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Alkaline molten salt thermal treatment of mixed waste plastics for oil production: Insight into the effects of molten salt alkalinity and plastic molecular structure

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Fuel 2025年 399卷

作者： Ren, Yang Dai, Qiqi He, Jing Hu, Hongyun Li, Xian Li, Aijun Zhang, Changbin Yao, Hong State Key Laboratory of Coal Combustion School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan430074 China Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen518000 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China

Pyrolysis has emerged as the primary strategy for recycling waste plastics into oil. However, the low thermal conductivity of plastics results in inefficient heat transfer and extended residence times, which is unfavorable for oil production. Here, a novel method by using thermally stable alkaline molten salt as an effective medium to enhance heat transfer and thermal reaction was proposed. The oil yield exhibited a direct correlation with molten salt alkalinity. NaOH-Na2CO3 system achieved remarkable gas upgrading: >99 % chlorine immobilization coupled with alkali-mediated hydrogen enrichment (H2 ratio > 80 %), enabled by catalytic carbon-alkali interactions. Plastic molecular structures governed product selectivity during molten salt thermal treatment: polyolefins (PE/PP) predominantly yielded α-olefins through promoting β-scission reactions, while polyvinyl chloride (PVC) and polystyrene decomposition generated aromatic hydrocarbons (BTX, styrene) via enhancing dehydrochlorination and aromatization. In co-processing of mixed plastics, weak interactions existed between PE and PP during both conventional and molten salt conversions, with product distributions resembling linear combinations of individual pyrolysis results. PVC-PS blends exhibited significant cross-reactivity: HCl evolved from PVC decomposition engaged in secondary reactions with styrene (PS product). Primary radicals on PS chains post-scission drove depolymerization pathways, elevating ethylbenzene/α-methylstyrene formation at the expense of styrene monomers. Molten salt reduced PVC-PS cross-reactivity via chlorine capture and H-radical redistribution, increasing styrene monomer yields by 142 %. These findings facilitate the high-value recycling of mixed waste plastics for oil production. © 2025 Elsevier Ltd

关键词： Isomers

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A General Framework for Chinese Domain Knowledge Graph Question Answering Based on TransE 3

A General Framework for Chinese Domain Knowledge Graph Quest...

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2020 3rd International Conference on Computer Information science and Artificial Intelligence, CISAI 2020

作者： Pei, Zhongmin Zhang, Jie Xiong, Wei Li, Li Luo, Zhangkai Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China Gaojing Network Management and Security Center Beijing China

This paper introduces a general question answering (QA) framework for Chinese domain knowledge graphs to serve various industries. The question is analyzed by shielding invalid characters in this framework, and the TransE calculation of entities and relations is used to search answer, rather than traditional logical queries that rely heavily on predefined rules. In this way, the QA framework can be easily applied to different fields with little manual participation, and reduce the migration cost caused by the lack of scalability of the existing QA systems, which are designed only for specific domains. Then, the proposed framework is operated on the space launch knowledge graph and has achieved HITS@1, HITS@3, HITS@5 scores of 60.60%, 80.87%, 85.61% separately, which is competitive with other restricted domain knowledge graphs. In addition, numerical results on the knowledge graph of the Three Kingdoms and the COVID-19-Character verified the scalability of the QA framework. © Published under licence by IOP Publishing Ltd.

关键词： Knowledge graph

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Association of PM_(2.5)Reduction with Improved Kidney Function:A Nationwide Quasiexperiment among Chinese Adults

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Health Data science 2022年第1期2022卷 115-123页

作者： Yiqun Han Tao Xue Frank J.Kelly Yixuan Zheng Yao Yao Jiajianghui Li Jiwei Li Chun Fan Pengfei Li Tong Zhu Environmental Research Group MRC Centre for Environment and HealthImperial College LondonLondonUK BIC-ESAT and SKL-ESPC College of Environmental Sciences and EngineeringCenter for Environment and HealthPeking UniversityBeijing 100871China Institute of Reproductive and Child Health/Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijingChina Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental Planning100012 BeijingChina China Center for Health Development Studies Peking UniversityBeijingChina College of Computer Science and Technology Zhejiang UniversityHangzhouChina Computer Center Peking University and Peng Cheng LaboratoryChina Advanced Institute of Information Technology Peking UniversityChina

*** evidence from human studies has revealed the adverse impact of ambient fine particles(PM_(2.5))on health outcomes related to metabolic disorders and distant *** exposure to ambient PM_(2.5)leads to kidney impairment remains *** rapid air quality improvement driven by the clean air actions in China since 2013 provides an opportunity for a quasiexperiment to investigate the beneficial effect of PM_(2.5)reduction on kidney *** on two repeated nationwide surveys of the same population of 5115 adults in 2011 and 2015,we conducted a difference-indifference *** in long-term exposure to ambient PM_(2.5)were associated with changes in kidney function biomarkers,including estimated glomerular filtration rate by serum creatinine(GFRscr)or cystatin C(GFRcys),blood urea nitrogen(BUN),and uric acid(UA).*** a 10μg/m^(3)reduction in PM_(2.5),a significant improvement was observed for multiple kidney functional biomarkers,including GFRscr,BUN and UA,with a change of 0.42(95%confidence interval[CI]:0.06,0.78)mL/min/1.73m^(2),-0.38(-0.64,-0.12)mg/dL,and-0.06(-0.12,-0.00)mg/dL,respectively.A lower socioeconomic status,indicated by rural residence or low educational level,enhanced the adverse effect of PM_(2.5)on kidney *** results support a significant nephrotoxicity of PM_(2.5)based on multiple serum biomarkers and indicate a beneficial effect of improved air quality on kidney function.

关键词： Kidney organs ambient

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Semantic segmentation of track image based on deep neural network

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The Journal of China Universities of Posts and Telecommunications 2020年第5期27卷 23-33页

作者： Wang Zhaoying Zhou Junhua Liao Zhonghua Zhai Xiang Zhang Lianping School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Complex Product Advanced Manufacturing Kngineering Research Center Beijing Simulation CenterBeijing 100854China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China Alibaba Cloud Computing Beijing 100020China

In this paper,deep learning technology was utilited to solve the railway track recognition in intrusion detection *** railway track recognition can be viewed as semantic segmentation task which extends image processing to pixel level *** encoder-decoder architecture DeepLabv3+model was applied in this work due to its good performance in semantic segmentation *** images of the railway track collected from the video surveillance of the train cab were used as experiment dataset in this work,the following improvements were made to the *** first aspect deals with over-fitting problem due to the limited amount of training *** augmentation and transfer learning are applied consequently to rich the diversity of data and enhance model robustness during the training ***,different gradient descent methods are compared to obtain the optimal optimizer for training model *** third problem relates to data sample imbalance,cross entropy(CE)loss is replaced by focal loss(FL)to address the issue of serious imbalance between positive and negative *** of the improved DeepLabv3+model with above solutions is demonstrated by experiment results with different system parameters.

关键词： railway track recognition convolutional neural networks semantic segmentation DeepLabv3+

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Multiple Algorithms Against Multiple Hardware Architectures: Data-Driven Exploration on Deep Convolution Neural Network 16th

Multiple Algorithms Against Multiple Hardware Architectures:...

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16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019

作者： Xu, Chongyang Luan, Zhongzhi Gao, Lan Wang, Rui Zhang, Han Zhang, Lianyi Liu, Yi Qian, Depei Beihang University Beijing China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9783030307080

With the rapid development of deep learning (DL), various convolution neural network (CNN) models have been developed. Moreover, to execute different DL workloads efficiently, many accelerators have been proposed. To guide the design of both CNN models and hardware architectures for a high-performance inference system, we choose five types of CNN models and test them on six processors and measure three metrics. With our experiments, we get two observations and conduct two insights for the design of CNN algorithms and hardware architectures. © 2019, IFIP International Federation for Information Processing.

关键词： Neural network models

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High nitrogen fertilizer input enhanced the microbial network complexity in the paddy soil

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Soil Ecology Letters 2024年第2期6卷 97-109页

作者： Yanan Chen Yan Li Tianyi Qiu Haoran He Ji Liu Chengjiao Duan Yongxing Cui Min Huang Chunyan Wu Linchuan Fang The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of EducationYangling712100China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water Conservation CAS and MWRYangling712100China University of Chinese Academy of Sciences Beijing100049China Institute of Environment Resource and Soil Fertilizer Zhejiang Academy of Agricultural SciencesHangzhou310021China College of Natural Resources and Environment Northwest A&F UniversityYangling712100China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhan430079China Department of Ecohydrology Leibniz Institute of Freshwater Ecology and Inland FisheriesBerlin12587Germany Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing100871China College of Resources and Environmental Engineering Wuhan University of TechnologyWuhan430070China CAS Center for Excellence in Quaternary Science and Global Change Xi’an710061China

N fertilizer altered bacterial community compositions by changing soil nutrients.•Bacterial ammonia oxidation became predominated with the increasing N rate.•Excessive N input caused the information of a more complex microbial network.•Intensified microbial competition by excessive N was due to negative link ***(N)fertilization drives the structure and function of soil microbial communities,which are crucial for regulating soil biogeochemical cycling and maintaining ecosystem *** the N fertilizer effects on soil microbial composition and diversity have been widely investigated,it is generally overlooked that ecosystem processes are carried out via complex associations among microbiome ***,we examined the effects of five N fertilization levels(0,135,180,225,and 360 kg N ha−1)on microbial co-occurrence networks and key functional taxa such as ammonia-oxidizers in paddy *** results showed that N addition altered microbial community composition,which were positively related to soil total N and available phosphorus(P)*** abundance of ammonia-oxidizing archaea(AOA)significantly decreased after N addition,whereas ammonia-oxidizing bacteria(AOB)increased in N360 *** with low-N group(N0 and N135),the high-N group(N225 and N360)shaped more complex microbial webs and thus improved the stability of the microbial *** least squares path modeling further revealed that N fertilizer had a higher effect on microbial network complexity in the high-N group(0.83)than the low-N group(0.49).Although there were more positive links across all microbial networks,the proportion of negative links significantly increased in the high-N network,suggesting that excess N addition aggravated the competition among microbial *** these interactions between microbial communities and N fertilization advances our understanding of biogeochemical processes in paddy soils and their effects on nutrient supply to

关键词： nitrogen fertilizer paddy soil co-occurrence network microbial interaction

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Integrating NLP and Ontology Matching into a Unified system for Automated Information Extraction from Geological Hazard Reports

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Journal of Earth science 2023年第5期34卷 1433-1446页

作者： Qinjun Qiu Zhen Huang Dexin Xu Kai Ma Liufeng Tao Run Wang Jianguo Chen Zhong Xie Yongsheng Pan Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of GeosciencesWuhan 430074China Beijing Key Laboratory of Urban Spatial Information Engineering Beijing 100045China School of Geography and Information Engineering China University of GeosciencesWuhan 430074China Wuhan Geomatics Institute Wuhan 430074China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China Geological Environmental Center of Hubei Province Wuhan 430034China Faculty of Earth Resources China University of GeosciencesWuhan 430074China State Key Laboratory of Geological Processes and Mineral Resources China University of GeosciencesWuhan 430078China Wuhan Zondy Cyber Science&Technology Co. Ltd.Wuhan 430074China

Many detailed data on past geological hazard events are buried in geological hazard reports and have not been fully utilized. The growing developments in geographic information retrieval and temporal information retrieval offer opportunities to analyse this wealth of data to mine the spatiotemporal evolution of geological disaster occurrence and enhance risk decision making. This study presents a combined NLP and ontology matching information extraction framework for automatically recognizing semantic and spatiotemporal information from geological hazard reports. This framework mainly extracts unstructured information from geological disaster reports through named entity recognition, ontology matching and gazetteer matching to identify and annotate elements, thus enabling users to quickly obtain key information and understand the general content of disaster reports. In addition, we present the final results obtained from the experiments through a reasonable visualization and analyse the visual results. The extraction and retrieval of semantic information related to the dynamics of geohazard events are performed from both natural and human perspectives to provide information on the progress of events.

关键词： geological hazard report spatiotemporal information geological hazard ontology natural language processing gazetteers onlology machine learning

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Characterizing ammonia emission from light-duty gasoline vehicles under the influence of multiple factors and its correlation with conventional pollutants

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science of the Total Environment 2024年 945卷 173967页

作者： Jiang, Han Zhao, Haiguang Lai, Yitu Kang, Yu Cao, Yang Fu, Mingliang Ding, Yan State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation Chinese Research Academy of Environmental Sciences Beijing100012 China Vehicle Emission Control Center of Ministry of Ecology and Environment Chinese Research Academy of Environmental Sciences Beijing100012 China Xiamen Environment Protection Vehicle Emission Control Technology Center Xiamen361023 China Department of Automation University of Science and Technology of China Hefei230026 China

Ammonia (NH3), which is a precursor of secondary particulate matter (PM), can be produced through three-way catalyst (TWC) side reactions in light-duty gasoline vehicles (LDGVs), posing a threat to human health and air quality. To explore ammonia emission characteristics, 8 LDGVs and 1 hybrid electric light-duty vehicle (HEV) with various mileages traveled were analyzed with a chassis dynamometer system during regulation driving cycles. The emission factors of the adopted China VI in-use LDGVs were 7.04 ± 2.61 mg/km under cold-start conditions and 4.94 ± 1.69 mg/km under hot-start conditions. With increasing mileage traveled, the total ammonia emissions increased, and the difference between the cold/hot-start results decreased. The emissions of in-use LDGVs with bi-fuel engines were analyzed, and more ammonia was generated in the compressed natural gas (CNG) mode through the hydrocarbon (HC) reforming reaction. The relationship between the emissions of ammonia and conventional pollutants was established. During the initial cold-start phase, a delay in ammonia formation was observed, and the ammonia emissions conformed with the CO and HC emissions after exhaust heating. Vehicle specific power (VSP) analysis revealed that the interval of highest ammonia emissions corresponded to acceleration events at high speeds. For the HEV, the transition from motor to engine drive conditions contributed to ammonia emission occurrence because of the more pronounced cold-start events. The use of HEV technology could introduce additional uncertainties in controlling urban ammonia emissions. Detailed analysis of emission characteristics could provide data support for future research on ammonia emission standards and control strategies for LDGVs. © 2024 Elsevier B.V.

关键词： Health risks

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The Mechanism of a Submerged Aquatic Plant to Micro-Nano Plastics Stress in Ecological Constructed Wetland

SSRN

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SSRN 2023年

作者： Zhang, Siyu Yuan, Run Han, Lurui Peng, Jianfeng Liu, Ruiping Liu, Huijuan Qu, Jiuhui Tsinghua University China Center for Water and Ecology State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China Key Laboratory of Drinking Water Science and Technology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China

Wetlands are the most self-purifying ecosystems in nature and are known as the kidneys of the Earth. The widespread use of plastic products has led to the storage of large amounts of microplastics that can negatively affect wetland plants. This of great concern owing to their refractory degradation and widespread presence in various environmental media. Current research focused on the effects of microplastic concentration gradients and ignored the potential effects of particle size differences. This study investigated the physiological responses of Vallisneria natans (V. natans) to polyethylene microplastics (PE-MPs) of different sizes. The uptake of nitrogenous substances by V. natans did not significantly differ among PE-MPs of different sizes. V. natans had increased chlorophyll content following short-term exposure to 50 nm and 500 nm polyethylene that disappeared after 28d of continuous exposure. The leaf antioxidant defense system is activated by PE-MP pollution stress, and oxidative stress becomes more pronounced as the particle size decreases. Moreover, PE-MPs caused changes in the dominant microbial communities and increased metabolic activities related to amino acid transport, energy metabolism, and signaling. This study provides a theoretical reference to utilize submerged plants in wetland restoration. © 2023, The Authors. All rights reserved.

关键词： Microplastic

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Applications of MXenes in human-like sensors and actuators

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Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina

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