Advanced Switchable Molecules and Materials for Oil Recovery and Oily Waste Cleanup
Bibliographic record
Abstract
Advanced switchable molecules and materials have shown great potential in numerous applications. These novel materials can express different states of physicochemical properties as controlled by a designated stimulus, such that the processing condition can always be maintained in an optimized manner for improved efficiency and sustainability throughout the whole process. Herein, the recent advances in switchable molecules/materials in oil recovery and oily waste cleanup are reviewed. Oil recovery and oily waste cleanup are of critical importance to the industry and environment. Switchable materials can be designed with various types of switchable properties, including i) switchable interfacial activity, ii) switchable viscosity, iii) switchable solvent, and iv) switchable wettability. The materials can then be deployed into the most suitable applications according to the process requirements. An in-depth discussion about the fundamental basis of the design considerations is provided for each type of switchable material, followed by details about their performances and challenges in the applications. Finally, an outlook for the development of next-generation switchable molecules/materials is discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".