Advances of Interfacial Property Determination Using X-Ray Micro Imaging
Bibliographic record
Abstract
The main objectives of this research project are to analyze the challenges X-ray micro imaging has to determine interfacial properties, propose a solution to be able to implement X-rays in the determination of contact angle and interfacial tension and establish the reliability and practicality of microtomography in the determination of interfacial properties. An extensive set of experiments has been executed using a legacy cell to analyze the challenges previous work faced. A new and improved cell to use in a micro CT-scanner has been designed and constructed which gave us an easier manner to set up the experiments in the micro CT scanner. New experiments were conducted using a proposed solution to these challenges and the results obtained have accuracy and reliability. Finally, the determination of contact angle and interfacial tension was conducted in water-wet, neutral and oil-based substrate systems at standard conditions. The limitations given by the micro CT-scanner were in a great manner resolved. Even though the procedure is tedious and time consuming it is accurate and reliable. This makes microtomography attractive to be used in the determination of interfacial properties. Further experimentation is recommended in the development of this new method under different conditions, especially reservoir conditions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".