Thermodynamics, Phase Diagrams, and Stability of Bitumen−Polymer Blends
Bibliographic record
Abstract
Infrared spectroscopy was used to measure the stability, segregation rates, and equilibrium concentrations of blends with bitumen and styrene−butadiene (SB)-type copolymers stored at 100−180 °C. The effects of SB concentration, molecular weight, S:B ratio, branching, and bitumen source were investigated. The results were analyzed in light of established mechanisms for phase segregation, blend thermodynamics, and phase diagrams for binary mixtures. It is shown that the phase diagram for bitumen−SB blends is tridimensional and that it contains a lower critical solution temperature (LCST) that decreases in temperature with an increase in polymer content or molecular weight. Equilibrium blend stability is governed by the entropy and enthalpy of mixing, i.e., molecular weights and intermolecular interactions. The rate of segregation, if any, is affected by the molecular shape of the blend components and their molecular weights. It is also found that SBS branching does not affect blend stability and that the morphology of incompatible blends likely results from spinodal decomposition. Hildebrand solubility coefficients provide inaccurate predictions of interactions between bitumen and SBS, but infrared frequency shifts do reveal the nature and strength of the intermolecular interactions. The colloidal instability index, the aromatics content, and the asphaltenes content in bitumen lead to discordant stability predictions for bitumen−SBS blends. This study provides a theoretical framework for understanding the complex interrelationship of the various parameters that affect the stability of bitumen−polymer blends in general.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".