释放生物质的价值:机器学习对棉秆还原催化分馏的启示

IF 3.2 4区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of the Indian Chemical Society Pub Date : 2024-09-23 DOI:10.1016/j.jics.2024.101394
{"title":"释放生物质的价值:机器学习对棉秆还原催化分馏的启示","authors":"","doi":"10.1016/j.jics.2024.101394","DOIUrl":null,"url":null,"abstract":"<div><div>Lignocellulosic biomass valorization has become an intensive area of research due to the importance of renewable nature and availability of biomass. However, biomass fractionation and depolymerization produce numerous datasets, that are difficult to visualise and interpret for the scale-up of the process. Therefore, machine learning algorithms, which can discover hidden patterns in data are applied to these datasets. Reductive Catalytic Fractionation (RCF) of lignocellulosic biomass is an emerging methodology to valorize biomass completely and effectively. Herein, the present work includes the Correlation Analysis and the Principal Component Analysis (PCA) of product distribution obtained from RCF of cotton stalks. Interactions between process variables and delignification (DL), sugar retention (SR), total phenolic monomers (PM), and individual phenolic monomers yield were evaluated. Correlations among DL, SR, and PM yields were also evaluated at different reaction conditions through PCA, which were explained using the reaction mechanism and molecular chemistry of lignin.</div></div>","PeriodicalId":17276,"journal":{"name":"Journal of the Indian Chemical Society","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unlocking biomass valorization: Machine Learning insights for Reductive Catalytic Fractionation of cotton stalks\",\"authors\":\"\",\"doi\":\"10.1016/j.jics.2024.101394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Lignocellulosic biomass valorization has become an intensive area of research due to the importance of renewable nature and availability of biomass. However, biomass fractionation and depolymerization produce numerous datasets, that are difficult to visualise and interpret for the scale-up of the process. Therefore, machine learning algorithms, which can discover hidden patterns in data are applied to these datasets. Reductive Catalytic Fractionation (RCF) of lignocellulosic biomass is an emerging methodology to valorize biomass completely and effectively. Herein, the present work includes the Correlation Analysis and the Principal Component Analysis (PCA) of product distribution obtained from RCF of cotton stalks. Interactions between process variables and delignification (DL), sugar retention (SR), total phenolic monomers (PM), and individual phenolic monomers yield were evaluated. Correlations among DL, SR, and PM yields were also evaluated at different reaction conditions through PCA, which were explained using the reaction mechanism and molecular chemistry of lignin.</div></div>\",\"PeriodicalId\":17276,\"journal\":{\"name\":\"Journal of the Indian Chemical Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Indian Chemical Society\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0019452224002747\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Indian Chemical Society","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019452224002747","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

由于生物质的可再生性和可用性的重要性,木质纤维素生物质增值已成为一个密集的研究领域。然而,生物质分馏和解聚会产生大量数据集,这些数据集很难可视化,也很难在扩大工艺规模时进行解释。因此,可以发现数据中隐藏模式的机器学习算法被应用于这些数据集。木质纤维素生物质的还原催化分馏(RCF)是一种新兴的方法,可全面有效地实现生物质的价值化。本研究包括对棉花秆还原催化分馏产物分布的相关性分析和主成分分析。评估了工艺变量与去木质素(DL)、糖分保留(SR)、总酚类单体(PM)和单个酚类单体产量之间的相互作用。还通过 PCA 评估了不同反应条件下 DL、SR 和 PM 产量之间的相关性,并利用木质素的反应机理和分子化学解释了这些相关性。
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
Unlocking biomass valorization: Machine Learning insights for Reductive Catalytic Fractionation of cotton stalks
Lignocellulosic biomass valorization has become an intensive area of research due to the importance of renewable nature and availability of biomass. However, biomass fractionation and depolymerization produce numerous datasets, that are difficult to visualise and interpret for the scale-up of the process. Therefore, machine learning algorithms, which can discover hidden patterns in data are applied to these datasets. Reductive Catalytic Fractionation (RCF) of lignocellulosic biomass is an emerging methodology to valorize biomass completely and effectively. Herein, the present work includes the Correlation Analysis and the Principal Component Analysis (PCA) of product distribution obtained from RCF of cotton stalks. Interactions between process variables and delignification (DL), sugar retention (SR), total phenolic monomers (PM), and individual phenolic monomers yield were evaluated. Correlations among DL, SR, and PM yields were also evaluated at different reaction conditions through PCA, which were explained using the reaction mechanism and molecular chemistry of lignin.
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
3.50
自引率
7.70%
发文量
492
审稿时长
3-8 weeks
期刊介绍: The Journal of the Indian Chemical Society publishes original, fundamental, theorical, experimental research work of highest quality in all areas of chemistry, biochemistry, medicinal chemistry, electrochemistry, agrochemistry, chemical engineering and technology, food chemistry, environmental chemistry, etc.
期刊最新文献
Exploring the antimicrobial activity of hydrothermally synthesized copper pyrophosphate nanoflakes Solvation modeling and optical properties of CdSO4-Doped L-Valine crystals Study of halogen interactions in dichlorovinyldiazenes: Structural analysis, DFT simulation and molecular modeling Analysis and quantification of selected heavy metals and paraphenylenediamine in commercially available herbal black hair dyes in Sri Lanka Morphology studies, optic proprieties, hirschfeld electrostatic potential mapping, docking molecular anti-inflammatory, and dynamic molecular approaches of hybrid phosphate
×
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