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Constraints on what controls millennial-scale basin-wide denudation across mountain belts,Asia

science China Earth sciences 2025年第1期68卷 74-93页

作者： Ye YANG Steven A.BINNIE Sheng XU Cong-Qiang LIU Tibor J.DUNAI Institute of Surface-Earth system science School of Earth System ScienceTianjin UniversityTianjin300072China Institute of Geology and Mineralogy University of CologneCologne50674Germany

The terrestrial cosmogenic nuclide dataset consisting of 1233^(10)Be measurements of fluvial sediment samples across the Asian mountain belts is used to constrain the influence of climate,tectonics and topography on Earth-surface denudation processes.^(10)Be-derived basin-wide denudation rates were recalculated using a Monte Carlo simulation approach that relied on pixel-by-pixel production *** rates derived span four orders of magnitude,from 7.4±0.7 mm kyr^(-1)(1σ;Central Tibetan Plateau)to 9,646_(-744)^(+777)mm kyr^(-1)(1σ;Southern Tibetan Plateau),with a median of 186 mm kyr^(-1).Comparing our results with the traditional basin-wide production rate scaling model using a centroid coordinate and mean elevation,suggests that 96.6%of production rates will be underestimated using the latter method,especially for basins with a large *** bias between both methods reaches as large as 40%,caused by basin hypsometry and the nonlinear scaling of production rate with elevation and *** of the correlations between uniformly recalculated denudation rates and tectonics,climate,topography and rock lithology will facilitate the extrapolation of denudation rates in unknown basins using available *** the perspective of local scales,precipitation coupled with neotectonics-driven landslides is likely the most influential factor in subtropical Taiwan Island,while topography primarily constrains surface denudation rates in the eastern Tibetan Plateau within a narrow range of *** highland regions with glacier coverage,such as the Pamir,central and southern Tibetan Plateau high denudation rates are affected by glaciation,whereas lower precipitation and high erosion base level may limit river incision and evolving relief in the Central Tibetan *** contrast to local-scale findings highlighting a dominant factor constraining denudation rate,our large-scale quantitative analyses across the Asian mountain belts finds that(1)topographic

关键词： ^(10)Be-derived denudation rate Climate change Tectonic uplift Topographic gradient Asian mountains

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RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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science China(Information sciences) 2025年第2期68卷 103-119页

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao ZHU Hai JIN National Engineering Research Center for Big Data Technology and system Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

关键词： knowledge graph reasoning temporal knowledge graph Hawkes process semantic evidence

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Upcycling of monomers derived from waste polyester plastics via electrocatalysis

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Journal of Energy Chemistry 2025年第2期101卷 535-561页

作者： Haoye Wang Richard Lee Smith Jr Xinhua Qi College of Environmental science and Engineering Nankai University graduate school of Environmental Studies Tohoku University

Electrocatalysis offers efficient and targeted conversion of monomers derived from waste polyester plastics to chemical products under ambient temperature and pressure *** review provides analysis of research on electrochemical upgrading of monomers derived from waste polyester plastics published from2021 to *** for assessing upgrading of waste polyester plastics include alkaline hydrolysis pretreatment,indices of electrochemical reaction process(activity,stability,and techno-economic a nalysis),separation,and product *** of depolymerization monomers and their value-added products are summarized along with electrocatalytic mechanisms and reaction ***,cathode coupled reactions offer significant value for anodic waste plastic oxidation during electrolysis *** of bifunctional electrocatalysts can reduce the cost of coupled systems and complexity of the *** and recycling of waste plastic monomers using electrocatalytic technology should undergo downstream processing to form high-value products containing C-N and C-S derived functional groups obtained from depolymerized monomers,Electrochemical conversion and upgrading of monomers derived from waste polyester plastics can contribute to industrialization and global economies and help to realize environmental sustainability.

关键词： Coupling reaction Electrocatalysis Monomer Upgrade recycling Value-added products Waste plastics

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Experimental demonstration of 220-GHz terahertz signals wireless transmission over 4.6 km

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science China(Information sciences) 2025年第1期68卷 386-388页

作者： Yi WEI Jianjun YU Mingxu WANG Xiongwei YANG Qiutong ZHANG Jingwen TAN Bing ZHANG Ying WU Yang HAN Peng TIAN Wen ZHOU Kaihui WANG Feng ZHAO State Key Laboratory of ASIC and system Key Laboratory for Information Science of Electromagnetic Waves (MoE)School of Information Science and Technology Fudan University school of Electronic Engineering Xi'an University of Posts and Telecommunications

The advancement of terahertz (THz) communication technology drives the evolution of wireless communication systems,offering novel pathways and technical means for the development of future 6G communication *** wireless communication systems are often constrained by bandwidth limitations of electronic devices in high frequency ***,THz communication technology leverages the characteristics of electromagnetic waves to transcend these limitations,enabling communication athigher frequencies and wider bandwidths.

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Magnetically-responsive phase change thermal storage materials:Mechanisms,advances,and beyond

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Journal of Energy Chemistry 2025年第2期101卷 485-510页

作者： Yan Gao Yang Li Jinjie Lin Panpan Liu Xiao Chen Ge Wang Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory of Function Materials for Molecule & Structure Construction School of Materials Science and Engineering University of Science and Technology Beijing school of Physics and Astronomy Beijing Normal University Shunde graduate school University of Science and Technology Beijing

Rapid advances in thermal management technology and the increasing need for multi-energy conversion have placed stringent energy efficiency requirements on next-generation shape-stable composite phase change materials(PCMs).Magnetically-responsive phase change thermal storage materials are considered an emerging concept for energy storage systems,enabling PCMs to perform unprecedented functions(such as green energy utilization,magnetic thermotherapy,drug release,etc.).The combination of multifunctional magnetic nanomaterials and PCMs is a milestone in the creation of advanced multifunctional composite ***,a timely and comprehensive review of composite PCMs based on magnetic nanoparticle modification is still ***,we furnish an exhaustive exposition elucidating the cutting-edge advancements in magnetically responsive composite *** delve deeply into the multifarious roles assumed by distinct nanoparticles within composite PCMs of varying dimensions,meticulously scrutinizing the intricate interplay between their architectures and thermophysical ***,we prognosticate future research trajectories,delineate alternative stratagems,and illuminate prospective *** review is intended to stimulate broader academic interest in interdisciplinary fields and provide valuable insights into the development of next-generation magnetically-responsive composite PCMs.

关键词： Magnetic nanoparticles Magnetic-thermal conversion Phase change materials Response mechanism Thermal energy storage

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Distributed Observer for Full-Measured Nonlinear systems Based on Knowledge of FMCF

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 69-85页

作者： Haotian Xu Shuai Liu Yueyang Li Ke Li the school of Control science and Engineering Shandong University and also with Key Laboratory of Machine Intelligence and System Control Ministry of Education IEEE the school of Electrical Engineering University of Jinan

Driven by practical applications, the achievement of distributed observers for nonlinear systems has emerged as a crucial advancement in recent years. However, existing theoretical advancements face certain limitations: They either fail to address more complex nonlinear phenomena, rely on hard-to-verify assumptions, or encounter difficulties in solving system ***, this paper aims to address these challenges by investigating distributed observers for nonlinear systems through the full-measured canonical form(FMCF), which is inspired by full-measured system(FMS) theory. To begin with, this study addresses the fact that the FMCF can only be obtained through the observable canonical form(OCF) in existing FMS *** paper demonstrates that a class of nonlinear systems can directly obtain FMCF through state space equations, independent of OCF. Also, a general method for solving FMCF in such systems is provided. Furthermore, based on the FMCF, A distributed observer is developed for nonlinear systems under two scenarios: Lipschitz conditions and open-loop bounded *** paper establishes their asymptotic omniscience and demonstrates that the designed distributed observer in this study has fewer design parameters and is more convenient to construct than existing approaches. Finally, the effectiveness of the proposed methods is validated through simulation results on Van der Pol oscillators and microgrid systems.

关键词： Distributed observer full-actuated system full-measured system (FMS) nonlinear observer sensor networks

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Mesh-supported V2O5-WO3/TiO2 nanosheet array catalysts for efficient removal of NOx

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Tungsten 2025年第1期7卷 100-111页

作者： Zhi-Qi Zhang Liu Yang Wen Luo Vladimir An Jing Li Bao-Dan Liu school of Materials science and Engineering Northeastern University Foshan graduate school of Innovation Northeastern University Kizhner Research Center School of Advanced Manufacturing Technologies Tomsk Polytechnic University

The design and synthesis of vanadium-based denitration catalysts with low-temperature activity pose significant challenges in the field of toxic gas *** this study,we have developed a novel approach to fabricate highly efficient V2O5-WO3/TiO2monolithic mesh catalysts for NOxreduction at low ***,TiO2nanosheets with strong adhesion and large surface area were grown on Ti mesh using plasma electrolytic oxidation technology and hydrothermal ***,super-small traces of WO3and V2O5active nano-species were subsequently deposited on TiO2nanosheets using the deposition-precipitation *** to traditional ceramic-based V2O5-WO3/TiO2catalysts,our V2O5-WO3/TiO2monolithic mesh catalyst exhibits superior mechanical performance,excellent thermal conductivity,lower pressure drop,higher utilization of active components,and stronger synergistic ***,the V2O5-WO3/TiO2monolithic mesh catalysts exhibited excellent low-temperature catalytic activity with 98% of NOxconversion at 220℃,and remarkable long-term SO2tolerance and water resistance in the selective catalytic reduction（SCR） of NOxwith *** SCR reaction of tiny V2O5and WO3active species supported on TiO2nanosheets directly demonstrated to follow the Eley-Rideal mechanism by in situ infrared spectra.

关键词： Low temperature activity Monolithic mesh catalysts NH3-SCR SO2 tolerance V2O5-WO3/TiO2

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Subduction thermal state, slab metamorphism, and seismicity in the Makran Subduction Zone

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Earth and Planetary Physics 2025年第02期9卷 266-278页

作者： Haris Faheem YingFeng Ji WeiLing Zhu Rui Qu Ye Zhu Shoichi Yoshioka State Key Laboratory of Tibetan Plateau Earth system Environment and Resources (TPESER) Institute of Tibetan Plateau Research Chinese Academy of Sciences University of Chinese Academy of sciences Research Center for urban Safety and Security Kobe University Department of Planetology Graduate School of Science Kobe University

The dependence of the subduction regime on three-dimensional slab geometry poses a challenge for accurately estimating the evolving thermal structure of megathrusts globally. Although slab dips and ages have gained attention, the specific impacts of oblique subduction remain unmeasured. Here, we present an integrated thermal model that quantifies how slab morphology can shape the thermal state of megathrusts, such as those in the Makran Subduction Zone. The model considers both slab obliquity and depth variations along the trench. We find a considerable match between the slab petrological dehydration zone and the distribution of great crustal earthquakes. We suggest that the accumulation of fluids along megathrusts by slab metamorphism can foster more polarized conditions for decreasing plate coupling and increasing interplate ruptures. It is thus imperative to improve model representation and more realistically represent how drivers of slab geometry affect metamorphic transitions and the occurrence of earthquakes at megathrusts.

关键词： thermal regime slab dehydration earthquake 3-D model Makran Subduction Zone

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Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions

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Journal of Environmental sciences 2025年第3期149卷 68-78页

作者： Qiang Zhang Xin Li Long Yu Lingxiao Wang Zhiqing Wen Pengchen Su Zhenli Sun Suhua Wang school of Environmental science and Engineering Guangdong University of Petrochemical TechnologyMaoming 525000China MOE Key Laboratory of Resources and Environmental system Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China

The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient *** this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous *** proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/***,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/*** fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data ***,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model ***,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride *** results demonstrate that the developed model excels in terms of accuracy and *** groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.

关键词： Machine learning Aluminum ion detection Fluorine ion detection Fluorescence probe K-means model

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Optimizing battery deployment: Aging trajectory prediction enabling homogenous performance grouping

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Journal of Energy Chemistry 2025年第1期100卷 565-577页

作者： Shuquan Wang Feng Gao Zhan Ma Hao Tian Yusen Zhang school of Control science and Engineering Shandong UniversityJinan 250061ShandongChina Key Lab of Power system Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061ShandongChina

As battery deployments in electric vehicles and energy storage systems grow, ensuring homogeneous performance across units is crucial. We propose a multi-derivative imaging fusion(MDIF) model, employing advanced imaging and machine learning to predict battery aging trajectories from minimal initial data, thus facilitating effective performance grouping before deployment. Utilizing a derivative strategy and Gramian Angular Difference Field for dimensional enhancement, the MDIF model uncovers subtle predictive features from discharge curve data after only ten cycles. The architecture includes a parallel convolutional neural network with lateral connections to enhance feature integration and *** on a self-developed dataset, the model achieves an average root-mean-square error of 0.047 Ah and an average mean absolute percentage error of 1.60%, demonstrating high precision and *** robustness is further validated through transfer learning on two publicly available datasets, adapting with minimal retraining. This approach significantly reduces the testing cycles required, lowering both time and costs associated with battery testing. By enabling precise battery behavior predictions with limited data, the MDIF model optimizes battery utilization and deployment strategies, enhancing system efficiency and sustainability.

关键词： Lithium-ion battery Battery prognostics Fusion model Convolutional neural network Transfer learning

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