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Renewable conversion of coal gangue to 13-X molecular sieve for Cd^(2+)-containing wastewater adsorption performance

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Rare Metals 2024年第2期43卷 702-710页

作者： Le kang Si-Fan Liu Da-Wei Yi kai Wang Hui-Ling Du Hao-qi Huang Peng Chen College of Materials Science and Engineering Xi’an University of Science and TechnologyXi’an710054China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao266000China School of Metallurgy Northeastern UniversityShenyang110819China School of Materials and Chemical Engineering Tongren UniversityTongren554300China

Using coal gangue(CG)as raw material,a new type of all solid-waste-based 13-X molecular sieve material was controllably prepared by alkali fusion-hydrothermal *** synthetic molecular sieve was used as a solid adsorbent to treat Cd^(2+)-containing wastewater,and its adsorption behavior on Cd^(2+)in aqueous solution was studied and *** microstructure and morphology of the molecular sieve were investigated by X-ray diffraction(XRD),field emission scanning electron microscopy(FESEM)and specific surface area *** results show that the synthesized 13-X molecular sieve has higher Brunauer–Emmett–Teller(BET)specific surface area with higher crystallinity and higher adsorption capacity for the heavy metal Cd^(2+).The adsorption process of Cd^(2+)by molecular sieve conforms to the Langmuir isotherm adsorption equation and Lagergren pseudo-second-order rate *** with thermodynamic calculation,it can be concluded that the adsorption process is physically monolayer,spontaneous and *** this study,a low-cost and naturally available synthesis method of 13-X molecular sieve is *** with its adsorption mechanism for Cd^(2+),it provides a feasible and general method for removing heavy metal ions from coal gangue and also provides a new way for the utilization of coal gangue with high added value.

关键词： Coal gangue Hydrothermal synthesis 13-X molecular sieve Adsorption Wastewater containing Cd^(2+)

Research on blade tip clearance cavitation and turbulent kinetic energy characteristics of axial flow pump based on the partially-averaged Navier-Stokes model

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Journal of Hydrodynamics 2024年第1期36卷 184-201页

作者： Xiao-qi Jia Shuai-kang Zhang Zu-chao Zhu Key Laboratory of Fluid Transmission Technology of Zhejiang Province Zhejiang Sci-Tech UniversityHangzhou310018China

To reveal the cavitation forms of tip leakage vortex(TLV)of the axial flow pump and the flow mechanism of the flow field,this research adopts the partially-averaged Navier-Stokes(PANS)model to simulate the cavitation values of an axial flow pump,followed by experimental *** experimental result shows that compared with the shear stress transport(SST)k-ωmodel,the PANS model significantly reduces the eddy viscosity of the flow field to make the vortex structure clearer and allow the turbulence scale to be more robustly *** cavitation area within the axial flow pump mainly comprises of TLV cavitation,clearance cavitation and tip leakage flows combined effect of triangular cloud cavitation *** formation and development of cavitation are accompanied by the formation and evolution of vortex,and variations in vortex structure also generate and promote the development of *** addition,an in-depth analysis of the relationship between the turbulent kinetic energy(TKE)transport equation and cavitation patterns was also conducted,finding that the regions with relatively high TKE are mainly distributed around gas/liquid boundaries with serious cavitation and evident gas-liquid *** phenomenon is mainly attributed to the combined effect of the pressure action term,stress diffusion term and TKE production term.

关键词： Cavitation axial flow pump tip leakage vortex(TLV) partially-averaged Navier-Stokes(PANS)model turbulent kinetic energy(TKE)

Sound event localization and detection based on deep learning

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Journal of Systems Engineering and Electronics 2024年第2期35卷 294-301页

作者： ZHAO Dada DING kai qi Xiaogang CHEN Yu FENG Hailin School of Mathematics and Statistics Xidian UniversityXi’an 710071China Science and Technology on Near-Surface Detection Laboratory Wuxi 214035China

Acoustic source localization(ASL)and sound event detection(SED)are two widely pursued independent research *** recent years,in order to achieve a more complete spatial and temporal representation of sound field,sound event localization and detection(SELD)has become a very active research *** paper presents a deep learning-based multioverlapping sound event localization and detection algorithm in three-dimensional ***-Mel spectrum and generalized cross-correlation spectrum are joined together in channel dimension as input *** features are classified and regressed in parallel after training by a neural network to obtain sound recognition and localization results *** channel attention mechanism is also introduced in the network to selectively enhance the features containing essential information and suppress the useless ***,a thourough comparison confirms the efficiency and effectiveness of the proposed SELD *** experiments show that the proposed algorithm is robust to reverberation and environment and can achieve higher recognition and localization accuracy compared with the baseline method.

关键词： sound event localization and detection(SELD) deep learning convolutional recursive neural network(CRNN) channel attention mechanism

Molecular engineering binuclear copper catalysts for selective CO_(2) reduction to C_(2) products

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Journal of Energy Chemistry 2024年第6期93卷 166-173,I0005页

作者： qi Zhao kai Lei Bao Yu Xia Rachel Crespo-Otero Devis Di Tommaso Department of Chemistry School of Physical and Chemical SciencesQueen Mary University of LondonLondonE14NSUK Key Laboratory of Material Chemistry for Energy Conversion and Storage(Ministry of Education) Hubei Key Laboratory of Material Chemistry and Service FailureState Key Laboratory of Materials Processing and Die&Mould TechnologySchool of Chemistry and Chemical EngineeringHuazhong University of Science and Technology(HUST)Wuhan 430074HubeiChina Department of Chemistry University College LondonLondonWC1H 0AJUK Digital Environment Research Institute Queen Mary University of LondonEmpire HouseLondon E11HHUK

Molecular copper catalysts serve as exemplary models for correlating the structure-reaction-mechanism relationship in the electrochemical CO_(2) reduction(eCO_(2)R),owing to their adaptable environments surrounding the copper metal *** investigation,employing density functional theory calculations,focuses on a novel family of binuclear Cu molecular *** modulation of their coordination configuration through the introduction of organic groups aims to assess their efficacy in converting CO_(2) to C_(2)*** findings highlight the crucial role of chemical valence state in shaping the characteristics of binuclear Cu catalysts,consequently influencing the eCO_(2)R behaviour,Notably,the Cu(Ⅱ)Cu(Ⅱ)macrocycle catalyst exhibits enhanced suppression of the hydrogen evolution reaction(HER),facilitating proton trans fer and the eCO_(2)R *** rthermore,we explo re the impact of diverse electro n-withdrawing and electron-donating groups coordinated to the macrocycle(R=-F,-H,and-OCH_3)on the electron distribution in the molecular *** placement of-OCH_3 groups in the macrocycles leads to a favourable oxidation state of the Cu centres and subsequent C-C coupling to form C_(2) *** research provides fundamental insights into the design and optimization of binuclear Cu molecular catalysts for the electrochemical conversion of CO_(2) to value-added C_(2) products.

关键词： Molecular catalyst design Selective CO_(2)reduction C_(2)products Density functional theory calculations

The short and long-term effect of polystyrene nanoplastics on nitrifying sludge at high nitrite concentrations

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Journal of Environmental Sciences 2024年第1期135卷 222-231页

作者： Xiaolong Wang Jialu Huang Zhiqiang qi Ruiqin kang Chao Du Da Li School of Chemical and Environmental Engineering Anyang Institute of TechnologyAnyang 455000China Henan Licheng Environmental Technology Co. Ltd.Anyang 455000China State Key Laboratory of Urban Water Resource and Environment School of EnvironmentHarbin Institute of TechnologyHarbin 150090China

The effect of nanoplastics(NPs)on nitrite oxidation bacteria(NOB)community in treating high-strength wastewater remains unclear,which seriously affects the stability of nitrogen removal *** this study,highly active nitrifying sludge was enriched and exposed to 50nm polystyrene NPs(PS-NPs)for short-term(1,100,500,and 1000 mg/L,1.5 hr)and long-term(1,10,100 mg/L,40 days)at high nitrite *** contrast to previous studies,our results showed that the exposures to PS-NPs had little effect on nitrifying *** long-term exposure,the protein/polysaccharide ratios in extracellular polymeric substances(EPS)were positively correlated with PS-NPs concentrations(0.78–0.99).The produced reactive oxygen species(ROS)were gradually removed,and PS-NPs higher than 10 mg/L caused damage to membrane ***-term exposure for 40 days increased the community diversity and caused significant differences between the control and exposed *** control group were dominated by Nitrobacter and Exiguobacterium,while the exposure group was dominated by Bacillus,Mycobacterium,and Nitrospira.A noticeable shift in the NOB community from Nitrobacter(26.5%to 3.4%)to Nitrospira(1.61%to 14.27%)was observed.A KEGG analysis indicated a decrease in cell growth and death,cell motility and energy *** appeared that NOB could adapt to PS-NPs stress through enhanced secretion and removal of oxidative ***,this study provided new insights into the response mechanism of NOB to PS-NPs exposure.

关键词： Nanoplastics Nitrifying activity Extracellular polymeric substance(EPS) Exposure Community analysis

Incombustible solid polymer electrolytes:A critical review and perspective

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Journal of Energy Chemistry 2024年第6期93卷 264-281,I0007页

作者： kai Wu Jin Tan Zhenfang Liu Chenguang Bao Ao Li qi Liu Baohua Li College of Materials Science and Engineering Hunan UniversityChangsha 413000HunanChina Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 055GuangdongChina

Since the advent of the solid-state batteries,employing solid polymer electrolytes(SPEs)to replace routine flammable liquid electrolytes is regarded to be one of the most promising solutions in pursing highenergy-density battery *** with superior thermal stability,good processability,and high mechanical modulus obtain increasing ***,SPE-based batteries are not impenetrable due to their decomposition and combustibility under extreme *** believe incorporating appropriate flame-retardant additives/solvents/fragments into SPEs can intrinsically reduce their flammability to solve the battery safety *** this review,the recent research progress of incombustible SPEs,with special emphasis on flame-retardant structural design,is ***,a brief introduction of flame-retardant mechanism,evaluation index for safety of SPEs,and a detailed overview of the latest advances on diverse-types SPEs in various battery systems are *** deep insight into thermal ru naway process,the free-standing incombustible GPEs,and the ratio nal design of pouch cell structures may be the main directions to motivate revolutionary next-generation for safety batteries.

关键词： Non-flammable electrolyte Solid polymer electrolyte High safety electrolyte Solid state electrolyte Solid state battery

Hybridization-mediated quasiparticle and phonon dynamics in single crystal cerium films

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Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 146-153页

作者： Yunhe Pei Yi Wu kai Hu Zhengxing Wei YiFeng Yang Yang Liu Jingbo qi State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology of ChinaChengdu 611731China Center for Correlated Matter and Department of Physics Zhejiang UniversityHangzhou 310058China Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Songshan Lake Materials Laboratory Dongguan 523808China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China

We report the ultrafast optical pump-probe spectroscopy measurements on the single-crystal cerium *** experimental results of temperature-dependent quasiparticle dynamics reveal development of the hybridization between localized f moments and conduction electrons,i.e.,evolving from fluctuating hybridization to collective *** phonon renormalization is discovered to appear at the emerging temperature(T^(+))of fluctuating hybridization apart from its known presence at the coherent temperature(T^(*)),and can hardly be explained by the mean-field *** quasiparticle relaxation at high temperatures indicates coexistence of nonthermal electron-electron scattering and inelastic Kondo scattering,while its behavior at low temperatures suggests onset ofαphase in theγ-phase dominated *** also extract the indirect gap below T^(*),representing the appearance of collective *** findings provide novel information about the hybridization and phase evolution in the heavy fermion systems.

关键词： cerium quasiparticle dynamics hybridization phonon renormalization

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A Novel Supercapacitor Degradation Prediction Using a 1D Convolutional Neural Network and Improved Informer Model

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Protection and Control of Modern Power Systems 2024年第4期9卷 51-68页

作者： Hao Zhang Zhenxiao Yi Le kang Yi Zhang kai Wang the College of Materials Science and Engineering Xi’an University of Science and Technol-ogyXi’an 710054China the School of Electrical Engineering Qingdao UniversityQingdao 266071China the School of Energy Sciences and Engineering Nanjing Tech UniversityNanjing 211816China

Safety and reliability are crucial for the next-generation supercapacitors used in energy storage systems,while accurate prediction of the degradation trajectory and remaining useful life(RUL)is essential for analyzing degradation and evaluating performance in energy storage *** study proposes a novel data processing and improved one-dimensional convolutional neural network(1D CNN)-informer framework for robust RUL *** data preprocessing,all data from two structures are adjusted to a unified format,and cross-entropy loss is used to couple the 1D CNN and ***,the minimum-maximum feature scaling method is used for normalization to accelerate the training process in reaching the minimum cost function.A relative position encoding algorithm is introduced to improve the Informer model,enabling it to better learn the sequence relationships between data and effectively reduce prediction *** data in dif-ferent working conditions are used to validate the proposed *** with other existing methods,the maximum root mean square error is reduced by 32.71%,the mean absolute error is reduced by 28.50%,and R^(2) is increased by 4.79%.The strategy considers the complementarity between two single models,which can extract features and enrich local details,as well as enhance the model’s global perception *** experimental results demonstrate that the proposed model achieves high-precision and robust RUL prediction,thereby pro-moting the industrial application of supercapacitors.

关键词： Supercapacitors remaining useful life convolution neural network transformer informer

Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery

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Frontiers in Energy 2024年第2期18卷 223-240页

作者： Nan qi kang YAN Yajuan YU Rui LI Rong HUANG Lai CHEN Yuefeng SU Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China Department of Energy and Environmental Materials School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Electric Vehicle Co. Ltd.Beijing 100176China

As the intersection of disciplines deepens,the field of battery modeling is increasingly employing various artificial intelligence(AI)approaches to improve the efficiency of battery management and enhance the stability and reliability of battery *** paper reviews the value of AI methods in lithium-ion battery health management and in particular analyses the application of machine learning(ML),one of the many branches of AI,to lithium-ion battery state of health(SOH),focusing on the advantages and strengths of neural network(NN)methods in ML for lithium-ion battery SOH simulation and *** is one of the important branches of ML,in which the application of NNs such as backpropagation NN,convolutional NN,and long short-term memory NN in SOH estimation of lithium-ion batteries has received wide *** so far have shown that the utilization of NN to model the SOH of lithium-ion batteries has the advantages of high efficiency,low energy consumption,high robustness,and scalable *** the future,NN can make a greater contribution to lithium-ion battery management by,first,utilizing more field data to play a more practical role in health feature screening and model building,and second,by enhancing the intelligent screening and combination of battery parameters to characterize the actual lithium-ion battery SOH to a greater *** in-depth application of NN in lithium-ion battery SOH will certainly further enhance the science,reliability,stability,and robustness of lithium-ion battery management.

关键词： machine learning lithium-ion battery state of health neural network artificial intelligence