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Record W2650508982 · doi:10.1346/ccmn.2017.064059

Kaolinite Aggregation in Book-Like Structures from Non-Aqueous Media

2017· article· en· W2650508982 on OpenAlexafffund
Rola Mansa, Guy B. Ngassa Piegang, Christian Detellier

Bibliographic record

VenueClays and Clay Minerals · 2017
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of Ottawa
FundersInstitute for Oil Sands Innovation, University of AlbertaNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaUniversity of Ottawa
KeywordsKaoliniteAqueous solutionChemical engineeringPolymerMaterials scienceFourier transform infrared spectroscopySolventChemistryMineralogyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract To control a vast spectrum of applications and processes, an understanding of the morphologies of clay mineral assemblies dispersed in aqueous or non-aqueous media is important. As such, the objective of this study was to verify the relationship between dispersion medium type and the size and morphology of the clay aggregates that are formed, which can increase knowledge on the assembly formation process. Scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared (FTIR) spectroscopy were used in an attempt to describe kaolinite platelet organization in non-aqueous media and to compare it to the organization in aqueous media or in media with or without a selection of dissolved organic polymers. The SEM images indicated that the kaolinite platelet assembly process occurs during slow evaporation of the solvent. Because the experimental procedure was rigorously identical for all cases in this study, the SEM images compared how the effects of various media and environments on kaolinite platelet interactions can lead to different morphologies. Quite spectacular morphological differences were indeed observed between samples dispersed in aqueous and non-aqueous media, particularly when the kaolinite platelets were dispersed in an organic solvent with dissolved organic polymers. For kaolinite dispersed in water, only small aggregates were observed after slow evaporation. In contrast, large kaolinite booklets or vermiform aggregates were formed by slow solvent evaporation when kaolinite was first dispersed into some organic solvents. The aggregates were particularly large when an organic polymer was dissolved in the organic solvent. For example, kaolinite aggregates dispersed in a binary cyclohexane/toluene mixture with dissolved ethyl cellulose (EC) had top apparent surface areas (i.e. stacking length × width) of more than 3,000 µm2. Other dissolved polymers, such as polystyrene or the polysaccharide, guar gum, gave similar results. Kaolinite platelet aggregation resulted from face-to-face interactions as well as edge-to-face and edge-to-edge interactions. The XRD results showed that ethyl cellulose led to the formation of smaller kaolinite platelets with an increased tendency to form larger aggregates, which is due to the ability of EC to chemically interact with silanol and/or the aluminol groups of kaolinite.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.226
Teacher spread0.214 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations30
Published2017
Admission routes2
Has abstractyes

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