Journal Highlight: Accelerated nuclear magnetic resonance spectroscopy with deep learning

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  • Published: Oct 3, 2019
  • Author: spectroscopyNOW
  • Channels: NMR Knowledge Base
thumbnail image: Journal Highlight: Accelerated nuclear magnetic resonance spectroscopy with deep learning

A proof‐of‐concept of application of deep learning and neural network has been presented for high‐quality, reliable, and very fast NMR spectra reconstruction from limited experimental data

Qu, X., Huang, Y., Lu, H. et al. (2019). Accelerated nuclear magnetic resonance spectroscopy with deep learning. Angewandte Chemie International Edition online

Abstract: Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof‐of‐concept of application of deep learning and neural network for high‐quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural network training can be achieved using solely synthetic NMR signal, which lifts the prohibiting demand for large volume of realistic training data usually required in the deep learning approach.

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