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Record W2392063876

CO_2 UPTAKE CAPACITY OF CONCRETE PRIMARY INGREDIENTS

2010· article· en· W2392063876 on OpenAlexaff
Tran Stanley

Bibliographic record

VenueGuisuanyan xuebao · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsCarbonationMaterials sciencePortland cementCementBasic oxygen steelmakingSlag (welding)Curing (chemistry)MetallurgyCarbon dioxideWaste managementLadleComposite materialSteelmakingChemistry
DOInot available

Abstract

fetched live from OpenAlex

The feasibility of using concrete products to uptake carbon dioxide emitted from cement production were investigated.All three primary ingredients of concrete:cement binder,fine aggregates and coarse aggregates,are considered as CO2 absorbents to maximize carbon sequestration in concrete and produce concrete aggregates from calcium-containing steel slag.It is found that two-hour carbonation enabled the Portland cement can consume ≥14% of CO2,and its strength is comparable to that after 7 d conventional curing.Ladle slag fines could take 4%-12% of CO2 due to their smaller particle size and can be used as a substitution to natural river sand.Basic oxygen furnace(BOF) slag shows an excellent reactivity with CO2.The CO2 uptake capacity in manufactured coarse BOF slag aggregates reaches 12%.The solid BOF steel slag compact produced has a strength compared to crushed limestone.If all three solid components of concrete can be used to uptake CO2,one typical concrete masonry unit(CMU,20 cm × 20 cm × 20 cm) can sequester 1.39 kg of CO2.Carbon sequestration in concrete is an economic and effective approach that directly reduces carbon emission from cement industry.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.990

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)0.0110.001

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 head0.017
GPT teacher head0.245
Teacher spread0.227 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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