Practical Problems of Nuclear Resonance Spectroscopy

NMR spectroscopy is one of the most important analytical methods chemists have available to elucidate or confirm the structure of small (and large) molecules.1 While the instrument hardware is undoubtedly the crucial part in acquiring NMR data with good quality and in a reasonable amount of time, NMR analysis software is often a factor that is overlooked when it comes to productivity and efficiency in the field.

Spectrus JS is a web-based application which allows chemists to process, analyse, predict and report their NMR spectra in their web browser. With this software, chemists can securely process NMR data from all major NMR instrument vendors across Windows, macOS, and Linux operating systems. The ability to use the software from the web browser means that there is no need for the individual chemist to download, install, update and maintain their NMR software, and allows chemists to focus on the analysis of their NMR data.

This presentation will showcase four key features of Spectrus JS: Firstly, NMR processing will be demonstrated using real Bruker NMR data for a small molecule. This includes Fourier Transformation of the raw data, phase and baseline correction, referencing, peak picking and integration, as well as the determination of coupling constants. Secondly, the ability to organise NMR data into projects will be shown, a functionality which helps chemists to collate project related NMR data in a single file. Thirdly, the prediction of 1D and 2D spectra of compounds will be demonstrated. NMR spectrum prediction is often a key function chemists use to help interpret their own spectra quicker and more confidently.2 And lastly, it will be shown how to generate spectra reports and multiplet reports, which are often needed for journal or patent submissions, fast and efficiently.

References 1. Bross-Walch, N., Kühn, T., Moskau, D., & Zerbe, O. (2005). Strategies and tools for structure determination of natural products using modern methods of NMR spectroscopy. Chemistry & biodiversity, 2(2), 147-177. 2. Jonas, E., Kuhn, S., & Schlörer, N. (2022). Prediction of chemical shift in NMR: A review. Magnetic Resonance in Chemistry, 60(11), 1021-1031.