ArticleAngewandte Chemie (International ed. in English)2023
Pure Isotropic Proton NMR Spectra in Solids using Deep Learning.
Article in Angewandte Chemie (International ed. in English), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
6 citing papers in PubMed.
- Super-Resolution solid-state NMR Spectroscopy.Journal of biomolecular NMR · 2026Article
- Deep Learning Assisted Proton Pure Shift NMR Spectroscopy.Journal of the American Chemical Society · 2026Article
- Proton-Detected Solid-State NMR for Deciphering Structural Polymorphism and Dynamic Heterogeneity of Cellular Carbohydrates in Pathogenic Fungi.Journal of the American Chemical Society · 2025Article
- Spiers Memorial Lecture: NMR crystallography.Faraday discussions · 2025Article
- Artificial intelligence-driven shimming for parallel high field nuclear magnetic resonance.Scientific reports · 2023Article
- Pure Isotropic Proton NMR Spectra in Solids using Deep Learning.Angewandte Chemie (International ed. in English) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The resolution of proton solid-state NMR spectra is usually limited by broadening arising from dipolar interactions between spins. Magic-angle spinning alleviates this broadening by inducing coherent averaging. However, even the highest spinning rates experimentally accessible today are not able to completely remove dipolar interactions. Here, we introduce a deep learning approach to determine pure isotropic proton spectra from a two-dimensional set of magic-angle spinning spectra acquired at different spinning rates. Applying the model to 8 organic solids yields high-resolution
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Registered trials
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