A Workup Protocol Combined with Direct Application of Quantitative Nuclear Magnetic Resonance Spectroscopy of Aqueous Samples from Large-Scale Steam Explosion of Biomass
Journal article, Peer reviewed
Published version
![Thumbnail](/bora-xmlui/bitstream/handle/11250/2978112/ACS_Omega_Lohre.pdf.jpg?sequence=7&isAllowed=y)
Åpne
Permanent lenke
https://hdl.handle.net/11250/2978112Utgivelsesdato
2021Metadata
Vis full innførselSamlinger
- Department of Chemistry [442]
- Registrations from Cristin [10237]
Sammendrag
Methods for thermochemical conversion of biomass into renewable energy and materials rapidly increase in range and outreach. A focus on the target product streams for valorization is natural, yet several pretreatment steps and conversion methods also result in an aqueous byproduct, which has been given less attention. This paper aims to fill this knowledge gap in the existing literature on identification and quantification of organic components in such aqueous phases by reporting a fast and direct workup protocol combined with application of quantitative analytical nuclear magnetic resonance (NMR) spectroscopy. Laboratory workup procedures combined with subsequent proton NMR spectroscopy with water signal suppression using presaturation pulses during relaxation delay, noesygppr1d, have been established, evaluated, and approved by testing on three different Bruker BioSpin NMR spectrometers; an 850 MHz AVANCE III HD with a 5 mm TCI CryoProbe, a 600 MHz AVANCE NEO with a QCI CryoProbe, and a 500 MHz AVANCE with a 5 mm BBO room-temperature probe additionally confirmed the quantification method to be applicable. The analytical procedure identified furfural, methanol, acetic acid, and formic acid as the dominating compounds in the analyzed aqueous samples, which were process effluents generated by the patented Arbacore pellet production process using steam explosion of wood shavings. A selected range of quantitative results in the aqueous phase from large-scale steam explosion is included in the study. The described procedure provides excellent quantitative reproducibility with experimental series standard deviations of <1% (mM), is nondestructive, and can be automated on demand.