Observation of asphalt binder microstructure with ESEM.
Bibliographic record
Abstract
The observation of asphalt binder with the environmental scanning electron microscope (ESEM) has shown the potential to observe asphalt binder microstructure and its evolution with binder aging. A procedure for the induction and identification of the microstructure in asphalt binder was established in this study and included sample preparation and observation parameters. A suitable heat-sampling asphalt binder sample preparation method was determined for the test and several stainless steel and Teflon sample moulds developed, finding that stainless steel was the preferable material. The magnification and ESEM settings conducive to observing the 3D microstructure were determined through a number of observations to be 1000×, although other magnifications could be considered. Both straight run binder (PG 58-28) and an air blown oxidised binder were analysed; their structures being compared for their relative size, abundance and other characteristics, showing a clear evolution in the fibril microstructure. The microstructure took longer to appear for the oxidised binder. It was confirmed that the fibril microstructure corresponded to actual characteristics in the asphalt binder. Additionally, a 'bee' micelle structure was found as a transitional structure in ESEM observation. The test methods in this study will be used for more comprehensive analysis of asphalt binder microstructure.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".