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Record W2895599145 · doi:10.7939/r3wh2v

Rheological behavior and nano-microstructure of complex fluids: Biomedical and Bitumen-Heavy oil applications

2010· article· en· W2895599145 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity of Alberta Library · 2010
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRheologyAsphaltMicrostructureNano-Materials scienceNanotechnologyPolymer scienceMetallurgyComposite material

Abstract

fetched live from OpenAlex

The main objective of this research was to exploit the interrelations between the rheological behavior and nano-microstructure of complex fluids in solving two state-of-the-art problems, one in the field of biomedical engineering: controlling the amount and characteristics of bioaerosol droplets generated during coughing, and the other in the bitumen-heavy oil industry: characterizing the nano-microstructure of asphaltene particles in bitumen and heavy oil from their rheological behavior. For the first problem, effect of viscoelastic and surface properties of artificial mucus simulant gels on the size distribution and amount of airborne bioaerosol droplets generated during simulated coughing were investigated. The results revealed that suppressing the generation of bioaerosol droplets and/or reducing the number of emitted droplets to a minimum during coughing are practically achievable through modulation of mucus viscoelastic properties. While variation of surface tension did not show any change in the droplet size distribution, an increase in particle size was observed as the samples changed from elastic solid type to viscoelastic type to viscous fluid type samples. This knowledge will help in the development of a new class of drugs being developed at the University of Alberta, aimed at controlling the transmission of airborne epidemic diseases by modifying the viscoelastic properties of mucus. For the second problem, studies of viscoelastic behavior of Athabasca bitumen (Alberta) and Maya crude (Mexico) oil samples, along with their Nano-filtered and chemically separated-plus-reconstituted samples were performed. The results revealed that the rheological behaviors of the bitumen-heavy oil samples are governed by their multiphase nature. The rheological behavior of all feeds, permeates and retentate samples followed a single master curve over the entire temperature interval, consistent with that of a slurry comprising a Newtonian liquid plus a dispersed solid comprising non-interacting hard spheres. The behavior of asphaltenes in the reconstituted samples, however, was found to be significantly different from that in nanofiltered samples. The information about the characteristics and behaviors of asphaltenes obtained in this study will help better understand the asphaltene structures, and support the effort to determine solutions for numerous asphaltene-related industrial problems. In the long run, this knowledge will help to create more efficient extraction and upgrading processes for bitumen and heavy oils.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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