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State of the art in applications of machine learning in steelmaking process modeling

International Journal of Minerals,Metallurgy and Materials 2023年第11期30卷 2055-2075页

作者： runhao zhang Jian Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking *** learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of *** application of machine learning in the steelmaking process has become a research hotspot in recent *** paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other *** three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,*** data in the steelmaking plants are frequently ***,data processing,especially data cleaning,is crucially important to the performance of machine learning *** detection of variable importance can be used to optimize the process parameters and guide *** learning is used in hot metal pretreatment modeling mainly for endpoint S content *** predictions of the endpoints of element compositions and the process parameters are widely investigated in primary *** learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization *** development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.

关键词： machine learning steelmaking process modeling artificial neural network support vector machine case-based reasoning data processing

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Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 508-517页

作者： runhao zhang Jian Yang Han Sun Wenkui Yang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringShanghai UniversityShanghai 200444China

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking *** ELM model exhibites the best performance compared with the models of MLR and ***-ELM and FOS-ELM are applied for sequential learning and model *** optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the *** variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization *** lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one *** hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,*** coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,*** system exhibits desirable performance for applications in actual industrial pro-duction.

关键词： basic oxygen furnace steelmaking machine learning lime utilization ratio dephosphorization online sequential extreme learning machine forgetting mechanism

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Electrifying the future:the advances and opportunities of electrocatalytic carbon dioxide reduction in acid

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Science China Chemistry 2023年第12期66卷 3426-3442页

作者： runhao zhang Haoyuan Wang Yuan Ji Qiu Jiang Tingting Zheng Chuan Xia Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 230026China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731China

Transforming carbon dioxide(CO_(2))into products using renewable electricity is a crucial and captivating quest for a green and circular *** with commonly used alkali electrolytes,acidic media for electrocatalytic CO_(2) reduction(CO_(2)RR)boasts several advantages,such as high carbon utilization efficiency,high overall energy utilization rate,and low carbonate formation,making it a compelling choice for industrial ***,the acidic CO_(2)RR also struggles with formidable hurdles,encompassing the fierce competition with the hydrogen evolution reaction,the low CO_(2) solubility and availability,and the suboptimal performance of *** review provides a comprehensive overview of the CO_(2)RR in acidic *** elucidating the underlying regulatory mechanism,we gain valuable insights into the fundamental principles governing the acidic CO_(2)***,we examine cutting-edge strategies aimed at optimizing its performance and the roles of reactor engineering,especially membrane electrode assembly reactors,in facilitating scalable and carbon efficient ***,we present a forward-looking perspective,highlighting the promising prospects of acidic CO_(2)RR research in ushering us towards a carbon-neutral society.

关键词： electrocatalytic CO_(2)reduction acidic electrolyte microenvironment alkali metal cations electrolysers

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Super-assembled highly compressible and flexible cellulose aerogels for methylene blue removal from water

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Chinese Chemical Letters 2021年第6期32卷 2091-2096页

作者： Mingfu Luo Meng Wang Huaipeng Pang runhao zhang Jing Huang Kang Liang Pu Chen Peipei Sun Biao Kong National Supercomputer Research Center of Advanced Materials Advanced Materials InstituteQilu University of Technology(Shandong Academy of Sciences)Ji'nan 250014China Department of Chemistry Shanghai Key Lab of Molecular Catalysis and Innovative Materials iChEMFudan UniversityShanghai 200433China School of Chemical Engineering and Graduate School of Biomedical Engineering The University of New South WalesNSW 2052Australia Department of Chemical Engineering University of WaterlooWaterlooOntario N2L 3G1Canada

Physical adsorption is a common method to solve the contamination of methylene blue in dyeing *** a kind of adsorption material,cellulose aerogels with high porosity and surface areas have great potential application in methylene blue ***,the week hydrogen bonding between cellulose nanofibers making the cellulose aerogels with the poor mechanical properties and can be easily destroyed during ***,the preparation of cellulose aerogels with high mechanical strength is still a great ***,we report a robust super-assembly strategy to fabricate cellulose aerogels by combining cellulose nanofibers with PVA and *** resulting cellulose aerogels not only has a robust chemically cross-linked network,but also has strong H-bonds,which greatly enhance the mechanical *** resulting cellulose aerogels possess a low density of 19.32 mg/cm^(3).Furthermore,the cellulose aerogel shows 93%shape recovery under 60%strain(9.5 k Pa under 60%strain)after 100 cycles,showing excellent mechanical *** adsorption capacity of cellulose aerogel to methylene blue solution of 20 mg/L is 2.28 mg/g and the adsorption kinetics and adsorption isotherms have also been ***-second-order kinetic model and Freundlich isotherm model are more acceptable for indicating the adsorption process of methylene blue on the cellulose ***,this compressible and durable cellulose aerogel is a very prospective material for dyeing wastewater cleanup.

关键词： Cellulose nanofiber Aerogel Compressible Adsorption Methylene blue

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Super-assembled core-shell mesoporous silica-metal-phenolic network nanoparticles for combinatorial photothermal therapy and chemotherapy

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Nano Research 2020年第4期13卷 1013-1019页

作者： Bo Yang Shan Zhou Jie Zeng Liping zhang runhao zhang Kang Liang Lei Xie Bing Shao Shaoli Song Gang Huang Dongyuan Zhao Pu Chen Biao Kong Department of Chemistry Shanghai Key Lab of Molecular Catalysis and Innovative MaterialsiChEMFudan UniversityShanghai 200032China School of Chemical Engineering and Graduate School of Biomedical Engineering The University of New South WalesNSW 2052Australia Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning Beijing Center for Disease Prevention and ControlBeijing 100013China Department of Nuclear Medicine Shanghai Cancer CenterFudan UniversityShanghai 200032China Shanghai Key Laboratory of Molecular Imaging Shanghai University of Medicine and Health SciencesShanghai 201318China Institute of Clinical Nuclear Medicine Renji Hospital Shanghai Jiao Tong University School of MedicineShanghai 200127China Department of Chemical Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada

Multimodal combinatorial therapy merges different modes of therapies in one platform,which can overcome several clinical challenges such as premature drug loss during blood circulation and significantly improve treatment *** we report a combinatorial therapy nanoplatform that enables dual photothermal therapy and pH-stimulus-responsive *** super-assembly of mesoporous silica nanoparticles(MSN)with metal-phenolic networks(MPN),anti-cancer drugs can be loaded in the MSN matrix,while the outer MPN coating allows dual photothermal and pH-responsive *** near-infrared light irradiation,the MSN@MPN nanoplatform exhibits excellent photothermal effect,and demonstrates outstanding pH-triggered drug release *** vitro cell experiments suggest the MSN@MPN system exhibits superior biocompatibility and can effectively kill tumor cells after loading anti-cancer ***,the MSN@MPN system shows promising prospects in clinical application for tumor therapy.

关键词： pH-responsive photothermal therapy metal-polyphenol complex synergistic therapy

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Super-assembled sandwich-like Au@MSN@Ag nanomatrices for high-throughput and efficient detection of small biomolecules

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Nano Research 2022年第3期15卷 2722-2733页

作者： Dantong Zhao Chunxia Ma Meng Gao Yong Li Bo Yang Hui Li runhao zhang Minglu Hao Jing Huang Kang Liang Pu Chen Lei Xie Rong Rong Biao Kong College of Medicine Shandong University of Traditional Chinese MedicineJinan 250355China Shandong Analysis and Test Center National Supercomputer Research Center of Advanced MaterialsAdvanced Materials InstituteQilu University of Technology(Shandong Academy of Sciences)Jinan 250014China Heze Institute for Food and Drug Control Heze 274000China School of Chemical Engineering and Graduate School of Biomedical Engineering The University of New South WalesNSW 2052Australia Department of Chemical Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada Department of Chemistry Shanghai Key Lab of Molecular Catalysis and Innovative MaterialsiChEMFudan UniversityShanghai 200032China

Small biomolecules(m/z<500)are the material basis of organisms and participate in life activities,but their comprehensive and accurate detection in complex samples remains a ***-assisted laser desorption/ionization mass spectrometry(MALDI-MS)is a powerful detection tool for molecular analysis with high *** development of a new matrix is essential to improve the efficiency of the MALDI-MS for molecular compound *** this work,the sandwich-like gold nanoparticles@mesoporous silica nanocomposite@silver nanoparticles(Au@MSN@Ag)nanospheres were prepared by layer-by-layer super-assembly strategy,and can be used as a novel matrix for the quantitative detection and enrichment of small biomolecules by *** sandwich-like nanospheres form a unique plasma resonant cavity that effectively absorbs the laser energy,while the homogeneous mesoporous structure of MSN can lock the analyte,which is essential for efficient LDI of small *** to traditional matrices,Au@MSN@Ag shows the advantages of low background,wide application range,high sensitivity,super high salt and protein tolerance,and good *** example,the detection limit of glucose was as low as 5 fmol,and showed a good linear relationship in the range of 1−750μg/***@MSN@Ag assisted LDI-MS allows the enrichment and detection of small molecules in traditional Chinese medicine(TCM)without derivatization and purification,classification of herbs using the accurate quantitative results oligosaccharides,and identification of gelatin by amino acid *** research could help in designing more efficient nanostructure matrices and further explored the application of LDI-MS.

关键词： matrix-assisted laser desorption/ionization mass spectrometry(MALDI-MS) matrix sandwich-like nanostructures small biomolecules traditional Chinese medicine(TCM)

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Manipulation of π-aromatic conjugation in two-dimensional Sn-organic materials for efficient lithium storage

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eScience 2023年第2期3卷 123-130页

作者： Jingwei Liu Jialong Jiang Qingyang Zhou Zhonghang Chen runhao zhang Xiufang Xu Xue Han Sihai Yang Zhen Zhou Peng Cheng Wei Shi Department of Chemistry Key Laboratory of Advanced Energy Materials Chemistry(MOE)and Renewable Energy Conversion and Storage Center(RECAST)College of ChemistryNankai UniversityTianjin300071China Department of Chemistry University of ManchesterManchesterM139PLUK Institute of New Energy Material Chemistry School of Materials Science and EngineeringNankai UniversityTianjin300350China Haihe Laboratory of Sustainable Chemical Transformations Tianjin300192China

Sn-based materials are promising candidates for lithium storage but suffer generally from huge volume change during the(de)lithiation ***-organic materials with monodispersed Sn centers surrounded by lithium active ligands can alleviate the volume change of anode materials based on reversible(de)lithiation ***,the structural factors governing the kinetics of lithium storage and utilization efficiency of active sites are not well understood to ***,we report three two-dimensional Sn-organic materials with enhanced lithium storage performance by manipulation ofπ-aromatic conjugation of the *** increasingπ-aromatic conjugation plays a key role in promoting efficient lithium storage,and the volume expansion during the(de)lithiation reaction is suppressed in these Sn-organic *** work reveals that theπ-aromatic conjugation of the ligand is crucial for improving the kinetics of lithium storage and the utilization of active sites in metalorganic materials with minimised volume expansion.

关键词： Lithium-ion batteries Sn-organic materials π-aromatic conjugation Volume expansion buffer

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襄阳市家具产业发展研究

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湖北文理学院学报 2014年第2期35卷 74-77页

作者：张润昊襄阳职业技术学院高职教育研究所湖北襄阳441050

襄阳市林木资源禀赋条件优势明显,但家具产业集群发展水平较低,文章分析总结了襄阳家具行业发展中存在的政府重视程度低、产业集群未形成、品牌观念淡薄、管理人员素质亟待提高等问题,为襄阳家具行业发展提出了政府层面拟定襄阳家具行... 详细信息

襄阳市林木资源禀赋条件优势明显,但家具产业集群发展水平较低,文章分析总结了襄阳家具行业发展中存在的政府重视程度低、产业集群未形成、品牌观念淡薄、管理人员素质亟待提高等问题,为襄阳家具行业发展提出了政府层面拟定襄阳家具行业发展规划、加强家具园区建设、拓展融资渠道等政策建议.

关键词：家具产业襄阳市市场潜力品牌观念拓展融资

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基于高斯自适应拟合的苹果目标分割方法研究

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农机化研究 2015年第6期37卷 13-17页

作者：张润浩李军任静宋怀波西北农林科技大学机械与电子工程学院陕西杨凌712100

苹果目标的准确识别是苹果机械化采摘需要解决的关键问题之一。为此,基于YUV颜色空间模型,提出了一种结合色差分量与高斯自适应拟合算法的苹果目标分割方法。该方法采用首先将苹果目标由RGB颜色空间转换至YUV颜色空间,并利用色差分量V... 详细信息

苹果目标的准确识别是苹果机械化采摘需要解决的关键问题之一。为此,基于YUV颜色空间模型,提出了一种结合色差分量与高斯自适应拟合算法的苹果目标分割方法。该方法采用首先将苹果目标由RGB颜色空间转换至YUV颜色空间,并利用色差分量V建立果实与背景分割的高斯分布拟合模型,根据拟合结果自动获取分割阈值,以实现自然场景下苹果目标的准确分割。为了验证文中算法的有效性,利用多幅图像进行了试验并与Otsu自适应阈值分割算法进行了比较。试验结果表明,采用文中算法得到的苹果果实的平均检出率达87.08%,识别率领先Otsu算法9.91%。因此,对于着色度较为均匀的苹果目标,采用高斯自适应拟合方法可以有效提高其识别率。

关键词：苹果高斯分布颜色空间图像分割

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复杂环境下的UWB精确定位技术研究

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无线互联科技 2023年第3期20卷 100-102页

作者：杨瑞张敏张润豪西京学院陕西西安710123

文章主要解决在强干扰下的室内精确定位的问题。根据UWB测距原理得出靶点坐标与锚点距离的关系,求解出靶点的三维坐标,利用卡尔曼滤波方法进一步提升定位坐标的精度,从而得到靶点的精确位置,并对采集的数据进行计算。另外,设定靶点的初... 详细信息

文章主要解决在强干扰下的室内精确定位的问题。根据UWB测距原理得出靶点坐标与锚点距离的关系,求解出靶点的三维坐标,利用卡尔曼滤波方法进一步提升定位坐标的精度,从而得到靶点的精确位置,并对采集的数据进行计算。另外,设定靶点的初始值,建立自适应参数目标模型对目标的运动轨迹进行估计。结果显示,根据卡尔曼滤波方法对其进行预测和定位,预测结果与真实结果基本吻合,并最终得到动态靶点的运动轨迹图。随着UWB技术的不断发展,相信未来室内的定位技术可以得到更快的发展。

关键词：线性卡尔曼滤波误差估计精确定位

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