The relationship between thermal, rheological, and tack properties of copolyester-based hot melt adhesives
Bibliographic record
Abstract
This paper studies the interrelationships between the molecular weight, rheology, crystallinity, and tackiness of three types of commercial thermoplastic hot melt adhesives. The hot melt adhesives employed here differ in their compositions and molecular weights, even though all are copolyesters primarily based on poly(butylene terephthalate). Differences in the composition were found to influence the adhesives’ crystallization and melting behavior. These structural variations can translate into different thermal responses and processing characteristics relevant for tailoring adhesive selection to application requirements. Furthermore, adhesives with higher molecular weight were observed to possess larger elasticity, leading to significantly enhanced tackiness properties, as evidenced by the higher values of tensile modulus, peak stress, and work of debonding. This elevated tackiness was linked to the increased fibrillation process observed in polymers with higher molecular weights. Additionally, all tested adhesives exhibited storage moduli below the Dahlquist threshold (G′ < 3.3 × 105 Pa), which supports their ability to achieve measurable tackiness during the initial bonding process. The results presented in this study underscore the diversity among hot melt adhesives and the critical properties that should be considered when selecting adhesives for specific applications.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".