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arXiv · 2103.12169

A Pilot Study For Fragment Identification Using 2D NMR and Deep Learning

Stefan Kuhn·Eda Tumer·Simon Colreavy-Donnelly·Ricardo Moreira Borges
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Abstract

This paper presents a method to identify substructures in NMR spectra of mixtures, specifically 2D spectra, using a bespoke image-based Convolutional Neural Network application. This is done using HSQC and HMBC spectra separately and in combination. The application can reliably detect substructures in pure compounds, using a simple network. It can work for mixtures when trained on pure compounds only. HMBC data and the combination of HMBC and HSQC show better results than HSQC alone.

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Stefan Kuhn, Eda Tumer, Simon Colreavy-Donnelly, Ricardo Moreira Borges. 2021-03-18. A Pilot Study For Fragment Identification Using 2D NMR and Deep Learning. https://doi.org/10.1002/mrc.5212

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