Carbon dioxide capture technologies are set to play a vital role in mitigating the current climate crisis. Solid‐state 17O NMR spectroscopy can provide key mechanistic insights that are crucial to effective sorbent development. In this work, we present the fundamental aspects and complexities for the study of hydroxide‐based CO2 capture systems by 17O NMR. We perform static density functional theory (DFT) NMR calculations to assign peaks for general hydroxide CO2 capture products, finding that 17O NMR can readily distinguish bicarbonate, carbonate and water species. However, in application to CO2 binding in two test case hydroxide‐functionalised metal‐organic frameworks (MOFs): MFU‐4l and KHCO3‐cyclodextrin‐MOF, we find that a dynamic treatment is necessary to obtain agreement between computational and experimental spectra. We therefore introduce a workflow that leverages machine‐learning forcefields to capture dynamics across multiple chemical exchange regimes, providing a significant improvement on static DFT predictions. In MFU‐4l, we parameterise a two‐component dynamic motion of the bicarbonate motif involving a rapid carbonyl seesaw motion and intermediate hydroxyl proton hopping. For KHCO3‐CD‐MOF, we combined experimental and modelling approaches to propose a new mixed carbonate‐bicarbonate binding mechanism and thus, we open new avenues for the study and modelling of hydroxide‐based CO2 capture materials by 17O NMR.

17O NMR spectroscopy reveals CO2 speciation and dynamics in hydroxide‐based carbon capture materials