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Chinese Journal of Polymer Science 2021年第11期39卷 1481-1488页

作者： zhong-zhu liu Guo-Qiang Zheng Hong-Hui Shi Chun-Tai liu Li-Wei Mi Qian Li Xian-Hu liu College of Material and Chemical Engineering Henan Key Laboratory of Functional Salt MaterialsCenter for Advanced Materials ResearchZhongyuan University of TechnologyZhengzhou 450007China National Center for International Joint Research of Micro-Nano Molding Technology School of Mechanics&Safety EngineeringZhengzhou UniversityZhengzhou 450002China College of Materials Science and Engineering National Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450001China

Herein,isotactic polypropylene films with smallβ-nucleating agent content were fabricated via a melt-extrusion-stretched technology with intended"shear-free"in barrel and *** with neat films,the tensile strength,elongation at break and strain energy density at break of i PP film with 0.05 wt%β-nucleating agent are significantly improved by 13.8%,39.6%and 90.6%,respectively,indicating the simultaneously enhanced toughness and ***,theβ-crystal content gradually increases with increasingβ-NA content,while the relative total daughter content ofα-andβ-crystal exhibits opposite ***,nucleation and crystal growth induced by variousβ-NA contents are *** work proves an efficient strategy to enhance mechanical properties of isotactic polypropylene film via controlling elongation flow and addition of appropriateβ-NA content.

关键词： Melt-extrusion Isotactic polypropylene β-Nucleating agent Crystallization Mechanical properties

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Sustainable Agricultural Model of High Output, Low Input and Less Pollution in Paddy Field

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Agricultural Sciences in China 2001年第1期 123-129页

作者： TANG Long-fei HUANG Yi-bin WENG Bo-qi liu zhong-zhu liu Xia-shi National Azolla Research Center Fujian Academy of Agricultural Sciences Fuzhou 350013 National Azolla Research Center Fujian Academy of Agricultural Sciences Fuzhou 350013 National Azolla Research Center Fujian Academy of Agricultural Sciences Fuzhou 350013 National Azolla Research Center Fujian Academy of Agricultural Sciences Fuzhou 350013 National Azolla Research Center Fujian Academy of Agricultural Sciences Fuzhou 350013

A model of sustainable agriculture of "high output, low input and less pollution" (HLL model)in paddy (Oryza L. )fields has been developed. About 10 - 13t/ha of rice and 3 - 4t/ha of fish were harvested by adopting the comprehensive technical system. The amount of chemical fertilizer and pesticide decreased by about 50%, thus greatly controlled the environmental pollution, and simultaneously decreased the methane emission. It was concluded that these comprehensive techniques for this model should be popularized.

关键词： Rice-azolla- fish CH4 emission Potassium enrichment HLL model

Recent progress on photoactive nonprecious transition-metal complexes

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Science China Chemistry 2025年第1期68卷 46-95页

作者： zhong-Liang Gong Hong-Jie Zhang Yan Cheng Jianxun liu Yuhan Ai Yaqin Li Zhihui Feng Qiong Zhang Shaolong Gong Yong Chen Chang-Jiang Yao Yuan-Yuan zhu Liang-Jin Xu Yu-Wu zhong CAS Key Laboratory of Photochemistry Institute of Chemistry Chinese Academy of Sciences State Key Laboratory of Structural Cemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences School of Chemistry and Chemical Engineering Anhui Key Laboratory of Advanced Catalytic Materials and Reaction EngineeringHefei University of Technology State Key Laboratory of Explosion Science and Safety Protection School of Mechatronical Engineering Beijing Institute of Technology College of Chemistry and Molecular Sciences Hubei Key Lab on Organic and Polymeric Optoelectronic Materials Wuhan University School of Chemistry and Chemical Engineering Anhui University Key Laboratory of Photochemical Conversion and Optoelectronic Materials & CAS-HKU Joint Laboratory on New Materials Technical Institute of Physics and Chemistry Chinese Academy of Sciences

Photoactive complexes of nonprecious transition metals, mainly including those in the first-row and partially the second-row of the Periodic table of elements, have received increasing attention in view of their low cost and long-term sustainability. They are recognized as promising alternatives to noble transition metal complex congeners that have been extensively studied in optoelectronic devices, artificial photosynthesis, photocatalysis, biodiagnostics, and therapeutics, etc. This review is devoted to a comprehensive summary on the classical and recent advances on photoactive nonprecious transition metal complexes, including photoactive Zr, V, Cr, Mo, and W complexes, Mn complexes and hybrids, Fe, Co, Ni, and Cu complexes, and Zn and Cd complexes and hybrids. A particular focus is given on the molecular design, modulation of photophysical and photochemical properties, and applications of the representative and lately-developed nonprecious metal complexes. In addition, a perspective on the future development in this field is provided at the end of this review.

关键词： photoactive metal complexes earth-abundant metals nonprecious metal complexes luminescence photochemistry

Chiral phosphoramidite ligand-modulated palladium auto-tandem catalysis for asymmetric dehydrogenative dienylation of imines with α-alkenes

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Science China Chemistry 2025年

作者： zhong-Sheng Nong Hao-Fan Qian Ying-Chun Chen Pu-Sheng Wang liu-zhu Gong Hefei National Research Center for Physical Sciences at the Microscale and Department of Chemistry University of Science and Technology of China Key Laboratory of Drug Targeting and Drug Delivery System (Sichuan University) Ministry of Education and Sichuan Research Center for Drug Precision Industrial Technology West China School of Pharmacy Sichuan University School of Materials and Chemistry Southwest University of Science and Technology

The development of efficient processes allowing rapid access to complex chiral molecules from easily available alkenes is a long-term pursuit in the synthetic chemistry community. Transition metal-catalyzed asymmetric functionalization of allylic C–H bond represents a unique alternative toward this goal. However, enantioselective dehydrogenative transformation of olefins to value-added optically enriched molecules remains yet to be discovered. Here, we report a highly enantioselective dehydrogenative dienylation of imines with unactivated α-alkenes driven by the synergistic action of palladium complex and carboxylic acid. Chiral phosphoramidite ligands turned out to be superior in modulating the performance of palladium autotandem catalysis and allowed a broad range of α-alkenes and imines to be transformed into chiral dienylamines. Mechanistic studies suggest that the dienes could be in situ generated from α-alkenes through a palladium(0)-mediated dehydrogenative process in the presence of excess benzoquinone oxidants, and then participated in the Pd-chiral phosphoramidite-catalyzed intermolecular vinylogous-type addition to the imines activated by the carboxylic acid co-catalyst. Notably, the second β-H elimination occurring in the dienylation event might be the turnover-limiting step.

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing liu Wei zhu Di LI Xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Specific staining and precise killing of cancer cells through fusion of pharmaceutical chemistry and π-bridge effect design philosophy

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Science China Chemistry 2025年

作者： Qiong liu Qiyun Deng Changxu zhu Kongqi Chen Lidan Chen Zhaohui Sun Ben zhong Tang Zhiming Wang AIE Institute Center for Aggregation-Induced Emission State Key Laboratory of Luminescent Materials and Devices Key Laboratory of Luminescence from Molecular Aggregates of Guangdong Province South China University of Technology Department of Laboratory Medicine General Hospital of Southern Theater Command School of Life Sciences The Chinese University of Hong Kong Shenzhen Institute of Aggregate Science and Technology School of Science and Engineering The Chinese University of Hong Kong HKUST-Shenzhen Research Institute

The development of an advanced phototheranostic platform that combines imaging and therapy in a single agent is an appealing yet challenging *** this study,we successfully constructed three novel fluorescent probes by leveraging pharmaceutical chemistry and the design philosophy of theπ-bridge *** a systematic comparative analysis of their fluorescence properties,water solubility,molecular conformation,and electrostatic potential,we revealed the fundamental principles governing the optical behavior and biological selectivity of these ***,the probe TPhIQ-CNTh demonstrated extended fluorescence in the near-infrared region,a significant aggregation-induced emission (AIE) effect,and the ability to distinguish tumor cells from normal ***,it efficiently generated reactive oxygen species (ROS) and specifically labeled lipid droplets,enabling the precise staining and killing of cancer *** study presents a practical strategy for designing precise tumor treatments that integrate efficient imaging-guided photodynamic therapy (PDT) by harnessing the unique properties of AIE materials.

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Low-cost and fluoride-free synthesis of MFI zeolite nanosheets with enhanced stability for benzene alkylation with ethanol

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Journal of Energy Chemistry 2025年第1期100卷 458-468页

作者： Peng zhu Cun liu Yiren Yu Guoshu Gao Yumeng Zhao Xiongfu Zhang Guodong liu Guohui Yang State Key Laboratory of Fine Chemicals School of Chemical Engineering Dalian University of Technology State Key Laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences

Zeolite nanosheets with a short b-axis thickness are highly desirable in lots of catalytic reactions due to their reduced diffusion resistance. Nevertheless, conventional synthesis methods usually require expensive structure-directing agents(SDAs), pricey raw materials, and eco-unfriendly fluorine-containing additives. Here, we contributed a cost-effective and fluoride-free synthesis method for synthesizing high-quality MFI zeolite nanosheets through a Silicalite-1(Sil-1) seed suspension and urea cooperative strategy, only with inexpensive colloidal silica as the Si source. Our approach was effective for synthesizing both Sil-1 and aluminum-containing ZSM-5 nanosheets. By optimizing key synthesis parameters,including seed aging time, seed quantity, and urea concentration, we achieved precise control over the crystal face aspect ratio and b-axis thickness. We also revealed a non-classical oriented nanosheet growth mechanism, where Sil-1 seeds induced the formation of quasi-ordered precursor particles, and the(010)crystal planes of these particles facilitated urea adsorption, thereby promoting c-axis-oriented *** obtained ZSM-5 nanosheets exhibited exceptional catalytic performance in the benzene alkylation with ethanol, maintaining stability for over 500 h, which is 5 times longer than traditional ZSM-5 catalysts. Furthermore, large-scale production of ZSM-5 nanosheets was successfully carried out in a 3 L highpressure autoclave, yielding samples consistent with those from laboratory-scale synthesis. This work marks a significant step forward in the sustainable and efficient production of MFI nanosheets using inexpensive and environmentally friendly raw materials, offering the broad applicability in catalysis.

关键词： Aspect ratio

Software-defined process-near-memory architecture using 3D hybrid bonding integration

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Science China(Information Sciences) 2025年第1期68卷 366-378页

作者： Anlin XU Chenchen DENG Jianfeng zhu Yao WANG Shaojun WEI Leibo liu School of Integrated Circuits Tsinghua University Beijing Institution of Tracking and Communication Technology Beijing National Research Center for Information Science and Technology Tsinghua University

With the unprecedented explosive growing amount of global data, the development of computing chips, which encounter bottlenecks such as power wall and memory wall, cannot satisfy the demanding requirement. This work proposes a software-defined process-near-memory(SDPNM) computing architecture implemented using 3D hybrid bonding *** software-defined chip architecture, featuring spatial computations and dynamic reconfiguration, innovates in a top-down manner to achieve high energy efficiency while maintaining flexibility after fabrication. The process-near-memory integration further advances the SDNPM chip in a bottom-up way to reduce the energy consumption of data movement while improving the bandwidth. Utilizing a relatively mature fabrication and bonding process can result in feasible solutions for both data-intensive and compute-intensive applications including digital signal processing and artificial intelligence. The logic die is fabricated in the SMIC 40 nm process and the DRAM die is fabricated in the PSMC 25 nm process. The hybrid bonding is implemented by XMC. The experimental results show that the energy efficiency of the proposed SDPNM chip is 33.1× better than the state-of-the-art FPGA ranging from 8.2× to 104.1×.

关键词： software-defined chips process near memory energy efficiency dynamic reconfiguration domain specific

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Nitrogen addition promotes soil carbon accumulation globally

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Science China Life Sciences 2025年第1期68卷 284-293页

作者： Xuemei Yang Suhui Ma Erhan Huang Danhua Zhang Guoping Chen Jiangling zhu Chengjun Ji Biao zhu Lingli liu Jingyun Fang Institute of Ecology College of Urban and Environmental Sciencesand Key Laboratory for Earth Surface Processes of the Ministry of EducationPeking University Ministry of Education Key Laboratory for Transboundary Ecosecurity of Southwest China School of Ecology and Environmental ScienceYunnan University State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of Sciences

Soil is the largest carbon(C) reservoir in terrestrial ecosystems and plays a crucial role in regulating the global C cycle and climate *** nitrogen(N) deposition has been widely considered as a critical factor affecting soil organic carbon(SOC) storage, but its effect on SOC components with different stability remains unclear. Here, we analyzed extensive empirical data from 304 sites worldwide to investigate how SOC and its components respond to N addition. Our analysis showed that N addition led to a significant increase in bulk SOC(6.7%), with greater increases in croplands(10.6%) and forests(6.0%) compared to grasslands(2.1%). Regarding SOC components, N addition promoted the accumulation of plant-derived C(9.7%–28.5%) over microbial-derived C(0.2%), as well as labile(5.7%) over recalcitrant components(–1.2%), resulting in a shift towards increased accumulation of plant-derived labile C. Consistently, N addition led to a greater increase in particulate organic C(11.9%) than mineral-associated organic C(3.6%), suggesting that N addition promotes C accumulation across all pools, with more increase in unstable than stable pools. The responses of SOC and its components were best predicted by the N addition rate and net primary productivity. Overall, our findings suggest that N enrichment could promote the accumulation of plant-derived and non-mineral associated C and a subsequent decrease in the overall stability of soil C pool, which underscores the importance of considering the effects of N enrichment on SOC components for a better understanding of C dynamics in soils.

关键词： meta-analysis nitrogen enrichment soil organic carbon carbon accumulation carbon stability

Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng Wang Ruisong zhu Ruijie liu Jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control Engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning