The flexible sensors provide high sensitivity, while the Wheatstone bridge circuit enables accurate and stable detection of deformation during the gripping process. Integrated into the octopus-inspired suction cup, this system allows for real-time monitoring of deformation and adsorption stability. The self-sensing suction cup demonstrates good performance across a 0–25 kPa negative pressure range, with outstanding linearity (R2 = 0.993) and high sensitivity (GF = 10.436 kPa−1). Experimental results confirm that the suction cup can achieve stable adsorption under varying loads and enable real-time monitoring of the suction cup status during the gripping process. This design provides a promising solution for intelligent gripping systems, logistics, and object recognition in challenging environments.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3912-0
This erratum corrects an error in the Chinese name of co-first author Tianxiao Xiao (肖天孝) as originally published in the article 'A multi-modal smart chest patch for real-time cardiopulmonary monitoring and anomaly detection' (Sci China Mater, 2025, 68(12): 4413–4422). The corrected Chinese name is 肖天笑. The correction applies solely to the author's name and does not affect the scientific content, experimental data, or conclusions of the original paper. The authors and publisher apologize for any inconvenience caused.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202506041
Urban and rural multi-source organic waste faces bottlenecks including high compositional heterogeneity, single resource recovery pathways, and uneven product quality. In the Taihu Lake region, active tourism and catering, high greening, and dense water networks generate large volumes of diverse waste with high moisture content, exacerbating these issues. This study evaluated a coupled bio-drying and aerobic composting process at a demonstration center in Linhu Town, Suzhou, Jiangsu Province, employing a three-stage control strategy: gradient dewatering, high-temperature stabilization, and maturation enhancement. Continuous operation showed that kitchen waste moisture content decreased from 77.70% to 58.69% after 1 day of bio-drying, to 23.22% after 7 days of silo reactor composting, and to 17.70% after at least 20 days of maturation. The aerobic composting phase maintained temperatures above 55°C for over 5 days, reaching a maximum of 68.1°C, meeting the harmless treatment requirements of CJJ 52—2014. After 20 days of maturation, the organic fertilizer product had an electrical conductivity below 4.00 mS·cm−1, organic matter content of 51.22%, total nutrient content of 5.61%, and heavy metal concentrations below the limits of NY/T 525—2021. The results provide technical support for efficient treatment and resource utilization of urban and rural organic waste.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604009
Biological nitrogen removal in wastewater treatment plants (WWTPs) is often limited by insufficient influent carbon sources, necessitating external carbon addition to enhance denitrification. Conventional single carbon sources, such as sodium acetate, frequently fail to meet the metabolic demands of complex microbial communities, compromising nitrogen removal efficiency and stability. Composite carbon sources, by providing multiple electron donors, can improve metabolic cooperation among microorganisms, yet their underlying microbial mechanisms remain insufficiently understood. In this study, activated sludge from a municipal WWTP was used to investigate the microbial mechanisms of composite carbon sources during denitrification. Batch denitrification experiments were conducted in combination with metagenomic and metatranscriptomic analyses to systematically characterize microbial community structure and functional gene expression under different carbon source conditions. Results showed that, compared with sodium acetate as the single carbon source, the composite carbon source system (sodium acetate: sodium succinate: ethanol = 2:1:3) increased the denitrification rate from (6.822 ± 0.141) mg/(L·h) to (8.370 ± 0.186) mg/(L·h), representing a 22.7% improvement, while reducing N2O accumulation by approximately 55%. Metagenomic analysis revealed that Ottowia, Rubrivivax, Thauera, and Zoogloea were the dominant denitrifying genera. Metatranscriptomic results further demonstrated that the composite carbon sources significantly upregulated the transcription of key denitrification genes, with nirS, norB, and nosZ increasing by 37.8%, 27.4%, and 48.6%, respectively. In addition, the composite carbon sources promoted complementary carbon metabolic strategies among different microbial communities, enhancing electron donor supply and improving denitrification efficiency. These findings indicate that composite carbon sources synergistically enhance denitrification performance through regulation of functional gene transcription in complex microbial communities, providing a theoretical basis for carbon source optimization in WWTPs.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2026030202
High nitrogen (N) inputs, low N use efficiency, and substantial greenhouse gas emissions constrain sustainable double-cropping rice production in the middle and lower reaches of the Yangtze River. To evaluate whether humic acid urea (HAU) can reconcile yield stability with N reduction and carbon mitigation, a field experiment was conducted in a double-cropping rice system. Five treatments were established: conventional urea at the recommended N rate (U), HAU at the recommended N rate (HAU), conventional urea with a 20% reduction in N input (U-20), HAU with a 20% reduction in N input (HAU-20), and a no-N control (CK). Rice yield, N uptake and utilization, and the full life-cycle carbon footprint were quantified. Results showed that HAU significantly increased double-cropping rice yield by 6.46% (early rice) and 8.76% (late rice) compared to U (P < 0.05). HAU-20 maintained yield equivalent to U, while U-20 significantly reduced yield. HAU-20 significantly improved nitrogen fertilizer apparent utilization rate, agronomic efficiency, and partial factor productivity. Specifically, apparent utilization rate increased by 9.24 percentage points (early rice) and 7.80 percentage points (late rice); agronomic efficiency increased by 18.51% and 26.69%, and partial factor productivity by 22.79% and 25.58% for early and late rice, respectively (P < 0.05). Life-cycle carbon footprint was significantly reduced by 26.25% (early rice) and 40.38% (late rice) under HAU-20 compared to U, with per-unit product carbon footprint reduced by 0.22 t CO2-eq·t−1 and 0.86 t CO2-eq·t−1, respectively. The reduction was primarily attributed to decreased CH4 and N2O emissions: early rice CH4 and N2O cumulative emissions decreased by 28.92% and 44.34%, and late rice by 44.46% and 63.85% (P < 0.05). In conclusion, HAU with 20% N reduction sustains yield, enhances N use efficiency, and significantly lowers carbon footprint, offering a viable path for green and low-carbon double-cropping rice production.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(26)60710-4
Lignin pyrolysis is a promising route for sustainable production of high-value phenolic chemicals, yet the intricate radical reaction network remains a major bottleneck to optimizing product selectivity. This work constructs a standardized DFT computational database that systematically describes the fast pyrolysis of vanillyl alcohol at 823.15 K. The database features three key components: primary reaction pathways, thermodynamic energy barriers, and atomic-level electronic fingerprints. The dataset covers primary reaction pathways, secondary rearrangements, and both global and local reactivity indices of key intermediates. Notably, it innovatively integrates electronic-structure fingerprints, filling the gap in reaction-network–electronic-property correlation data. Standardized computational workflows and rigorous quality control ensure accuracy, consistency, and reproducibility. The public release of this dataset provides a reliable theoretical benchmark for mechanistic studies of lignin pyrolysis and offers foundational data support for rational design of new catalysts and refinement of reaction kinetic models. Ultimately, this database not only provides an important reference for data-driven catalyst development but also lays a theoretical foundation for precise regulation of lignin depolymerization.