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Prediction of BOF endpoint carbon content and temperature via CSSA-BP neural network model

Journal of Iron and Steel Research International 2025年第3期32卷 578-593页

作者： Xiao-feng Qiu Run-hao Zhang Jian Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai200444China

To predict the endpoint carbon content and temperature in basic oxygen furnace (BOF), the industrial parameters of BOF steelmaking are taken as input values. Firstly, a series of preprocessing works such as the Pauta criterion, hierarchical clustering, and principal component analysis on the original data were performed. Secondly, the prediction results of classic machine learning models of ridge regression, support vector machine, gradient boosting regression (GBR), random forest regression, back-propagation (BP) neural network models, and multi-layer perceptron (MLP) were compared before and after data preprocessing. An improved model was established based on the improved sparrow algorithm and BP using tent chaotic mapping (CSSA-BP). The CSSA-BP model showed the best performance for endpoint carbon prediction with the lowest mean absolute error (MAE) and root mean square error (RMSE) values of 0.01124 and 0.01345 mass% among seven models, respectively. And the lowest MAE and RMSE values of 8.9839 and 10.9321 ℃ for endpoint temperature prediction were obtained among seven models, respectively. Furthermore, the CSSA-BP and GBR models have the smallest error fluctuation range in both endpoint carbon content and temperature predictions. Finally, in order to improve the interpretability of the model, SHapley additive interpretation (SHAP) was used to analyze the results.

关键词： BOF steelmaking Principal component analysis Hierarchical clustering CSSA-BP SHapley additive interpretation

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Effect of Al content on nanoprecipitates, austenite grain growth and toughness in coarse-grained heat-affected zones of Al–Ti–Ca deoxidized shipbuilding steels

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International Journal of Minerals,Metallurgy and materials 2025年第4期32卷 879-891页

作者： Tingting Li Jian Yang Yinhui Zhang Han Sun Yanli Chen Yuqi Zhang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

This work focuses on the influence of Al content on the precipitation of nanoprecipitates,growth of prior austenite grains(PAGs),and impact toughness in simulated coarse-grained heat-affected zones (CGHAZs) of two experimental shipbuilding steels after being subjected to high-heat input welding at 400 kJ·cm^(-1).The base metals (BMs) of both steels contained three types of precipitates Type Ⅰ:cubic (Ti,Nb)(C,N),Type Ⅱ:precipitate with cubic (Ti,Nb)(C,N) core and Nb-rich cap,and Type Ⅲ:ellipsoidal Nb-rich *** the BM of 60Al and 160Al steels,the number densities of the precipitates were 11.37×10^(5) and 13.88×10^(5) mm^(-2),respectively The 60Al and 160Al steel contained 38.12% and 6.39% Type Ⅲ precipitates,*** difference in the content of Type Ⅲ precipitates in the 60Al steel reduced the pinning effect at the elevated temperature of the CGHAZ,which facilitated the growth of PAGs The average PAG sizes in the CGHAZ of the 60Al and 160Al steels were 189.73 and 174.7μm,*** the 60Al steel,the low lattice mismatch among Cu_(2)S,TiN,and γ-Al_(2)O_(3)facilitated the precipitation of Cu_(2)S and TiN onto γ-Al_(2)O_(3)during welding,which decreased the number density of independently precipitated (Ti,Nb)(C,N) particles but increased that of γ-Al_(2)O_(3)–Ti N–Cu_(2)S *** abnormally large PAGs formed in the CGHAZ of the 60Al steel,and they reached a maximum size of 1 *** PAGs greatly reduced the microstructural homogeneity and consequently decreased the impact toughness from 134 (0.016wt%Al) to 54 J (0.006wt%Al)at-40℃.

关键词： oxide metallurgy Al–Ti–Ca deoxidization Al content precipitates coarse-grained heat-affected zone

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Ultrafast Laser Irradiation Induced Oxidation of Dopant-Free Spiro-OMeTAD for Improving the Perovskite Solar Cells Performance

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Energy & Environmental materials 2025年第2期8卷 288-294页

作者： Jiaqi Meng Xiangyu Chen Weihan Li Nianyao Chai Zhongle Zeng Yunfan Yue Fengyi Zhao Xuewen Wang Center of Femtosecond Laser Manufacturing for Advanced Materials and Devices State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology School of Materials Science and Engineering Wuhan University of Technology International School of Materials Science and Engineering Wuhan University of Technology National Energy Key Laboratory for New Hydrogen-Ammonia Energy Technologies Foshan Xianhu Laboratory

The exceptional photoelectric performance and high compatibility of perovskite materials render perovskite solar cells highly promising for extensive development,thus garnering significant *** perovskite solar cells,the hole transport layer plays a crucial *** the commonly employed organic small molecule hole transport material Spiro-OMeTAD,a certain period of oxidation treatment is required to achieve complete transport ***,this posttreatment oxidation processes typically rely on ambient oxidation,which poses challenges in terms of precise control and leads to degradation of the perovskite light absorption *** approach fails to meet the demands for high efficiency and stability in practical ***,the mechanism of ultrafast laser on Spiro-OMeTAD and the reaction process for laser-induced oxidation of it are ***2at Perovskite/Spiro-OMeTAD interface breaks down to produce I2upon ultrafast laser irradiation and I2promote the oxidation *** the laser irradiation oxidation processing,a higher stability of perovskite solar cells is *** work establishes a new approach toward oxidation treatment of Spiro-OMeTAD.

关键词： hole transport layer perovskite solar cells ultrafast laser irradiation undoped Spiro-OMeTAD

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Significant increase in thermal conductivity of cathode material LiFePO_(4) by Na substitution:A machine learning interatomic potential-assisted investigation

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Chinese Physics B 2025年第2期34卷 463-468页

作者： Shi-Yi Li Qian Liu Yu-Jia Zeng Guofeng Xie Wu-Xing Zhou School of Materials Science and Engineering Hunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and ConversionHunan University of Science and TechnologyXiangtan 411201China

LiFePO_(4) is a cathode material with good thermal stability,but low thermal conductivity is a critical *** this study,we employ a machine learning potential approach based on first-principles methods combined with the Boltzmann transport theory to investigate the influence of Na substitution on the thermal conductivity of LiFePO_(4) and the impact of Li-ion de-embedding on the thermal conductivity of Li_(3/4)Na_(1/4)FePO_(4),with the aim of enhancing heat dissipation in Li-ion *** results show a significant increase in thermal conductivity due to an increase in phonon group velocity and a decrease in phonon anharmonic scattering by Na *** addition,the thermal conductivity increases significantly with decreasing Li-ion concentration due to the increase in phonon *** work guides the improvement of the thermal conductivity of Li FePO_4,emphasizing the crucial roles of both substitution and Li-ion detachment/intercalation for the thermal management of electrochemical energy storage devices.

关键词： lattice thermal conductivity machine learning potential LiFePO_(4)

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Microstructure and mechanical properties of high-pressure sintered B6O-SiC nanocomposites

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材料科学技术（英文版） 2025年第1期204卷 238-244页

作者： Bin Zhang Rongxin Sun Pan Ying Song Zhao Yitong Zou Lei Sun Zihe Li Yufei Gao Mengdong Ma Lingyu Liu Chao Liu Bo Xu Center for High Pressure Science(CHiPS) State Key Laboratory of Metastable Materials Science and TechnologyYanshan UniversityQinhuangdao 066004China National Key Laboratory of Advanced Casting Technologies MIIT Key Laboratory of Advanced Metallic and Intermetallic Materials TechnologyEngineering Research Center of Materials Behavior and DesignMinistry of Education Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of Materials and Surface Technology(Ministry of Education) School of Materials Science and EngineeringXihua UniversityChengdu 610039China School of Materials Science and Engineering Faculty of Materials Metallurgy and ChemistryJiangxi University of Science and TechnologyGanzhou 341000China

Boron suboxide(B6O)is recognized as a superhard material with a low mass density,high resistance to chemical wear,and excellent wear *** its desirable properties,the limited fracture tough-ness of B6O restricts its application in industrial *** study presents the structural and me-chanical characterization of B6O-SiC nanocomposites,which were synthesized via a high-pressure high-temperature sintering process of B6O powders and SiC *** sintering process induced fragmen-tation of SiC whiskers,resulting in the homogenous distribution of SiC fragments within the B6O *** increase in SiC content was observed to decrease the composite's hardness,while initially reducing then enhancing its *** nanocomposites containing 20 wt％and 30 wt％SiC whiskers exhibited significant improvements in fracture toughness,averaging 6.5 MPa m1/2 and 7.0 MPa m1/2,respectively-approximately threefold the toughness of polycrystalline B6O-while sustaining high hardness values of 36.3 GPa and 35.6 GPa on *** analyses revealed that the composites'superior me-chanical performance is due to the presence of strong grain boundaries,as well as a high density of nan-otwins and stacking *** findings demonstrate a viable method for producing B6O-based nanocom-posites with enhanced hardness and toughness,potentially expanding their industrial applicability.

关键词： B6O Ceramic nanocomposite Mechanical properties Microstructure

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Machine learning assisted screening of binary alloys for metal-based anode materials

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Journal of Energy Chemistry 2025年第5期104卷 62-68页

作者： Xingyue Shi Linming Zhou Yuhui Huang Chaohui Wu Yongjun Wu Juan Li Zijian Hong State Key Laboratory of Silicon and Advanced Semiconductor Materials School of Materials Science and Engineering Zhejiang University Nanhu Brain-Computer Interface Institute Zhejiang Key Laboratory of Advanced Solid State Energy Storage Technology and Applications Research Institute of Zhejiang University-Taizhou Inner Mongolia Electric Power Economic and Technological Research Institute Institute of Fundamental and Transdisciplinary Research Zhejiang University College of Materials Science and Engineering Zhejiang University of Technology School of Engineering Hangzhou City University

Metal alloy anode materials with high specific capacity and low voltage have recently gained significant attention due to their excellent electrochemical performance and the ability to suppress dendrite ***, experimental investigations of metal alloys can be time-consuming and expensive, often requiring extensive experimental design and effort. In this study, we developed a machine learning model based on the Crystal Graph Convolutional Neural Network(CGCNN) to screen alloy anode materials for seven battery systems, including lithium(Li), sodium(Na), potassium(K), zinc(Zn), magnesium(Mg), calcium(Ca), and aluminum(Al). We utilized data with tens of thousands of alloy materials from the materials Project(MP) and Automatic FLOW for materials Discovery(AFLOW) databases. Without any experimental voltage input, we identified over 30 alloy systems that have been experimentally validated with good precision. Additionally, we predicted over 100 alloy anodes with low potential and high specific capacity. We hope this work to spur further interest in employing advanced machine learning models for the design of battery materials.

关键词： Alloy anodes CGCNN Machine learning Metal-based batteries

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Optimizing the overall performance of Cu–Ni–Si alloy via controllingnanometer-lamellar discontinuous precipitation structure

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International Journal of Minerals,Metallurgy and materials 2025年第4期32卷 915-924页

作者： Jinyu Liang Guoliang Xie Feixiang Liu Wenli Xue Rui Wang Xinhua Liu Key Laboratory for Advanced Materials Processing(MOE) Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China Beijing Laboratory of Metallic Materials and Processing for Modern Transportation Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China State Key Laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing 100083China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Institute of Materials Genome Engineering Henan Academy of SciencesZhengzhou 450046China

Simultaneously achieving high strength and high electrical conductivity in Cu–Ni–Si alloys pose a significant challenge, which greatly constrains its applications in the electronics industry. This paper offers a new pathway to improve properties, by preparation of nanometer lamellar discontinuous precipitates(DPs) arranged with the approximate same direction through a combination of deformationaging and cold rolling process. The strengthening effect is primarily attributed to nanometer-lamellar DPs strengthening and dislocation strengthening mechanism. The accumulation of dislocations at the interface between nanometer lamellar DPs and matrix during cold deformation process can results in the decrease of dislocation density inside the matrix grains, leading to the acceptably slight reduction of electrical conductivity during cold rolling. The alloy exhibits an electrical conductivity of 45.32%IACS(international annealed copper standard, IACS), a tensile strength of 882.67 MPa, and a yield strength of 811.33 MPa by this method. This study can provide a guidance for the composition and microstructure design of a Cu–Ni–Si alloy in the future, by controlling the morphology and distribution of DPs.

关键词： Cu–Ni–Si alloys discontinuous precipitates nanometer-lamellar strengthening dislocation strengthening

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Rapid and high-resolution 3D printing via photoacid generator induced cationic RAFT polymerization

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science China Chemistry 2025年第05期68卷 2010-2016页

作者： Bowen Zhao Jiajia Li Chongyang Yang Xiangqiang Pan Zhengbiao Zhang Jian Zhu State Local Joint Engineering Laboratory for Novel Functional Polymeric Materials Jiangsu Key Laboratory of Advanced Functional Polymer Design and ApplicationSuzhou Key Laboratory of Macromolecular Design and Precision SynthesisDepartment of Polymer Science and EngineeringCollege of ChemistryChemical Engineering and Materials ScienceSoochow University

Vinyl ethers, while being typical monomers for living cationic polymerization, have limited commercial use due to the poor mechanical properties of their polymers at room temperature. We explored the use of photoacid generators to induce cationic reversible addition-fragmentation chain transfer（RAFT） polymerization for the rapid high-resolution three-dimensional（3D） printing of various vinyl ethers. The process demonstrated controlled molecular weights and narrow molecular weight distributions（MWD）, with monomer conversions exceeding 90% in minutes. Incorporating a crosslinker enabled 3D printing at speeds up to 8.46 cm h-1with layer thicknesses as thin as 50 μm. The mechanical properties of the printed objects were tunable by adjusting resin components, allowing for a range of material characteristics from brittle to elastomeric（tensile strength ranging from 13.9 to 31.7 MPa, Young's modulus ranging from 185.6 to 992.7 MPa and elongation at break ranging from 2.8%to 68.3%）. Moreover, polymer welding facilitated the creation of gradient materials, showcasing the potential for engineered applications of poly（vinyl ethers）(PVEs).

关键词： 3D printing cationic RAFT polymerization vat photopolymerization vinyl ether

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Soft Crawling and Flipping Robots Based on Liquid Metal-Liquid Crystal Elastomer Composites

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Chinese Journal of Polymer science 2025年第4期43卷 588-596页

作者： Ling-Xin Yuan Chang-Yue Liu Ji-Ping Yang Zhi-Jian Wang Key Laboratory of Aerospace Advanced Materials and Performance Ministry of EducationSchool of Materials Science and EngineeringBeihang UniversityBeijing 100191China Tianmushan Laboratory Hangzhou 310023China

Soft robots have shown great advantages with simple structure,high degree of freedom,continuous deformation,and benign human-machine *** the past decades,a variety of soft robots,including crawling,jumping,swimming,and climbing robots,have been developed inspired by living ***,most of the reported bionic soft robots have only a single mode of motion,which limits their practical ***,we report a fully 3D printed crawling and flipping soft robot using liquid metal incorporated liquid crystal elastomer(LM-LCE)composite as the *** the application of voltage,liquid metal works as the conductive Joule heating material to induce the contraction of the LCE *** bending angle of the LM-LCE composite actuator highly depends on the applied *** further demonstrate that the soft robot can exhibit distinct moving behaviors,such as crawling or flipping,by applying different *** fully 3D printed LM-LCE composite structure provides a strategy for the fast construction of soft robots with diverse motion modes.

关键词： Liquid crystal elastomer Liquid metal Soft actuator 3D printing

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High-temperature optoelectronic synaptic devices based on 4H-SiC

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science China(Information sciences) 2025年第4期68卷 151-159页

作者： Mingxuan BU Yue WANG Zhenyi NI Dongke LI Deren YANG Xiaodong PI State Key Laboratory of Silicon and Advanced Semiconductor Materials & School of Materials Science and Engineering Zhejiang University Institute of Advanced Semiconductors & Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University

Optoelectronic synaptic devices operating at high temperatures have application potential across many important fields, including the aerospace and defense industries. However, limited research exists on such devices. Herein, we fabricate4H-SiC-based high-temperature optoelectronic synaptic devices that are capable of achieving diverse synaptic functionalities at temperatures as high as 600 K. The synaptic functionalities are realized for these devices through carrier capture and release of the deep-level defects introduced via electronic irradiation. A 3 × 3 array of high-temperature optoelectronic synaptic devices enables the image memory functions. A neural network model constructed using this array addresses the issue of color quantization. The optoelectronic synaptic devices thus developed are capable of high-temperature applications.

关键词： optoelectronic synaptic devices 4H-SiC synaptic plasticity neuromorphic computing high-temperature devices

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