This study reports a deep learning approach that utilises message passing neural networks (MPNNs) for predicting chemical shifts in 13C NMR spectra of small molecules. MPNNs were trained on two distinct datasets: one with approximately 4000 labelled structures and another with over 40,000.

Join LOGS and Mestrelab as we dive into a common challenge faced by research facilities: managing the ever-growing mountain of measurement data. As a facility manager, you’re all too familiar with the constant juggling act of handling sample submissions, data collection, and distribution—all while trying to keep your workflows efficient and your focus on the science.

This white paper critically examines the limitations of traditional LCMS-based purity measurements in synthetic chemistry, questioning commonly accepted simplifying assumptions.