{"title":"Modeling and Experimental Researches on Redox Reactions of Iron Ore Oxygen Carriers in Chemical Looping","authors":"Wang Hui, Lei Liu, Kexin Li, Di Zhong","doi":"10.1002/eng2.13064","DOIUrl":null,"url":null,"abstract":"<p>Developing a reliable kinetic model for these redox reactions is crucial for understanding and improving oxygen carriers practical in chemical looping applications. The traditional pore model assumes that the solid product forms a continuous layer uniformly covering the solid reactant surface during the gas–solid reactions, in the result the model fails to capture the kinetic transitions caused by the actual solid structure change. We integrated product island growth theory into random pore model (RPM). The model assumes the oxygen carrier has randomly distributed and overlapped pores, involving surface chemical reactions, product island growth, product layer diffusion, internal gas diffusion, and external gas diffusion to the particle surface. The model was verified using data of a natural iron ore from micro-fluidized bed thermogravimetric analysis (MFB-TGA) experiments. The kinetic parameters include chemical reaction rate constant (<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>k</mi>\n <mi>s</mi>\n </msub>\n </mrow>\n <annotation>$$ {k}_{\\mathrm{s}} $$</annotation>\n </semantics></math>), critical product layer thickness (<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>h</mi>\n <mi>C</mi>\n </msub>\n </mrow>\n <annotation>$$ {h}_{\\mathrm{C}} $$</annotation>\n </semantics></math>), and product layer diffusion coefficient (<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>D</mi>\n <mi>P</mi>\n </msub>\n </mrow>\n <annotation>$$ {D}_{\\mathrm{P}} $$</annotation>\n </semantics></math>). The reduction reaction rate is primarily governed by the chemical reaction, while both surface chemical reactions and product layer diffusion significantly influence the oxidation reaction. The reduction reaction, with an activation energy of 84.2 kJ/mol, is more temperature-sensitive than the oxidation reaction, which has an activation energy of 41.88 kJ/mol. Reaction temperature, particle size, and reactant gas concentration significantly impact the reaction rate and conversion of iron ore oxygen carriers. The model effectively predicts and analyzes the redox behavior of natural iron ore oxygen carrier, providing insights to optimize its performance.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":"7 2","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.13064","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.13064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Developing a reliable kinetic model for these redox reactions is crucial for understanding and improving oxygen carriers practical in chemical looping applications. The traditional pore model assumes that the solid product forms a continuous layer uniformly covering the solid reactant surface during the gas–solid reactions, in the result the model fails to capture the kinetic transitions caused by the actual solid structure change. We integrated product island growth theory into random pore model (RPM). The model assumes the oxygen carrier has randomly distributed and overlapped pores, involving surface chemical reactions, product island growth, product layer diffusion, internal gas diffusion, and external gas diffusion to the particle surface. The model was verified using data of a natural iron ore from micro-fluidized bed thermogravimetric analysis (MFB-TGA) experiments. The kinetic parameters include chemical reaction rate constant (), critical product layer thickness (), and product layer diffusion coefficient (). The reduction reaction rate is primarily governed by the chemical reaction, while both surface chemical reactions and product layer diffusion significantly influence the oxidation reaction. The reduction reaction, with an activation energy of 84.2 kJ/mol, is more temperature-sensitive than the oxidation reaction, which has an activation energy of 41.88 kJ/mol. Reaction temperature, particle size, and reactant gas concentration significantly impact the reaction rate and conversion of iron ore oxygen carriers. The model effectively predicts and analyzes the redox behavior of natural iron ore oxygen carrier, providing insights to optimize its performance.