检索结果-南通市图书馆

High-efficiency crystalline carbon nitride photocatalysts:Status and perspectives

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2024年第9期17卷 7840-7863页

作者： Wenji Pu Yunqiao Zhou lingfeng.yang Haifeng Gong Yuhan Li Qingyu yang Dieqing Zhang Engineering Research Center for Waste Oil Recovery Technology and Equipment Ministry of EducationChongqing Key Laboratory of Catalysis and New Environmental MaterialsChongqing Technology and Business UniversityChongqing 400067China The Education Ministry Key Lab of Resource Chemistry Joint International Research Laboratory of Resource Chemistry of Ministry of EducationShanghai Key Laboratory of Rare Earth Functional Materialsand Shanghai Frontiers Science Center of Biomimetic CatalysisShanghai Normal UniversityShanghai 200234China State Key Laboratory of Tibetan Plateau Earth System Resources and EnvironmentInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China

Crystallinity and crystal structure greatly influence the photocatalytic behavior of *** g-C3N4 produced by traditional thermal-induced polycondensation reaction bears low crystallinity and thus poor photoactivity,which originates from the incomplete polymerization of the precursor containing amine groups,abundant hydrogen bonds,and unreacted amino,as well as cyanide functional groups in the *** photocatalytic process,these residual functional groups often work as electron trap sites,which may hinder the transfer of electrons on the plane,resulting in low ***,crystalline carbon nitride(CCN)was reported as a promising photocatalyst because its increased crystallinity not only reduces the number of carriers recombination centers,but also increases charge conductivity and improves light utilization due to extendedπ-conjugated systems and delocalizedπ-*** such,we summarize the recent studies on CCN-based photocatalysts for the photoactivity ***,the unique structure and properties of CCN materials are ***,the preparation methods and modification strategies are well *** also sum up the applications of CCN-based materials in the environmental purification and energy ***,this review concerning CNN materials ends with prospects and challenges in the obtainment of high crystallinity by effective techniques,and the deep understanding of photocatalytic mechanism.

关键词： crystalline carbon nitride preparation method modification strategy photocatalytic application

Efficient optimization of electron transfer pathway by constructing phosphide/ceria interface boosts seawater hydrogen production

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2024年第8期95卷 490-498,I0011页

作者： Yifan Zhao lingfeng.yang Youyu Long Min Xi Anran Chen Hua Zhang School of Materials and Energy Yunnan UniversityKunming 650091YunnanChina Electron Microscopy Centre of Yunnan University Yunnan UniversityKunming 650091YunnanChina

Developing efficient and durable hydrogen evolution reaction(HER)electrocatalysts is one of the most important issues for the commercialization of seawater electrolysis,but it remains ***,we report a CeO_(2)-CoP nanoneedle array catalyst loaded on Ti mesh(CeO_(2)-CoP/TM)with workfunction-induced directional charge transport *** CeO_(2)-CoP/TM catalyst showed superior HER catalytic activity and stability,with over potentials of 41 and 60 mV to attain 10 mA cm^(-2),in 1 M KOH and 1 M KOH+seawater electrolyte,*** results and theoretical calculations reveal that the work function drives the charge transfer from CeO_(2)to CoP,which effectively balances the electronic density of CoP and CeO_(2),optimizes the d-band center,and accelerates the water activation kinetics,thus enhancing the HER *** solar-driven water electrolysis device displays a high and stable solar-to-hydrogen conversion efficiency of 19.6%.This study offers a work function-induced directional charge transport strategy to design efficient and durable catalysts for hydrogen production.

关键词： Work function Heterostructure Charge transport Seawater splitting Solar-to-hydrogen

Diverse responses of fungal functional groups to desertification in forest soils of Pinus densata on the Chinese Tibetan plateau

在线全文

学校读者我要写书评

暂无评论

Journal of Forestry Research 2024年第5期35卷 120-130页

作者： Jiani Hua Jiangbao Zhang Baohan Song Tianyi Wang Jingji Li Nan yang lingfeng Mao Co-Innovation Center for Sustainable Forestry in Southern China Laboratory of Biodiversity and ConservationCollege of Ecology and EnvironmentNanjing Forestry University210037 NanjingPeople’s Republic of China Institute of Ecological Resources and Landscape Architecture Chengdu University of Technology610059 ChengduPeople’s Republic of China

Rapid increase in desertification is an environ-mental concern,especially for the health and sustainabil-ity of ecosystems in changing *** ecosystems respond to such changes may be partially understood by studying interactions and performance of critically impor-tant groups such as soil fungi functional *** study investigated variations in diversities of three soil fungi functional guilds(saprotrophic,symbiotic,pathogenic)and influencing abiotic factors in a Pinus densata forest on the southeast Tibetan Plateau where desertification is *** results indicate desertification significantly decreased the proportion of dominant fungal guild-symbiotic fungi(mean relative abundance decreasing from 97.0%to 68.3%),in contrast to saprotrophic fungi(increasing from 2.7%to 25.7%)and pathogenic(from 0.3%to 5.9%).Soil pH had the most significant impact on fungal community structure and negatively correlated with symbiotic fungal richness,which was significantly lower in arid soils,and positively correlated with saprotrophic and pathogenic fungal alpha-diversity,which were *** community struc-tures and regulators of the three fungi communities were observed,with pH,total phosphorus and ammonium(NH_(4)^(+))as the main *** study links the biotic and abi-otic components during desertification and the interactions between them,and may be used as indicators of ecosystem health and for amendments to mitigate the effects of a chang-ing climate.

关键词： Desertification Fungal diversity Saprotrophs Ectomycorrhizal fungi Climate change

Coordination for a Closed-loop Supply Chain with Recycling Platform Considering Dynamic Setting

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Science and Systems Engineering 2024年第4期33卷 425-451页

作者： Zehua Xiang Ting Ji lingfeng Dong School of Management Zhejiang UniversityHangzhou310058China School of Business Hangzhou City UniversityHangzhou310015China Alibaba Business College Hangzhou Normal UniversityHangzhou311121China

This paper presents a dynamic closed-loop supply chain(CLSC)model,incorporating a manufacturer,a retailer,and an internet recycling platform(IRP),utilizing differential game theory while considering the forgetting effect of *** model encompasses factors such as the quality level of used products and Big Data marketing(BDM),comparing optimal equilibriums under decentralized and cooperative decision *** effectively coordinate the dynamic CLSC at each time point,we propose a revenue-sharing and cost-sharing(RSCS)combined *** addition to ensuring reasonable sharing of revenues and costs,this contract allows the manufacturer to flexibly adjust wholesale prices for final products and transfer prices for used products in order to distribute profits appropriately and achieve Pareto optimality within the CLSC ***,our results indicate that there exists a threshold for Big Data marketing efficiency;high-efficiency BDM not only facilitates increased recycling on Internet platforms but also reduces unit recycling costs for ***,when implementing the combined contract,Big Data marketing efficiency does not impact the transfer price paid by manufacturers to Internet recycling platforms.

关键词： Big Data marketing differential game closed-loop supply chain coordination internet recycling platform

Revolutionizing plasmonic platform via magnetic field-assisted confined ultrafast laser deposition of high-density,uniform,and ultrafine nanoparticle arrays

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Extreme Manufacturing 2024年第3期6卷 428-438页

作者： Jin Xu lingfeng Wang Peilin yang Haoqing Jiang Huai Zheng Licong An Xingtao Liu Gary J Cheng School of Industrial Engineering Purdue UniversityWest LafayetteIN 47906United States of America Institute of Technological Sciences Wuhan UniversityWuhanHubei 430072People’s Republic of China

The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves havegarnered significant ***,the challenge of large-scale manufacturing of uniform,well-aligned,and tunable plasmonic surfaces has hindered their *** address this,we present a groundbreaking tunable plasmonic platform design achieved throughmagnetic field(MF)assisted ultrafast laser direct deposition in *** precise control of metal nanoparticles(NPs),with cobalt(Co)serving as the model material,employing an MF,and fine-tuning ultrafast laser parameters,we have effectively converted coarse and non-uniform NPs into densely packed,uniform,and ultrafine NPs(~3 nm).This revolutionary advancement results in the creation of customizable plasmonic‘hot spots,’which play a pivotal role insurface-enhanced Raman spectroscopy(SERS)*** profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and *** the plasmonic nanostructures resonate with incident light,they generate intense local electromagnetic fields,thus vastly increasing the Raman scattering *** enhancement leads to an outstanding 2–18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10^(-10)***,the plasmonic platform also demonstratesrobustness,retaining its sensing capability even after undergoing 50 cycles of rinsing andre-loading of ***,this work adheres to green manufacturing standards,making it an efficient and environmentally friendly method for customizing plasmonic‘hot spots’inSERS *** study not only achieves the formation of high-density,uniform,and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation betweenplasmonic resonance and energy *** outstanding results observed in SERS sensors further emphasize the immense potential of this technology for energy-relatedapplications,including photocatalysis,ph

关键词： magnetic field manipulation laser deposition metasurface SERS

Machine learning for predicting fatigue properties of additively manufactured materials

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Aeronautics 2024年第4期37卷 1-22页

作者： Min YI Ming XUE Peihong CONG yang SONG Haiyang ZHANG lingfeng WANG Liucheng ZHOU Yinghong LI Wanlin GUO State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China Institute for Frontier Science Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Shenyang Engine Research Institute Shenyang 110015China Liaoning Key Laboratory of Impact Dynamics on Aero Engine Shenyang 110015China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China

Fatigue properties of materials by Additive Manufacturing(AM) depend on many factors such as AM processing parameter, microstructure, residual stress, surface roughness, porosities, post-treatments, etc. Their evaluation inevitably requires these factors combined as many as possible, thus resulting in low efficiency and high cost. In recent years, their assessment by leveraging the power of Machine Learning(ML) has gained increasing attentions. A comprehensive overview on the state-of-the-art progress of applying ML strategies to predict fatigue properties of AM materials, as well as their dependence on AM processing and post-processing parameters such as laser power, scanning speed, layer height, hatch distance, built direction, post-heat temperature,etc., were presented. A few attempts in employing Feedforward Neural Network(FNN), Convolutional Neural Network(CNN), Adaptive Network-Based Fuzzy Inference System(ANFIS), Support Vector Machine(SVM) and Random Forest(RF) to predict fatigue life and RF to predict fatigue crack growth rate are summarized. The ML models for predicting AM materials' fatigue properties are found intrinsically similar to the commonly used ones, but are modified to involve AM features. Finally, an outlook for challenges(i.e., small dataset, multifarious features,overfitting, low interpretability, and unable extension from AM material data to structure life) and potential solutions for the ML prediction of AM materials' fatigue properties is provided.

关键词： Additive manufacturing Machine learning Fatigue life Fatigue crack growth rate Prediction

A unified pre-training and adaptation framework for combinatorial optimization on graphs

在线全文

学校读者我要写书评

暂无评论

Science China Mathematics 2024年第6期67卷 1439-1456页

作者： Ruibin Zeng Minglong Lei lingfeng Niu Lan Cheng School of Computer Science and Technology University of Chinese Academy of SciencesBeijing100049China Faculty of Information Technology Beijing University of TechnologyBeijing100124China School of Economics and Management University of Chinese Academy of SciencesBeijing100190China School of Mathematics and Statistics Central South UniversityChangsha410075China

Combinatorial optimization(CO)on graphs is a classic topic that has been extensively studied across many scientific and industrial ***,solving CO problems on graphs through learning methods has attracted great *** deep learning methods,e.g.,graph neural networks(GNNs),have been used to effectively assist the process of solving ***,current frameworks based on GNNs are mainly designed for certain CO problems,thereby failing to consider their transferable and generalizable abilities among different COs on ***,simply using original graphs to model COs only captures the direct correlations among objects,which does not consider the mathematical logicality and properties of *** this paper,we propose a unified pre-training and adaptation framework for COs on graphs with the help of the maximum satisfiability(Max-SAT)*** first use Max-SAT to bridge different COs on graphs since they can be converted to Max-SAT problems represented by standard formulas and clauses with logical *** we further design a pre-training and domain adaptation framework to extract the transferable and generalizable features so that different COs can benefit from *** the pre-training stage,Max-SAT instances are generated to initialize the parameters of the *** the fine-tuning stage,instances from CO and Max-SAT problems are used for adaptation so that the transferable ability can be further *** experiments on several datasets show that features extracted by our framework exhibit superior transferability and Max-SAT can boost the ability to solve COs on graphs.

关键词： combinatorial optimization graph neural networks domain adaptation maximum satisfiability problem

Heterogeneous bimetallic oxides/phosphides nanorod with upshifted d band center for efficient overall water splitting

在线全文

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2024年第9期35卷 414-420页

作者： Ji Chen Yifan Zhao Shuwen Zhao Hua Zhang Youyu Long lingfeng.yang Min Xi Zitao Ni Yao Zhou Anran Chen School of Materials and Energy Yunnan UniversityKunming 650091China School of Engineering The University of EdinburghSouth BridgeEdinburgh EH89YLUnited Kingdom Electron Microscopy Center Yunnan UniversityKunming 650091China School of Internet of Things Engineering Jiangnan UniversityWuxi 214122China

Electrocatalytic water splitting is the most directly available route to generate renewable and sustainable ***,we report the design of a composite material in which arrays of square pillar-like NiMoO4nanorods coated with N,P-doped carbon layers are uniformly contained in numerous nested nanoparticle *** catalysts have superior catalytic activity,requiring only 59 mV and 187 mV for HER and OER to attain a current density of 10 mA/cm^(2),*** assembled two-electrode electrolytic cell required a voltage of 1.48 V to reach 10 mA/cm^(2),along with excellent long-term *** calculations reveal that electrons aggregate and redistribute at the heterogeneous interface,with the d-band centers of the Ni and Fe atoms being positively shifted compared to the Fermi level,effectively optimizing the adsorption of intermediates and reducing the Gibbs free energy,thus accelerating the catalytic ***,an integrated solar-driven water-splitting system demonstrated a high and stable solar-to-hydrogen efficiency of 18.20%.This work provides new possibilities for developing non-precious metal-based bifunctional electrocatalysts for large-scale water splitting applications.

关键词： Hydrogen evolution reaction Bimetallic oxides Bimetallic phosphides Overall water splitting Solar-to-hydrogen efficiency

Enhancing cut selection through reinforcement learning

在线全文

学校读者我要写书评

暂无评论

Science China Mathematics 2024年第6期67卷 1377-1394页

作者： Shengchao Wang Liang Chen lingfeng Niu Yu-Hong Dai Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China Research Center on Fictitious Economy and Data Science Chinese Academy of SciencesBeijing100190China

With the rapid development of artificial intelligence in recent years,applying various learning techniques to solve mixed-integer linear programming(MILP)problems has emerged as a burgeoning research *** from constructing end-to-end models directly,integrating learning approaches with some modules in the traditional methods for solving MILPs is also a promising *** cutting plane method is one of the fundamental algorithms used in modern MILP solvers,and the selection of appropriate cuts from the candidate cuts subset is crucial for enhancing *** to the reliance on expert knowledge and problem-specific heuristics,classical cut selection methods are not always transferable and often limit the scalability and generalizability of the cutting plane *** provide a more efficient and generalizable strategy,we propose a reinforcement learning(RL)framework to enhance cut selection in the solving process of ***,we design feature vectors to incorporate the inherent properties of MILP and computational information from the solver and represent MILP instances as bipartite ***,we choose the weighted metrics to approximate the proximity of feasible solutions to the convex hull and utilize the learning method to determine the weights assigned to each ***,a graph convolutional neural network is adopted with a self-attention mechanism to predict the value of weighting ***,we transform the cut selection process into a Markov decision process and utilize RL method to train the *** experiments are conducted based on a leading open-source MILP solver *** on both general and specific datasets validate the effectiveness and efficiency of our proposed approach.

关键词： reinforcement learning mixed-integer linear programming cutting plane method cut selection