Papers › On-the-Fly, Sample-Tailored Optimisation of NMR Experiments

On-the-Fly, Sample-Tailored Optimisation of NMR Experiments

16 Aug 2021arXiv:2108.07121archive 2025-07-28

Jonathan R. J. Yong, Mohammadali Foroozandeh

NMR experiments, indispensable to chemists in many areas of research, are often run with generic, unoptimised experimental parameters. This approach makes robust and automated acquisition on different samples and instruments extremely challenging. Here, we introduce NMR-POISE (Parameter Optimisation by Iterative Spectral Evaluation), the first demonstration of on-the-fly, sample-tailored, and fully automated optimisation of a wide range of NMR experiments. We illustrate how POISE maximises spectral sensitivity and quality with a diverse set of 1D and 2D examples, ranging from HSQC and NOESY experiments to ultrafast and pure shift techniques. Our Python implementation of POISE has an interface integrated into Bruker's TopSpin software, one of the most widely used platforms for NMR acquisition and automation, allowing NMR optimisations to be run without direct user supervision. We predict that POISE will find widespread usage in academia and industry, where sample-specific and automated experiment optimisation is mandatory.

PaperPDFCode

Code

foroozandehgroup/nmrpoise officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Datasets

Introduced by this paper, per the archive.

Raw data for NMR-POISE

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections