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Analysis of complex mixtures with benchtop nuclear magnetic resonance: Solvent suppression with T2 and diffusion filters.
Le-McClain, Anh; Zanelotti, Curt; Robert, Hector; Casanova, Federico.
Afiliação
  • Le-McClain A; Magritek Inc., Malvern, Pennsylvania, USA.
  • Zanelotti C; Magritek Inc., Malvern, Pennsylvania, USA.
  • Robert H; Magritek Inc., Malvern, Pennsylvania, USA.
  • Casanova F; Magritek GmbH, Aachen, Germany.
Magn Reson Chem ; 62(7): 497-504, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38369688
ABSTRACT
Benchtop nuclear magnetic resonance (NMR) spectrometers are being employed in a wide variety of applications from undergraduate teaching and research in academia to quality control and process monitoring in industrial settings. Incorporating benchtop NMR in some of these applications presents opportunities for new practical uses of the technology and challenges that truly test the capabilities of compact NMR spectrometers. For instance, the use of protonated solvents in manufacturing or process monitoring requires separating and quantitating the analyte signals of interest from the strong (overwhelming) response from the solvents. Furthermore, due to the lower field strength available with permanent magnet spectrometers, the NMR spectra of complex mixtures can be more difficult to analyze due to partial or complete signal overlap. To address some of these challenges and to extend the range of applications of benchtop NMR, we investigate NMR techniques that enable quantitative analysis of different components in mixtures. These pulse sequences can be used to suppress one or multiple solvent peaks, to filter out signals by spin-spin relaxation time (T2), or to separate signal components by a molecule's diffusion coefficient (NMR diffusometry). In this paper, we discuss quantitative analysis of excipients in buffers for therapeutic proteins to highlight the usefulness of these NMR pulse sequences in the analysis of complex samples with benchtop NMR spectrometers.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article