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Record W4413027690 · doi:10.1016/j.cscm.2025.e05150

Effect of acid attack coupled with elevated temperatures on carbonation-cured calcium sulfoaluminate and ordinary Portland cement paste

2025· article· en· W4413027690 on OpenAlexaff
Kunal Das, Xuanru Wu, Geon Ho Noh, Jong-Han Lee, Jeong Gook Jang

Bibliographic record

VenueCase Studies in Construction Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité de Sherbrooke
FundersMinistry of Science and ICT, South KoreaNational Research Foundation of KoreaNational Research Foundation
KeywordsCarbonationPortland cementMaterials scienceCementCalciumComposite materialMetallurgy

Abstract

fetched live from OpenAlex

This study evaluated the performance of ordinary Portland cement (OPC) and calcium sulfoaluminate (CSA) cement pastes subjected to water and carbonation curing, followed by exposure to sulfuric acid and elevated temperatures of 200 °C and 600 °C. Carbonation curing significantly enhanced the performance of CSA samples, which retained 82.90% of their strength after acid attack, compared to only 31.73% strength retention in OPC. Thermogravimetric analysis revealed the presence of calcium carbonate in carbonation-cured CSA samples, which decomposes at higher temperatures and thereby improves thermal resistance. Visual inspection showed that water-cured OPC samples developed a thick gypsum layer, with X-ray diffraction confirming traces of thaumasite, which masked internal damage and corrosion. In contrast, water-cured CSA samples displayed minimal visible changes, while carbonation-cured CSA samples exhibited no visible changes. After exposure to elevated temperatures, extensive cracking was observed in carbonation-cured OPC samples, whereas carbonation-cured CSA samples exhibited minimal cracking, highlighting their superior resistance to combined acid and thermal deterioration.

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 score0.002
Threshold uncertainty score0.649

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 head0.018
GPT teacher head0.317
Teacher spread0.299 · 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
Published2025
Admission routes1
Has abstractyes

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