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Record W4407780643 · doi:10.1139/cjce-2024-0425

Research progress on carbon dioxide curing of cementitious materials: a review

2025· article· en· W4407780643 on OpenAlexvenueno aff
Fating Xie, Daocheng Zhou, Maohua Zhang

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCementitiousCuring (chemistry)Carbon dioxideForensic engineeringEnvironmental scienceCementMaterials scienceEngineeringComposite materialChemistry

Abstract

fetched live from OpenAlex

The process of CO 2 curing in cementitious materials involves a semi-dry carbonation reaction that transpires between carbon dioxide (CO 2 ) and cementitious substances in the presence of water following initial molding. This reaction facilitates carbon fixation, contributing to the reduction of CO 2 emissions and the production of low-carbon, high-value-added building materials. Cementitious materials subjected to CO 2 curing exhibit effective CO 2 sequestration and demonstrate improvements in mechanical properties and durability to a certain degree. This paper reviews and discusses significant advancements in the CO 2 curing of cementitious materials, encompassing aspects such as the chemical reactions involved, the degree of carbonation, the CO 2 curing regime, and the mathematical models associated with the CO 2 curing process. Notably, it is emphasized that the CO 2 curing process is primarily governed by the carbonation reactions of unhydrated mineral phases, specifically C 3 S and β-C 2 S, within the cement, resulting in the formation of amorphous SiO 2 and crystalline CaCO 3 as final products.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2025
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicConcrete and Cement Materials ResearchFrench-language works237,207