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Optimized the vanadium electrolyte with sulfate-phosphoric mixed acids to enhance the stable operation at high-temperature

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Frontiers of Chemical Science and Engineering 2024年第2期18卷 13-26页

作者： ling Ge tao Liu Yimin Zhang Hong Liu School of Resource and Environmental Engineering Wuhan University of Science and TechnologyWuhan 430081China State Environmental Protection Key Laboratory of Mineral Metallurgical Resources Utilization and Pollution Control Wuhan University of Science and TechnologyWuhan 430081China Hubei Collaborative Innovation Center for High Efficient Utilization of Vanadium Resources Wuhan University of Science and TechnologyWuhan 430081China Hubei Provincial Engineering Technology Research Center of High Efficient Cleaning Utilization for Shale Vanadium Resource Wuhan University of Science and TechnologyWuhan 430081China School of Resource and Environmental Engineering Wuhan University of TechnologyWuhan 430070China

Herein, the influence of the concentration design and comprehensive performance of the sulfate-phosphoric mixed acid system electrolyte is investigated to realize an electrolyte that maintains high energy density and stable operation at high temperatures. Static stability tests have shown that VOPO4 precipitation occurs only with vanadium(V) electrolyte. The concentration of vanadium ion of 2.0–2.2 mol·L^(–1), phosphoric acid of 0.10–0.15 mol·L^(–1), and sulfuric acid of 2.5–3.0 mol·L^(–1) are suitable for a vanadium redox flow battery in the temperature range from –20 to 50 ℃. The equations for predicting the viscosity and conductivity of electrolytes are obtained by the response surface method. The optimized electrolyte overcomes precipitation generation. It has 2.8 times higher energy density than the non-phosphate electrolyte, and a coulomb efficiency of 94.0% at 50 ℃. The sulfate-phosphoric mixed acid system electrolyte promotes the electrode reaction process, increases the current density, and reduces the resistance. This work systematically optimizes the concentrations of composition of positive and negative vanadium electrolytes with mixed sulfate-phosphoric acid. It provides a basis for the different valence states and comprehensive properties of sulfate-phosphoric mixed acid system vanadium electrolytes under extreme environments, guiding engineering applications.

关键词： all vanadium redox flow battery mixed-acid vanadium electrolyte concentration optimization response surface methodology high-temperature stability

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Editable semiconductor photo-electrodes for sustainable ammonia synthesis

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Nano Research 2024年第4期17卷 3107-3112页

作者： Ning Lan Kun Du Erling Zhao Wei Zhao tao ling Key Laboratory for Advanced Ceramics and Machining Technology of Ministry of Education Institute of New-EnergySchool of Materials Science and EngineeringTianjin UniversityTianjin 300072China School of Materials Science and Engineering Tianjin Chengjian UniversityTianjin 300384China

Powered by an inexhaustible supply of solar energy,photoelectrochemical(PEC)nitrogen reduction reaction(NRR)provides an ideal solution for the synthesis of green ammonia(NH_(3)).Although great efforts have been made in the past decades,there are still significant challenges in increasing the NH_(3) yields of the PEC-NRR *** addition to the issues of low activity and selectivity similar to electrochemical NRR,the progress of PEC-NRR is also impeded by the limited increase in NH_(3) yields as the electrode is ***,we propose an editable electrode design strategy that parallels unit photo-electrodes to achieve a linear increase in NH_(3) yields with electrode active *** demonstrate that the editable electrode design strategy minimizes the electrode charge transfer resistance,allowing more photo-generated carriers to reach the electrode surface and promote the catalytic *** believe that this editable electrode design strategy provides an avenue to achieve sustainable PEC NH_(3) production.

关键词： editable electrode photoelectrochemical nitrogen reduction reaction parallel electrode ZnSe

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Feedback linearization and equivalent-disturbance compensation control strategy for piezoelectric stage

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Nanotechnology and Precision Engineering 2024年第2期7卷 49-59页

作者： tao Huang Yingbin Wang Zhihong Luo Huajun Cao Guibao tao Mingxiang ling State Key Laboratory of Mechanical Transmissions for Advanced Equipment Chongqing UniversityChongqing 400044China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China Hongdu Aviation Industry Group NanchangJiangxi 330000China Robotics and Microsystems Center Soochow UniversitySuzhou 215123China

Piezoelectric stages use piezoelectric actuators and flexure hinges as driving and amplifying mechanisms,*** systems have high positioning accuracy and high-frequency responses,and they are widely used in various precision/ultra-precision positioning ***,the main challenge with these devices is the inherent hysteresis nonlinearity of piezoelectric actuators,which seriously affects the tracking accuracy of a piezoelectric *** by this challenge,in this work,we developed a Hammerstein model to describe the hysteresis nonlinearity of a piezoelectric *** particular,in our proposed scheme,a feedback-linearization algorithm is used to eliminate the static hysteresis *** addition,a composite controller based on equivalent-disturbance compensation was designed to counteract model uncertainties and external *** analysis of the stability of a closed-loop system based on this feedback-linearization algorithm and composite controller was performed,and this was followed by extensive comparative experiments using a piezoelectric stage developed in the *** experimental results confirmed that the feedback-linearization algorithm and the composite controller offer improved linearization and trajectory-tracking performance.

关键词： Piezoelectric stage Hysteresis nonlinearity Feedback linearization Equivalent-disturbance compensation

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Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1786-1801页

作者： Sheng Qi Rui Wang tao Zhang Weixiong Huang Fan Yu ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China College of Systems Engineering National University of Defense TechnologyChangsha 410073and also with the Xiangjiang LaboratoryChangsha 410205China College of Transportation and Engineering Central South UniversityChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and ***,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational ***,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables *** paper is dedicated to addressing the challenges posed by *** start,we introduce innovative objective functions customized to mine maximum and minimum candidate *** substantial enhancement dramatically improves the efficacy of frequent pattern *** this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific ***,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero *** novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function *** extensively tested our algorithm across eight benchmark problems and four real-world *** results demonstrate that our approach achieves competitive solutions across various challenges.

关键词： Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.

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A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1342-1357页

作者： Sheng Qi Rui Wang tao Zhang Xu Yang Ruiqing Sun ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Xiangjiang Laboratory Changsha 410205China College of Computer National University of Defense TechnologyChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China IEEE

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are *** a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec ***,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables ***,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is *** data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between *** by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these *** mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast ***-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

关键词： Evolutionary algorithms learning swarm optimiza-tion sparse large-scale optimization sparse large-scale multi-objec-tive problems two-layer encoding.

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MCM-41 Prepared with Ionic Liquid and Cethytrimethylammonium Bromide as Co-templates

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Journal of Wuhan University of Technology(Materials Science) 2009年第1期24卷 25-29页

作者：张光旭 School of Chemical Engineering Wuhan University of Technology College of Chemistry and Molecular sciences Wuhan University

The mesoporous molecular sieves MCM-41 were prepared using room tempera-ture ionic liquid （RTIL） synthesized in laboratory and cethytrimethylammonium bromide （CTAB） as compound templates for the first time. They were prepared under low aging temperature and short aging time. Via characterizing by XRD and nitrogen adsorption instrument, MCM-41 synthesized by this new method exhibited good crystal structure and narrow pore distribution. The following pre-paratory conditions was optimal： the molar ratio of RTIL to CTAB was 1.0∶1.0, aging at 80 ℃, for 40 h and calcined at 540 ℃. It is found that the acidified MCM-41 improves its activity as catalyst over the unmodified ones.

关键词： mesoporous molecular sieve hydrothermal crystallization co-templates ionicliquid MCM-41

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LaMnO_(3)/Co_(3)O_(4) nanocomposite for enhanced triethylamine sensing properties

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Journal of Rare Earths 2024年第4期42卷 733-742页

作者： Jian Zhang Yanping Chen ling Li Xue Chen Wenya An Xiujuan Qian Yuye tao School of Science Shandong Jianzhu UniversityJinan250100China

LaMnO_(3) modified Co_(3)O_(4) nanocomposites were prepared by simple hydrothermal method co mbined with sol-gel *** gas sensitivity properties of pure Co_(3)O_(4) and LaMnO_(3)/Co_(3)O_(4) with different composite proportions are *** is found that 0.6-LMO/Co_(3)O_(4) sensor has higher sensitivity to triethylamine(TEA)than pure Co_(3)O_(4) sensor,which is improved by 9.27 *** the working temperature is reduced from 150 to 130℃.Besides,it has excellent gas selectivity and *** improvement of the gas sensitivity of LaMnO_(3)/Co_(3)O_(4) sensor may be due to the fact that LaMnO_(3) is an effective catalyst,and the catalytic performance perhaps is beneficial to improving the sensing *** addition,the formation of p-p heterojunctions may be the key factor to improve the gas sensing *** work provides a new Co_(3)O_(4)-based gas sensing material for the detection of TEA.

关键词： Gas sensing Co_(3)O_(4) LaMnO_(3) Triethylamine Rareearths

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Clustering for Bivariate Functional Data

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 613-629页

作者： Shi-yun CAO Yan-qiu ZHOU Yan-ling WAN tao ZHANG School of Science Guangxi University of Science and TechnologyLiuzhou 545006China School of Marxism Guangxi University of Science and TechnologyLiuzhou 545006China Key Laboratory of Intelligent Information Processing and Graph Processing Guangxi University of Science and TechnologyLiuzhou 545006China

In this paper,we consider the clustering of bivariate functional data where each random surface consists of a set of curves recorded repeatedly for each *** k-centres surface clustering method based on marginal functional principal component analysis is proposed for the bivariate functional data,and a novel clustering criterion is presented where both the random surface and its partial derivative function in two directions are *** addition,we also consider two other clustering methods,k-centres surface clustering methods based on product functional principal component analysis or double functional principal component *** results indicate that the proposed methods have a nice performance in terms of both the correct classification rate and the adjusted rand *** approaches are further illustrated through empirical analysis of human mortality data.

关键词： bivariate functional data -centres surface clustering functional principal component analysis partial derivative function

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Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li tao Zhang ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

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Impact of next-generation sequencing on antimicrobial treatment in immunocompromised adults with suspected infections

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World Journal of Emergency Medicine 2024年第2期15卷 105-110页

作者： Jia Li Jiazhen Luo tao Hu ling Cheng Weiwei Shang Li Yan Department of Intensive Care Unit Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China Department of Emergency Medicine Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China Tongji Medical College Huazhong University of Science and TechnologyWuhan 430030China Department of Geriatrics Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China

BACKGROUND:Prompt pathogen identification can have a substantial impact on the optimization of antimicrobial *** objective of the study was to assess the diagnostic value of next-generation sequencing(NGS)for identifying pathogen and its clinical impact on antimicrobial intervention in immunocompromised patients with suspected ***:This was a retrospective *** January and August 2020,47 adult immunocompromised patients underwent NGS testing under the following clinical conditions:1)prolonged fever and negative conventional cultures;2)new-onset fever despite empiric antimicrobial treatment;and 3)afebrile with suspected infections on *** data,including conventional microbial test results and antimicrobial treatment before and after NGS,were *** were analyzed according to documented changes in antimicrobial treatment(escalated,no change,or deescalated)after the NGS ***:The median time from hospitalization to NGS sampling was 19 *** relevant pathogens were detected via NGS in 61.7% of patients(29/47),more than half of whom suffered from fungemia(n=17),resulting in an antimicrobial escalation in 53.2% of patients(25/47)and antimicrobial de-escalation in 0.2% of patients(1/47).Antimicrobial changes were mostly due to the identification of fastidious organisms such as Legionella,Pneumocystis jirovecii,and *** the remaining three cases,NGS detected clinically relevant pathogens also detected by conventional cultures a few days *** antimicrobial treatment was subsequently adjusted according to the susceptibility test ***,NGS changed antimicrobial management in 55.3%(26/47)of patients,and conventional culture detected clinically relevant pathogens in 14.9% of the patients(7/47).CONCLUSION:With its rapid identification and high sensitivity,NGS could be a promising tool for identifying relevant pathogens and enabling rapid appropriate treatment in immunocompromised patients w

关键词： Immunocompromised patients Next-generation sequencing Antimicrobial management

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