Data on making uniform lignin building blocks via in-situ real-time monitoring of hydroxyethyl modification
Bibliographic record
Abstract
In this work, a lab-designed apparatus was developed to collect and record the CO2 amount during the hydroxyethyl modification of lignin. We presented the CO2 volume amount and the production rate under different reaction conditions (80 – 120 °C and 2 – 6 hrs). Nuclear magnetic resonance spectroscopy was performed to analyze the chemical structure of the hydroxyethyl lignin corresponding with different amounts of CO2 that evolved during the reaction. The aliphatic hydroxyl, aromatic hydroxyl, and carboxylic acid groups were analyzed and tabulated. The acetylated hydroxyethyl lignin samples were characterized by 13C NMR to obtain the aliphatic hydroxyl (primary and secondary), phenol (ortho substituted and ortho-free), hydroxyethyl, methoxy, and aromatic hydrogen groups semi-quantitatively. Fourier-transform infrared (FTIR) spectroscopy was adopted to analyze the surface functional groups including alkyl aryl ether bond, carboxylic acid groups, and aromatic hydroxyl groups. Gel permeation chromatography combined with a multi-angle light scattering detector and differential refractive index detector were used to obtain the molar mass of lignin before and after the modification.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".