ArticleScientific reports2025
Integrated analysis of cellulose structure and properties using solid-state low-field H-NMR and photoacoustic spectroscopy.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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6 authors.
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Abstract
In this study, we explore the structural intricacies of cellulose, a polymer composed of glucose monomers arranged in a linear chain, primarily investigated through solid-state NMR techniques. Specifically, we employ low-field proton nuclear magnetic resonance (H-NMR) to delve into the diverse hydrogen atom types within the cellulose molecule. The low-field H-NMR technique allows us to discern these hydrogen atoms based on their distinct chemical shifts, providing valuable insights into the various functional groups present in cellulose. Our focus extends to the examination of anomeric protons of glucose units and protons linked to carbon atoms engaged in glycosidic linkages within cellulose chains, which exist in diverse crystalline and amorphous forms. Solid-state low-field H-NMR spectroscopy aids in characterizing the crystallinity degrees and amorphous regions within cellulose, revealing time-dependent changes in free induction decay (FID) signals. Complementing this, we investigate the photo-absorption properties of cellulose fibers under both continuous and modulated irradiation using reversed double-beam photoacoustic spectroscopy (RDB-PAS). This photoacoustic approach allows us to observe ultraviolet- and visible light-induced processes, including electron trap filling and reductive changes on the fiber surface. Our findings suggest that RDB-PAS is a feasible method for estimating the electron trap distribution, serving as a potential measure of the density of crystalline cellulose defects. This integrated approach of combining solid-state low-field H-NMR and RDB-PAS techniques offers a comprehensive understanding of cellulose structure and properties, enhancing our ability to characterize its diverse features.
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