Model‐free kinetics: Curing behavior of phenol formaldehyde resins by differential scanning calorimetry
Bibliographic record
Abstract
Abstract Isoconversional analysis was used to treat nonisothermal DSC data and yield the dependence of activation energy on conversion during the curing process of PF resins. The shape of the dependence revealed that the curing process of PF resins displayed a change in the reaction mechanism from a kinetic to a diffusion regime. In the kinetic regime a comparative DSC experimental analysis between monomer mixtures and PF resins showed that the addition reactions between phenol and formaldehyde had been mostly completed during the synthesis of PF resins and that the main kinetic reactions contained parallel condensations in the curing process. For the diffusion regime a modified equation for the diffusion rate constant, kD= D0 exp(−ED/RT + K1α + K2α2), is proposed. This equation is in good agreement with the experimental dependence of Eα on α in the diffusion regime, which shows the effect of both temperature and conversion on diffusion. A prediction of the conversion advancement with the reaction time under isothermal condition for PF resin has been made. This prediction can be useful in practical applications for evaluating isothermal behavior of thermosetting systems from nonisothermal experimental data. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 433–440, 2003
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".