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Effects of vacancy and external electric field on the electronic properties of the MoSi_(2)N_(4)/graphene heterostructure

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Chinese Physics B 2024年第3期33卷 542-550页

作者：梁前罗祥燕钱国林王远帆梁永超谢泉 College of Big Data and Information Engineering Institute of New Optoelectronic Materials and TechnologyGuizhou UniversityGuiyang 550025China

Recently,the newly synthesized septuple-atomic layer two-dimensional(2D)material MoSi_(2)N_(4)(MSN)has attracted attention *** work delves into the effect of vacancies and external electric fields on the electronic properties of the MSN/graphene(Gr)heterostructure using first-principles *** find that four types of defective structures,N-in,N-out,Si and Mo vacancy defects of monolayer MSN and MSN/Gr heterostructure are stable in ***,vacancy defects can effectively modulate the charge transfer at the interface of the MSN/Gr heterostructure as well as the work function of the pristine monolayer MSN and MSN/Gr ***,the application of an external electric field enables the dynamic switching between n-type and p-type Schottky *** work may offer the possibility of exceeding the capabilities of conventional Schottky diodes based on MSN/Gr heterostructures.

关键词： MoSi_(2)N_(4) vacancy defects external electric field Schottky contacts

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Single Solution Optimization Mechanism of Teaching-Learning-Based Optimization with Weighted Probability Exploration for Parameter Estimation of Photovoltaic Models

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Journal of Bionic engineering 2024年第5期21卷 2619-2645页

作者： Jinge Shi Yi Chen Zhennao Cai Ali Asghar Heidari Huiling Chen Institute of Big Data and Information Technology Wenzhou UniversityWenzhou325000China School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran

This article presents a novel optimization approach called RSWTLBO for accurately identifying unknown parameters in photovoltaic(PV)*** objective is to address challenges related to the detection and maintenance of PV systems and the improvement of conversion *** combines adaptive parameter w,Single Solution Optimization Mechanism(SSOM),and Weight Probability Exploration Strategy(WPES)to enhance the optimization ability of *** algorithm achieves a balance between exploitation and exploration throughout the iteration *** SSOM allows for local exploration around a single solution,improving solution quality and eliminating inferior *** WPES enables comprehensive exploration of the solution space,avoiding the problem of getting trapped in local *** algo-rithm is evaluated by comparing it with 10 other competitive algorithms on various PV *** results demonstrate that RSWTLBO consistently achieves the lowest Root Mean Square Errors on single diode models,double diode models,and PV module *** also exhibits robust performance under varying irradiation and temperature *** study concludes that RSWTLBO is a practical and effective algorithm for identifying unknown parameters in PV models.

关键词： Teaching-learning-based optimization Single solution optimization Solar energy Photovoltaic models Weighted probability exploration

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Graphene effectively activating "dead" water molecules between manganese dioxide layers in potassium-ion battery

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Journal of Energy Chemistry 2024年第6期93卷 306-315,I0008页

作者： Xinhai Wang Wensheng Yang Shengshang Lu Shangshu Peng Tong Guo Quan Xie Qingquan Xiao Yunjun Ruan Institute of Advanced Optoelectronic Materials and Technology College of Big Data and Information EngineeringGuizhou UniversityGuiyang 550025GuizhouChina

Aqueous potassium-ion batteries(APIBs),recognized as safe and reliable new energy devices,are considered as one of the alternatives to traditional *** MnO_(2),serving as the main cathode,exhibits a lower specific capacity in aqueous electrolytes compared to organic systems and operates through a different reaction *** application of highly conductive graphene may effectively enhance the capacity of APIBs but could complicate the potassium storage *** this study,a MnO_(2) cathode pre-intercalated with K~+ions and grown on graphene(KMO@rGO) was developed using the microwave hydrothermal method for ***@rGO achieved a specific capacity of 90 mA h g^(-1) at a current density of 0.1 A g^(-1),maintaining a capacity retention rate of>90% after 5000 cycles at 5 A g^(-1).In-situ and exsitu characterization techniques revealed the energy-storage mechanism of KMO@rGO:layered MnO_(2)traps a large amount of "dead" water molecules during K~+ions ***,the introduction of graphene enables these water molecules to escape during K~+ ions insertion at the *** galvanostatic intermittent titration technique and density functional theory confirmed that KMO@rGO has a higher K~+ions migration rate than MnO_(2).Therefore,the capacity of this cathode depends on the interaction between dead water and K~+ions during the energy-storage *** optimal structural alignment between layered MnO_(2) and graphene allows electrons to easily flow into the external *** charge compensation forces numerous low-solvent K~+ions to displace interlayer dead water,enhancing the *** unique reaction mechanism is unprecedented in other aqueous battery studies.

关键词： Graphene K-ion batteries Mn-based layered oxide Water molecules Density functional theory

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Prediction of(n,2n)reaction cross-sections of long-lived fission products based on tensor model

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Nuclear Science and Techniques 2024年第10期35卷 208-221页

作者： Jia-Li Huang Hui Wang Ying-Ge Huang Er-Xi Xiao Yu-Jie Feng Xin Lei Fu-Chang Gu Long Zhu Yong-Jing Chen Jun Su Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen UniversityZhuhai 519082China China Nuclear Data Center China Institute of Atomic EnergyBeijing 102413China Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China

Interest has recently emerged in potential applications of(n,2n)reactions of unstable *** have arisen because of the scarcity of experimental cross-sectional *** study aims to predict the(n,2n)reaction cross-section of long-lived fission products based on a tensor *** tensor model is an extension of the collaborative filtering algorithm used for nuclear *** is based on tensor decomposition and completion to predict(n,2n)reaction cross-sections;the corresponding EXFOR data are applied as training *** reliability of the proposed tensor model was validated by comparing the calculations with data from EXFOR and different *** were made for long-lived fission products such as^(60)Co,^(79)Se,^(93)Zr,^(107)P,^(126)Sn,and^(137)Cs,which provide a predicted energy range to effectively transmute long-lived fission products into shorter-lived or less radioactive *** method could be a powerful tool for completing(n,2n)reaction cross-sectional data and shows the possibility of selective transmutation of nuclear waste.

关键词： (n,2n)Reaction cross-section Tensor model Machine learning Collaborative filtering algorithm Selective transmutation

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Investigation of the Architecture for A Application Creation Platform Leveraging Modern Technology on Smart Campus 24

Investigation of the Architecture for A Application Creation...

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5th International Conference on Computer Science and Management Technology, ICCSMT 2024

作者： Huang, Jie Ma, Kai He, Xiaosong He, Hongjing Institute of Big Data Technology and Application Chongqing Institute of Engineering Chongqing China School of Big Data and Artificial Intelligence Chongqing Institute of Engineering Chongqing China

ISBN: (纸本)9798400709999

Intelligent technologies are driving the development of smart campuses, fostering a dynamic and diverse intelligent ***, the current trend of customizing smart campus solutions often positions campus citizens as mere bystanders or end *** enhance participatory engagement in campus development and increase the autonomy of platform construction, this paper leverages the strengths of big data warehouses, data analytics, the Internet of Things (IoT), and cloud computing-specifically their security, concurrency, reliability, redundancy, and scalability-to propose a campus application creation *** platform aims to streamline the software development process, facilitate the publication of software products, and promote functionality sharing and collaborative *** introduce an architectural model comprising four components: the data lake and warehouse layer, the data ferry layer, the resource service layer, and the platform *** internal operational mechanisms of this architecture are discussed from the perspectives of"applications as data, " self-feedback analysis, application evaluation systems, and system *** advantages of the platform are analyzed, along with application cases from both teacher and student *** also explore the platform's significance within the campus context, including its potential to adjust campus functionality, enhance overall innovation capabilities in education, and increase the autonomy of software *** findings suggest that a modern application creation platform can significantly facilitate the self-improvement of smart campus functionalities, thereby further enhancing the intelligence of the campus. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Cloud platforms

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Theoretical Exploration of Alloying Effects on Stabilities and Mechanical Properties ofγʹPhase in Novel Co–Al–Nb-Base Superalloys

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Acta Metallurgica Sinica(English Letters) 2024年第7期37卷 1238-1248页

作者： Guan-Cheng Gu Zhao-Jing Han Ze-Yu Chen Zhao-Xuan Li Sheng-Bao Xia Zheng-Ning Li Hua Jin Wei-Wei Xu Xing-Jun Liu Shenzhen Research Institute of Xiamen University School of Aerospace EngineeringXiamen UniversityXiamen361005China Institute of Materials Genome and Big Data Harbin Institute of TechnologyShenzhen518055China

The new developedγ/γʹCo–Al–Nb-base alloys show great potentials as high-temperature ***,finding appropriate compositions to improve performance of alloys still poses a great challenge to the development of Co–Al–Nb-base *** by the lack of alloying effects on fundamental properties of criticalγʹphase,we systematically performed a theoretical investigation on the effect of alloying elements TM(TM:Ti,V,Cr,Zr,Mo,Ta,W,Re,and Ru)on phase stabilities and mechanical properties of L1_(2)-typeγʹ(Co,Ni)_(3)(Al,Nb).By analyzing the stability ofγʹphase with respect to its competitive B2 and D0_(19) phases,the results shown that Ti,V,and Cr enhance the L1_(2) stability and widen the L1_(2)–D0_(19) energy barrier,in which V yields the maximum *** analysis of electronic structure indicated that the alternation of valence electrons at fermi level would be the atomic origin for doping TM inγʹ*** calculated results of mechanical properties shown that V and Cr are expected to be optimal dopant for enhancing the strength and the ductility ofγʹ*** addition of Ta is also beneficial for enhancing the strength at the slight expense of ductility ofγʹ*** drawing the mechanical maps,the preferred composition range for the phases with desired properties is roughly demarcated in theory for the multi-addition of V/Cr and V/Ta inγʹ*** findings would be useful for optimizing the performance of novelγ/γʹCo–Al–Nb-base superalloys.

关键词： Co-Al-Nb-base superalloys γ/γʹdual-phase Phase stability Mechanical properties First-principle methods

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Classification and structural characteristics of amorphous materials based on interpretable deep learning

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Chinese Physics B 2023年第9期32卷 356-363页

作者：崔佳梅李韵洁赵偲郑文 Institute of Public Safety and Big Data College of Data ScienceTaiyuan University of TechnologyJinzhong 030600China Shanxi Engineering Research Center for Intelligent Data Assisted Treatment Changzhi Medical CollegeChangzhi 046000China

Defining the structure characteristics of amorphous materials is one of the fundamental problems that need to be solved urgently in complex materials because of their complex structure and long-range *** this study,we develop an interpretable deep learning model capable of accurately classifying amorphous configurations and characterizing their structural *** results demonstrate that the multi-dimensional hybrid convolutional neural network can classify the two-dimensional(2D)liquids and amorphous solids of molecular dynamics *** classification process does not make a priori assumptions on the amorphous particle environment,and the accuracy is 92.75%,which is better than other convolutional neural ***,our model utilizes the gradient-weighted activation-like mapping method,which generates activation-like heat maps that can precisely identify important structures in the amorphous configuration *** obtain an order parameter from the heatmap and conduct finite scale analysis of this *** findings demonstrate that the order parameter effectively captures the amorphous phase transition process across various *** results hold significant scientific implications for the study of amorphous structural characteristics via deep learning.

关键词： amorphous interpretable deep learning image classification finite scale analysis

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EEG-based Incongruency Decoding in AR with sLDA, SVM, and EEGNet

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Current Directions in Biomedical engineering 2024年第3期10卷 21-24页

作者： Wimmer, Michael Veas, Eduardo E. Müller-Putz, Gernot R. Know-Center Graz Austria Institute of Neural Engineering Graz Austria Institute of Interactive Systems and Data Science Graz Austria

Augmented reality (AR) technologies enhance a user’s physical environment by providing contextual information about their surroundings. This information might appear incongruent to users, either due to their current mental context or factual errors in the data. This paper explores the feasibility of incongruency decoding using electroencephalographic (EEG) signals from 19 participants acquired during an interactive AR task. Previous studies on single-trial N400 decoding for brain-computer interfaces using EEG data are limited. Therefore, we implemented commonly used classification approaches and assessed their decoding performance compared to the convolutional neural network EEGNet. We found that the investigated approaches offer comparable accuracies ranging from 63.3% to 64.8%. Successful decoding of incongruency effects can foster more contextually appropriate interactions within AR environments. © 2024 The Author(s), published by De Gruyter.

关键词： Convolutional neural networks

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Saliency-guided meta-hallucinator for few-shot learning

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Science China(Information Sciences) 2024年第10期67卷 189-210页

作者： Hongguang ZHANG Chun LIU Jiandong WANG Linru MA Piotr KONIUSZ Philip H.S.TORR Lin YANG Systems Engineering Institute Academy of Military Sciences Data61 Commonwealth Scientific and Industrial Research Organisation Australian National University Oxford University

Learning novel object concepts from limited samples remains a considerable challenge in deep learning. The main directions for improving the few-shot learning models include(i) designing a stronger backbone,(ii) designing a powerful(dynamic) meta-classifier, and(iii) using a larger pre-training set obtained by generating or hallucinating additional samples from the small scale dataset. In this paper, we focus on item(iii) and present a novel meta-hallucination strategy. Presently, most image generators are based on a generative network(i.e., GAN) that generates new samples from the captured distribution of images. However, such networks require numerous annotated samples for training. In contrast, we propose a novel saliency-based end-to-end meta-hallucinator, where a saliency detector produces foregrounds and backgrounds of support images. Such images are fed into a two-stream network to hallucinate feature samples directly in the feature space by mixing foreground and background feature samples. Then, we propose several novel mixing strategies that improve the quality and diversity of hallucinated feature ***, as not all saliency maps are meaningful or high quality, we further introduce a meta-hallucination controller that decides which foreground feature samples should participate in mixing with backgrounds. To our knowledge, we are the first to leverage saliency detection for few-shot learning. Our proposed network achieves state-of-the-art results on publicly available few-shot image classification and anomaly detection benchmarks, and outperforms competing sample mixing strategies such as the so-called Manifold Mixup.

关键词： few-shot learning saliency detection object recognition anomaly detection computer vision

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Dislocation mechanism of Ni_(47)Co_(53) alloy during rapid solidification

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Chinese Physics B 2023年第6期32卷 410-419页

作者：刘云春梁永超陈茜张利马家君王蓓高廷红谢泉 Institute of Advanced Optoelectronic Materials and Technology School of Big Data and Information EngineeringGuizhou UniversityGuiyang 550025China

Dislocations and other atomic-level defects play a crucial role in determining the macroscopic properties of crystalline materials,but it is extremely difficult to observe the evolution of dislocations due to the limitations of the most advanced experimental ***,in this work,the rapid solidification processes of Ni_(47)Co_(53) alloy at five cooling rates are studied by molecular dynamics simulation,and the evolutions of their microstructures and dislocations are investigated as *** results show that face-centered cubic(FCC) structures are formed at the low cooling rate,and the crystalline and amorphous mixture appear at the critical cooling rate,and the amorphous are generated at the high cooling *** crystallization temperature and crystallinity decrease with cooling rate *** are few at the cooling rates of 1×10^(11) K/s,5×10^(12) K/s,and 1×10^(13) K/s,and they are most abundant at the cooling rates of 5×10^(11) K/s and1 × 10^(12) K/s,in which their dislocation line lengths are both almost *** appear a large number of dislocation reactions at both cooling rates,in which the interconversion between perfect and partial dislocations is *** dislocation reactions are more intense at the cooling rate of 5×10^(11) K/s,and the slip of some dislocations leads to the interconversion between FCC structure and hexagonal close packed(HCP) structure,which causes the twin boundaries(TBs) to *** FCC and HCP are in the same atomic layer,and dislocations are formed at the junction due to the existence of TBs at the cooling rate of 1 ×10^(12) K/*** present research is important in understanding the dislocation mechanism and its influence on crystal structure at atomic scales.

关键词： molecular dynamics simulation rapid solidification crystal structure dislocation interaction

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