Effect of poly(ethylene oxide) molecular mass on miscibility and hydrogen bonding with lignin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The effect of the molecular mass of poly(ethylene oxide) (PEO) on lignin-PEO blends was studied using thermal analysis and FT-IR. Differential scanning calorimetry (DSC) analysis revealed miscible blends over the entire blend ratio. A negative deviation in T g from a simple weighted average was observed, indicating the existence of relatively weak favorable interactions between blend components. Analysis of the data revealed no difference in the magnitude or propensity of intermolecular interactions with increasing PEO molecular mass in the kraft lignin-PEO blends. By contrast, the fitting parameters obtained for organosolv lignin were substantially different; the higher molecular mass PEO had a higher propensity to form slightly stronger intermolecular inter-actions than the lower molecular mass PEO. Low molecular mass poly(ethylene glycol) dimethylether (M-PEG)-lignin blends had a much higher degree of crystallinity than the PEO blends, resulting in an increase in T g at high PEG content. FT-IR analysis revealed the presence of strong intermolecular hydrogen bonding between lignin and PEO. However, the band shape of the ν OH region of the M-PEG blends was slightly different from the PEO blends; some of the original lignin inter- and intramolecular hydrogen bonding was still present in the M-PEG-lignin blends.
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.
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 it