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Record W4391428873 · doi:10.1080/21650373.2024.2310508

Synthesis, performance and mechanism of novel polymer-type shrinkage reducing agents for cement-based materials

2024· article· en· W4391428873 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Sustainable Cement-Based Materials · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsUniversity of British Columbia
FundersMinistry of Science and Technology, IsraelNational Natural Science Foundation of China
KeywordsShrinkageCementMaterials sciencePorositySurface tensionPolymerComposite materialMortar

Abstract

fetched live from OpenAlex

Simplifying the synthesis process and preparing a new type of shrinkage reducing agent (SRA) with a low dosage and high efficiency are beneficial for promoting the development of SRA and its application in cement-based materials. This study aims to synthesize three novel polymer-type SRAs with diverse structures through free radical copolymerization and to investigate their performance and working mechanisms in cement-based materials. Results clearly showed that the three synthesized SRAs reduced the surface tension of pore solution, and increased the flowability of cement paste. The SRAs-1 with butyl resulted in higher flowability of cement paste due to lower surface tension. Their addition at a low dosage of 0.5% by cement mass effectively mitigated the shrinkage of cement mortar. Among the three, SRAs-1 with butyl exhibited a higher capability of reducing drying shrinkage due to lower surface tension, lower porosity in the range of 2.5–50 nm, and lower total porosity.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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