中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Highly Efficient Conversion of Xylose to Furfural in a Water-MIBK System Catalyzed by Magnetic Carbon-Based Solid Acid

文献类型:期刊论文

作者Qi, Zhiqiang2,3; Wang, Qiong3; Liang, Cuiyi3; Yue, Jun1; Liu, Shuna3; Ma, Shexia4; Wang, Xiaohan3; Wang, Zhongming3; Li, Zhihe2; Qi, Wei3
刊名INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
出版日期2020-09-30
卷号59期号:39页码:17046-17056
ISSN号0888-5885
DOI10.1021/acs.iecr.9b06349
通讯作者Li, Zhihe(lizhihe@sdut.edu.cn) ; Qi, Wei(qiwei@ms.giec.ac.cn)
英文摘要In this work, the conversion of xylose to furfural (FF) was effectively achieved in a water-MIBK biphasic solvent system over a synthesized magnetic carbon-based solid acid catalyst (MMCSA). The effect of various reaction conditions was studied on the dehydration of xylose, and the highest FF yield of 79.04% was obtained. Byproducts in the reaction process were identified by high-performance liquid chromatography-mass spectrometry (LC-MS), which provides insights into the reaction pathway of the xylose conversion to FF over the current catalyst. The observed deactivation of the catalyst at high temperature (190 degrees C) was addressed by its regeneration with concentrated sulfuric acid (98 wt %). A comparable FF yield (73.74%) was achieved over the regenerated MMCSA. The possible deactivation- regeneration mechanism of this catalyst has also been proposed. Overall, this work provides a valuable basis for the efficient synthesis of FF by solid acid-catalyzed conversion of xylose or hemicellulose.
WOS关键词CORNCOB SACCHARIFICATION ; SELECTIVE CONVERSION ; PROMISING PLATFORM ; BIPHASIC SYSTEM ; BIOMASS ; HYDROLYSIS ; CELLULOSE ; FUEL ; PRETREATMENT ; DEHYDRATION
资助项目National Natural Science Foundation of China[51676193] ; National Natural Science Foundation of China[51861145103] ; National Natural Science Foundation of China[2171101430] ; National Key Research and Development Program of China[2018YFC1901201] ; Youth Innovation Promotion Association, CAS[2017401] ; Municipal Science and Technology Program of Guangzhou[201804010187] ; National Natural Science Foundation of China (NSFC)[21811530627] ; Dutch Research Council (NWO)[21811530627] ; NWO[040.21.006] ; Foundation of State Key Laboratory of Coal Combustion[FSKLCCA1804]
WOS研究方向Engineering
语种英语
出版者AMER CHEMICAL SOC
WOS记录号WOS:000577113500012
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China ; Youth Innovation Promotion Association, CAS ; Municipal Science and Technology Program of Guangzhou ; National Natural Science Foundation of China (NSFC) ; Dutch Research Council (NWO) ; NWO ; Foundation of State Key Laboratory of Coal Combustion
源URL[http://ir.giec.ac.cn/handle/344007/32189]  
专题中国科学院广州能源研究所
通讯作者Li, Zhihe; Qi, Wei
作者单位1.Univ Groningen, Dept Chem Engn, Engn & Technol Inst Groningen, NL-9747 AG Groningen, Netherlands
2.Shandong Univ Technol, Shandong Res Ctr Engn & Technol Clean Energy, Sch Agr Engn & Food Sci, Zibo 255000, Peoples R China
3.Chinese Acad Sci, Guangzhou Inst Energy Convers, CAS Key Lab Renewable Energy, Guangdong Prov Key Lab New & Renewable Energy Res, Guangzhou 510640, Peoples R China
4.Minist Ecol & Environm, State Environm Protect Key Lab Environm Protect H, South China Inst Environm Sci, Guangzhou 510535, Guangdong, Peoples R China
推荐引用方式
GB/T 7714
Qi, Zhiqiang,Wang, Qiong,Liang, Cuiyi,et al. Highly Efficient Conversion of Xylose to Furfural in a Water-MIBK System Catalyzed by Magnetic Carbon-Based Solid Acid[J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH,2020,59(39):17046-17056.
APA Qi, Zhiqiang.,Wang, Qiong.,Liang, Cuiyi.,Yue, Jun.,Liu, Shuna.,...&Qi, Wei.(2020).Highly Efficient Conversion of Xylose to Furfural in a Water-MIBK System Catalyzed by Magnetic Carbon-Based Solid Acid.INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH,59(39),17046-17056.
MLA Qi, Zhiqiang,et al."Highly Efficient Conversion of Xylose to Furfural in a Water-MIBK System Catalyzed by Magnetic Carbon-Based Solid Acid".INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 59.39(2020):17046-17056.

入库方式: OAI收割

来源:广州能源研究所

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