Physical Properties of Liquid Crystals in Athabasca Bitumen Fractions
Bibliographic record
Abstract
Naturally occurring amphotropic liquid-crystals were recently identified in unreacted hydrocarbon resources and resource fractions from around the world, including Athabasca bitumen. Liquid crystal forming constituents are present in both asphaltene and maltene fractions and appear to be an important class of materials that is missed entirely during conventional hydrocarbon characterization, i.e.: SIMDIST or SARA analysis. In this contribution, some physical properties of liquid crystals in Athabasca asphaltenes and maltenes identified using experimental methods as diverse as polarized light microscopy, differential scanning calorimetry (DSC), and mid- and near-infrared photoacoustic spectroscopy with depth profiling are reported. Liquid crystals, comprising materials with an aromaticity between that of maltenes and asphaltenes, form irreversibly on the surface of both asphaltene particles and maltene drops on heating. At higher temperatures the liquid crystals become isotropic but remain on particle surfaces. Liquid crystals do not reappear on cooling or subsequent reheating unless the samples are frozen and crushed between heating cycles. The interdependence of these phase properties on sample thermal and mechanical history may help explain unexpected and frequently deleterious surface and interfacial phenomena arising during Athabasca bitumen production and processing.
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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 | 0.000 |
| 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".