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Analyzing of Metal Organic Frameworks Performance in Gas Adsorption Using Machine Learning Techniques: A Gbrt Model Based on Small Training Dataset

SSRN

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SSRN 2023年

作者： Wei, Xin Peng, Ding Shen, Lin Ai, Yuejie Lu, Zhanhui School of Control and Computer Engineering North China Electric Power University Beijing102206 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Institute of Material Genome Engineering Shandong Yantai265505 China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environment and Chemical Engineering North China Electric Power University Beijing102206 China School of Mathematics and Physics North China Electric Power University Beijing102206 China

Metal organic frameworks (MOFs) have already been widely used in the field of gas adsorption and *** combination of various organic ligands and metal ions results in large MOF libraries with different topological structures. However, such large structural databases make it difficult to screen out MOF materials with high adsorption performance towards a given gas to establish statistical pictures through experiments or molecular simulations. In this work, we studied and built machine learning (ML) models based on the hypothetical MOF (hMOF) database. A gradient-boosted regression trees (GBRT) model with 1000 samples can predict the methane adsorption capacity of more than 130,000 hMOFs with high accuracy. A fast high-throughput screening on the entire database was performed using the constructed regression model, which extracts several molecular fragments from the top 1% of materials with the largest methane adsorption capacity. Careful analysis of the chemical structure of these fragments indicates that MOF materials containing cyano, hydroxyl, carboxyl and/or aromatic rings may possess high adsorption performance. The electrostatic potential distribution of these fragments was obtained at the ab initio computational level and was highlighted to be another important descriptor. We further extended the GBRT predictor to diverse MOF libraries including tobacco MOF (tobmof) and CoRE MOF. The molecular fragments extracted from the ML-based screening on the real CoRE MOF database as well as the corresponding electrostatic properties were compared with the results of hMOFs, which provides new insight into the design of MOF materials. © 2023, The Authors. All rights reserved.

关键词： Database systems

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Fluorescent Nanosensor Platform Based on Cdte Qds-Aptamer Probe and MoS2 Nanosheets for Detection of Silver(Ⅰ) Ions

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SSRN 2023年

作者： Li, Qianfeng Sun, Jian Li, Xiang Yan, Changling Wang, Gongke School of Materials Science and Engineering Henan Engineering Research Center of Design and Recycle for Advanced Electrochemical Energy Storage Materials Henan Normal University Henan Xinxiang453007 China School of Environment Henan Key Laboratory for Environmental Pollution Control Henan Normal University Henan Xinxiang453007 China School of Chemistry and Chemical Engineering Key Laboratory of Green Chemical Media and Reactions Ministry of Education Collaborative Innovation Center of Henan Province for Green Manufacturing of Fine Chemicals Henan Normal University Henan Xinxiang453007 China

Silver ion (Ag+) is one of the most dangerous metal pollutants. Long-term exposure to toxic heavy metals will do great harm to humans and animals. Therefore, it is urgent to develop an efficient method for detecting Ag+. Herein, we have developed a simple, sensitive, highly selective and cost-effective fluorescence "off-on" mode nanosensor based on environmentally friendly and biocompatible materials for sensitive detection of Ag+ in aqueous environments. In this sensing strategy, Ag+ can specifically interact with the cytosine-cytosine (C-C) mismatch in single-stranded DNA, where Ag+ induces the folding of single-stranded DNA to form hairpin structures and stable metal-mediated cytosine-Ag+-cytosine (C-Ag+-C) base pairs via coordinate bonds. Massive changes to the molecular volume and fluorescence signal are brought about by the development of the C-Ag+-C complex. To reach our objective, CdTe quantum dots with low toxicity and strong signal were prepared as fluorophores for detecting Ag+ target. The fluorescence turn-off of CdTe QDs is achieved by effective photoinduced electron transfer between CdTe QDs and MoS2 nanosheets, and the subsequent fluorescence turn-on process is due to the formation of C-Ag+-C complex, which makes its probe fluorophore far away from the surface of MoS2 nanosheets, thus realizing fluorescence "off-on" sensing strategy. The proposed nanosensor can distinguish Ag+ from other interfering ions with high sensitivity and selectivity. The nanosensor proposed here possesses a quick response time of 8 minutes and an ultra-low detection limit of 1.1 nM. © 2023, The Authors. All rights reserved.

关键词： Semiconductor quantum dots

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From mild to explosive: understanding the aggravating effects of ZrB2's reaction in the water vapor oxygen coupled environment

SSRN

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SSRN 2024年

作者： Liu, Zhi-Jie Zhang, Lin-Bo Jiang, Xian-Yu Zhao, Yu-Jie Agathopoulos, Simeon Runowski, Marcin Ahmed, Jahangeer Chen, Hai-Yan Han, Tian-Cheng Lu, Hai-Peng Xie, Jian-Liang Yin, Liang-Jun Liu, Tong National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China 2006 Xiyuan Road Chengdu611731 China Key Laboratory of Multi-spectral Absorbing Materials and Structures of Ministry of Education University of Electronic Science and Technology of China 2006 Xiyuan Road Chengdu611731 China School of Materials Science and Engineering Henan University of Science and Technology Luoyang471023 China Materials Science and Engineering Department University of Ioannina Greece Department of Rare Earths Faculty of Chemistry Adam Mickiewicz University Uniwersytetu Poznańskiego 8 Poznań61-614 Poland Department of Chemistry College of Science King Saud University Riyadh11451 Saudi Arabia Key Laboratory of Green Chemical Process of Ministry of Education Hubei Key Laboratory of Novel Reactor and Green Chemical Technology School of Chemical Engineering and Pharmacy Wuhan Institute of Technology Wuhan430205 China

The study of ultra-high temperature ceramic materials, specifically zirconium diboride (ZrB2), is of great interest due to their potential applications in extreme environments, such as the aerospace and nuclear industries. This research aims to comprehend the reaction dynamics of ZrB2 powders in water vapor oxygen coupled environments, which is a common scenario in high-temperature applications. The study aims to provide a comprehensive insight into the behaviour of ZrB2 in a controlled water vapor oxygen environment, highlighting the two-stage reaction process and its implications for material stability and potential industrial applications. ZrB2 powders were used to investigate their reactivity in a hydrothermal kettle through a series of experiments. This study improves our understanding of ZrB2's reactivity and suggests its potential in applications such as hydrogen production. However, it also highlights the need for improved stability in such reactive environments. © 2024, The Authors. All rights reserved.

关键词： Oxygen

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The continuous increased stability of sediment dissolved organic matter implies ecosystem degradation of lakes in the cold and arid regions

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Science of the Total Environment 2024年 947卷 174384页

作者： Guo, Ying Liu, XiaoFei Dong, Yue Ni, Zhaokui Zhou, Chunyang Chen, Chao Wang, Shengrui Chen, Qiuying Yan, Yanting Guangdong-Hong Kong Joint Laboratory for Water Security Center for Water Research Advanced Institute of Natural Sciences Beijing Normal University at Zhuhai Zhuhai519087 China College of Water Sciences Beijing Normal University Beijing100875 China Engineering Research Center of Ministry of Education on Groundwater Pollution Control and Remediation Beijing100875 China Instrumentation and Service Center for Science and Technology Beijing Normal University at Zhuhai Zhuhai519087 China Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake Watershed Yunnan Province Kunming650034 China North China Institute of Science and Technology School of Chemical Safety Langfang101601 China

The characteristics of lake dissolved organic matter (DOM) pool and lake ecosystem interact, and studying the responses between sediment DOM characteristics and lake ecosystem changes may shed light on the inherent connection between ecosystem evolution and carbon biogeochemical cycles. Lakes in cold and arid regions are sensitive to changes and accumulate large amounts of carbon as DOM, which may provide a window into more explicit relationships between ecosystem evolution and changes in sediment DOM characteristics in time dimension. However, considerable blind spots exist in the responses between the sediment DOM and ecosystem evolution on time scale and the underlying mechanisms. In this study, multiple approaches were combined to investigate the relationship between the variation trend of sediment DOM characteristics and the evolution of fragile lake ecosystems across three different lake ecosystems in cold and arid regions of China. A strong positive relationship between sediment DOM stabilities, especially humification, and ecosystem degradation was found, consistent for the three lakes. Ultra-high-resolution mass spectrometry and structural equation modeling revealed that the changes of ecosystems affected sediment DOM stability through direct pathways (0.24), such as the contents of terrestrial DOM in lake DOM pool, and indirect pathways, including algae-mediated (0.43) and salinity-mediated pathways (0.22), which all increased the contents of refractory DOM in the lake DOM pool and sediments. Based on the fact that DOM stability changes could act on the ecosystem in turn, a possible positive feedback mechanism between ecosystem degradation and increased DOM stability was further inferred. These results suggested that the continuous increased stability of sediment DOM in may implies ecosystem degradation of lakes in the cold and arid regions. This study provides a new perspective for recognizing ecosystem evolution through sediment DOM and improves the unde

关键词： Lakes

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Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries

Exponential Weighted Moving Average-Based Variational Mode D...

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Data Driven control and Learning Systems (DDCLS)

作者： Penghao Wu Hongfeng Tao Engang Tian Tangwen Yin Hongtian Chen Yiyang Chen School of Mechanical and Electrical Engineering Soochow University Suzhou P. R. China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi P. R. China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai P. R. China Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods.

关键词： Fault diagnosis Learning systems Employee welfare Sensitivity Power supplies Noise Electric vehicles

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Corrections to “Practical Fixed-Time Consensus Tracking for Multiple Euler–Lagrange Systems With Stochastic Packet Losses and Input/Output Constraints”

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IEEE Systems Journal 2022年第1期16卷 1709-1709页

作者： He Li Cheng-Lin Liu Ya Zhang Yang-Yang Chen Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Institute of Automation Jiangnan University Wuxi China School of Automation Southeast University Nanjing China

In [1], several errors were introduced during the production process, which are corrected here.

关键词： Packet loss

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Preface

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2023年 492卷 v-vi页

作者： Luan, Xiaoli He, Shuping Liu, Fei Key Laboratory of Advanced Process Control for Light Industry [Ministry of Education Institute of Automation Jiangnan University Jiangsu Wuxi China Key Laboratory of Intelligent Computing and Signal Processing [Ministry of Education School of Electrical Engineering and Automation Anhui University Anhui Hefei China

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A Generalized Probabilistic Monitoring Model with Both Randomand Sequential Data

arXiv

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arXiv 2022年

作者： Yu, Wanke Wu, Min Huang, Biao Lu, Chengda The School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

Many multivariate statistical analysis methods and their corresponding probabilistic counterparts have been adopted to develop process monitoring models in recent decades. However, the insightful connections between them have rarely been studied. In this study, a generalized probabilistic monitoring model (GPMM) is developed with both random and sequential data. Since GPMM can be reduced to various probabilistic linear models under specific restrictions, it is adopted to analyze the connections between different monitoring methods. Using expectation maximization (EM) algorithm, the parameters of GPMM are estimated for both random and sequential cases. Based on the obtained model parameters, statistics are designed for monitoring different aspects of the process system. Besides, the distributions of these statistics are rigorously derived and proved, so that the control limits can be calculated accordingly. After that, contribution analysis methods are presented for identifying faulty variables once the process anomalies are detected. Finally, the equivalence between monitoring models based on classical multivariate methods and their corresponding probabilistic graphic models is further investigated. The conclusions of this study are verified using a numerical example and the Tennessee Eastman (TE) process. Experimental results illustrate that the proposed monitoring statistics are subject to their corresponding distributions, and they are equivalent to statistics in classical deterministic models under specific restrictions. Copyright © 2022, The Authors. All rights reserved.

关键词： process monitoring

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Tension Soft Sensor of Continuous Annealing Lines Using Cascade Frequency Domain Observer with Combined PCA and Neural Networks Error Compensation

Tension Soft Sensor of Continuous Annealing Lines Using Casc...

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2010 49th IEEE Conference on Decision and control

作者： Qiang Liu Tianyou Chai Hong Wang S. Joe Qin Key Laboratory of Integrated Automation of Process Industry (Northeastern University) Ministry of Education and Research Center of Automation Northeastern University Shenyang China Control Systems Centre the University of Manchester Manchester M60 1QD the United Kingdom Mork Family Department of Chemical Engineering and Materials Science the Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles CA 90089-1211 USA

ISBN: (纸本)9781424477456

In continuous annealing processes, strip tension is an important factor which indicates whether the annealing line works steadily. The strip tension detection in the continuous annealing process, therefore, is essential for the reliable and stable operation of the units, and will help to improve the quality of strip products. However, in real annealing processes, only a limited number of strip tensions can be measured. Since installing tension sensors everywhere will be unrealistic and expensive, in this paper a cascade reduced-order observer method with principal component analysis (PCA) and neural networks (NN) compensation is proposed to estimate the unknown tensions between each two neighboring rolls so as to monitor the tension profile for the whole line. When the main observer model is established, the influences of strip inertia and roll eccentricity on tensions are taken into account for better estimation. Moreover, when the error compensation is designed, PCA scores are used as the inputs to the NN. The application results show the effectiveness of the proposed method, with the estimated tensions used for the analysis of the strip-breaks fault.

关键词： Error compensation Continuous annealing annealing tension strip tension stability operations Neural network cascades

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SPAHN novel approach for PL-AG gateway discovery for internet connectivity

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Peer-to-Peer Networking and Applications 2020年第4期14卷 2275-2284页

作者： Kannan, K. Sivaranjani, P. Sathish Kumar, S. Nalini, M. Balaji, V. R. Sanjeevi, P. Department of ECE R.M.K. College of Engineering and Technology Chennai India Department of Electronics and communication Engineering Kongu Engineering College Erode India Dept of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Thalavapalayam India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of ECE Sri Krishna College of Engineering and Technology Coimbatore India Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

Internet Gateway(IGW) main role is detecting availability nodes and providing internet to Mobile Ad Hoc Network(MANET) have whenever connected to internet. Discovery time of gateway is changed based on the throughput and packet delay. Many of the situations the mobile nodes are have fixed host connection to the internet using minimum hop path, it is not good for waiting packets because of that packets are have longer path interface queue. This research paper object is avoided above the problem mentioning using a novel approach of SPAHN (Solving Problem of Ad-Hoc Network). This paper mainly focus is classify the routing protocols of load-aware in MANET and from this classify discover the proactive load-aware gateway (PL-AG) from a device into interface queue size and min-hop-metric. This novel approach has been allowing and gives better handoff between two internet gateways for fixed host seamless connectivity. We justify the performance of the SPAHN approach using two metrics like average end-to-end delay and throughput based on this examination the SPAHN system yield good simulation results comparably existing systems.

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