Revisiting biomass compositions determination using thermogravimetric analysis and independent parallel reaction model

IF 3.1 2区 化学 Q2 CHEMISTRY, ANALYTICAL Thermochimica Acta Pub Date : 2024-07-10 DOI:10.1016/j.tca.2024.179814
Nanta Sophonrat, Margaret Wooldridge
{"title":"Revisiting biomass compositions determination using thermogravimetric analysis and independent parallel reaction model","authors":"Nanta Sophonrat,&nbsp;Margaret Wooldridge","doi":"10.1016/j.tca.2024.179814","DOIUrl":null,"url":null,"abstract":"<div><p>The determination of biomass composition via thermogravimetric analysis (TGA) has been a subject of considerable interest for many years. The current work proposes a revised workflow for determining the amounts of cellulose, hemicellulose, and lignin in biomass by combining TGA under an inert atmosphere with analyses of extractives and ash. An independent parallel reaction (IPR) model used for the deconvolution of the derivative thermogravimetry data was improved by constraining model parameters, i.e., thermal decomposition kinetic parameters and char fractions of cellulose, hemicellulose, and lignin, with values compiled from the literature using statistical analysis. The workflow is developed and demonstrated using cellulose and starch mixtures and then applied to biomass with varying levels of ash, including pine, birch, and oak wood, switchgrass, and pine bark. Using extractive-free biomass in the new TGA-IPR workflow improved the composition results compared with untreated biomass. The compositions determined by this method agreed well with values reported in the literature (within approx. 8 wt%) for the tested samples. The results demonstrate improved biomass composition accuracy using an accessible and rapid TGA-based approach.</p></div>","PeriodicalId":23058,"journal":{"name":"Thermochimica Acta","volume":"739 ","pages":"Article 179814"},"PeriodicalIF":3.1000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thermochimica Acta","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0040603124001539","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0

Abstract

The determination of biomass composition via thermogravimetric analysis (TGA) has been a subject of considerable interest for many years. The current work proposes a revised workflow for determining the amounts of cellulose, hemicellulose, and lignin in biomass by combining TGA under an inert atmosphere with analyses of extractives and ash. An independent parallel reaction (IPR) model used for the deconvolution of the derivative thermogravimetry data was improved by constraining model parameters, i.e., thermal decomposition kinetic parameters and char fractions of cellulose, hemicellulose, and lignin, with values compiled from the literature using statistical analysis. The workflow is developed and demonstrated using cellulose and starch mixtures and then applied to biomass with varying levels of ash, including pine, birch, and oak wood, switchgrass, and pine bark. Using extractive-free biomass in the new TGA-IPR workflow improved the composition results compared with untreated biomass. The compositions determined by this method agreed well with values reported in the literature (within approx. 8 wt%) for the tested samples. The results demonstrate improved biomass composition accuracy using an accessible and rapid TGA-based approach.

Abstract Image

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
利用热重分析和独立平行反应模型重新审视生物质成分测定方法
多年来,通过热重分析法(TGA)测定生物质成分一直是一个颇受关注的课题。目前的研究提出了一种新的工作流程,通过将惰性气氛下的热重分析与萃取物和灰分分析相结合,确定生物质中纤维素、半纤维素和木质素的含量。通过对模型参数(即热分解动力学参数以及纤维素、半纤维素和木质素的炭分数)进行约束,并利用统计分析从文献中整理出的数值,改进了用于导数热重分析数据解卷积的独立平行反应(IPR)模型。该工作流程使用纤维素和淀粉混合物进行开发和演示,然后应用于灰分含量不同的生物质,包括松木、桦木、橡木、开关草和松树皮。与未经处理的生物质相比,在新的 TGA-IPR 工作流程中使用不含萃取剂的生物质可改善成分结果。用这种方法测定的成分与文献中报道的测试样品的成分值非常吻合(在约 8 wt% 的范围内)。结果表明,使用基于 TGA 的简便快速的方法提高了生物质成分的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Thermochimica Acta
Thermochimica Acta 化学-分析化学
CiteScore
6.50
自引率
8.60%
发文量
210
审稿时长
40 days
期刊介绍: Thermochimica Acta publishes original research contributions covering all aspects of thermoanalytical and calorimetric methods and their application to experimental chemistry, physics, biology and engineering. The journal aims to span the whole range from fundamental research to practical application. The journal focuses on the research that advances physical and analytical science of thermal phenomena. Therefore, the manuscripts are expected to provide important insights into the thermal phenomena studied or to propose significant improvements of analytical or computational techniques employed in thermal studies. Manuscripts that report the results of routine thermal measurements are not suitable for publication in Thermochimica Acta. The journal particularly welcomes papers from newly emerging areas as well as from the traditional strength areas: - New and improved instrumentation and methods - Thermal properties and behavior of materials - Kinetics of thermally stimulated processes
期刊最新文献
Editorial Board Sustainable humification of food waste slurry through thermally activated persulfate oxidation Molecular dynamics simulation of combustion reaction process and products of oxygen-containing functional groups in coal based on Machine Learning Potential Pyrolysis of industrial hemp biomass from contaminated soil phytoremediation: Kinetics, modelling transport phenomena and biochar-based metal reduction Effects of Cu(OH)F nanoparticles on the thermal oxidation and ignition characteristics of micron-sized Al powder
×
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