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Open access Aug 2026

MolDeTr: A Chemistry-Informed Deep Learning Model for Next-Generation Automated Analysis of 1H NMR Spectra

MolDeTr addresses the spectrum-conditioned inverse problem and extracts spin-system parameters directly from measured 1D 1H NMR spectra, thereby substantially improving chemical-shift prediction precision by one to 2 orders of magnitude compared to existing structure-conditioned approaches.

N. Schmid, Marc Wanner, G. Fischetti et al. · 1 citation