Mnova Tips
Peer Reviewed Publications
Podcasts
Episode 8
Innovation in Lab Automation and Digitalization
Discover how lab automation and digitalization are reshaping R&D and quality control, with insights on robotics, workflow integration, and intelligent data management. Learn how automation enhances efficiency, reproducibility, and adaptability, preparing laboratories for the future of scientific discovery.
Episode 7
AI and Digital Transformation
Explore the evolving landscape of digital transformation, with expert insights on the strategies driving innovation and helping companies navigate rapid technological change. Don’t miss this conversation on the future of life sciences and the role of digitalization in shaping tomorrow’s industry standards.
Episode 6
qNMR-Based Digital Reference Materials: USP & Mestrelab
Explore the transformative impact of qNMR technology on scientific research and regulatory practices. Don’t miss this insightful discussion on the future of analytical chemistry and digital innovation in the industry.
Mnova Tips
S2E9 – Sort Traces in a Stacked Plot
Follow this Mnova Tip to enhance your data visualization when working with stacked spectra. Easily rearrange spectrum positions by sorting traces based on acquisition order or your preferred criteria. Streamline your analysis and focus on the details that matter most!
S2E8 – Display the Pages Navigator in Mnova
In this Mnova Tip, we show you two easy ways to display the Pages Navigator in Mnova, whether you've accidentally closed it or are accessing it for the first time. We hope you find this tip helpful—stay tuned for more Mnova tips!
S2E7 – Customizing the Palette of 2D NMR
In this Mnova Tip, discover the palette options for your 2D NMR spectrum. Learn how to enhance data clarity and presentation using advanced features. Optimize your Mnova documents for visual appeal and scientific accuracy with this expert tip.
Peer Reviewed Publications
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.
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.
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.