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Effect of Noncontact Ultrasonic Technology on Solidification Quality of Electroslag Steel

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Journal of Iron and Steel Research International 2016年第11期23卷 1168-1176页

作者： Xiao-fang SHI Li-zhong CHANG zheng-hai zhu Jian-jun WANG Li ZHOU School of Metallurgy Engineering Anhui University of Technology

A new electroslag furnace with ultrasonic vibration introduced through water-cooled base plate was de- signed and the effects of ultrasonic power on the distribution of elements, compactness and carbides in the electroslag remelting （ESR） ingots was investigated. The results showed that the distribution of elements on the entire excita- tion section changed with the change of ultrasonic power under experimental conditions. The statistical segregation of elements was minimum when the ultrasonic power was 500 W, whereas excessively high or excessively low power was not conducive to the uniform distribution of elements. Meanwhile, the compactness of ESR ingots gradually in- creased with the increase in ultrasonic power and distribution of compactness was the most uniform when ultrasonic power reached 500 W. Further increase in the ultrasonic power was not conducive to the improvement of compactness. The distribution characteristic of carbides was similar to the distribution of elements and compactness. The re- sults indicated that the ultrasonic vibration introduced through water-cooled base plate was advantageous in impro- ving solidification quality. However, this method needed reasonable ultrasonic power. Moreover, the effects of ultra- sonic power varied for different elements.

关键词： ultrasonic eleetroslag remelting solidification element distribution carbide

Effect of Ti/V ratio on thermodynamics and kinetics of MC in γ/α matrices of Ti-V microalloyed steels

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Journal of Iron and Steel Research International 2021年第8期28卷 1019-1029页

作者： Ke Zhang Xin-jun Sun Zhao-dong Li Kun Xu Tao Jia zheng-hai zhu Xiao-yu Ye Jun-yu Kang Qi-long Yong State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization Panzhihua Group Co.Ltd.Panzhihua 617000SichuanChina School of Metallurgical Engineering Anhui University of TechnologyMaanshan 243032AnhuiChina Institute of Structural Steels Central Iron and Steel Research InstituteBeijing 100081China State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang 110819LiaoningChina

Through the solubility product theory of the ternary secondary phase,classical nucleation theory,and Ostwald ripening theory,a model was established to describe the thermodynamics and kinetics of(Ti,V)C precipitates in austenite/ferrite(y/α)*** model was used to calculate the volume fraction,precipitation-temperature-time(PTT)curve,and nucleation rate-temperature(NrT)curve of MC(M=Ti,V)precipitates in γ/α matrices in Ti-V microalloyed steels with various Ti/V ratios,which is verified by hardness tester,transmission electron microscopy and energy-dispersive X-ray *** calculations indicate that,by decreasing Ti/V ratio from Ti4V0 steel to Ti0V4 steel,the complete-dissolution temperature decreases monotonically from 1226 to 830℃,and the equilibrium volume fraction of MC pre-cipitated from austenite decreases from 0.333%to 0.091%at 900℃.Moreover,the maximum nucleation temperature of MC precipitated from α matrix decreases from 748 to 605℃and the fastest precipitation temperature decreases from 844 to 675℃as Ti/V ratio *** and NrT diagrams of MC precipitated from α matrices in different Ti-V microalloyed steels all exhibit C-shaped and inverse C-shaped *** addition,both theoretical calculation and experimental results show that when tempered at 600℃for 100 h,Ti2V2 steel shows the largest hardness value of 312 HV among the three steels tested because it has a larger volume fraction(0.364%),a larger precipitate density(1689 μm-2),and the smallest average size(8.4 nm)of(Ti,V)C *** theoretical calculations are consistent with experimental results,which indicates that the thermodynamics and kinetics model for(Ti,V)C precipitates is reliable and accurate.

关键词： (Ti V)C precipitate Thermodynamics Kinetics Ti-V microalloyed steel Coarsening rate Hardness

Precipitation Behavior and Microstructural Evolution of Ferritic Ti–V–Mo Complex Microalloyed Steel

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Acta Metallurgica Sinica(English Letters) 2018年第9期31卷 997-1005页

作者： Ke Zhang Hui Wang Xin-Jun Sun Feng-Li Sui Zhao-Dong Li En-Xiang Pu zheng-hai zhu Zhen-Yi Huang Hong-Bo Pan Qi-Long Yong Key Laboratory of Metallurgical Emission Reduction and Resources Recycling Anhui University of TechnologyMinistry of EducationMaanshan 243032China School of Metallurgical Engineering Anhui University of TechnologyMaanshan 243032China Central Iron and Steel Research Institute Beijing 100081China

Precipitation behavior of （Ti, V, Mo）C and microstructural evolution of the ferritic Ti-V-Mo complex microalloyed steel were investigated through changing coiling temperature （CT）. It is demonstrated that the strength of the Ti-V-Mo microalloyed steel can be ascribed to the combination of grain refinement hardening and precipitation hardening. The variation of hardness （from 318 to 415 HV, then to 327 HV） with CT （from 500 to 600-625 ℃, then to 700 ℃） was attributed to the changes of volume fraction and particle size of （Ti, V, Mo）C precipitates. The optimum CT was considered as 600-625 ℃, at which the maximum hardness value （415 HV） can be obtained. It was found that the atomic ratios of Ti, V and Mo in （Ti, V, Mo）C carbides were changed as the CT increased. The precipitates with the size of 〈 10 nm were the V-rich particles at higher CT of 600 and 650 ℃, while the Ti-rich particles were observed at lower CT of 500 and 550 ℃. Theoretical calculations indicated that the maximum nucleation rate of （Ti, V, Mo）C in ferrite matrix occurred around 630 ℃, which was consistent with the 625 ℃ obtained from experiment results.

关键词： Nano-sized precipitates Precipitation hardening Ti-V-Mo Coiling temperature Ferrite

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收发信机射频损伤的UDN协同波束形成

北京邮电大学学报 2016年第5期39卷 11-15页

作者：方正黎海涛朱广李艳航空电子系统综合技术重点实验室上海200241 北京工业大学北京100124

为了进一步提高超密集无线网络(UDN)性能,提出一种同时考虑收发信机射频损伤的协同波束形成方法.首先,建立了包含射频损伤的UDN协同波束形成模型,并利用凸优化方法求解得到其最优解;然后,针对此最优解的结构特征,结合其在实际系统中难... 详细信息

为了进一步提高超密集无线网络(UDN)性能,提出一种同时考虑收发信机射频损伤的协同波束形成方法.首先,建立了包含射频损伤的UDN协同波束形成模型,并利用凸优化方法求解得到其最优解;然后,针对此最优解的结构特征,结合其在实际系统中难以实现的局限,设计了由信号泄漏噪声比波束形成导向矢量和最优功率分配构成的线性次优波束形成器.仿真结果表明,收发信机射频损伤的协同波束形成器能有效降低干扰,并且可提高UDN的系统容量.

关键词：协同波束形成和速率射频损伤凸优化

Defect Engineering with Rational Dopants Modulation for High‑Temperature Energy Harvesting in Lead‑Free Piezoceramics

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Nano-Micro Letters 2025年第3期17卷 87-101页

作者： Kaibiao Xi Jianzhe Guo Mupeng zheng Mankang zhu Yudong Hou Key Laboratory of Advanced Functional Materials Ministry of EducationCollege of Materials Science and EngineeringBeijing University of TechnologyBeijing 100124People’s Republic of China

High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless ***,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported ***,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese *** to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese *** HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.

关键词： Lead-free piezoceramic Defect engineering Dopants modulation High-temperature Piezoelectric energy harvester

CNKSR2 interactome analysis indicates its association with the centrosome/microtubule system

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Neural Regeneration Research 2025年第8期20卷 2420-2432页

作者： Lin Yin Yalan Xu Jie Mu Yu Leng Lei Ma Yu zheng Ruizhi Li Yin Wang Peifeng Li hai zhu Dong Wang Jing Li Institute for Translational Medicine The Affiliated Hospital of Qingdao UniversityMedical CollegeQingdao UniversityQingdaoShandong ProvinceChina School of Basic Medicine Qingdao UniversityQingdaoShandong ProvinceChina College of Life Sciences and School of PharmacyMedical CollegeQingdao UniversityQingdaoShandong ProvinceChina Department of Urology Qingdao Municipal Hospital Affiliated to Qingdao UniversityQingdaoShandong ProvinceChina

The protein connector enhancer of kinase suppressor of Ras 2(CNKSR2),present in both the postsynaptic density and cytoplasm of neurons,is a scaffolding protein with several protein-binding *** of the CNKSR2 gene have been implicated in neurodevelopmental disorders,particularly intellectual disability,although the precise mechanism involved has not yet been fully *** has demonstrated that CNKSR2 plays a role in facilitating the localization of postsynaptic density protein complexes to the membrane,thereby influencing synaptic signaling and the morphogenesis of dendritic ***,the function of CNKSR2 in the cytoplasm remains to be *** this study,we used immunoprecipitation and high-resolution liquid chromatography-mass spectrometry to identify the interactors of *** a combination of bioinformatic analysis and cytological experiments,we found that the CNKSR2 interactors were significantly enriched in the proteome of the *** also showed that CNKSR2 interacted with the microtubule protein DYNC1H1 and with the centrosome marker *** colocalization analysis confirmed the centrosomal localization of *** we downregulated CNKSR2 expression in mouse neuroblastoma cells(Neuro 2A),we observed significant changes in the expression of numerous centrosomal *** manipulation also affected centrosome-related functions,including cell size and shape,cell proliferation,and ***,we found that CNKSR2 interactors were highly enriched in de novo variants associated with intellectual disability and autism spectrum *** findings establish a connection between CNKSR2 and the centrosome,and offer new insights into the underlying mechanisms of neurodevelopmental disorders.

关键词： autism spectrum disorder centrosome CNKSR2 intellectual disability interactome mass spectrometry microtubule neurodevelopmental disease protein complexes protein-protein interactions

Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng zheng Wang Ruisong zhu Ruijie Liu Jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control Engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

Ammonia-induced CuO/13X for H_(2)S removal from simulated blast furnace gas at low temperature

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Green Energy & Environment 2025年第1期10卷 139-149页

作者： Erping Cao Yuhua zheng Hao Zhang Jianshan Wang Yuran Li Tingyu zhu Zhan-guo Zhang Guangwen Xu Yanbin Cui State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing100190China State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization PanGang Group Research Institute Co.Ltd.Panzhihua Sichuan617000China Shenyang University of Chemical Technology Shenyang110142China University of Chinese Academy of Sciences Beijing 100049China

Blast furnace gas(BFG)is an important by-product energy for the iron and steel industry and has been widely used for heating or electricity ***,the undesirable contaminants in BFG(especially H_(2)S)generate harmful environmental *** desulfurization of BFG is urgent for integrated steel plants due to the stringent ultra-low emission *** with other desulfurization materials,zeolite-based adsorbents represent a viable option with low costs and long service *** this study,an ammonia-induced CuO modified 13X adsorbent(NH3–CuO/13X)was prepared for H_(2)S removal from simulated BFG at low *** XRD,H_(2)-TPR and TEM analysis proved that smaller CuO particles were formed and the dispersion of Cu on the surface of 13X zeolite was improved via the induction of *** on H_(2)S adsorption performance of the adsorbent was carried out using simulated BFG,and the results showed that NH3–CuO/13X-3 has better breakthrough sulfur capacity,which was more than twice the sulfur capacity of CuO/*** is proposed that the enhanced desulfurization performance of NH3–CuO/13X is attributed to an abundant pore of 13X,and combined action of 13X and *** work provided an effective way to improve the sulfur capacity of zeolite-based adsorbents via impregnation method by ammonia induction.

关键词： Blast furnace gas Desulfurization Ammonia-induced CuO 13X zeolite

RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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Science China(Information Sciences) 2025年

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao zhu hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

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