Mechanical and Thermal Properties of Epoxy Resin upon Addition of Low-Viscosity Modifier
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Bibliographic record
Abstract
Thermoset-based polymer composites containing functional fillers are promising materials for a variety of applications, such as in the aerospace and medical fields. However, the resin viscosity is often unsuitably high and thus impedes a successful filler dispersion in the matrix. This challenge can be overcome by incorporating suitable low-viscosity modifiers into the prepolymer. While modifiers can aptly influence the prepolymer rheology, they can also affect the prepolymer curing behavior and the mechanical and thermal properties of the resulting matrix material. Therefore, this study investigates the effects that a commercial-grade low-viscosity additive (butyl glycidyl ether) has on a common epoxy polymer system (diglycidyl ether of bisphenol-A epoxy with a methylene dianiline curative). The weight percentage of the modifier inside the epoxy was varied from 0 to 20%. The rheological properties and cure kinetics of the resulting materials were investigated. The prepolymer viscosity decreased by 97% with 20 wt% modifier content at room temperature. Upon curing, 20 wt% modifier addition reduced the exothermic peak temperature by 12% and prolonged the time to reach the peak by 60%. For cured material samples, physical and thermo-mechanical properties were characterized. A moderate reduction in glass transition temperature and an increase in elastic modulus was observed with 20 wt% modifier content (in the order of 10%). Based on these findings, the selected material system is seen as an expedient base for material design due to the ease of processing and material availability. The present study thus provides guidance to researchers developing polymer composites requiring reduced prepolymer viscosity for successful functional filler addition.
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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