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Record W7086840175 · doi:10.18280/acsm.490408

Temperature-Induced Changes in Binders Produced from Concrete Waste: Strength and Rehydration Mechanisms

2025· article· en· W7086840175 on OpenAlexvenueno aff

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMineralogy and Gemology Studies
Canadian institutionsnot available
FundersUniversity of Anbar
KeywordsCreepWork (physics)Deformation (meteorology)Welding

Abstract

fetched live from OpenAlex

This study aims to investigate the effect of elevated temperatures simulating fire exposure conditions on the strength and rehydration behavior of binders produced from concrete waste.The concrete waste was ground in a laboratory mill to a specific surface area of approximately 350 m 2 /kg.The binder was burned at 400 and 600℃.Compression and density tests showed that the mechanical properties were not significantly affected at 600℃.The microstructure of the samples was analyzed, and the results indicated that the natural behavior of the samples during hydration and aging was identical to that of reference samples.Differential thermal analysis revealed that the mass loss curves during heating exhibit no abrupt transitions except at 133 and 778℃.Polymorphic changes in C3S and C2S begin at temperatures of 920℃ and above.Therefore, it was concluded that burning temperatures of 400 and 600℃ do not affect the mineral components of the binder.To evaluate the hydraulic hardening capacity and deformation behavior of the specimen, the results indicated that the behavior of the specimens was not affected by the firing of the binder at temperatures of 400 and 600℃.The results of this research revealed valuable insights into the effects of temperature, suggesting the potential use of concrete waste from building demolition exposed to high temperatures as a sustainable basic binder.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.020
GPT teacher head0.247
Teacher spread0.226 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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