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Record W3165505233 · doi:10.1002/advs.202004082

Advanced Switchable Molecules and Materials for Oil Recovery and Oily Waste Cleanup

2021· review· en· W3165505233 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced Science · 2021
Typereview
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceNanotechnologyProcess engineeringWaste managementWettingEnhanced oil recoveryEngineeringComposite material

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.291
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it