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Reverse modulation of defect density of Ce-MOF-808 by solventassisted ligand exchange for dicyclopentadiene hydrogenation

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Science China Chemistry 2025年

作者： Danfeng Zhao Fajie Hu Rushuo Li Xinmeng Xu Zhaokun Wang Zuoshuai Xi jun tong Xiubing Huang Ge Wang Advanced Innovation Center for Materials Genome Engineering Beijing Key Laboratory of Function Materials for Molecule & Structure Construction School of Materials Science and Engineering University of Science and Technology Beijing

Defect engineering is a pivotal strategy for tailoring the electronic structure and physicochemical properties of catalysts, yet the straightforward manipulation of defect density in porous materials presents a current challenge. In this work, we achieved precise control over the coordination unsaturated site（CUS） content and pore architecture of Ce-MOF-808 by employing 2-fluorobenzoic acid（2-FBA） as a modifier. Leveraging the p Kadisparities among three ligands（1,3,5-tricarboxylic benzoic acid,formic acid, and 2-FBA）, we preserved the spn topology of Ce-MOF within an aqueous system, while realizing partial substitution of the auxiliary ligands and saturation of the CUS. The amount of 2-FBA was negatively correlated with the number of ligand defects, and the consequent decrease in Ce3+content and the increase in the number of ligand linkages also induced crystal structure transformation. The modulation of the defect structure was correlated with the catalytic performance of dicyclopentadiene（DCPD） hydrogenation reaction, in which Ce-MMF0.15, constructed by the modulation of 0.15 mol amount of 2-fluorobenzoic acid, exhibited an optimal ligand defect density and micro-mesoporous structure, enabling almost complete conversion of DCPD at 100 ℃ and 2 MPa. This article also elucidates the correlation between the regulation of defect density and the accessibility of frustrated Lewis pair（FLP） active sites, guiding the application of novel porous intrinsic FLP materials in hydrogenation catalysis.

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Application of Wavelets Transform to Fault Detection in Rotorcraft UAV Sensor Failure

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Journal of Bionic Engineering 2007年第4期4卷 265-270页

作者： jun-tong Qi Jian-da Han Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 P. R. China Graduate School Chinese Academy of Sciences Beijing 100049 P. R. China

This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcrafi Unmanned Aerial Vehicle （RUAV） sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.

关键词： RUAV wavelet transform fault detection sensor failure

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Modeling of laser adjustment for large diameter tubes using robotic kinematic theories

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Advances in Manufacturing 2018年第4期6卷 401-408页

作者： Pin Li jun-tong Xi School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 People's Republic of China School of Mechanical Engineering Jiangsu University Zhenjiang 212013 Jiangsu Province People's Republic of China

Laser adjustment is a new technique that employs laser forming processes to align components along specific directions. To develop a laser adjustment solution with a minimal number of bends, herein, a new modeling and calculation method that uses robotic kinematic theories is introduced. A numerical example and the corresponding laser adjustment solution are presented. The simulation results suggest that a straight tube with a flange connector can be adjusted to match the corresponding connector with three bends. Finally, the simulation results were verified using experiments. The maximum deviation was approximately 0.4 mm and the deviation of the flange connector was smaller, showing that a good adjustment quality could be achieved using the specific adjustment solution.

关键词： Laser adjustment Large diameter tube Robotic kinematics theories Production of exponential formula

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Synthesis and Crystal Structure of a New Complex [CuL(Phen)]·NO_3

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Chinese Journal of Structural Chemistry 2006年第11期25卷 1343-1346页

作者： QIU Xiao-Hang ZHAO jun tong Xiao-Lan Department of Chemistry Nankai University Tianjin 300071 China

A new mononuclear copper（Ⅱ） complex [CuL（Phen）]-NO3 （L - 2-{2-[（3,5-dibro- mosalicylidene）amino]ethyl }- 1 H- 1,3-benzimidazole, Phen = 1,10-phenanthroline） has been synthesized and its crystal structure was determined by X-ray diffraction method. It crystallizes in monoclinic, space group C2/c with a = 24.966（7）, b = 15.673（4）, c = 16.600（5） A,β = 123.981（4）°, C28H20Br2CuN604, Mr = 727.86, V = 5386（2） A^3, Z = 8, Dc = 1.795 g/cm^3,μ（MoKα = 3.826 mm^-1, F（000） = 2888, the final R = 0.0508 and wR = 0.1024 for 5440 independent reflections with Rint = 0.1134. The title compound is composed of [CuL（Phen）]＋ cation and NO3^- anion. The coordination geometry around copper atom is a highly distorted trigonal bipyramid consisting of one benzimidazole nitrogen atom, one phenolato oxygen atom and one phenanthroline nitrogen atom on the equatorial plane together with one imine nitrogen atom and one phenanthroline nitrogen atom occupying the axial positions. The hydrogen bonding and π-π stacking interactions link the copper complex molecules into a 3-D supramolecular structure.

关键词： crystal structure copper complex 1,10-phenanthroline hydrogen bonds

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Host load prediction in cloud based on classification methods

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The Journal of China Universities of Posts and Telecommunications 2014年第4期21卷 40-46页

作者： tong jun-jie E Hai-hong SONG Mei-na SONG jun-de chool of Computer Science Beijing University of Posts and Telecommunications

The host load prediction problem in cloud computing has also been received much attention. To solve this problem, we have to use the historical load data to predict the future load level. Accurate prediction methods are useful for host load balance and virtual machine migration. Although cloud is likely to grids at some extent, the length of tasks are much shorter and host loads change more frequently with higher noise. The above characteristics introduce challenges for host load prediction. In this paper, based on the proposed exponentially segmented pattern and the corresponding transformation, prediction problem is transformed into the traditional classification problem, This classification problem can be solved based on the traditional methods, and features are given for training the classification model. For achieving accurate prediction, a new feature periodical coefficient is introduced and some existed classification methods are implemented. Experiments on the real world dataset invalidate the efficiency of the new proposed feature, which is in the most effective combinations of features, it increases successful rate （SR） 1.33%-2.82% and decreases the mean square error （MSE） 1.37%-2.91%. And the results also show that support vector machine （SVM） method can achieve nearly the same performance as the Bayes methods and their performance is about 50% higher in successful rate and 17% better in the mean square error compared to the existed methods.

关键词： cloud computing host load exponentially segmented pattern load prediction classification

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Adaptive semi-empirical model for non-contact atomic force microscopy

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Chinese Physics B 2022年第8期31卷 682-687页

作者： Xi Chen jun-Kai tong Zhi-Xin Hu Center for Joint Quantum Studies and Department of Physics Institute of ScienceTianjin UniversityTianjin 300350China State Key Laboratory of Precision Measuring Technology and Instruments Tianjin UniversityTianjin 300072China

Non-contact atomic force microscope is a powerful tool to investigate the surface topography with atomic *** we propose a new approach to estimate the interaction between its tips and samples,which combines a semi-empirical model with density functional theory(DFT)*** generated frequency shift images are consistent with the experiment for mapping organic molecules using CuCO,Cu,CuCl,and CuO_(x)*** approach achieves accuracy close to DFT calculation with much lower computational cost.

关键词： semi-empirical model atomic force microscopy density functional theory functionalized tips

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Nonparametric Estimation of Extreme Conditional Quantiles with Functional Covariate

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Acta Mathematica Sinica,English Series 2018年第10期34卷 1589-1610页

作者： Feng Yang HE Ye Bin CHENG Tie jun tong Department of Statistics Ji'nan University Guangzhou 510632 P. R. China Glorious Sun School of Business and Management Donghua University Shanghai 250001 P. R. China Department of Mathematics Hong Kong Baptist University Hong Kong P. R. China

Estimation of the extreme conditional quantiles with functional covariate is an important problem in quantile regression. The existing methods, however, are only applicable for heavy-tailed distributions with a positive conditional tail index. In this paper, we propose a new framework for estimating the extreme conditional quantiles with functional covariate that combines the nonparametric modeling techniques and extreme value theory systematically. Our proposed method is widely applicable, no matter whether the conditional distribution of a response variable Y given a vector of functional covariates X is short, light or heavy-tailed. It thus enriches the existing literature.

关键词： Extreme conditional quantile extreme value theory nonparametric modeling functional covariate

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Joint Limit Distributions of Exceedances Point Processes and Partial Sums of Gaussian Vector Sequence

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Acta Mathematica Sinica,English Series 2012年第8期28卷 1647-1662页

作者： Zuo Xiang PENG Jin jun tong Zhi Chao WENG School of Mathematics and Statistics Southwest University Department of Actuarial Science Faculty of Business and EconomicsUniversity of LausanneUNIL-Dorigny 1015 LausanneSwitzerland

In this paper, we study the joint limit distributions of point processes of exceedances and partial sums of multivariate Gaussian sequences and show that the point processes and partial sums are asymptotically independent under some mild conditions. As a result, for a sequence of standardized stationary Gaussian vectors, we obtain that the point process of exceedances formed by the sequence （centered at the sample mean） converges in distribution to a Poisson process and it is asymptotically independent of the partial sums. The asymptotic joint limit distributions of order statistics and partial sums are also investigated under different conditions.

关键词： Multivariate Gaussian sequence exceedances point process partial sum order statistic joint limit distribution

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Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation

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Frontiers of Information Technology & Electronic Engineering 2018年第4期19卷 471-480页

作者： Ji-jun tong Peng ZHANG Yu-xiang WENG Dan-hua ZHU School of lnformation Science and Technology Zhejiang Sci-Tech UniversityHangzhou 310018China Department of Neurosurgery The First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310003China State Key Laboratory for Diagnosis and Treatment of lnfectious Diseases Collaborative Innovation Center for Diagnosis and Treatment of Infectious DiseasesThe First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310003China

The segmentation of brain tumor plays an important role in diagnosis, treatment planning, and surgical simulation. The precise segmentation of brain tumor can help clinicians obtain its location, size, and shape information. We propose a fully automatic brain tumor segmentation method based on kernel sparse coding. It is validated with 3D multiple-modality magnetic resonance imaging(MRI). In this method, MRI images are pre-processed first to reduce the noise, and then kernel dictionary learning is used to extract the nonlinear features to construct five adaptive dictionaries for healthy tissues, necrosis, edema, non-enhancing tumor, and enhancing tumor tissues. Sparse coding is performed on the feature vectors extracted from the original MRI images, which are a patch of m×m×m around the voxel. A kernel-clustering algorithm based on dictionary learning is developed to code the voxels. In the end, morphological filtering is used to fill in the area among multiple connected components to improve the segmentation quality. To assess the segmentation performance, the segmentation results are uploaded to the online evaluation system where the evaluation metrics dice score, positive predictive value(PPV), sensitivity, and kappa are used. The results demonstrate that the proposed method has good performance on the complete tumor region(dice: 0.83; PPV: 0.84; sensitivity: 0.82), while slightly worse performance on the tumor core(dice: 0.69; PPV: 0.76; sensitivity: 0.80) and enhancing tumor(dice: 0.58; PPV: 0.60; sensitivity: 0.65). It is competitive to the other groups in the brain tumor segmentation challenge. Therefore, it is a potential method in differentiation of healthy and pathological tissues.

关键词： Brain tumor segmentation Kernel method Sparse coding Dictionary learning

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Reduction in Microsegregation in Al-Cu Alloy by Alternating Magnetic Field

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Acta Metallurgica Sinica(English Letters) 2020年第2期33卷 267-274页

作者： Sheng-Ya He Chuan-jun Li tong-jun Zhan Wei-Dong Xuan Jiang Wang Zhong-Ming Ren State Key Laboratory of Advanced Special Steel and School of Materials Science and Engineering Shanghai UniversityShanghai 200444China Helmholtz-Zentrum Dresden-Rossendorf(HZDR) 01328 DresdenGermany

The microsegregation behavior of the Al-4.5 wt%Cu alloy solidified at different cooling rates under the alternating magnetic field(AMF) was *** experimental results showed that the amount of non-equilibrium eutectics in the interdendritic region decreased upon applying the AMF at the same cooling *** change in microsegregation could be explained quantificationally by the modifications of dendritic coarsening,solid-state back diffusion and convection in the *** enhanced diffusivity in the solid owing to the AMF was beneficial for the improvement in microsegregation compared to the cases without an *** contrast,the enhanced dendritic coarsening and forced convection in the AMF were found to aggravate the microsegregation *** the contributions of the changes in above factors,an increase in solid diffusivity was found to be primarily responsible for the reduced microsegregation in the *** addition,the microsegregation in the AMF was modeled using the analytical model developed by *** calculated and experimental results were in reasonable agreement.

关键词： Microsegregation Solidification Alternating magnetic field Diffusion Coarsening Convection

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