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Solar-driven photothermal catalytic co. co.version:a review

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Rare Metals 2024年第7期43卷 2913-2939页

作者： Bachirou Guene Lougou Bo-Xi Geng Ru-Ming Pan Wei Wang Tian-Tian Yan Fang-Hua Li Hao Zhang Oraléou Sangué Djandja Yong Shuai Meisam Tabatabaei Daniel Sabi Takou School of Energy Science and Engineering Harbin Institute of Technology MIIT Key Laboratory of Critical Materials Technology for New Energy co.version and Storage Harbin Institute of Technology State Key Laboratory of Urban Water Resource and Environment Harbin Institute of Technology School of Electrical Engineering and Automation Harbin Institute of Technology Guangdong Provincial Key Laboratory of Distributed Energy Systems Engineering Research Center of None-Food Biomass Efficient Pyrolysis and Utilization Technology of Guangdong Higher Education InstitutesDongguan University of Technology Higher Institution Centre of Excellence (HIco.) Institute of Tropical Aquaculture and Fisheries (AKUATROP)Universiti Malaysia Terengganu Department of Biomaterials Saveetha Dental CollegeSaveetha Institute of Medical and Technical Sciences éco.e Polytechnique d'Abomey-Calavi University of Abomey-Calavi

It is highly desirable to seek green and sustainable technologies,such as employing photo thermal effects to drive energy catalysis processes to address the high energy demand and associated environmental impacts induced by the current *** photothermocatalysis process is an emerging research area with great potential in efficiently co.verting solar energy through various catalytic ***,achieving simultaneously high co.version efficiency,cyclability,and durability is still a daunting ***,tremendous work is still needed to enhance solar photo thermal catalytic co.version and promote its large-scale *** review developed the principles of co.pling solar photon and thermal fields underlying the photothermal effect,exploration of efficient nanocatalysts,development of optofluidic reactor model,and photo thermal synergistic-driven co.reduction *** ultimate goal was to provide an effective approach that can effectively co.vert solar energy into photocarriers/hot-electrons and heat,and importantly,can co.ple them to regulate catalysis reaction pathways toward the production of value-added fuel and chemical energy.

关键词： Photochemistry Photothermal co 2 catalytic co.version Nanomaterial Solar fuels and chemicals

Application of CPS Under the Background of Intelligent co.struction

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Journal of World Architecture 2022年第4期6卷 22-33页

作者： XiaoXu Zheng MO DIAN GO Intelligent Technology(dongguan)co. Ltd.Dongguan 523000Guangdong ProvinceChina

The advent of the fourth industrial revolution(Industry 4.0)has brought about new opportunities for the intelligent transformation and upgrading of the co.struction industry to achieve high-quality and sustainable *** the basis of analyzing the background of the industry and the development status of the co.responding technologies used in intelligent co.struction,the application of cyber-physical system(CPS)is *** CPS intelligent co.struction platform is created in response to the demands of the co.struction industry’s current growth to provide digital *** drawbacks and challenges in the current co.struction development process have aided in the industry’s transformation and upgrading.

关键词： CPS Digital twin Cyber-physical system Smart building

Advances in 3D printing scaffolds for peripheral nerve and spinal co.d injury repair

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International Journal of Extreme Manufacturing 2023年第3期5卷 264-300页

作者： Juqing Song Baiheng Lv Wenco.g Chen Peng Ding Yong He School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808People’s Republic of China China Nuclear Power Technology Research Institute co. LtdShenzhen 518000People’sRepublicof China School of Mechanical Engineering Zhejiang UniversityHangzhou310058People’s Republic of China

Because of the co.plex nerve anatomy and limited regeneration ability of natural tissue,the current treatment effect for long-distance peripheral nerve regeneration and spinal co.d injury(SCI)repair is not *** an alternative method,tissue engineering is a promising method to regenerate peripheral nerve and spinal co.d,and can provide structures and functions similar to natural tissues through scaffold materials and seed ***,the rapid development of 3D printing technology enables researchers to create novel 3D co.structs with sophisticated structures and diverse functions to achieve high bionics of structures and *** this review,we first outlined the anatomy of peripheral nerve and spinal co.d,as well as the current treatment strategies for the peripheral nerve injury and SCI in *** that,the design co.siderations of peripheral nerve and spinal co.d tissue engineering were discussed,and various 3D printing technologies applicable to neural tissue engineering were elaborated,including inkjet,extrusion-based,stereolithography,projection-based,and emerging printing ***,we focused on the application of 3D printing technology in peripheral nerve regeneration and spinal co.d repair,as well as the challenges and prospects in this research field.

关键词： peripheral nerve regeneration spinal co.d repair 3D printing co.struct bionic structure bionic function

TOF–SIMS surface analysis of chemical co.ponents of size–fractioned urban aerosols in a typical heavy air pollution event in Beijing

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Journal of Environmental Sciences 2018年第7期30卷 61-76页

作者： Wenjun Li Hong Li Jinjuan Li Xueli Cheng Zhengzheng Zhang Fahe Chai Hao Zhang Ting Yang Pengli Duan Defeng Lu Yizhen Chen co.lege of Resource and Environmental Engineering Guizhou University Guiyang 550025 China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing 100012 China co.laborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science andTechnology Nanjing 210044 China sae Technology development (dongguan) co. Ltd. Guangdong 523087 China Environment Research Institute Shandong University Jinan 250100 China co.lege of Earth Sciences Jilin University Changchun 130061 China Institute of Environment Science Shanxi University Shanxi 030001 China co.e Tech Integrated (Beijing) Pty. Ltd. Beijing 100086 China

Size–fractioned atmospheric aerosol particles were co.lected during a typical heavy air pollution event in Beijing. The organic and inorganic co.ponents on the surfaces of the samples were analyzed using time–of–flight seco.dary ion mass spectrometry（TOF–SIMS）.The variation characteristics of the surface chemical co.position and influencing factors were studied, and the possible sources of these chemical co.positions were identified through principal co.ponent analysis. The results showed that inorganic co.ponents such as crustal elements and sulfate, and organic co.ponents such as aliphatic hydrocarbons and oxygen–co.taining organic groups were present. Some surface co.ponents, such as polycyclic aromatic hydrocarbons, heavy metals and fluorides may exert adverse effects on human health. The species and relative percentages of the chemical co.ponents varied with particle size, diurnal and pollution progress. During a heavy pollution event, the species and relative percentages of seco.dary co.ponents such as oxygen–co.taining organic groups and sulfurous co.pounds increased, indicating that particles aged during this event. The surface chemical co.position of the aerosol particles was affected mainly by emissions from co.l co.bustion and motor vehicles. In addition, air pollution, meteorological factors, and air mass transport also exerted a significant effect on the surface chemical co.position of aerosol particles.

关键词： Atmospheric aerosol particles Air pollution event Surface chemical co.position Influence factor Static Time-of-flight seco.dary ion mass spectrometry Beijing

A Distributed Framework for Large-scale Protein-protein Interaction Data Analysis and Prediction Using MapReduce

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 160-172页

作者： Lun Hu Shicheng Yang Xin Luo Huaqiang Yuan Khaled Sedraoui MengChu Zhou School of co.puter Science and Technology Dongguan University of TechnologyDongguan 523808China School of co.puter Science and Technology Wuhan University of TechnologyWuhan 430070China Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent ComputingChongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of SciencesUrumqi 830000China Center of Research Excellence in Renewable Energy and Power Systems and the Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Electrical and co.puter Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA

Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them *** address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,co.ex,using *** do so,an in-depth analysis of its limitations is co.ducted from the perspectives of efficiency and memory co.sumption when applying it for large-scale PPI data analysis and *** solutions are then devised to overco.e these *** particular,we adopt a novel tree-based data structure to reduce the heavy memory co.sumption caused by the huge sequence information of *** that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been co.ducted to evaluate the performance of our framework in terms of both efficiency and *** results well demonstrate that the proposed framework can co.siderably improve its co.putational efficiency by more than two orders of magnitude while retaining the same high accuracy.

关键词： Distributed co.puting large-scale prediction machine learning MapReduce protein-protein interaction(PPI)