Understanding Interfacial Behavior of Ethylcellulose at the Water–Diluted Bitumen Interface
Bibliographic record
Abstract
An environmentally friendly and commercially available polymer, ethylcellulose (EC), was found to be effective for water removal from water-in-diluted-bitumen emulsions. In a previous study, atomic force microscopy images of bitumen films transferred from the water–toluene interface onto a silicon wafer revealed progressive disruption of bitumen films by increasing the addition of EC. The in situ micropipet experiments, on the other hand, demonstrated the flocculation and enhanced coalescence of two approaching water droplets at low and high EC concentrations, respectively. In this study, we investigated the effect of EC addition on compressibility, composition, thickness, and surface properties of the interfacial films formed by surface-active components of bitumen, aiming to understand the interfacial behavior of EC at the water–diluted bitumen interface. The pressure–area isotherms of Langmuir interfacial films indicated a transformation of a rigid interfacial film formed by surface-active components of bitumen to become much more compressible in the presence of EC. The polarized infrared spectroscopy analysis of the Langmuir–Blodgett (LB) interfacial films proved the adsorption of EC at the water–oil interface, while the thickness measurement of the film indicated the displacement of interfacially active materials by EC. The thickness and contact angle measurements of LB interfacial films revealed an irreversible nature of EC adsorption at the interface. In conclusion, EC is able to irreversibly displace/disrupt the interfacial film formed by surface-active components of bitumen at the water–oil interface and increase the compressibility of the interfacial film, promoting the coalescence of water droplets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".