Strong structuring arising from weak cooperative O-H···π and C-H···O hydrogen bonding in benzene-methanol solution

Journal article

Here we investigate the local structural organization in liquid neat 5-hydroxymethylfurfural (HMF) by the synergic use of high energy X-ray scattering, NMR spectroscopy and molecular dynamics simulations, providing atomistic insight into the correlations that characterise HMF liquid state. HMF has been acknowledged as one of the “sleeping giants” among those renewable compounds, with yet underexploited market potential. It can be obtained from renewable carbohydrate sources via a few consecutive steps and, due to its different functional groups, it can be potentially transformed into a plethora of compounds. An adequate knowledge of the driving interactions into its liquid state can be of fundamental relevance in individuating successful solvents, where HMF can be dissolved, extracted and treated to deliver new compounds. As such, this study has then the potential to provide new, sustainable routes in HMF manipulation, alternatively to current methods. The X-ray scattering validated MD study reveals the existence of a distinct π–π stacking arrangement, characterising the mutual ordering between neighbour HMF molecules. Further correlations involve hydrogen bonding between aldehyde and hydroxyl oxygen and hydroxyl hydrogen. Furthermore, indication of the existence of OH⋅⋅⋅π hydrogen bonding interaction has been detected. An NMR strategy has been applied to confirm the existence of these mutual interactions, identifying the associated structural motifs. These findings underscore the complex and heterogeneous nature of the structural organization of liquid HMF

Authors: Di Mino, C; Seel, AG; Clancy, AJ; Headen, TF; Földes, T

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Nature Communications
• Volume: 14
• Issue: 1
• Article number: 5900
• Publication date: 2023-09-22
• DOI: 10.1038/s41467-023-41451-y
• EISSN: 2041-1723
• ISSN: 2041-1723
• Language: English
• Keywords: Structuring