In NMR, the chemical shift provides structural information, with distinct resonance frequencies for different carbon types, such as carbonyl and methyl. Traditionally, the relationship between structure and chemical shift has relied on empirical rules based on prior experience. However, recent advancements in affordable computing and novel quantum chemistry methods have enabled ab initio calculations of chemical shifts for reasonably sized molecules. This development prompts the exploration of whether these theoretical approaches can yield new structural insights into complex chain molecules in polymer science. Solid-state 13C-NMR spectra of glassy amorphous polymers exhibit broad, partially structured resonance regions that reflect the disorder within polymer chains. The chemical shift varies with chain geometry, and the broad resonance can be attributed to an inhomogeneous superposition of different chain geometries. This review introduces a novel method that integrates polymer chain statistical models, quantum chemistry, and solid-state NMR to provide quantitative insights into local chain geometry in amorphous polymers. The statistical model determines the relative occurrence of various geometries, while quantum chemistry, combined with force field geometry optimization, establishes the connection between geometry and chemical shift.
