Study of the Curing Kinetics of Epoxy Resins with Biobased Hardener and Epoxidized Soybean Oil
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
High Resolution Image Download MS PowerPoint Slide The goal of this research was to study the kinetics of the reaction of diglycidyl ether of bisphenol A (DGEBA)-based epoxy resin cured with sebacic acid as a biobased hardener in the presence of three different loadings of epoxidized soybean oil (ESO) (i.e., 10, 20, 30 wt %). Nonisothermal differential scanning calorimetric (DSC) and model-free isoconversional method was used to analyze the curing kinetic data and determine the activation energy of the reactions. It was found that the biobased hardener increased the enthalpy of reaction as well as the activation energy of reaction in comparison to the amine hardeners that are currently used for epoxy curing. The addition of epoxidized soybean oil increased the enthalpy of reaction, maximum exothermic temperature, and activation energy of the system. Kissinger–Akahira–Sunose (KAS) and Starink methods were used to determine the activation energy of the studied systems. It was also found that the curing reaction of epoxy with 30 wt % of ESO is diffusion controlled in comparison with other counterparts.
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