Combination of DOSY and 1D selective gradient TOCSY: Versatile NMR tools for identify the mixtures from glycerol hydrogenolysis reaction

Zexiang Lyu, Fen Yue, Xiuyin Yan, Jianfeng Shan, Danlei Xiang, Christian Marcus Pedersen, Chunju Li*, Yingxiong Wang, Yan Qiao

*Corresponding author for this work
4 Citations (Scopus)

Abstract

Hydrogenolysis is necessary for preparing various value-added chemicals from glycerol. Routine methods like GC and HPLC are not sufficient for analysis the reaction mixtures because the products usually have high boiling or similar polarity, especially when new chromatographic peaks are found which requires other technologies such as NMR. Although they were developed for years, but either DOSY or 1D selective TOCSY NMR has nature limitations. Herein we took their advantages and combined them to analyse glycerol hydrogenolysis mixtures for the first time. A model reaction mixture was first pseudo separated in DOSY spectrum, and 1D selective gradient TOCSY was further applied to assign the overlapped signal which could not be confirmed just by DOSY. A genuine reaction mixture was tried afterwards, and main signals could be assigned well in DOSY diffusion dimension. Notably, n-propanol was found as by-product by 1D selective gradient TOCSY, which is not visible in DOSY spectrum. The experimental results demonstrate that the combination of these two NMR methods could provide a fast, effective, feasible and reliable way for the identification of glycerol hydrogenolysis mixtures and is expected to apply in other research areas.

Original languageEnglish
JournalFuel Processing Technology
Volume171
Pages (from-to)117-123
Number of pages7
ISSN0378-3820
DOIs
Publication statusPublished - 2018

Keywords

  • 1D selective TOCSY
  • DOSY
  • Glycerol hydrogenolysis
  • Mixture analysis
  • NMR

Fingerprint

Dive into the research topics of 'Combination of DOSY and 1D selective gradient TOCSY: Versatile NMR tools for identify the mixtures from glycerol hydrogenolysis reaction'. Together they form a unique fingerprint.

Cite this