Low‐temperature bitumen stiffness and viscous paraffinic nano‐ and micro‐domains by cryogenic AFM and PDM
Bibliographic record
Abstract
In an effort to better understand the structure and behaviour of bitumen in low temperature, we describe the first use of cryogenic atomic force microscopy and phase detection microscopy to characterize bitumen nano- and micro-structures. The results were interpreted in light of glass transition temperatures (T(g)s) for bitumen fractions. The domains visible by microscopy, the catana, peri and para phases, were attributed to domains rich in asphaltenes, naphthene and polar aromatics, and saturates, respectively. Between -10 degrees C and -30 degrees C, atomic force microscopy images revealed topographic features not visible in atomic force microscopy images acquired at room temperature. According to phase detection microscopy and T(g)s, the features were assigned to viscous unfrozen saturates. Upon cooling to -72 degrees C, unfrozen domains of 20-400 nm were observed. These domains were found in the paraphase rich in saturates and in the periphase rich in naphthene aromatics and polar aromatics. The findings indicate that new viscous domains form upon cooling to low temperatures owing to phase segregation, and that some bitumens are never entirely rigid in low temperatures.
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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 | 0.000 |
| 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) | 0.001 | 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".