Polyurea Structure Characterization by HR-MAS NMR Spectroscopy
Bibliographic record
Abstract
Owing to the presence of abundant interchain interactions such as hydrogen bonds, polyureas (PU) are only swellable or soluble in a limited number of highly protonic solvents, and the viscosity of the solutions obtained is very high, making their chemical structure characterization hard or even impossible by standard NMR. Accurate structure analysis is also hard by solid-state NMR due to low spectral resolution. The presence of a side reaction in their synthesis generating biuret cross-links is often invoked to explain their insolubility. Here we demonstrate that High Resolution Magic Angle Spinning (HR-MAS) NMR is an efficient tool for the chemical structure analysis even for cross-linked PU. With 1 H, 13 C, and 1 H– 15 N HSQC combined, a variety of linear and cross-linked PU is analyzed by HR-MAS NMR, and conclusive information on their chemical structure is obtained, which reveals for the first time that the biuret group is absent in all PU.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".