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Record W2072886554 · doi:10.1002/aic.11073

Flocculation of kaolinite clay suspensions using a temperature‐sensitive polymer

2006· article· en· W2072886554 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAIChE Journal · 2006
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSettlingFlocculationKaolinitePolymerAdhesionChemical engineeringMaterials scienceChemistryComposite materialMineralogyThermodynamics

Abstract

fetched live from OpenAlex

Abstract A temperature‐sensitive polymer, poly(N‐isopropylacrylamide) [poly(NIPAM)], was tested to flocculate kaolinite clay suspensions. Settling tests at both room temperature and 40°C were carried out. The results show that settling at 40°C resulted in significantly higher settling rates and smaller sediment volumes. This behavior indicates that the polymer molecules changed from a stretched structure to a coil‐like conformation with increasing temperature. It is the change in conformation that induced more compacted flocs, thus resulting in faster settling. To understand the role of temperature in the flocculation, the long‐range interaction and adhesion forces between kaolinite clay particles in the polymer solutions at both room temperature and 40°C were measured using an atomic force microscope (AFM). The measured adhesion forces correlated well with the settling characteristics: a stronger adhesion led to a higher initial settling rate. The retraction force profiles obtained at different temperatures confirmed the conformational change of the polymer with temperature. © 2006 American Institute of Chemical Engineers AIChE J, 2007.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.424

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.022
GPT teacher head0.292
Teacher spread0.271 · 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