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Recent progress in single-molecule fluorescence technology in nanocatalysis

Nano Research 2022年第12期15卷 10316-10327页

作者： Jing Cao Dezheng Zhang Weilin Xu State Key Laboratory of Electroanalytical Chemistry and Jilin Province Key Laboratory of Low Carbon Chemical Power Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China University of Science and Technology of China Hefei230026China

Nanoparticles(NPs)play a vital role in the energy catalysis process,so understanding the heterogeneous catalytic properties of nanocatalysts is of great significance for rationally guiding the design of catalysts.However,the traditional method obtains the average information based on the whole and cannot study the catalytic activity of a single nanoparticle.It is critical to investigate the catalytic activity of individual nanoparticles using in situ techniques.This review summarizes some of Prof.Xu's recent accomplishments in studying the catalytic behavior of nanoparticles at the single-particle level using single-molecule fluorescence microscopy(SMFM).These achievements include revealing the effect of size,shape,and surface atoms of Pd nanoparticles on catalytic kinetics and dynamics as well as obtaining the activation energy of single Au nanoparticles for catalytic reactions by single-molecule methods.It is the first time to study the kinetics and dynamics of single-atom Pt catalysts.Furthermore,the method was extended to study the Pt deactivation process for hydrogen oxidation reactions as well as the catalytic kinetics of two-electron oxygen reduction reactions of individual Fe3O4 nanoparticles in electrocatalysis.Finally,single-molecule super-resolution techniques were used to observe the evolution of the activity of single Sb doped TiO2 nanorod domains.These studies are of guiding significance for in-depth understanding and realization of rational design of optimal catalysts.

关键词： single-molecule fluorescence microscopy nanocatalysis kinetics and dynamics activation energy electrocatalysis super-resolution imaging

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Heterostructured Pt-Ni_(3)Mo_(3)N formed via ammonia-containing polyoxometalates for highly efficient electrocatalytic hydrogen evolution in acid medium

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Journal of Energy Chemistry 2024年第5期92卷 698-704页

作者： Bianqing Ren Xue Gong Jing Cao Dezheng Zhang Zizhun Wang Ping Song Ce Han Weilin Xu State Key Laboratory of Electroanalytical Chemistry Jilin Province Key Laboratory of Low Carbon Chemical PowerChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022JilinChina School of Applied Chemistry and Engineering University of Science and Technology of ChinaHefei 230026AnhuiChina Key Laboratory of Automobile Materials MOE School of Materials Science&EngineeringJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsElectron Microscopy Centerand International Center of Future ScienceJilin UniversityChangchun 130012JilinChina

Constructing heterostructured nanohybrid is considered as a prominent route to fabricate alternative electrocatalysts to commercial Pt/C for hydrogen evolution reaction(HER).In this work,(NH_(4))_(4)[NiH_(6)Mo_(6)O_(4)]·5H_(2)O polyoxometalates(NiMo_(6))are adopted as the cluster precursors for simple fabrication of heterostructured Pt-Ni_(3)Mo_(3)N nanohybrids supported by carbon black(Pt-Ni_(3)Mo_(3)N/C)without using additional N sources.The improved porosity and enhanced electronic interaction of Pt-Ni_(3)Mo_(3)N/C should be attributed to the integration of Pt with NiMo_(6),which favors the mass transport,promotes the formation of exposed catalytic sites,and benefits the regulation of intrinsic activity.Thus,the as-obtained Pt-Ni_(3)Mo_(3)N/C exhibits impressive and durable HER performance as indicated by the low overpotential of 13.7 mV at the current density of 10 mA cm^(-2) and the stable overpotential during continuous working at 100 mA cm^(-2) for 100 h.This work provides significant insights for the synthesis of new highly active heterostructured electrocatalysts for renewable energy devices.

关键词： Polyoxometalates Cluster precursors Heterostructured nanohybrids Hydrogen evolution reaction Electrocatalysis

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Layout design of thin-walled structures with lattices and stiffeners using multi-material topology optimization

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Chinese Journal of Aeronautics 2023年第4期36卷 496-509页

作者： Yang LI Tong GAO Qianying ZHOU Ping CHEN dezheng YIN Weihong zhang State IJR Center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical UniversityXi’an 710072China Institute of Intelligence Material and Structure Unmanned System TechnologiesNorthwestern Polytechnical UniversityXi’an 710072China Beijing Aerospace Technology Institute Beijing 100074China Beijing Institute of Long March Space Vehicle Beijing 100076China

In this paper,the thin-walled structures with lattices and stiffeners manufactured by additive manufacturing are investigated.A design method based on the multi-material topology optimization is proposed for the simultaneous layout optimization of the lattices and stiffeners in thin-walled structures.First,the representative lattice units of the selected lattices are equivalent to the virtual homogeneous materials whose effective elastic matrixes are achieved by the energy-based homogenization method.Meanwhile,the stiffeners are modelled using the solid material.Subsequently,the multi-material topology optimization formulation is established for both the virtual homogeneous materials and solid material to minimize the structural compliance under mass constraint.Thus,the optimal layout of both the lattices and stiffeners could be simultaneously attained by the optimization procedure.Two applications,the aircraft panel structure and the equipment mounting plate,are dealt with to demonstrate the detailed design procedure and reveal the effect of the proposed method.According to numerical comparisons and experimental results,the thin-walled structures with lattices and stiffeners have significant advantages over the traditional stiffened thin-walled structures and lattice sandwich structures in terms of static,dynamic and anti-instability performance.

关键词： Layout design Thin walled structures Topology optimization Lattice Stiffener

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Auxiliary Diagnosis Based on the Knowledge Graph of TCM Syndrome

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Computers, Materials & Continua 2020年第10期65卷 481-494页

作者： Yonghong Xie Liangyuan Hu Xingxing Chen Jim Feng Dezheng Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China Amphenol Global Interconnect Systems San JoseCA 95131USA

As one of the most valuable assets in China,traditional medicine has a long history and contains pieces of knowledge.The diagnosis and treatment of Traditional Chinese Medicine(TCM)has benefited from the natural language processing technology.This paper proposes a knowledge-based syndrome reasoning method in computer-assisted diagnosis.This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path.According to this reasoning path,we could infer the path from the symptoms to the syndrome and get all possibilities via the relationship between symptoms and causes.Moreover,this study applies the Term Frequency-Inverse Document Frequency(TF-IDF)idea to the computer-assisted diagnosis of TCM for the score of syndrome calculation.Finally,combined with symptoms,syndrome,and causes,the disease could be confirmed comprehensively by voting,and the experiment shows that the system can help doctors and families to disease diagnosis effectively.

关键词： Knowledge graph reinforcement learning auxiliary diagnosis inference path

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A Heterogeneous Ensemble of Extreme Learning Machines with Correntropy and Negative Correlation

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Tsinghua Science and Technology 2017年第6期22卷 691-701页

作者： Adnan O.M.Abuassba Yao zhang Xiong Luo Dezheng Zhang Wulamu Aziguli School of Computer and Communication Engineering University of Science and Technology Beijing(USTB)Beijing 100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China School of Engineering New York UniversityBrooklynNY 11201USA

The Extreme Learning Machine（ELM） is an effective learning algorithm for a Single-Layer Feedforward Network（SLFN）. It performs well in managing some problems due to its fast learning speed. However, in practical applications, its performance might be affected by the noise in the training data. To tackle the noise issue, we propose a novel heterogeneous ensemble of ELMs in this article. Specifically, the correntropy is used to achieve insensitive performance to outliers, while implementing Negative Correlation Learning（NCL） to enhance diversity among the ensemble. The proposed Heterogeneous Ensemble of ELMs（HE2 LM） for classification has different ELM algorithms including the Regularized ELM（RELM）, the Kernel ELM（KELM）, and the L2-norm-optimized ELM（ELML2）. The ensemble is constructed by training a randomly selected ELM classifier on a subset of the training data selected through random resampling. Then, the class label of unseen data is predicted using a maximum weighted sum approach. After splitting the training data into subsets, the proposed HE2 LM is tested through classification and regression tasks on real-world benchmark datasets and synthetic datasets. Hence, the simulation results show that compared with other algorithms, our proposed method can achieve higher prediction accuracy, better generalization, and less sensitivity to outliers.

关键词： Extreme Learning Machine（ELM） ensemble classification correntropy negative correlation

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Neural Dialogue Model with Retrieval Attention for Personalized Response Generation

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Computers, Materials & Continua 2020年第1期62卷 113-122页

作者： Cong Xu Zhenqi Sun Qi Jia Dezheng Zhang Yonghong Xie Alan Yang School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science University of Science and Technology BeijingBeijing100083China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Amphenol AssembleTech HoustonTX 77070US

With the success of new speech-based human-computer interfaces,there is a great need for effective and friendly dialogue agents that can communicate with people naturally and continuously.However,the lack of personality and consistency is one of critical problems in neural dialogue systems.In this paper,we aim to generate consistent response with fixed profile and background information for building a realistic dialogue system.Based on the encoder-decoder model,we propose a retrieval mechanism to deliver natural and fluent response with proper information from a profile database.Moreover,in order to improve the efficiency of training the dataset related to profile information,we adopt a method of pre-training and adjustment for general dataset and profile dataset.Our model is trained by social dialogue data from Weibo.According to both automatic and human evaluation metrics,the proposed model significantly outperforms standard encoder-decoder model and other improved models on providing the correct profile and high-quality responses.

关键词： Dialogue system LSTM encoder-decoder model attention mechanism

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A Soft Sensor with Light and Efficient Multi-scale Feature Method for Multiple Sampling Rates in Industrial Processing

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Machine Intelligence Research 2024年第2期21卷 400-410页

作者： dezheng Wang Yinglong Wang Fan Yang Liyang Xu Yinong zhang Yiran Chen Ning Liao School of Automation Southeast UniversityNanjing 210096China Software and Artificial Intelligence College Chongqing Institute of EngineeringChongqing 400056China Beijing National Research Center for Information Science and Technology(BNRist) Department of AutomationTsinghua UniversityBeijing 100084China Liangjiang International College Chongqing University of TechnologyChongqing 401135China Smart City College Beijing Union UniversityBeijing 100101China

In industrial process control systems,there is overwhelming evidence corroborating the notion that economic or technical limitations result in some key variables that are very difficult to measure online.The data-driven soft sensor is an effective solution because it provides a reliable and stable online estimation of such variables.This paper employs a deep neural network with multiscale feature extraction layers to build soft sensors,which are applied to the benchmarked Tennessee-Eastman process(TEP)and a real wind farm case.The comparison of modelling results demonstrates that the multiscale feature extraction layers have the following advantages over other methods.First,the multiscale feature extraction layers significantly reduce the number of parameters compared to the other deep neural networks.Second,the multiscale feature extraction layers can powerfully extract dataset characteristics.Finally,the multiscale feature extraction layers with fully considered historical measurements can contain richer useful information and improved representation compared to traditional data-driven models.

关键词： Multi-scale feature extractor deep neural network(DNN) multirate sampled industrial processes prediction

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Relationships between In SAR Seismic Deformation and Fault Motion Sense,Fault Strike,and Ascending/Descending Modes

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Acta Geologica Sinica(English Edition) 2017年第1期91卷 93-108页

作者： QU Chunyan SHAN Xinjian ZHAO dezheng zhang Guohong SONG Xiaogang Key Laboratory of Earthquake Dynamics Institute of Geology China Earthquake Administration Beijing 100029

Based on the working principle of satellite radars, the earthquake deformation field measured by interferometric synthetic aperture（InSAR） is the projection of ground displacement associated with the seismogenic fault in the line of sight（LOS） of the satellite. However, LOS projections are complex, and are not only related to the ascending/descending modes and incidence angles of SAR data, but also related to the strike and motion senses of the fault. Even for the same earthquake, the LOS deformation derived from different ascending/descending data can be almost identical in one case, but quite different in another case, which makes the interpretation of InSAR seismic deformation and its comparison with field observations difficult. In this study, we undertook a quantitative analysis of the relationships between LOS observation sensitivity of InSAR and fault strike, fault motion sense, and ascending/descending modes, as well as 3D deformation fields. We studied the features and differences of the LOS deformation fields in different types of earthquakes using ascending/descending modes, with a particularly detailed analysis of the relations for a strikeslip type of earthquake. We also summarized the characteristics of LOS deformation fields of faults with different strikes and optimal observational data modes. Taking the strike-slip Yushu earthquake and the normal Gaize event as examples, we used SAR data of the ascending/descending modes to verify the results of quantitative calculations. These analyses will not only provide a more reasonable interpretation of InSAR seismic deformation fields and but also help understand the differences of seismic deformation fields revealed by data with different observational modes, therefore promoting the application of InSAR technology in seismology.

关键词： InSAR fault earthquake deformation ascending/descending modes

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Classification with ensembles and case study on functional magnetic resonance imaging

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Digital Communications and Networks 2022年第1期8卷 80-86页

作者： Adnan OM.Abuassba zhang dezheng Hazrat Ali Fan zhang Khan Ali Department of Computer Science Arab Open University-PalestineRamallahPalestine Department of Computer Science and Communication Engineering University of Science and Technology BeijingChina and Beijing Key Laboratory of Knowledge Engineering for Materials ScienceBeijing100083China Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabadPakistan

The ensemble is a technique that strategically combines basic models to achieve better accuracy rates.Diversity,combination methods,and selection topology are the main factors determining ensemble performance.Consequently,it is a challenging task to design an efficient ensemble scheme.Even though numerous paradigms have been proposed to classify ensemble schemes,there is still much room for improvement.This paper proposes a general framework for creating ensembles in the context of classification.Specifically,the ensemble framework consists of four stages:objectives,data preparing,model training,and model testing.It is comprehensive to design diverse ensembles.The proposed ensemble approach can be used for a wide variety of machine learning tasks.We validate our approach on real-world datasets.The experimental results show the efficiency of the proposed approach.

关键词： Classification Ensemble learning Extreme learning machine

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从“凯恩斯批判”到“卢卡斯批判”——论经济计量学批判史上的两大批判

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西部学刊 2023年第6期 50-54页

作者：张德政河北工程大学管理工程与商学院

自经济计量学诞生起,理论经济学家对经济计量学的严肃批判就绵绵不绝。在经济计量学批判史上,“凯恩斯批判”和“卢卡斯批判”是最为著名的两大批判。根据这两大批判,可以将迄今为止的经济计量学发展史划分为“前古典”“古典”和“后... 详细信息

自经济计量学诞生起,理论经济学家对经济计量学的严肃批判就绵绵不绝。在经济计量学批判史上,“凯恩斯批判”和“卢卡斯批判”是最为著名的两大批判。根据这两大批判,可以将迄今为止的经济计量学发展史划分为“前古典”“古典”和“后古典”三个阶段。通过转换统计推断技术的具体发展方向,经济计量学从局部修补了凯恩斯和卢卡斯所揭示的若干疑难问题,但并未解决这门学科与生俱来的逻辑缺陷。“后古典经济计量学”在西方主流经济学界强势崛起的直接后果,是“经济学帝国主义”让位于“统计学帝国主义”。“统计学帝国主义”抬高了经济学科研与教育工作者的从业门槛,但给经济学这门学科带来的智慧贡献却乏善可陈。

关键词：经济计量学凯恩斯批判卢卡斯批判统计学帝国主义

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