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Boosting the catalytic performance of Cu-SAPO-34in NO_(x) removal via hydrothermal treatment

Journal of Environmental sciences 2024年第1期135卷 640-655页

作者： Xiaoyan Tian Huimin Wang Siyuan Xu Lianyun Gao Jinyan Cao Jianjun Chen Qiulin Zhang Ping Ning Jiming Hao Faculty of Environmental Science and Engineering Kunming University of Science and TechnologyKunming 650500China National-Regional Engineering Center for Recovery of Waste Gases from Metallurgical and Chemical Industries Kunming University of Science and TechnologyKunming 650500China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution ControlTsinghua UniversityBeijing 100084China

Phosphate ions promoted Cu-SAPO-34(P-Cu-SAPO-34)were prepared using bulk CuO particles as Cu^(2+)precursor by a solid-state ion exchange technique for the selective catalytic reduction of NO_(x) with NH_3(NH_3-SCR).The effects of high temperature(H-T)hydrothermal aging on the NO_(x) removal(de-NO_(x))performance of Cu-SAPO-34 with and without phosphate ions were systematically investigated at atomic *** results displayed that both Cu-SAPO-34 and P-Cu-SAPO-34 presented relatively poor NO_(x) removal activity with a low conversion(<30%)at 250-500℃.However,after H-T hydrothermal treatment(800℃ for 10 hr at 10%H_2O),these two samples showed significantly satisfied NO_(x) elimination performance with a quite high conversion(70%-90%)at 250-500℃.Additionally,phosphate ions decoration can further enhance the catalytic performance of Cu-SAPO-34 after hydrothermal treatment(Cu-SAPO-34H).The textural properties,morphologies,structural feature,acidity,redox characteristic,and surface-active species of the fresh and hydrothermally aged samples were analyzed using various characterization *** systematical characterization results revealed that increases of 28%of the isolated Cu^(2+)active species(Cu^(2+)-2Z,Cu(OH)^(+)-Z)mainly from bulk CuO and 50%of the Bronsted acid sites,the high dispersion of isolated Cu^(2+)active component as well as the Bronsted acid sites were mainly responsible for the accepted catalytic activity of these two hydrothermally aged samples,especially for P-Cu-SAPO-34H.

关键词： NH_(3)-SCR Cu-SAPO-34 Hydrothermal induced Phosphate ions

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Novel quantitative structure activity relationship models for predicting hexadecane/air partition coefficients of organic compounds

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Journal of Environmental sciences 2023年第2期124卷 98-104页

作者： Ya Wang Weihao Tang Zijun Xiao Wenhao Yang Yue Peng Jingwen Chen Junhua Li State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China Key Laboratory of Industrial Ecology and Environmental Engineering(MOE) School of Environmental Science and TechnologyDalian University of TechnologyLinggong Road 2Dalian 116024China

Predicting the logarithm of hexadecane/air partition coefficient(L)for organic compounds is crucial for understanding the environmental behavior and fate of organic compounds and developing prediction models with polyparameter linear free energy ***,two quantitative structure activity relationship(QSAR)models were developed with 1272 L values for the organic compounds by using multiple linear regression(MLR)and support vector machine(SVM)*** the basis of the OECD principles,the goodness of fit,robustness and predictive ability for the developed models were *** SVM model was first developed,and the predictive capability for the SVM model is slightly better than that for the MLR *** applicability domain(AD)of these two models has been extended to include more kinds of emerging pollutants,i.e.,oraganosilicon *** developed QSAR models can be used for predicting L values of various organic *** van derWaals interactions between the organic compound and the hexadecane have a significant effect on the L value of the *** in silico models developed in current study can provide an alternative to experimental method for high-throughput obtaining L values of organic compounds.

关键词： L value Quantitative structure-activity relationship Multiple linear regression Support vector machine Oraganosilicon compounds

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Analysis of Algorithm Comparison Results on Real-World Multi-Objective Problems 13

Analysis of Algorithm Comparison Results on Real-World Multi...

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13th IEEE Congress on Evolutionary computation, CEC 2024

作者： Pang, Lie Meng Ishibuchi, Hisao Shang, Ke Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China

ISBN: (纸本)9798350308365

Recently, several real-world multi-objective optimization problem suites have been proposed to facilitate the evaluation of the performance of evolutionary multi-objective optimization (EMO) algorithms. In spite of the importance of using real-world problems to evaluate EMO algorithms, their characteristics are not well understood compared to artificial test problems. Thus, there is a need to examine and understand the challenges posed by these real-world problems. In this study, we attempt to explore the characteristics of the most recently proposed real-world application suite (i.e., RWA suite). Six EMO algorithms are evaluated on the RWA suite, including three classic algorithms and three recently-proposed algorithms. Based on the performance comparison results, we systematically analyze the RWA suite in terms of convergence and diversity difficulties. © 2024 IEEE.

关键词： Optimization algorithms

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Distance-Based Subset Selection With a Knee Point for Multi-Objective Optimization 13

Distance-Based Subset Selection With a Knee Point for Multi-...

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Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Pang, Lie Meng Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China

ISBN: (纸本)9798350373332

Recently, the use of an unbounded external archive in the design of evolutionary multi-objective optimization (EMO) algorithms has received increasing attention. An important component in the use of an unbounded external archive is its subset selection method used to select a pre-specified number of solutions from the archive. One of the most commonly used subset selection method is distance-based subset selection (DSS) since it is very easy to calculate and can easily scale to many-objective optimization. However, the DSS's selection mechanism usually lead to a small hypervolume value for the selected subset even when the optimal subset with respect to the minimum distance among the selected solutions is obtained. In this paper, we propose a modification to the DSS algorithm by selecting a knee point as the first solution. The knee point is often a solution of interest to decision makers in the absence of preference information. Experimental results show that the inclusion of a knee point generally has a positive effect on improving the hypervolume value of the selected subset. © 2024 IEEE.

关键词： Optimization algorithms

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Games for Artificial Intelligence Research: A Review and Perspectives

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 5949-5968页

作者： Hu, Chengpeng Zhao, Yunlong Wang, Ziqi Du, Haocheng Liu, Jialin Research Institute of Trustworthy Autonomous System Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China LightSpeed Studios Tencent Shenzhen518057 China

Games have been the perfect test beds for artificial intelligence (AI) research for the characteristics that widely exist in real-world scenarios. Learning and optimization, decision-making in dynamic and uncertain environments, game theory, planning and scheduling, design, and education are common research areas shared between games and real-world problems. Numerous open-source games or game-based environments have been implemented to study AI. In addition to single- or multiplayer, collaborative, and adversarial games, there has also been growing interest in implementing platforms for creative design in recent years. Those platforms provide ideal benchmarks for exploring and comparing AI ideas and techniques. This article reviews the games and game-based platforms for AI research, provides guidance on matching particular types of AI with suitable games for testing and matching particular needs in games with suitable AI techniques, discusses the research trend induced by the evolution of those games and platforms, and gives an outlook. © 2024 IEEE.

关键词： Reinforcement learning

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Performance Evaluation of Evolutionary Multi-Objective Algorithms Using Real-World Problems with an Additional Total Constraint Violation Objective 13

Performance Evaluation of Evolutionary Multi-Objective Algor...

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13th IEEE Congress on Evolutionary computation, CEC 2024

作者： Nan, Yang Ishibuchi, Hisao Shu, Tianye Southern University of Science and Technology Guangdong Provinial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China

ISBN: (纸本)9798350308365

In the community of evolutionary multi-objective optimization (EMO), one important issue is the choice of test problems for performance evaluations of EMO algorithms. This is because performance evaluation results of EMO algorithms totally depend on the choice of test problems. This means that the research on new EMO algorithm design is also influenced by the choice of test problems. Recently, researchers have started to use real-world problems for performance evaluation of EMO algorithms. Among them, a real-world problem suite RE has attracted much attention and has been used in many studies. However, most RE problems have been created from real-world constrained problems by using the total constraint violation as an additional objective. That is, the original versions of most RE problems are not unconstrained multi-objective problems. Thus, even when a good solution set is obtained by an EMO algorithm for an RE problem, it can be a poor solution set for its original constrained problem. This is because many well-distributed solutions over the entire Pareto front of the transformed unconstrained problem are usually infeasible solutions of the original constrained problem with some positive total constraint violation values. In this paper, we examine whether good solution sets obtained by EMO algorithms for RE problems are also good solution sets for their original constrained problems. Our experimental results show that good solutions sets for most RE problems include good feasible solution sets for their original constrained problems. However, for a few RE problems, good solution sets obtained by some high performance EMO algorithms do not include good feasible solution sets. Our results show that high-performance EMO algorithms on most RE problems generate good feasible solution sets for their original constrained versions. This observation supports the usefulness of those RE problems as test problems for performance evaluation of EMO algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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MOFs fertilized transition-metallic single-atom electrocatalysts for highly-efficient oxygen reduction: Spreading the synthesis strategies and advanced identification

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Journal of Energy Chemistry 2022年第4期31卷 391-422页

作者： Kexin Song Yu Feng Wei Zhang Weitao Zheng State Key Laboratory of Automotive Simulation and Control School of Materials Science&EngineeringKey Laboratory of Automobile Materials MOEElectron Microscopy Centerand International Center of Future ScienceJilin UniversityChangchun 130012JilinChina

Metal-organic frameworks(MOFs) have been widely used in oxygen reduction reaction(ORR) of fuel cells and metal-air batteries, attributed to their unique structures and compositions. Recently, the preparation of transition-metallic single-atom electrocatalysts(TM-SACs) using MOFs as precursors or templates has made great progress. Herein, the development history of SACs prepared based on MOFs and their characterization are overviewed firstly, and then several strategies are summarized for preparing TM-SACs using MOFs and further modification. Finally, the challenges and opportunities confronted by TM-SACs are fully discussed. Consequently, our work can guide the realization of TM-SACs abundant with high activity, high loading and high stability.

关键词： Transition-metallic single-atom electrocatalysts(TM-SACs) Oxygen reduction reaction(ORR) Metal-organic frameworks(MOFs) Electron microscopy Spectroscopy

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PNESR-DDI: An Effective Drug-Drug Interaction Prediction Model Based on Pretraining Method and Enhanced Subgraph Reconstruction

PNESR-DDI: An Effective Drug-Drug Interaction Prediction Mod...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Chen, Ke Han, Xiaosong Li, Xiaoran Liang, Yanchun Xu, Dong Guan, Renchu Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Software Changchun China Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Changchun China Zhuhai College of Science and Technology Zhuhai Laboratory of Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education School of Computer Science Zhuhai China University of Missouri Christopher S. Bond Life Sciences Center Department of Electrical Engineering and Computer Science Columbia United States

ISBN: (纸本)9798350386226

Drug-Drug Interaction (DDI) task plays a crucial role in clinical treatment and drug development. Recently, deep learning methods have been successfully applied for DDI prediction. However, training deep learning models always need large amount of data, while known DDIs are scarce. To address this challenge, a graph neural network-based DDI prediction model named PNESR-DDI is proposed, which compensates for the lack of DDIs by enriching drug representations. First, to obtain initial node representations that incorporate rich semantic information from the biomedical knowledge graph (KG), a link prediction pre-training method on external KG is proposed in the node embedding pre-training module. Then, considering the large scale of the KG, subgraph extraction for the target drug pairs is introduced to reduce noise and decrease computational complexity in the subgraph anchoring module. After that, the subgraph is updated, and node similarities are propagated in the subgraph reconstruction module. Based on the node similarity scores, the subgraph is pruned and reconstructed, which adjusts node representations to be more conducive to DDI prediction. Finally, the drug embeddings, subgraph representations, and drug fingerprint features are concatenated to predict DDIs. PNESRDDI is evaluated on two benchmark DDI datasets: DrugBank and TWOSIDES. Experiment results show that PNESR-DDI achieves better performance than baselines. Ablation results validate the effectiveness of the pre-training method and the adaptive subgraph reconstruction strategy. © 2024 IEEE.

关键词： Knowledge graph

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Sensitivity investigation of 100-MeV proton irradiation to SiGe HBT single event effect

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Chinese Physics B 2024年第1期33卷 554-562页

作者：冯亚辉郭红霞刘益维欧阳晓平张晋新马武英张凤祁白如雪马晓华郝跃 State Key Laboratory of Wide Bandgap Semiconductor Devices School of MicroelectronicsXidian UniversityXi'an 710071China School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China School of Space Science and Technology Xidian UniversityXi'an 710071China State Key Laboratory of Experimental Simulation and Effects of Strong Pulse Radiation Northwest Institute of Nuclear TechnologyXi'an 710024China

The single event effect(SEE) sensitivity of silicon–germanium heterojunction bipolar transistor(Si Ge HBT) irradiated by 100-Me V proton is investigated. The simulation results indicate that the most sensitive position of the Si Ge HBT device is the emitter center, where the protons pass through the larger collector-substrate(CS) junction. Furthermore, in this work the experimental studies are also carried out by using 100-Me V proton. In order to consider the influence of temperature on SEE, both simulation and experiment are conducted at a temperature of 93 K. At a cryogenic temperature, the carrier mobility increases, which leads to higher transient current peaks, but the duration of the current decreases ***, at the same proton flux, there is only one single event transient(SET) that occurs at 93 K. Thus, the radiation hard ability of the device increases at cryogenic temperatures. The simulation results are found to be qualitatively consistent with the experimental results of 100-Me V protons. To further evaluate the tolerance of the device, the influence of proton on Si Ge HBT after gamma-ray(^(60)Coγ) irradiation is investigated. As a result, as the cumulative dose increases, the introduction of traps results in a significant reduction in both the peak value and duration of the transient currents.

关键词： silicon–germanium heterojunction bipolar transistor(Si Ge HBT) 100-Me V proton technology computer-aided design(TCAD) single event effect(SEE)

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Synergistic promotion of particulate matter reduction and production performance via adjusting electrochemical reactions in the zinc electrolysis industry

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Frontiers of Environmental science & engineering 2024年第1期18卷 23-33页

作者： Zizhen Ma Jingkun Jiang Lei Duan Jianguo Deng Fuyuan Xu Zehui Li Linhua Jiang Ning Duan School of Environmental and Municipal Engineering Qingdao University of TechnologyQingdao 266520China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of the EnvironmentTsinghua UniversityBeijing 100084China State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and EngineeringTongji UniversityShanghai 200092China School of Physics Peking UniversityBeijing 100871China

Heavy particulate matter (PM) pollution and high energy consumption are the bottlenecks of hydrometallurgy, especially in the electrolysis process. Therefore, an urgent need is to explore PM reduction methods with production performance co-benefits. This study presents three PM reduction methods based on controlling operating parameters, i.e., lowering electrolyte temperature, H2SO4 concentration, and current density of the cathode. The optimized conditions were also investigated using the response surface methodology to balance the PM reduction effect and Zn production. The results showed that lowering electrolyte temperature is the most efficient, with an 89.0% reduction in the PM generation flux (GFPM). Reducing H2SO4 concentration led to the minimum side effects on the current efficiency of Zn deposition (CEZn) or power consumption (PC). With the premise of non-deteriorating CEZn and PC, GFPM can be reduced by 86.3% at the optimal condition (electrolyte temperature = 295 K, H2SO4 = 110 g/L, current density = 373 A/m^(2)). In addition, the reduction mechanism was elucidated by comprehensively analyzing bubble characteristics, electrochemical reactions, and surface tension. Results showed that lower electrolyte temperature inhibited the oxygen evolution reaction (OER) and compressed gas volume. Lower H2SO4 concentration inhibited the hydrogen evolution reaction (HER) and reduced electrolyte surface tension. Lower current density inhibited both OER and HER by decreasing the reaction current. The inhibited gas evolutions reduced the microbubbles’ number and size, thereby reducing GFPM. These results may provide energy-efficient PM reduction methods and theoretical hints of exploring cleaner PM reduction approaches for industrial electrolysis.

关键词： Zinc electrolysis Particulate matter Energy consumption Operating parameters Bubble characteristic Electrochemical reaction

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