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Foamed concrete produced from CO2/N2 foam stabilized by CaCO3 nanoparticles and CTAB

2024· article· en· W4393216289 on OpenAlexafffund
Ahmed G. Mehairi, Rahil Khoshnazar, Maen M. Husein

Bibliographic record

VenueConstruction and Building Materials · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFoam concreteMaterials scienceComposite materialCarbon nanofoamNanoparticlePorosityNanotechnologyCement

Abstract

fetched live from OpenAlex

Foamed concrete (FC) has garnered popularity, especially with the growing demand for energy-efficient and sustainable construction materials. The stability of the FC slurry as it sets is crucial to the uniformity of the pore structure and, subsequently, FC performance. This study investigates the stability of a novel FC produced using aqueous CaCO3 nanoparticle (NP)/hexadecyltrimethylammonium bromide (CTAB) foam. The effect of NPs and gas type (pure N2, pure CO2, and a 2:1 gas mixture of CO2/N2) on the FC dry density, compressive strength, water absorption, macro- and microstructure, hydration products, and thermal insulation is explored. The results show that the dry density of FC increases with the inclusion of CO2 owing to gas liberation during mixing with the paste leading to less voids. Using the gas mixture, CaCO3/CTAB foam increases the compressive strength of the FC by 38% compared with CTAB alone owing to enhanced uniformity of the pore structure and a denser hydrated paste skeleton. Such structure leads to less connected pores, which reduces atmospheric carbonation, and improves thermal insulation performance. A 2-fold decrease in the largest pore size and a 25% decrease in surface temperature when exposed to an open flame are also achieved in the presence of CaCO3 NPs.

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 categoriesInsufficient payload (model declined to judge)
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 score0.024
Threshold uncertainty score0.996

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)0.0050.000

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 head0.007
GPT teacher head0.236
Teacher spread0.228 · 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.

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

Citations16
Published2024
Admission routes2
Has abstractyes

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