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2nd IEEE International Conference on Control, Electronics and Computer Technology, ICCECT 2024

作者： Zhao, Dan Shen, Hujun School of Information Guizhou University of Finance and Economics China Guizhou Education University Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou China

ISBN: (纸本)9798350380958

The deep learning-based computing paradigm plays a pivotal role in contemporary society. Nevertheless, current methods are plagued by the challenges of demanding extensive labeled data and excessive training resource consumption. Active learning (AL) diminishes the quantity of required training and labeling data by selecting representative samples. Nonetheless, traditional AL approaches demand a significant number of iterations and sample labels, making them susceptible to data bias and excessive human intervention. In response to these challenges, this paper presents a threshold classification algorithm based on query by committee (TC-QBC) that integrates reinforcement learning techniques. Unlike conventional sampling methods, TC-QBC assigned dynamic weights to labels during committee voting. Subsequently, a resampling operation was executed by establishing a threshold to attain the data classification objective. Following validation in pertinent experiments, TC-QBC exhibits outstanding classification prowess. Our work has shown that the proposed method can improve model performance while reducing the resources necessary for training. © 2024 IEEE.

关键词： Reinforcement learning

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Slow Phase Transition-Induced Scan Rate Dependence of Spin Crossover in a Two-Dimensional Supramolecular Fe(III)Complex

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CCS Chemistry 2023年第2期5卷 412-422页

作者： Zhao-Yang Li Ying-Ying Wu Yao Li Jin-Hua Wang Arshia Sulaiman Mohammad Khurram Javed Ya-Chao Zhang Wei Li Xian-He Bu School of Materials Science and Engineering Nankai UniversityTianjin 300350 Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education UniversityGuiyang 550018 College of Chemistry Nankai UniversityTianjin 300071

Spin crossover(SCO)is commonly accompanied by a synchronous phase transition.A few phase transitioncoupled SCO compounds have been reported,yet the synergy between SCO and phase transition on different time scales has not been ***,we report an[Fe(H-5-Cl-thsa-Et)(5-Cl-thsa-Et)]·H2O(1·H2O;H2-5-Cl-thsa-Et=5-chloro-salicylaldehyde ethylthiosemicarbazone)Fe(III)complex that displays a two-dimensional supramolecular structure and SCO behavior above room *** dehydrated form1 exhibits a two-step spin transition with aplateau in the temperature-dependent magnetization(M−T)curve at room temperature and a 51 K thermal hysteresis loop(Tc↑↓=299/248 K)at a rate of 5 K/*** improved SCOperformance in 1 could be attributed to the stronger intralayer but weaker interlayer interactions,which is supported by single-crystal structural analysis and density functional theory ***,complex 1 displays an unusual scan rate-dependent SCO behavior at rates of 0.5−30 K/min,in whichM−T curveplateaus appear at lower scan rates(<10 K/min)but vanish at faster scan rates(≥10 K/min).Scan rate-dependent differential scanning calorimetry,powder X-ray diffractometry,timedependent magnetic moment decays,and infrared spectroscopy consistently reveal that the slow structural relaxation is coupled with a slowcrystallographic phase transition,which is the mechanism for the unusual scan rate-dependent SCO.

关键词： supramolecular two-dimensional structures scan rate dependence spin crossover slow phase transition

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A Study on Image Classification Method for Lightweight Network Models Based on Adaptive Channel Number Transformation (ACT) 5

A Study on Image Classification Method for Lightweight Netwo...

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2023 5th International Conference on Artificial Intelligence and Computer Applications, ICAICA 2023

作者： Li, Dongyao Pan, Yunhui Shen, Hujun School of Information Guizhou University of Finance and Economics Guiyang China Guizhou Education University Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guiyang China

ISBN: (纸本)9798350323313

Significant strides have been made in the field of deep learning for computer vision, particularly in image classification, largely attributed to the widespread use of Convolutional Neural Networks (CNNs). Nevertheless, the deepening layers and increasing complexity of CNNs pose challenges in deploying these models due to substantial computational and storage costs. This impedes their application on smaller mobile devices like smartphones. This article delves into a strategy leveraging channel number transformation to mitigate the computational and storage expenses associated with CNNs, optimizing their performance in image classification tasks. An Adaptive Channel Number Transformation (ACT) framework is devised. In this framework, the fundamental concept is that, in image classification tasks, the regulations governing model channel number transformation should be jointly overseen by the classification number labels of the model and the classification task. These regulations are fine-tuned by the labels in the latter part of the model. The ACT framework is applied to the lightweight network model of the ShuffleNets series. Its objective is to curtail the deployment costs of CNNs, ensuring the network sustains accuracy while diminishing the count of model parameters and computational time through adaptive channel number transformation. © 2023 IEEE.

关键词： Image classification

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Halogen chlorine triggered oxygen vacancy-rich Ni(OH)_(2) with enhanced reaction kinetics for pseudocapacitive energy storage

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Journal of Energy Chemistry 2023年第7期82卷 296-306,I0007页

作者： Jiangyu Hao Lijin Yan Liang Luo Qiaohui Liu Youcun Bai Yuying Han Yang Zhou Xuefeng Zou Bin Xiang School of Chemistry and Chemical Engineering Chongqing UniversityChongqing 400044China Analytical and Testing Center Chongqing UniversityChongqing 400044China Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education UniversityGuiyang 550018GuizhouChina School of Materials Science and Engineering Institute of Materials Science and DeviceSuzhou University of Science and TechnologySuzhou 215009JiangsuChina

Two-dimensional (2D)Ni(OH)_(2) nanosheets can theoretically expose their active sites of 100%.Whereas,their intrinsic easy accumulation and low conductivity lead to weak and unsustainable reaction ***,we propose a novel halogen chlorine-triggered electrochemical etching strategy to controllably manage the reaction kinetics of 2D Ni(OH)_(2) nanosheets(EE/Cl-Ni(OH)_(2)).It is found that halogen chlorine doping can adjust the interlamellar spacing flexibly and promote the lattice oxygen activation to achieve controlled construction of superficial oxygen defects at the adjustable *** optimal EE/Cl-Ni(OH)_(2) electrode exhibits a high rate capability and excellent specific capacity of 206.9 mA h g^(-1) at 1 A g^(-1) in a three-electrode system,which is more than twice as high as the pristine Ni(OH)_(2).Furthermore,EE/Cl-Ni(OH)_(2) cathode and FeOOH@rGO anode are employed for developing an aqueous Ni-Fe battery with an excellent energy density of 83 W h kg^(-1),a high power density of 17051 W kg^(-1),and robust durability over 20,000 *** strategy exploits a fresh channel for the ingenious fabrication of highefficiency and stable nickel-based deficiency materials for energy storage.

关键词： Ni(OH)_(2) Electrochemical etching Lattice defects High energy density Ni-Fe battery

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Understanding the hydrogen evolution reaction activity of doped single-atom catalysts on two-dimensional GaPS_(4) by DFT and machine learning

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Journal of Energy Chemistry 2023年第6期81卷 93-100,I0004页

作者： Tianyun Liu Xin Zhao Xuefei Liu Wenjun Xiao Zijiang Luo Wentao Wang Yuefei Zhang Jin-Cheng Liu College of Physics and Electronic Science Guizhou Normal UniversityGuiyang 550025GuizhouChina Center for Rare Earth and Inorganic Functional Materials School of Materials Science and Engineering&National Institute for Advanced MaterialsNankai UniversityTianjin 300350China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China College of Information Guizhou University of Finance and EconomicsGuiyang 550025GuizhouChina Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education UniversityGuiyang 550018GuizhouChina

As a zero-carbon fuel,hydrogen can be produced via electrochemical water splitting using clean electric energy by the hydrogen evolution reaction(HER)*** ultimate goal of HER catalyst is to replace the expensive Pt metal benchmark with a cheap one with equivalent *** this work,we investigated the possibility of HER process on single-atom catalysts(SACs)doped on two-dimensional(2D)GaPS_(4)materials,which have a large intrinsic band gap that can be regulated by doping and tensile *** on the machine learning regression analysis,we can expand the prediction of HER performance to more catalysts without expensive DFT *** electron affinity and first ionization energy are the two most important descriptors related to the HER ***,constrain molecular dynamics with solvation models and constant potentials were applied to understand the dynamics barrier of HER process of Pt SAC on GaPS_(4)*** findings not only provide important insights into the catalytic properties of single-atom catalysts on GaPS_(4)2D materials,but also provides theoretical guidance paradigm for exploration of new catalysts.

关键词： Two-dimensional GaPS_(4) Hydrogen evolution reaction Single-atom catalysis First-principles calculation Machine learning

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Understanding the Intrinsic Mechanism of High-Performance Electrocatalytic Nitrogen Fixation by Heterogenization of Homonuclear Dual-Atom Catalysts

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Energy & Environmental materials 2025年第2期8卷 125-139页

作者： Yuefei Zhang Yu Yang Yu Zhang Xuefei Liu Wenjun Xiao Degui Wang Gang Wang Zhen Wang Jinshun Bi Jincheng Liu Xun Zhou Wentao Wang School of Integrated Circuit Guizhou Normal UniversityGuiyang 550025China School of physics and electronic science Guizhou Normal UniversityGuiyang 550025China Jincheng Research Institute of Opto-mechatronics Industry Jincheng 048000China Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems Jincheng 048000China Center for Rare Earth and Inorganic Functional Materials School of Materials Science and Engineering&National Institute for Advanced MaterialsNankai UniversityTianjin 300350China Haihe Laboratory of Sustainable Chemical Transformations Tianjin 300192China Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education UniversityGuiyang 550018China

A heteronuclear dual transition metal atom catalyst is a promising strategy to solve and relieve the increasing energy and environment ***,the role of each atom still does not efficiently differentiate due to the high activity but low detectability of each transition metal in the synergistic catalytic process when considering the influence of heteronuclear induced atomic difference for each transition metal atom,thus seriously hindering intrinsic mechanism ***,we proposed coordinate environment vary induced heterogenization of homonuclear dual-transition metal,which inherits the advantage of heteronuclear transition metal atom catalyst but also controls the variable of the two atoms to explore the underlying *** on this proposal,employing density functional theory study and machine learning,23 kinds of homonuclear transition metals are doping in four asymmetric C_(3)N for heterogenization to evaluate the underlying catalytic *** results demonstrate that five catalysts exhibit excellent catalytic performance with a low limiting potential of-0.28 to-0.48 *** the meantime,a new mechanism,"capture-charge distribution-recapturecharge redistribution",is developed for both side-on and end-on *** importantly,the pronate site of the first hydrogenation is identified based on this *** work not only initially makes a deep understanding of the transition dual metal-based heteronuclear catalyst indirectly but also broadens the development of complicated homonuclear dual-atom catalysts in the future.

关键词： electrocatalyst first principles heterogenizationofhomonuclear machine learning nitrogenreductionreaction

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Minimum-Modified Debye-Hückel Theory for Size-Asymmetric Electrolyte Solutions with Moderate Concentrations

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Chinese Journal of Chemical Physics 2023年第5期36卷 553-560,I0001,I0002页

作者： Tiejun Xiao Yun Zhou Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Synergetic Innovation Center of Scientific Big Data for Advanced Manufacturing TechnologyGuizhou Education UniversityGuiyang 550018China

A minimum-modified Debye-Hückel(DH)theory for electrolytes with size asymmetry is ***-pared with the conventional DH theory,the minimum-modified DH theory only introduces an extra surface charge density to capture the electrostatic effect of the size asymmetry of the electrolytes and hence facilitates a boundary element method for electrostatic potential *** theory can distinguish the electrostat-ic energies and excess chemical potentials of ions with the same sizes but opposite charges,and is applied to a binary primitive electrolyte solution with moderate electrostatic *** with the hyper-netted chain theory,the validity of this modified DH theory demonstrates significant improvement over the conventional DH theory.

关键词： Electrolyte solution Size-asymmetry Debye-Hückel theory Electrostatic ener-gy Chemical potential

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In-situ cation-inserted MnO_(2) with selective accelerated intercalation of individual H^(+) or Zn^(2+) ions in aqueous zinc ion batteries

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Journal of Energy Chemistry 2023年第7期82卷 88-102,I0003页

作者： Lijin Yan Baibai Liu Jiangyu Hao Yuying Han Chong Zhu Fuliang Liu Xuefeng Zou Yang Zhou Bin Xiang College of Chemistry and Chemical Engineering Chongqing UniversityChongqing 401331China College of Optoelectronic Engineering Chongqing UniversityChongqing 400044China Guizhou Meiling Power Co. Zunyi 563099GuizhouChina Nanjing University of Aeronautics and Astronautics Nanjing 210016JiangsuChina Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Normal UniversityGuiyang 550018GuizhouChina Analytical and Testing Center of Chongqing University Chongqing UniversityChongqing 401331China

The recognized energy storage mechanism of neutral aqueous zinc-manganese batteries is the co-insertion/extrusion of H^(+) and Zn^(2+) ***,modulating the kinetics of a single H^(+) or Zn^(2+) ion is scarce,which can provide meaningful insights into the energy storage mechanism of Zn ion ***,a distinctive doubly electric field in-situ induced cationic anchoring of two-dimensional layered MnO_(2) is successfully constructed to modulate the insertion/extrusion of a single H^(+) or Zn^(2+) *** a result,regulating the intercalation of different metal ions can precisely achieve the accelerated induction for the individual H^(+) or Zn^(2+) ions intercalation/***,the introduction of metal ions stabilizes the lattice distortion and alleviates the irreparable structural collapse,leading to an increase in the H^(+)/Zn^(2+) storage sites,efficiently diminishing the stagnation of the ordered structure and creating the more open channels,which is conducive to facilitating the diffusion of *** work delivers some innovative insights into pre-embedding strategies,and also serves as a precious reference for the cathode development of advanced aqueous batteries.

关键词： In-situ inductions Manganese dioxide Insertion mechanisms Zinc-ion batteries

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Magic hybrid structure as multifunctional electrocatalyst surpassing benchmark Pt/C enables practical hydrazine fuel cell integrated with energy-saving H_(2)production

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escience 2022年第4期2卷 416-427页

作者： Ziyun Li Wentao Wang Qizhu Qian Yin Zhu Yafei Feng Yangyang Zhang Huaikun Zhang Mingyu Cheng Genqiang Zhang Hefei National Research Center for Physical Sciences at the Microscale CAS Key Laboratory of Materials for Energy ConversionDepartment of Materials Science and EngineeringUniversity of Science and Technology of ChinaHefeiAnhui230026China Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education UniversityGuiyangGuizhou550018China

A hybrid catalyst structure can provide abundant active sites and tailored electronic properties,but the major challenge lies in achieving delicate control over its composition and architecture to improve the catalytic activity toward different electrochemical reactions ***,we present the rational design of a magic hybrid structure with low Pt loading(5.90 wt%),composed of CoPt_(3)and CoPt nanoparticles supported on N-doped carbon(CoPt_(3)/CoPt⊂PLNC).Importantly,it shows superior multifunctional catalytic activity in alkaline conditions,requiring a low overpotential of 341 and 20 mV to achieve 10 mA cm^(−2)for the hydrazine oxidation reaction(HzOR)/hydrogen evolution reaction(HER),respectively,and it delivers a half-wave potential of 0.847 V for the oxygen reduction reaction(ORR).Theoretical calculations reveal that the metal-carbon hybrid modulates kinetic behavior and induces electron redistribution,achieving the energetic requirements for multiple *** demonstrate sustainable H_(2)production utilizing solely the CoPt_(3)/CoPt⊂PLNC catalyst,without external electric power input,suggesting its inspiring practical utility.

关键词： Electrocatalysis Hybrid structure Fuel cell Hydrazine oxidation H_(2)production

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Committee-Based Threshold Classification Algorithm with Reinforcement Active Learning

Committee-Based Threshold Classification Algorithm with Rein...

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Control, Electronics and Computer Technology (ICCECT), IEEE International Conference on

作者： Dan Zhao Hujun Shen School of Information Guizhou University of Finance and Economics Guizhou Provincial Key Laboratory of Computational Nano-Material Science Guizhou Education University Guizhou China

ISBN: (数字)9798350380958

ISBN: (纸本)9798350380965

关键词： Training Couplings Data preprocessing Reinforcement learning Sampling methods Prediction algorithms Classification algorithms

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