谷歌浏览器插件
订阅小程序
在清言上使用

Valorization of Beverage Waste As a Sugar Source for 5-Hydroxymethylfurfural Production

Nattee Akkarawatkhoosith,Attasak Jaree, Chotika Yoocham, Thanakorn Damrongsakul,Tiprawee Tongtummachat

JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING(2024)

引用 0|浏览4
暂无评分
摘要
This study highlights the valorization of beverage waste as a promising sugar-based raw material for 5-hydroxymethylfurfural (5-HMF) production. In this work, both beverage waste purification and 5-HMF production were experimentally demonstrated through the practicality and effectiveness of continuous-flow processes. In the purification process, solid and liquid impurities were wholly eliminated through membrane filtration and a two-stage adsorption process using activated carbon. The purified beverage waste primarily consisted of fructose, glucose, and sucrose, offering a plentiful source of sugar. A mini fixed-bed reactor was employed to thoroughly investigate the impact of various operating variables on continuous 5-HMF production from synthetic beverage waste. The variables considered included residence time, reaction temperature, catalyst type, solvent type, water content, and sugar concentration. The optimization analysis was conducted to achieve both high 5-HMF yield and productivity. The optimal condition, which resulted in the 5-HMF yield of 42.6% and productivity of 3.3e−3 kg5-HMF/kgcat-h, was obtained with a residence time of 15 min, sugar feed concentration of 10 g/L, reaction temperature of 120 °C, and water content of 10 g/L. Dimethyl sulfoxide (DMSO) and Amberlyst 15 were the selected solvent and catalyst, respectively. The feasibility of producing 5-HMF from actual beverage waste was validated under optimal conditions. Furthermore, the stability of the catalyst was demonstrated over 24 h of time-on-stream. The proposed processes offer the potential for continuous purification of beverage waste and the efficient production of 5-HMF.
更多
查看译文
关键词
Waste pretreatment,Waste resource,Purification,Sustainable production,Catalyst,Adsorption
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要