Proton Probability Distribution in the O···H···O Low-Barrier Hydrogen Bond: A Combined Solid-State NMR and Quantum Chemical Computational Study of Dibenzoylmethane and Curcumin
Bibliographic record
Abstract
We report a combined solid-state ( 1 H, 2 H, 13 C, 17 O) NMR and plane-wave density functional theory (DFT) computational study of the O···H···O low-barrier hydrogen bonds (LBHBs) in two 1,3-diketone compounds: dibenzoylmethane ( 1 ) and curcumin ( 2 ). In the solid state, both 1 and 2 exist in the cis -keto–enol tautomeric form, each exhibiting an intramolecular LBHB with a short O···O distance (2.435 Å in 1 and 2.455 Å in 2 ). Whereas numerous experimental (structural and spectroscopic) and computational studies have been reported for the enol isomers of 1,3-diketones, a unified picture about the proton location within an LBHB is still lacking. This work reports for the first time the solid-state 17 O NMR data for the O···H···O LBHBs in 1,3-diketones. The central conclusion of this work is that detailed information about the probability density distribution of the proton (nuclear zero-point motion) across an LBHB can be obtained from a combination of solid-state NMR and plane-wave DFT computations (both NMR parameter calculations and ab initio molecular dynamics simulations). We propose that the precise proton probability distribution across an LBHB should provide a common basis on which different and sometimes seemingly contradicting experimental results obtained from complementary techniques, such as X-ray diffraction, neutron diffraction, and solid-state NMR, can be reconciled.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".