{"title":"二氧化碳等温条件下花生壳、腰果壳和小米秸秆生物糙米的活化动力学","authors":"Philippe Bernard Himbane, Lat Grand Ndiaye","doi":"10.1016/j.sajce.2024.06.004","DOIUrl":null,"url":null,"abstract":"<div><p>This study investigates the reactivity kinetics of biochar from biomass. The biochars were obtained by pyrolyzing peanut shells (PNS_800), cashew nut shells (CNS_800), and millet stalks (MS_800) at 800 °C in a fixed bed reactor. The chemical composition of the biochar samples shows that silicon (Si), potassium (K), and magnesium (Mg) are the major elements in the biochar of peanut shells (PNS_800) while potassium and magnesium are the major elements in the biochar of cashew nut shells (CNS_800) and millet stalks (MS_800). The biochars were activated in a CO<sub>2</sub> (200 Nml/min) atmosphere at temperatures 1123 K, 1173 K, and 1223 K under atmospheric pressure. The random pore model (RPM) and a modified random pore model (MRPM) were used to correlate the reactivity profiles versus carbon conversion and to determine the kinetic parameters. It was observed that biochar reactivity increases as the temperature increases, attaining at least three times at 1173 K than those corresponding to 1123 K. Furthermore, the increase in reactivity is more pronounced with the biochar MS_800. It was observed that the RPM model cannot follow the kinetic of the experimental reactivity of all biochar samples. However, a better fitting of the reactivity is obtained when using the MRPM model. The activation energies (E<sub>a</sub>) are distributed in the range of 98.11–148.46 kJ/mol while the pre-exponential factors (k<sub>0</sub>) are in the range of 19.31–249.53 s<sup>-1</sup>. It was observed that for the MRPM model, the lower activation energy and the lower pre-exponential factor were obtained by the biochar CNS_800. However, E<sub>a</sub> et k<sub>0</sub> are well evaluated for PNS_800 and MS_800 with a coefficient of determination of 99.76%. The proposed modified random pore model could be used to describe the reactivity of biochar from biomass as well as the reactivity of coal.</p></div>","PeriodicalId":21926,"journal":{"name":"South African Journal of Chemical Engineering","volume":"49 ","pages":"Pages 249-257"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1026918524000714/pdfft?md5=44e0e48000f5519c387ec31a42783633&pid=1-s2.0-S1026918524000714-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Activation kinetics of biochars from peanut shells, cashew nut shells, and millet stalks under isothermal conditions in CO2 atmosphere\",\"authors\":\"Philippe Bernard Himbane, Lat Grand Ndiaye\",\"doi\":\"10.1016/j.sajce.2024.06.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study investigates the reactivity kinetics of biochar from biomass. The biochars were obtained by pyrolyzing peanut shells (PNS_800), cashew nut shells (CNS_800), and millet stalks (MS_800) at 800 °C in a fixed bed reactor. The chemical composition of the biochar samples shows that silicon (Si), potassium (K), and magnesium (Mg) are the major elements in the biochar of peanut shells (PNS_800) while potassium and magnesium are the major elements in the biochar of cashew nut shells (CNS_800) and millet stalks (MS_800). The biochars were activated in a CO<sub>2</sub> (200 Nml/min) atmosphere at temperatures 1123 K, 1173 K, and 1223 K under atmospheric pressure. The random pore model (RPM) and a modified random pore model (MRPM) were used to correlate the reactivity profiles versus carbon conversion and to determine the kinetic parameters. It was observed that biochar reactivity increases as the temperature increases, attaining at least three times at 1173 K than those corresponding to 1123 K. Furthermore, the increase in reactivity is more pronounced with the biochar MS_800. It was observed that the RPM model cannot follow the kinetic of the experimental reactivity of all biochar samples. However, a better fitting of the reactivity is obtained when using the MRPM model. The activation energies (E<sub>a</sub>) are distributed in the range of 98.11–148.46 kJ/mol while the pre-exponential factors (k<sub>0</sub>) are in the range of 19.31–249.53 s<sup>-1</sup>. It was observed that for the MRPM model, the lower activation energy and the lower pre-exponential factor were obtained by the biochar CNS_800. However, E<sub>a</sub> et k<sub>0</sub> are well evaluated for PNS_800 and MS_800 with a coefficient of determination of 99.76%. The proposed modified random pore model could be used to describe the reactivity of biochar from biomass as well as the reactivity of coal.</p></div>\",\"PeriodicalId\":21926,\"journal\":{\"name\":\"South African Journal of Chemical Engineering\",\"volume\":\"49 \",\"pages\":\"Pages 249-257\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1026918524000714/pdfft?md5=44e0e48000f5519c387ec31a42783633&pid=1-s2.0-S1026918524000714-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Chemical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1026918524000714\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Chemical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1026918524000714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
摘要
本研究探讨了从生物质中提取生物炭的反应动力学。生物炭是在固定床反应器中于 800 °C 高温下热解花生壳 (PNS_800)、腰果壳 (CNS_800) 和小米秆 (MS_800) 得到的。生物炭样品的化学成分显示,花生壳(PNS_800)生物炭中的主要元素是硅(Si)、钾(K)和镁(Mg),而腰果壳(CNS_800)和小米秆(MS_800)生物炭中的主要元素是钾和镁。生物炭在二氧化碳(200 Nml/min)气氛中活化,温度分别为 1123 K、1173 K 和 1223 K,压力为大气压。使用随机孔隙模型(RPM)和改进的随机孔隙模型(MRPM)将反应性曲线与碳转化率相关联,并确定动力学参数。结果表明,生物炭的反应性随着温度的升高而增加,1173 K 时的反应性至少是 1123 K 时的三倍。据观察,RPM 模型无法跟踪所有生物炭样品的实验反应动力学。然而,使用 MRPM 模型可以更好地拟合反应活性。活化能 (Ea) 分布在 98.11-148.46 kJ/mol 的范围内,而预指数 (k0) 则在 19.31-249.53 s-1 的范围内。据观察,在 MRPM 模型中,生物炭 CNS_800 的活化能和预指数较低。然而,PNS_800 和 MS_800 的 Ea 和 k0 得到了很好的评估,确定系数为 99.76%。所提出的修正随机孔隙模型可用于描述生物质生物炭的反应性以及煤的反应性。
Activation kinetics of biochars from peanut shells, cashew nut shells, and millet stalks under isothermal conditions in CO2 atmosphere
This study investigates the reactivity kinetics of biochar from biomass. The biochars were obtained by pyrolyzing peanut shells (PNS_800), cashew nut shells (CNS_800), and millet stalks (MS_800) at 800 °C in a fixed bed reactor. The chemical composition of the biochar samples shows that silicon (Si), potassium (K), and magnesium (Mg) are the major elements in the biochar of peanut shells (PNS_800) while potassium and magnesium are the major elements in the biochar of cashew nut shells (CNS_800) and millet stalks (MS_800). The biochars were activated in a CO2 (200 Nml/min) atmosphere at temperatures 1123 K, 1173 K, and 1223 K under atmospheric pressure. The random pore model (RPM) and a modified random pore model (MRPM) were used to correlate the reactivity profiles versus carbon conversion and to determine the kinetic parameters. It was observed that biochar reactivity increases as the temperature increases, attaining at least three times at 1173 K than those corresponding to 1123 K. Furthermore, the increase in reactivity is more pronounced with the biochar MS_800. It was observed that the RPM model cannot follow the kinetic of the experimental reactivity of all biochar samples. However, a better fitting of the reactivity is obtained when using the MRPM model. The activation energies (Ea) are distributed in the range of 98.11–148.46 kJ/mol while the pre-exponential factors (k0) are in the range of 19.31–249.53 s-1. It was observed that for the MRPM model, the lower activation energy and the lower pre-exponential factor were obtained by the biochar CNS_800. However, Ea et k0 are well evaluated for PNS_800 and MS_800 with a coefficient of determination of 99.76%. The proposed modified random pore model could be used to describe the reactivity of biochar from biomass as well as the reactivity of coal.
期刊介绍:
The journal has a particular interest in publishing papers on the unique issues facing chemical engineering taking place in countries that are rich in resources but face specific technical and societal challenges, which require detailed knowledge of local conditions to address. Core topic areas are: Environmental process engineering • treatment and handling of waste and pollutants • the abatement of pollution, environmental process control • cleaner technologies • waste minimization • environmental chemical engineering • water treatment Reaction Engineering • modelling and simulation of reactors • transport phenomena within reacting systems • fluidization technology • reactor design Separation technologies • classic separations • novel separations Process and materials synthesis • novel synthesis of materials or processes, including but not limited to nanotechnology, ceramics, etc. Metallurgical process engineering and coal technology • novel developments related to the minerals beneficiation industry • coal technology Chemical engineering education • guides to good practice • novel approaches to learning • education beyond university.