The Evolving Landscape of NMR Structural Elucidation

TL;DR

This paper reviews how NMR spectroscopy has evolved with new technologies and methods to better determine molecular structures.

Contribution

The paper highlights recent advances in NMR, including the integration of computation and machine learning for improved structure determination.

Findings

Modern NMR methods now use ultrahigh magnetic fields and cryogenic probes for better resolution.

Automated analysis and machine learning are enhancing the accuracy of NMR structure determination.

NMR is being applied to a wider range of fields, including biomolecules and materials science.

Abstract

Nuclear Magnetic Resonance (NMR) spectroscopy has long been a cornerstone in the structural elucidation of molecules, offering unique insights into atomic-level connectivity, conformation, and dynamics. Over the past decades, methodological and technological advances have significantly expanded its capabilities and applications. This manuscript charts the evolution of NMR from classical 1D/2D experiments to modern methods empowered by ultrahigh magnetic fields, cryogenic probes, non-uniform sampling, new methodologies, and hyperpolarization. We emphasize the growing synergy between experiment and computation, where automated analysis, quantum chemical calculations, and machine learning are dramatically enhancing the accuracy and efficiency of structure determination. We also highlight NMR’s broadening scope in areas ranging from complex mixtures and natural products to biomolecular and materials science.

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