Projects per year
Abstract
Benchtop NMR spectrometers provide a promising alternative to high-field NMR for applications that are limited by instrument size and/or cost. 19F benchtop NMR is attractive due to the larger chemical shift range of 19F relative to 1H and the lack of background signal in most applications. However, practical applications of benchtop 19F NMR are limited by its low sensitivity due to the relatively weak field strengths of benchtop NMR spectrometers. Here we present a sensitivity-enhancement strategy that combines SABRE (Signal Amplification By Reversible Exchange) hyperpolarisation with the multiplet refocusing method SHARPER (Sensitive, Homogeneous, And Resolved PEaks in Real time). When applied to a range of fluoropyridines, SABRE-SHARPER achieves overall signal enhancements of up to 5700-fold through the combined effects of hyperpolarisation and line-narrowing. This approach can be generalised to the analysis of mixtures through the use of a selective variant of the SHARPER sequence, selSHARPER. The ability of SABRE-selSHARPER to simultaneously boost sensitivity and discriminate between two components of a mixture is demonstrated, where selectivity is achieved through a combination of selective excitation and the choice of polarisation transfer field during the SABRE step.
Original language | English |
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Pages (from-to) | 73-81 |
Number of pages | 9 |
Journal | ACS Measurement Science Au |
Volume | 3 |
Issue number | 1 |
Early online date | 8 Nov 2022 |
DOIs | |
Publication status | Published - 15 Feb 2023 |
Projects
- 2 Finished
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Lighting up Magnetic Resonance: SABRE optimisation powered by in situ detection
9/07/18 → 30/09/20
Project: Research project (funded) › Research
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A paradigm shift in low-field NMR spectroscopy for industrial process monitoring, control and optimisation
1/08/15 → 31/01/19
Project: Research project (funded) › Research
Datasets
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Enhancing 19F benchtop NMR spectroscopy by combining parahydrogen hyperpolarisation and multiplet refocusing
Halse, M. E. (Creator), University of York, 27 Oct 2022
DOI: 10.15124/252bc49d-8f1f-4c0d-b1bb-9aeadcdde0c8
Dataset