Visit us at the SciY booth #2327 and explore SciY’s innovative solutions in Digitalization, Automation, and AI Readiness.
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.
Join us at Scottish NMR User Group 2024 Postgraduate Course in NMR. It will be held at the University of Edinburgh on 2nd-3rd December.
In this work, we introduce a novel NMR apodization function designed to enhance spectral resolution while maintaining compatibility with qNMR standards. This function is based on a modified Savitzky–Golay filter, adapted for time-domain application.
StereoFitter offers a versatile way to use scalar (J) couplings as restraints for conformational analysis, using either Karplus type empirical equations¹ or DFT predictions. We will present here a rapid glimpse into the most frequent uses of J-coupling restraints inside StereoFitter.
The procedure for simulating the nuclear magnetic resonance spectrum linked to the spin system of a molecule for a certain nucleus entails diagonalizing the associated Hamiltonian matrix.
(SPANISH LANGUAGE) Con una inversión de nueve millones de euros, busca cimentar desde Santiago los pilares para que Galicia lidere el sector de la biotecnología: «Este es un salto de una magnitud enorme»