Literature DB >> 21919056

NMR quantitation: influence of RF inhomogeneity.

Huaping Mo1, John Harwood, Daniel Raftery.   

Abstract

The NMR peak integral is ideally linearly dependent on the sine of excitation angle (θ), which has provided unsurpassed flexibility in quantitative NMR by allowing the use of a signal of any concentration as the internal concentration reference. Controlling the excitation angle is particularly critical for solvent proton concentration referencing to minimize the negative impact of radiation damping, and to reduce the risk of receiver gain compression. In practice, due to the influence of RF inhomogeneity for any given probe, the observed peak integral is not exactly proportional to sin θ. To evaluate the impact quantitatively, we introduce a RF inhomogeneity factor I(θ) as a function of the nominal pulse excitation angle and propose a simple calibration procedure. Alternatively, I(θ) can be calculated from the probe's RF profile, which can be readily obtained as a gradient image of an aqueous sample. Our results show that without consideration of I(θ), even for a probe with good RF homogeneity, up to 5% error can be introduced due to different excitation pulse angles used for the analyte and the reference. Hence, a simple calibration of I(θ) can eliminate such errors and allow an accurate description of the observed NMR signal's dependence on the excitation angle in quantitative analysis.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 21919056      PMCID: PMC4755342          DOI: 10.1002/mrc.2812

Source DB:  PubMed          Journal:  Magn Reson Chem        ISSN: 0749-1581            Impact factor:   2.447


  10 in total

1.  NMR measurements of diffusion in concentrated samples: avoiding problems with radiation damping.

Authors:  Mark A Connell; Adrain L Davis; Alan M Kenwright; Gareth A Morris
Journal:  Anal Bioanal Chem       Date:  2004-03       Impact factor: 4.142

2.  Mapping the B1 field distribution with nonideal gradients in a high-resolution NMR spectrometer.

Authors:  A Jerschow; G Bodenhausen
Journal:  J Magn Reson       Date:  1999-03       Impact factor: 2.229

3.  Determination of analyte concentration using the residual solvent resonance in (1)H NMR spectroscopy.

Authors:  Gregory K Pierens; Anthony R Carroll; Rohan A Davis; Meredith E Palframan; Ronald J Quinn
Journal:  J Nat Prod       Date:  2008-04-05       Impact factor: 4.050

4.  Quantification of metabolites from two-dimensional nuclear magnetic resonance spectroscopy: application to human urine samples.

Authors:  Ratan Kumar Rai; Pratima Tripathi; Neeraj Sinha
Journal:  Anal Chem       Date:  2009-12-15       Impact factor: 6.986

5.  Analysis and implications of transition-band signals in high-resolution NMR.

Authors:  C Szántay
Journal:  J Magn Reson       Date:  1998-12       Impact factor: 2.229

6.  NMR quantitation of natural products at the nanomole scale.

Authors:  Doralyn S Dalisay; Tadeusz F Molinski
Journal:  J Nat Prod       Date:  2009-04       Impact factor: 4.050

7.  R: A quantitative measure of NMR signal receiving efficiency.

Authors:  Huaping Mo; John Harwood; Shucha Zhang; Yi Xue; Robert Santini; Daniel Raftery
Journal:  J Magn Reson       Date:  2009-07-09       Impact factor: 2.229

8.  Pre-SAT180, a simple and effective method for residual water suppression.

Authors:  Huaping Mo; Daniel Raftery
Journal:  J Magn Reson       Date:  2007-09-25       Impact factor: 2.229

9.  Solvent signal as an NMR concentration reference.

Authors:  Huaping Mo; Daniel Raftery
Journal:  Anal Chem       Date:  2008-12-15       Impact factor: 6.986

10.  Simultaneous quantification and identification of individual chemicals in metabolite mixtures by two-dimensional extrapolated time-zero (1)H-(13)C HSQC (HSQC(0)).

Authors:  Kaifeng Hu; William M Westler; John L Markley
Journal:  J Am Chem Soc       Date:  2011-01-19       Impact factor: 15.419

  10 in total
  2 in total

1.  Quantitative analysis of urea in human urine and serum by 1H nuclear magnetic resonance.

Authors:  Lingyan Liu; Huaping Mo; Siwei Wei; Daniel Raftery
Journal:  Analyst       Date:  2011-12-16       Impact factor: 4.616

2.  Signal Deconvolution and Noise Factor Analysis Based on a Combination of Time-Frequency Analysis and Probabilistic Sparse Matrix Factorization.

Authors:  Shunji Yamada; Atsushi Kurotani; Eisuke Chikayama; Jun Kikuchi
Journal:  Int J Mol Sci       Date:  2020-04-23       Impact factor: 5.923

  2 in total

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