Solid-state NMR reveals a structural deviation from cellulose Ibeta in bacterial cellulose
Bibliographic record
Abstract
Abstract Solid-state 13C nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for identifying the various polymorphs of cellulose, for example quantifying the proportions of cellulose Iα and Iβ polymorphs in the crystalline domains of various native celluloses. While marine invertebrate animals known as tunicates produce nearly pure cellulose Iβ, solid-state NMR reveals that bacterial cellulose is dominated by the Iα polymorph, but also has additional signals arising from a secondary crystalline form that are normally attributed to cellulose Iβ. However, in this paper we show that the 13C chemical shifts and correlation patterns in 2D NMR spectra for this secondary crystalline form in bacterial cellulose are not the same as those found in cellulose Iβ spectra reported for tunicate cellulose. In order to reach this conclusion, it was necessary to ensure all spectra were correctly set to the same chemical shift scale. In doing so, it became apparent there were spectral features for bacterial cellulose that were entirely consistent with previously reported spectra of bacterial cellulose but did not match those of the Iβ polymorph found in tunicate cellulose. Through a careful and detailed analysis of the 1D and 2D NMR spectra of three 13C-enriched bacterial cellulose samples, two sets of correlated 13C chemical shifts for this secondary crystalline form were identified. The fact that these chemical shifts and correlation patterns are different than those of tunicate cellulose suggests that there exists some sort of structural deviation from the Iβ polymorph in bacterial cellulose since the 13C NMR spectrum closely resembles, but is not identical to, the 13C spectrum of the Iβ polymorph found in tunicate cellulose.
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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 | 0.000 | 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) | 0.001 | 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".