MétaCan
Menu
Back to cohort
Record W2253453686 · doi:10.1680/jenes.15.00004

Fly ash/paper sludge as constituents of cements: hydration phases

2015· article· en· W2253453686 on OpenAlexvenueno aff
Rosario García Giménez, Raquel Vigil de la Villa, S. Goñi, Moisés Frı́as

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2015
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersMinisterio de Ciencia e Innovación
KeywordsPortlanditeEttringiteCalcium silicate hydrateThermogravimetric analysisPortland cementCementPozzolanic reactionMaterials scienceAluminateFly ashChemical engineeringPozzolanaPozzolanHydrateSilicateMineralogyNuclear chemistryChemistryMetallurgyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Ternary cements prepared with equal amounts of thermally activated paper sludge and fly ash in proportions of 35% and 50%, in substitution of ordinary Portland cement, are mixed to study their phase stability. The underlying intention is to increase the proportional substitution of waste products in these types of cement, thereby consigning less waste to landfill sites. The hydration phases of the cement specimens were analysed using thermogravimetric/derivative thermogravimetric (TG/DTG) analysis, X-ray diffraction, scanning electron microscopy/energy-dispersive X-ray (SEM/EDX) spectroscopy. The phases identified in the cement blends include Portlandite, monocarboaluminate compound C 4 AC̅H 12 , and layered double hydroxides–type compounds (LDH), as well as ettringite and calcium silicate hydrate gels. Increased formation of both tetracalcium aluminate carbonate 12 hydrate (C 4 ACH 12 ) and LDH-type compounds and reductions in ettringite and portlandite were observed when the proportional substitution of cement by waste products rose from 35% to 50%. A characteristic compound of pozzolanic reactions, bicalcium silicate (C 2 ASH 8 ), was not observed, suggesting that it is inhibited in these types of substitutions.

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)0.000
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 score0.033
Threshold uncertainty score0.259

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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicConcrete and Cement Materials ResearchFrench-language works237,207