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Record W2278121940 · doi:10.5539/esr.v5n1p67

Geo Polymerization of Kaolin and Metakaolin Incorporating NaOH and High Calcium Ash

2016· article· en· W2278121940 on OpenAlexvenueno aff
Nafeth Abdel Rahman Abdel Hadi

Bibliographic record

VenueEarth Science Research · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetakaolinCompressive strengthMaterials sciencePolymerizationNuclear chemistryPortland cementEfflorescenceMineralogyChemistryComposite materialCementPolymer

Abstract

fetched live from OpenAlex

<p><span lang="EN-GB">This research work aims to investigate the possibility to produce Ordinary Portland Cement free construction materials depending on the reactivity of high alkali liquids or solids with rich silica-alumina clay through geo polymerization process. Different mixtures of kaolin, metakaolin, bituminous limestone ash and NaOH were prepared and molded with different ratios. Standard cylindrical samples were prepared from each mixture and cured at ambient laboratory temperature for 28 days to investigate their physical and mechanical properties.</span></p><p><span lang="EN-GB">The unconfined compressive strength results of Kaolin-NaOH mixtures have ranged from 19 to 30 kg/cm<sup>2</sup> after 24 hours. The unconfined compressive strength results of kaolin ash mixtures have ranged from 23 to 36 kg/cm<sup>2</sup> at 28 days. The unconfined compressive strength results of ash-metakaolin mixtures have ranged from 32 to 56 kg/cm<sup>2</sup> at 28 days.</span></p><p class="zhengwen"><span lang="EN-GB">Kaolin-NaOH samples revealed various degrees of efflorescence when subjected to wetting and drying conditions, on the other hand, ash –kaolin samples showed efflorescence free surfaces and increasing of strength with increasing the curing time.</span></p>

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 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 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 score0.071
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.040
GPT teacher head0.302
Teacher spread0.262 · 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 teacher head, 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

Citations0
Published2016
Admission routes1
Has abstractyes

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