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

TL;DR

This paper introduces NMR-POISE, an automated, on-the-fly optimization method for NMR experiments that enhances spectral sensitivity and quality across various techniques, integrated into common NMR software.

Contribution

The paper presents the first fully automated, sample-tailored optimization method for NMR experiments, integrated into Bruker's TopSpin platform.

Findings

Maximizes spectral sensitivity and quality in diverse NMR experiments

Works automatically without user supervision

Applicable to a wide range of 1D and 2D NMR techniques

Abstract

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.