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NMR diffusion analysis of catalytic conversion mixtures from lignocellulose biomass using PSYCHE-iDOSY

Authors :
Qi Zhao
Christian Marcus Pedersen
Jiamin Wang
Rui Liu
Yuanli Zhang
Xiuyin Yan
Zhenzhou Zhang
Xianglin Hou
Yingxiong Wang
Source :
Green Energy & Environment, Vol 8, Iss 5, Pp 1409-1416 (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

The component analysis and structure characterization of complex mixtures of biomass conversion remain a challenging work. Hence, developing effective and easy to use techniques is necessary. Diffusion-ordered NMR spectroscopy (DOSY) is a non-selective and non-invasive method capable of achieving pseudo-separation and structure assignments of individual compounds from biomass mixtures by providing diffusion coefficients (D) of the components. However, the conventional 1H DOSY NMR is limited by crowded resonances when analyzing complex mixtures containing similar chemical structure resulting in similar coefficient. Herein we describe the application of an advanced diffusion NMR method, Pure Shift Yielded by CHirp Excitation DOSY (PSYCHE-iDOSY), which can record high-resolution signal diffusion spectra efficiently separating compounds in model and genuine mixture samples from cellulose, hemicellulose and lignin. Complicated sets of isomers (d-glucose/d-fructose/d-mannose and 1,2-/1,5-pentadiol), homologous compounds (ethylene glycol and 1,2-propylene glycol), model compounds of lignin, and a genuine reaction system (furfuryl alcohol hydrogenolysis with ring opening) were successfully separated in the diffusion dimension. The results show that the ultrahigh-resolution DOSY technique is capable of detecting and pseudo-separating the mixture components of C5/C6 sugar conversion products and its derivative hydrogenation/hydrogenolysis from lignocellulose biomass.

Details

Language :
English
ISSN :
24680257
Volume :
8
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Green Energy & Environment
Publication Type :
Academic Journal
Accession number :
edsdoj.827f4befacb9441f8e9fc67b69c2cc41
Document Type :
article
Full Text :
https://doi.org/10.1016/j.gee.2022.02.003