Suppr超能文献

通过还原催化分馏木质素对竹生物质进行连续利用。

Sequential utilization of bamboo biomass through reductive catalytic fractionation of lignin.

机构信息

Beijing Key Laboratory of Lignocellulosic Chemistry, Beijing Forestry University, Beijing 100083, China.

Center for Lignocellulose Science and Engineering, Liaoning Key Laboratory of Pulp and Papermaking Engineering, School of Light Industry and Chemical Engineering, Dalian Polytechnic University, Dalian 116034, China.

出版信息

Bioresour Technol. 2019 Aug;285:121335. doi: 10.1016/j.biortech.2019.121335. Epub 2019 Apr 11.

Abstract

Reductive catalytic fractionation (RCF) has emerged as a new biorefinery paradigm for the fractionation and sequential utilization of entire components of biomass. Herein, we investigated the RCF of bamboo, a highly abundant herbaceous feedstock, in the presence of Pd/C catalyst. The lignin fraction in bamboo was preferentially depolymerized into well-defined low-molecular-weight phenols, with leaving carbohydrates pulp as a solid residue. In the soluble fraction, four major phenolic compounds, e.g., methyl coumarate/ferulate derived from hydroxycinnamic units and propanol guaiacol/syringol derived from β-O-4 units, were generated up to 41.7 wt% yield based on original lignin content. In the insoluble fraction, the carbohydrates of bamboo were recovered with high retentions of cellulose (68%) and hemicellulose (49%), which upon treatment with enzyme gave glucose (90%) and xylose (85%). Overall, the three major components of bamboo could efficient to be fractionated and converted into useful platform chemicals on the basis of this study.

摘要

还原催化分级(RCF)已成为一种新的生物质炼制模式,可用于对生物质的全部成分进行分级和顺序利用。在此,我们研究了 Pd/C 催化剂存在下竹子这种丰富的草本原料的 RCF。竹子中的木质素部分优先解聚成明确的低分子量酚类物质,留下碳水化合物浆作为固体残渣。在可溶性部分中,根据原始木质素含量,生成了 4 种主要的酚类化合物,例如,来源于羟基肉桂基单元的甲基肉桂酸酯/阿魏酸酯和来源于 β-O-4 单元的丙醇愈创木酚/丁香酚,产率高达 41.7 wt%。在不溶性部分中,竹子的碳水化合物以纤维素(68%)和半纤维素(49%)的高保留率回收,经酶处理后可得到葡萄糖(90%)和木糖(85%)。总的来说,根据这项研究,竹子的这三种主要成分可以有效地进行分级,并转化为有用的平台化学品。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验