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Record W4403599941 · doi:10.1016/j.cscm.2024.e03894

Sulfate attack on portland-dolomite cement exposed to sodium sulfate solution at 5 ℃ and 20 ℃

2024· article· en· W4403599941 on OpenAlexaff
Fei Liu, Wei Cao, Tong Yang, Jiangtao Xu, Duyou Lu, R.D. Hooton

Bibliographic record

VenueCase Studies in Construction Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Toronto
FundersNatural Science Foundation for Young Scientists of Shanxi Province
KeywordsSulfateDolomitePortland cementSodium sulfateCementEttringiteSodiumMineralogyEnvironmental scienceMaterials scienceChemical engineeringMetallurgyGeologyEngineering

Abstract

fetched live from OpenAlex

The purpose of the study is to investigate the sulfate resistance of portland-dolomite cement (PDC) with varying dolomite contents, when exposed to sodium sulfate solution at 5 ℃ and 20 ℃. Visual appearance, expansion, mass change, and compressive strength of PDC mortars were tested, and XRD , FTIR , and SEM analyses were conducted to examine deterioration products and microstructure. Results indicate that at 20 ℃, the incorporation of 10 % dolomite in PDC had a negligible impact on sulfate resistance, whereas higher dolomite replacements of 20 % and 30 % notably diminished it. In contrast, exposure at 5 °C led to more severe deterioration in all PDC samples, regardless of dolomite content, and the higher dolomite content, the poorer resistance to sulfate attack . The increased formation of ettringite and gypsum resulted in reduced sulfate resistance of PDC at 20 ℃. However, at 5 ℃, the presence of dolomite significantly promoted the formation of thaumasite at later stages, which caused initial ettringite and subsequent late-stage thaumasite sulfate attack, ultimately leading to the failure of PDC. The findings suggest that PDC should be carefully considered when used in sulfate-rich environments, particularly at low temperatures.

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 score0.013
Threshold uncertainty score0.885

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)0.0010.000

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 head0.082
GPT teacher head0.339
Teacher spread0.256 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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