  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.
