High-quality pure shift NMR spectra by deep learning using multi-spectral input and joint loss functions

Weigang Cai; Yiyang Li; Xiaoxu Zheng; Zhengxian Yang; Ralph W. Adams; Zhong Chen; Mathias Nilsson; Maili Liu; Gareth A. Morris; Yanqin Lin

doi:10.1038/s41467-026-76276-y

High-quality pure shift NMR spectra by deep learning using multi-spectral input and joint loss functions

W Weigang Cai Y Yiyang Li (Wolfson Catalysis Centre, Department of Chemistry) X Xiaoxu Zheng Z Zhengxian Yang R Ralph W. Adams (Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.) Z Zhong Chen M Mathias Nilsson M Maili Liu (State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology) G Gareth A. Morris Y Yanqin Lin

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Article Details

Journal Nature Communications

Volume / Issue Vol. 1, Issue 1

Published August 03, 2026

DOI 10.1038/s41467-026-76276-y

ISSN 2041-1723

Publisher Nature Portfolio

Journal Info

Nature Communications

Nature Portfolio

ISSN: 2041-1723 Open Access Life Sciences

Authors (10)

W

Weigang Cai

Y

Yiyang Li

Wolfson Catalysis Centre, Department of Chemistry

X

Xiaoxu Zheng

Z

Zhengxian Yang

R

Ralph W. Adams

Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.

Z

Zhong Chen

M

Mathias Nilsson

M

Maili Liu

State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance in Wuhan, Innovation Academy for Precision Measurement Science and Technology

G

Gareth A. Morris

Y

Yanqin Lin

High-quality pure shift NMR spectra by deep learning using multi-spectral input and joint loss functions

Article Details

Journal Info

Authors (10)

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