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

Philippe Bernard Himbane, Lat Grand Ndiaye
{"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,&nbsp;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,&nbsp;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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.40
自引率
0.00%
发文量
100
审稿时长
33 weeks
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.
期刊最新文献
Effect of ethanol concentration on the catalytic performance of WO3/MCF-Si and WO3/SBA-15 catalysts toward ethanol dehydration to ethylene Parameter influences of FTO/ZnO/Cu₂O photodetectors fabricated by electrodeposition and spray pyrolysis techniques Predicting ash content and water content in coal using full infrared spectra and machine learning models A green route of antibacterial films production from shrimp (Penaeus monodon) shell waste biomass derived chitosan: Physicochemical, thermomechanical, morphological and antimicrobial activity analysis Synthesis of Mannich N-bases based on benzimidazole derivatives using SiO2OAlCl2 catalyst and their potential as antioxidant, antibacterial, and anticancer agents
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1