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Recent developments of nanomaterials-based conductive type methane sensors

Rare Metals 2021年第6期40卷 1515-1527页

作者： Ming-Zhi Jiao Xiao-Yu Chen Ke-Xiang Hu De-Yu Qian Xiao-Hu Zhao En-Jie Ding Research Center for Internet of Things State and Local Joint Engineering Laboratory of Perception MineChina University of Mining and TechnologyXuzhou 221008China Jiangsu Key Laboratory of Fire Safety in Urban Underground Space China University of Mining and TechnologyXuzhou 221008China School of Mines China University of Mining and TechnologyXuzhou 221116China

Methane is an explosive gas in coalmines and needs to be monitored by methane *** methane sensors are small,simple and stable,and they are very promising for mining safety or home safety *** can even be employed in mining internet of things if the power consumption can be lowered down to few *** researches of nanomaterialsbased conductive-type methane sensors have been reported *** review intends to present a comprehensive and critical summary on the recent progresses in the nanomaterials-based conductive-type methane sensors *** excellent methane-sensitive nanomaterials will be present,such as SnO2,ZnO,TiO2,WO3,carbon nanotubes,graphene,rare earth metal-based perovskite oxides and their *** attention is given to the synthetic methods of the nanomaterials,sensing mechanisms of the nanomaterials and the relationship between the sensing performance and the structures and components of the ***,the future trends and perspectives of nanomaterials-based conductive-type methane sensors are proposed.

关键词： Nanomaterials Methane sensors Conductive gas sensors Sensing mechanism

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Environmental risk assessment of industrial byproduct gypsum utilized for flling abandoned mines

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International Journal of Coal Science & technology 2022年第4期9卷 214-225页

作者： XueHong Du Xiangdong Li Qiyan Feng Lei Meng Yue Sun School of Environment Science and Spatial Informatics China University of Mining and TechnologyXuzhou 221116China The National and Local Joint Engineering Laboratory of Internet Application Technology On Mine China University of Mining and TechnologyXuzhou 221008Jiangsu ProvinceChina IoT Perception Mine Research Center China University of Mining and TechnologyXuzhou 221008Jiangsu ProvinceChina Jiangsu Vocational Institute of Architectural Technology No.26 Xueyuan RoadXuzhou 221433China

In response to the basic policy of green and low-carbon circular development to solve resource,environmental and ecological problems,gypsum is considered to be a flling material for mine *** explore the potential risks of gypsum to the groundwater environment due to the backflling of abandoned mines,a sequential batch leaching experiment was carried out in this paper,which used three types of industrial waste gypsum,namely,phosphorus gypsum(PG),titanium gypsum(TG)and fue gas desulfurization gypsum(FGDG).COMSOL Multiphysics 5.4 software was used to simulate and solve the migration process of the leached metal elements in the mine foor when these three gypsum types were used as flling materials to observe the concentration distributions and difusion distances of the metal elements from these three gypsum types in the mine *** results show that(1)during repeated contact of the three types of industrial waste gypsum with the leaching medium,the pH levels changed,and the changes in pH afected the leaching patterns for the heavy metal elements in the gypsum.(2)Based on the concentrations of the metal elements that were leached from the three types of gypsum,it can be determined that these three types of gypsum are not classifed as hazardous solid wastes,but they cannot be ruled out with regard to their risk to the groundwater environment when they are used as mine flling materials.(3)When the three types of gypsum are used as flling materials,the concentration distributions of the metal elements and their migration distances all exhibit signifcant changes over *** concentration distributions,difusion rates and migration distances of the metal elements from the diferent gypsum types are afected by their initial concentrations in the *** maximum migration distances of Zn in the foor from the PG,FGDG and TG are 8.2,8.1 and 7.5 m,respectively.

关键词： Industrial solid waste gypsum Coal mine back-flling Leaching of metal elements Patterns of migration

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Wide-Angle Ultra-Broadband Metamaterial Absorber with Polarization-Insensitive Characteristics

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Chinese Physics Letters 2021年第2期38卷 102-105页

作者： Peng Chen Xianglin Kong Jianfei Han Weihua Wang Kui Han Hongyu Ma Lei Zhao Xiaopeng Shen School of Materials Science and Physics China University of Mining and TechnologyXuzhou 221116China National and Local Joint Engineering Laboratory of Internet Application Technology on Mine China University of Mining and TechnologyXuzhou 221116China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

An ultra-wideband metamaterial absorber is developed,which is polarized-insensitive and *** layers of square resistive films comprise the proposed *** optimal values of geometric parameters are obtained,such that the designed absorber can achieve an ultra-broadband absorption response from 4.73 to 39.04 GHz(relative bandwidth of 156.7%)for both transverse electricity and transverse magnetic ***,impedance matching theory and an equivalent circuit model are utilized for the absorption mechanism *** compatibility of equivalent circuit calculation results,together with both full-wave simulation and experimental results,demonstrates the excellent performance and applicability of the proposed metamaterial absorber.

关键词： absorber transverse absorption

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Repeated Proof of Single Work Consensus Algorithm Based on Behavior Values

Repeated Proof of Single Work Consensus Algorithm Based on B...

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IEEE Information technology and Mechatronics engineering Conference (ITOEC)

作者： XiaoHu Zhao Tao Zhou Yue Wang College of Information and Control Engineering China University of Mining and Technology Jiangsu China National Local Joint Engineering Laboratory of Mining Internet Application Technology Jiangsu China

The proof-of-work consensus algorithm (PoW) ensures security by exhaustive search for difficulty values that meet the requirements, but there are problems such as waste of resources and slow block output speed. To address the above problems, the repeated proof of single work consensus algorithm (RPoSW) based on behavior values is proposed. Specifically, in the mining phase, the behavioral value is introduced based on the mechanism of dynamically adjusting the difficulty of mining, and the work of single mining determines the attribution of two rounds of bookkeeping rights. Reusing computing power in the mining process can reduce the consumption of resources, and introducing behavioral values can avoid relying solely on node computing power when selecting bookkeeping nodes. In the verification phase, the authoritative nodes with the top ranking in the behavior value list are selected to participate, which ensures the credibility of the verification environment and reduces the verification time. In addition, the reward and punishment mechanism of economy and reputation(RPoER) is proposed, which can increase the cost of nodes committing malicious behaviors. Through theoretical and experimental analysis, RPoSW can resist nodes from committing malicious behaviors and ensure system security while greatly saving arithmetic power.

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Energy evolution and water immersion‑induced weakening in sandstone roof of coal mines

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International Journal of Coal Science & technology 2022年第4期9卷 93-106页

作者： Wenjie Liu Ke Yang Shuai Zhang Zhainan Zhang Rijie Xu State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and TechnologyHuainan 232001China Hefei Comprehensive National Science Center Institute of EnergyHefei 230031AnhuiChina National and Local Joint Engineering Research Center of Precision Coal Mining Anhui University of Science and TechnologyHuainan 232001AnhuiChina Key Laboratory of Mining Coal Safety and Efciently Constructed By Anhui Province and Ministry of Education Anhui University of Science and TechnologyHuainan 232001China State Key Laboratory of Coal Resources and Safe Mining China University of Mining and TechnologyXuzhou 221116JiangsuChina

The instability of underground spaces in abandoned coal mines with water-immersed rocks is one of the main hazards hindering the geothermal energy use and ecological restoration of post-mining *** study conducted graded cyclic loading–unloading tests of fve groups of sandstone samples with diferent water *** evolution of input,elastic,dissipated,damping,and plastic energies were explored,considering the damping *** normalized plastic energy serves to characterize the damage evolution of sandstone samples,whose failure characteristics were analyzed from both the macroscopic and microscopic perspectives.X-ray difraction technique and scanning electron microscopy were used to reveal the softening mechanism of *** results show that under graded cyclic loading,input energy,elastic energy,and dissipated energy all increase gradually,and the fraction of elastic energy increases gradually at frst and then tends to *** variation in the fraction of dissipated energy is opposite to that of elastic *** each cycle,the input energy is stored primarily in the form of elastic energy,whereas the dissipated energy is used primarily to overcome the damping of *** the normalized number of cycles approached unity,the plastic energy fraction sharply increases,while that of the dampening energy drops *** increasing water content,the efect of pore water on the lubrication,the water wedge,and dissolution of mineral particles becomes more obvious,reducing the elastic-storage limit of sandstone,meanwhile the sandstone damage factor increases signifcantly under the same cycle and the failure mode changes from brittle to ductile.

关键词： Mining engineering Energy evolution Water-rock interaction Weakening mechanism

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Dynamic Disentangled Interactive Network

SSRN

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SSRN 2023年

作者： You, Peng Zhao, Xiaohu National and Local Joint Engineering Laboratory of Internet Applied Technology on Mines China University of Mining and Technology Jiangsu Province Xuzhou221008 China School of Information and Control Engineering China University of Mining and Technology Jiangsu Province Xuzhou221116 China Xuhai College China University of Mining and Technology Jiangsu Province Xuzhou221008 China

[Abstract] Continuous-time dynamic graphs (CTDGs) serve as abstractions of real-world dynamic networks. They represent a concrete and profound restoration of many scenarios in the real-world. For instance, various types of terminal intelligent agents in the industrial internet of Things will engage in dynamic interactive communication to facilitate collaborative work within specific group topologies. Despite recent advancements in research on representation learning for CTDGs, the factorized representation of features across different dimensions and potential causality have not been adequately considered or explicitly modeled to capture dynamic patterns. The existing literature predominantly relies on manual extraction of temporal and spatial features, which fails to adequately capture the underlying causal relationships. In this study, we propose a novel dynamic disentangled interactive network (DDIN) that effectively disentangles the spatio-temporal features of the dynamic network within our model. In spatial interaction, the constraints on feature extraction determined by the spatial topology of nodes within khop while in time temporal sequences, anonymous strategies are employed to extract sequential slice motifs, which correspond to low-dimensional features in different interactions, effectively capturing potential spatio-temporal dynamics. We further used a combination of loss functions to optimize the model. Our approach exhibits distinct advantages in both transductive and inductive settings across four authentic datasets. © 2023, The Authors. All rights reserved.

关键词： Intelligent agents

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Improved Routing Algorithm for Wireless Sensor Networks Based on LEACH

Improved Routing Algorithm for Wireless Sensor Networks Base...

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Communication engineering and Cloud Computing Conference (CECCC), International

作者： Junqi Mao Minming Gu Yu Huo The National Joint Engineering Laboratory of Internet Applied Technology of Mines China University of Mining and Technology Xuzhou China School of Electronic & Information Engineering Suzhou University of Science and Technology Suzhou China

This paper proposes an improved routing algorithm based on Low Energy Adaptive Clustering Hierarchy (LEACH). Routing algorithm is divided into cluster establishment stage and stable transmission stage. In the cluster building stage, the remaining energy and distance parameters of sensor nodes are used to optimize the selection of the cluster head node and cluster construction. In the stable transmission stage, the cluster head selects data forwarding nodes based on node spacing, residual energy and relative angle. Through simulation, the proposed algorithm compares to LEACH, LEACH-C and DEEC algorithms. The results show that using the improved LEACH algorithm, the total residual energy of WSN is increased by about 30%, the amount of data transmission is increased by about 136%, and the network life cycle is prolonged by about 24.7%. Compared with similar algorithms, the proposed algorithm is more reasonable in the selection of the cluster head and the adjustment of cluster size.

关键词： Wireless communication Wireless sensor networks Energy consumption Cloud computing Buildings Clustering algorithms Routing

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A Unified Platform for Information Extraction with Two-Stage Process 10th

A Unified Platform for Information Extraction with Two-Stage...

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10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021

作者： Zhao, Chongshuai Guo, Dongjie Dai, Xudong Gu, Chengmin Fa, Lingling Liu, Peng National Joint Engineering Laboratory of Internet Applied Technology of Mines China University of Mining and Technology Xuzhou Jiangsu China University of Science and Technology of China Hefei Anhui China Xi’an Jiaotong University Xi’an Shaanxi China Nanjing University of Science and Technology Nanjing Jiangsu China

ISBN: (纸本)9783030884826

The multi-format Information Extraction (IE) task in Language and Intelligence Challenge 2021 (LIC2021) consists of three subtasks: Relation Extraction (RE), Sentence-level Event Extraction (SentEE) and Document-level Event Extraction (DocEE). Deep learning methods have made great progress in each subtask these years. However, most of them cannot solve these subtasks by a unified platform. In this paper, we develop a unified neural model with two-stage process, which adopt the Enhanced NER module in stage one to obtained the ELEMENTs and corresponding LABELs. In stage two, we designed the customized manoeuvres to solve challenges in different subtasks. The submission shows that our model achieves competitive performance, which ranks 3rd on the final leaderboard. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

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Advancing Ultra-Short-Term Wind Power Forecasting with Multi-Channel ML Techniques

Advancing Ultra-Short-Term Wind Power Forecasting with Multi...

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Energy Systems and Electrical Power (ICESEP), International Conference on

作者： Jiapin Ren Chenlin Zhu Zeyu Huang Ruihan Chen Shurui Xu Peng You Department of Information and Electrical Engineering Xuhai College China University of Mining and Technology Xuzhou China Metropolitan College Boston University Boston USA School of Information Engineering China Jiliang University Hangzhou China School of Mathematical Sciences Zhejiang Normal University Jinhua China Cognitive Neuroscience Laboratory Beijing Meishi Cha Technology Co. Ltd. Beijing China National and Local Joint Engineering Laboratory of Internet Applied Technology on Mines China University of Mining and Technology School of Information and Control Engineering China University of Mining and Technology Xuhai College China University of Mining and Technology Xuzhou China

ISBN: (数字)9798350353563

ISBN: (纸本)9798350353570

To address the inherent unpredictability of wind speeds and directions, which significantly affect wind turbine output, this paper presents a multi-channel feature combination strategy for ultra-short term wind power prediction. The research utilises a number of data sources, including meteorological observations, historical power data and geographical inputs, to create a robust feature set for prediction models. By using advanced machine learning techniques, in particular deep learning models such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, the study effectively captures the complex dynamics of wind power generation. The novel approach of reclassifying data sets and refining model features through task-specific channels significantly improves prediction accuracy. Experimental results show significant improvements in prediction accuracy, highlighting the potential of the proposed method to optimise grid operation and energy management in real-time scenarios.

关键词： Accuracy Wind power generation Predictive models Feature extraction Data models Wind turbines Convolutional neural networks

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Carboxymethyl-Β-Cyclodextrin Enhanced Persulfate/Fe2+ System for Organic Contaminant Removal in Groundwater: Performance, Influencing Factors, and Mechanisms

SSRN

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SSRN 2025年

作者： Yang, Chaoge Huang, Yanli Liu, Fangyuan Zhang, Chunpeng Dong, Jun Li, Junmeng School of Mines China University of Mining & Technology Xuzhou221116 China Key Laboratory of Coal Resources and Green Mining in Xinjiang Ministry of Education Xinjiang Institute of Engineering Urumqi830000 China Changchun130021 China National and Local Joint Engineering Laboratory for Petrochemical Contaminated Site Control and Remediation Technology Jilin University 2519 Jiefang Road Changchun130021 China

The removal of contaminants by persulfate (PDS)/Fe2+ system is a promising groundwater decontamination technology, while the non-recyclability of Fe2+ and the restricted mass transfer of contaminants in water limit the decontamination efficiency. Here, we developed carboxymethyl-β-cyclodextrin (CM-β-CD) to chelate Fe2+ coupled with enhancing the solubization of contaminants in groundwater for efficient decontamination. Results showed that a 4.60-fold enhancement in the perchloroethylene (PCE) degradation rate following the addition of 1 g/L CM-β-CD to the PDS/Fe2+ system. The ternary complex formed by CM-β-CD, Fe2+ and PCE was confirmed via ultraviolet absorption spectra and nuclear magnetic resonance hydrogen spectrum. Electron paramagnetic resonance, complemented by chemical probe and radical quenching experiments, identified singlet oxygen (1O2), high-valent iron (Fe(IV)), and hydroxyl radicals (•OH) as the dominant reactive species in the PDS/Fe2+/CM-β-CD system, with relative contributions to PCE degradation quantified at 30.37%, 26.15%, and 18.08%, respectively. The system exhibited reduced PCE degradation efficiency under neutral pH conditions and at lower temperatures. Notably, the presence of HA and common inorganic ions (Cl−, SO42−, NO3−, Na+, K+, Ca2+, and Mg2+) showed negligible effects on PCE degradation efficiency. The primary degradation intermediate of PCE in the PDS/Fe2+/CM-β-CD system was identified as dichloromethane, with the degradation pathways predominantly mediated by 1O2, Fe(IV), and •OH, and PCE could undergo dechlorination and mineralization during the degradation. This study developed an environmentally sustainable remediation strategy utilizing CM-β-CD as a dual-functional agent for simultaneous Fe2+ chelation and contaminant solubilization, enabling efficient groundwater decontamination. © 2025, The Authors. All rights reserved.

关键词： Decontamination

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