Multinuclear and Multidimensional NMR Tools for Characterisation of Pyrolysis Bio-Oils and Other Complex Organic Mixtures

Abstract

Lignocellulosic biomass such as Brewers’ Spent Grains (BSG) can be used to produce fuel. Unlike other biomass resources grown specifically to produce fuel, BSG is considered an agriculture waste, with low cost and high availability. Bio-oils or pyrolysis oils produced from lignocellulosic biomass, such as BSG, are a promising carbon-neutral energy source for replacing fossil fuels. Pyrolysis oils are made up of hundreds of small molecules, including many oxygen-containing compounds. The main disadvantage of pyrolysis oils, which renders them incompatible with current infrastructures, is their acidity.

Analyses of pyrolysis oils are required, particularly the identification and quantification of the acidic, oxygen-containing compounds. However, this is usually hindered due to the complex nature of the mixtures. Nuclear Magnetic Resonance (NMR) is a versatile tool widely used to analyse complex mixtures. However, ¹H NMR analysis of pyrolysis oils is limited due to the severe overlapping signals of the many species present. The main challenge is simplifying the spectra without compromising chemical information.

the ¹⁹F qNMR analysis was translated from high-field to low-field, benchtop NMR. Benchtop NMR offers a cheaper, simpler alternative to traditional NMR methods, making NMR techniques more accessible to a wide range of audience. Second, alcohol groups are reacted with phosphorus-containing reagents, followed by ³¹P qNMR analysis. However, these spectra are still challenging due to the overlapping signals. Third, ³¹P diffusion-ordered spectroscopy techniques reveal additional chemical information such as molecular weights, easing the identification of compounds present in a sample. Interpretation of diffusion coefficients using power law method is explored. An alternative method for interpreting diffusion coefficient is the using the Stokes-Einstein Gierer-Writz Estimation (SEGWE). The interpretation of protein diffusion coefficients and extending the SEGWE to mixed aqueous solvents was explored. Finally, both novel NMR and traditional techniques have been used in combination to characterise pyrolysis oils produced from BSG.

Date of Award	May 2024
Original language	English
Awarding Institution	Aston University
Supervisor	Robert Evans (Supervisor) & Katie Chong (Supervisor)