4.6 Article

Cascade Strategy for the Tunable Catalytic Valorization of Levulinic Acid and γ-Valerolactone to 2-Methyltetrahydrofuran and Alcohols

期刊

CATALYSTS
卷 8, 期 7, 页码 -

出版社

MDPI
DOI: 10.3390/catal8070277

关键词

levulinic acid; gamma-valerolactone; 2-methyltetrahydrofuran; 2-butanol; 2-pentanol; hydrogenation; ruthenium; rhenium; niobium phosphate

资金

  1. PRIN 2015-Project HERCULES HEterogeneous Robust Catalysts to Upgrade Low valuE biomass Streams [20153T4REF]

向作者/读者索取更多资源

A cascade strategy for the catalytic valorization of aqueous solutions of levulinic acid as well as of gamma-valerolactone to 2-methyltetrahydrofuran or to monoalcohols, 2-butanol and 2-pentanol, has been studied and optimized. Only commercial catalytic systems have been employed, adopting sustainable reaction conditions. For the first time, the combined use of ruthenium and rhenium catalysts supported on carbon, with niobium phosphate as acid co-catalyst, has been claimed for the hydrogenation of gamma-valerolactone and levulinic acid, addressing the selectivity to 2-methyltetrahydrofuran. On the other hand, the use of zeolite HY with commercial Ru/C catalyst favors the selective production of 2-butanol, starting again from gamma-valerolactone and levulinic acid, with selectivities up to 80 and 70 mol %, respectively. Both levulinic acid and gamma-valerolactone hydrogenation reactions have been optimized, investigating the effect of the main reaction parameters, to properly tune the catalytic performances towards the desired products. The proper choice of both the catalytic system and the reaction conditions can smartly switch the process towards the selective production of 2-methyltetrahydrofuran or monoalcohols. The catalytic system [Ru/C + zeolite HY] at 200 degrees C and 3 MPa H-2 is able to completely convert both gamma-valerolactone and levulinic acid, with overall yields to monoalcohols of 100 mol % and 88.8 mol %, respectively.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据